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Appendix B
White Papers
Six workshop participants, through a keynote presenta- dimensions—community resilience, pre-event prediction
tion and associated white paper, were tasked with present- and planning, design of infrastructure, and post-event re-
ing a vision that would help guide the deliberations of the sponse and recovery. The white papers were distributed to
workshop participants. Each discussed a key component all participants prior to the workshop, and they are published
of earthquake engineering research—community, lifelines, here in their original form. Final responsibility for their con-
buildings, information technology, materials, and model- tent rests entirely with the individual author.
ing and simulation—and considered the four cross-cutting
43
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44 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
TRANSFORMATIVE EARTHQUAKE ENGINEERING in public safety, economic strength, and national security.
RESEARCH AND SOLUTIONS FOR ACHIEVING The White House National Security Strategy, released in
EARTHQUAKE-RESILIENT COMMUNITIES May 2010, offers the following definition of resilience: the
ability to prepare for, withstand, and rapidly recover from
Laurie A. Johnson, PhD, AICP
disruption, and adapt to changing conditions (White House,
Principal, Laurie Johnson Consulting | Research
2010). The first part of this definition encapsulates the vast
majority of work that has been done under NEHRP and as
Summary part of modern earthquake engineering research and practice:
strengthening the built environment to withstand earthquakes
This paper is prepared for the National Science
with life-safety standards and codes for new buildings and
Foundation–sponsored, and National Research Council–led,
lifeline construction, developing methods and standards for
Community Workshop to describe the Grand Challenges in
retrofitting existing construction, and preparing government
Earthquake Engineering Research, held March 14–15, 2011,
institutions for disaster response. The second half of this
in Irvine, California. It offers ideas to help foster workshop
definition captures much of the recent learning and research
discussions on transformative earthquake engineering re-
in earthquake engineering: codes and standards that consider
search and achieving earthquake resilience in communities.
post-disaster performance with minimal to no disruption, as
Over the next 50 years, America’s population will exceed
well as the linkages between building and lifeline perfor-
400 million, and much of it will be concentrated in the earth-
mance and business, macro-economic, societal, and institu-
quake-prone, mega-regions of the Northeast, Great Lakes,
tional recovery. But, there is much more work yet to be done,
Pacific Northwest, and northern and southern California.
particularly in translating research into practice.
To achieve an earthquake-resilient nation, as envisioned
What the 1994 Northridge, 1995 Kobe, and 2010 Chile
by the National Earthquake Hazards Reduction Program,
earthquake and the 2005 Hurricane Katrina disasters have
earthquake professionals are challenged to strengthen the
in common is that they all struck relatively dense, modern
physical resilience of our communities’ buildings and infra-
urban settings, and collectively illustrate varying degrees of
structure while simultaneously addressing the environmen -
resilience in modern societies. Resilient communities need
tal, economic, social, and institutional resilience of these
more than physical resilience, which is best characterized by
increasingly dense, complex, and interdependent urban
the physical condition of communities’ buildings, infrastruc-
environments. Achieving community resilience will require
ture, and hazard defenses. They need to have environmental,
a whole host of new, innovative engineering solutions, as
economic, social, and institutional resilience as well. They
well as significant and sustained political and professional
also need to do more than withstand disruption; resilient
leadership and will, an array of new financial mechanisms
communities need to be able to rapidly recover and adapt to
and incentives, and concerted efforts to integrate earthquake
the new conditions created by a disaster.
resilience into other urban design and social movements.
We are now familiar with the physical vulnerabilities of
There is tremendous need and opportunity for net-
New Orleans’ levee system, but Hurricane Katrina struck a
worked facilities and cyberinfrastructure in support of basic
city that lacked resilience across these other dimensions as
and applied research on community resilience. Key ideas
well; conditions that likely influenced New Orleans’ lack
presented in this paper include developing better models of
of adaptive capacity and slow recovery in the five years
community resilience in order to establish a baseline and to
following the disaster (Public Strategies Group, 2011).
measure resilience progress and effectiveness at an urban
P rior to Hurricane Katrina, New Orleans’ population
scale; developing more robust models of building risk/
(455,000 people in 2005) had been in decline for 40 years,
resiliency and aggregate inventories of community risk/
resulting in 40,000 vacant lots or abandoned residences,
resiliency for use in mitigation, land use planning, and emer-
a stagnant economy, and local budgetary challenges that
gency planning; enhancing efforts to upgrade the immense
severely affected the maintenance of local services, facili -
inventory of existing structures and lifelines to be more
ties, and infrastructure, most notably the school, water, and
earthquake-resilient; developing a broader understanding
sewer systems (Olshansky and Johnson, 2010). In addition,
of resiliency-based performance objectives for building and
New Orleans’ social fabric was also very fragile. In 2005,
lifeline design and construction; building the next generation
the city’s median household income of $27,000 was well
of post-disaster damage assessment tools and emergency
below the national average of $41,000, as were the home -
response and recovery “dashboards” based upon sensing net-
ownership and minimum literacy rates of 46 and 56 percent,
works; and sustaining systematic monitoring of post-disaster
respectively (compared with the national averages of 68 and
response and recovery activities for extended periods of time.
75 percent, respectively) (U.S. Census Bureau, 2000; U.S.
Department of Education, 2003). The city’s poverty rate of
Envisioning Resilient Communities, Now and in the Future 23.2 percent was also much higher than the national rate
of 12.7 percent, and 29 percent of residents didn’t own cars
The National Earthquake Hazards Reduction Program
(U.S. Census Bureau, 2004).
(NEHRP) envisions: A nation that is earthquake-resilient
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45
APPENDIX B
Although, in aggregate, these statistics might seem like square footage, and 70 billion square feet will be rebuilt or
an extreme case in community vulnerability, they are not dis- replaced (Lang and Nelson, 2007). These statistics were de-
similar from some of the conditions of, at least portions of, veloped before “The Great Recession” slowed housing starts
many of our most earthquake-prone communities in southern from annual rates of more than 2 million in 2005 and 2006
and northern California, the Pacific Northwest, and the cen- to 0.5 million in 2009 and 2010, and pushed annual fore-
tral and eastern United States. And, with the exception of a closure rates to more than 3 million (U.S. Census, 2011). The
few pockets in northern and southern California, and Seattle, recent recession has also dramatically slowed commercial
none of the most densely urbanized and vulnerable parts of development and postponed the upgrade of local facilities
our earthquake-prone communities have been impacted by a and infrastructure, much of which was already in sore need
recent, large, damaging earthquake. Our modern earthquake of modernization and maintenance before the recent fiscal
experience, like most of our disaster experience in the United crisis.
States, has largely been a suburban experience, and our engi- To achieve community resilience, now and in the fore-
neering and preparedness efforts of the past century have not seeable future, we must take a more holistic approach to our
yet been fully tested by a truly catastrophic, urban earthquake. work as earthquake professionals. With physical resilience as
In April 2010, the U.S. Census officially marked the the foundation of our communities’ resilience, we also need
country’s resident population at 308,745,538, and we are to focus on the environmental, economic, social, and insti-
expected to add another 100 million in the next 50 years tutional resilience of our increasingly dense, complex, and
(U.S. Census Bureau, 2011). This population growth is interdependent communities. Also, as past as well as future
expected to be accommodated in the country’s fifth wave projections suggest, physical resilience can’t be achieved
of migration, a wave of re-urbanism that began in the 1980s through expected rates of new construction and redevelop-
(Fishman, 2005). By the time the fifth migration is complete, ment. It is going to require a whole host of new, innovative
it is expected that 70 percent of the country’s population engineering solutions, as well as significant and sustained
will be concentrated within 10 “mega-regions” of the coun- political and professional leadership and will, an array of new
try (Barnett, 2007; Lang and Nelson, 2007). Half of these financial mechanisms and incentives, and concerted efforts
mega-regions are in earthquake-prone regions of the North- to integrate earthquake resilience into other urban design
east (from Washington D.C. to Boston); the Great Lakes and social movements. Otherwise, “an earthquake-resilient
(Cleveland, Cincinnati, Detroit, and Chicago/Milwaukee); nation” will remain an idealistic mantra of our profession,
Cascadia (Seattle and Portland); northern California (San and the expected earthquakes of the 21st century will cause
Francisco Bay Area); and southern California. unnecessary human, socioeconomic, and physical hardship
As these metropolitan areas continue to grow, it is for the communities they strike.
predicted that development patterns will get increasingly
dense as older urban cores are revitalized and the suburban
A “Sputnik Moment” in Earthquake Engineering Research
land use patterns of the last half of the 20th century become
more costly to both inhabit and serve (Barnett, 2007). These In his 2011 State of the Union address, President
assumptions are based upon expected increases in energy Obama referred to recent news of technological advances
costs, an emphasis on transportation and climate change by other nations as this generation of Americans’ “sputnik
policies that promote more centralized development, and moment,” and he called for a major national investment “in
the significant fiscal challenges that local agencies are likely biomedical research, information technology, and especially
to have in supporting distributed patterns of services. The clean energy technology—an investment that will strengthen
demographics of these regions are also likely to shift as our security, protect our planet, and create countless new
more affluent younger professionals, aging empty-nesters, jobs for our people” (White House, 2011). Following the
and immigrant populations concentrate in the metropolitan Soviet Union’s launch of the “sputnik” satellite into space
cores, a trend that is already advanced in Boston, New York, in 1957, the United States responded with a major sustained
Chicago, Los Angeles, and San Francisco/Oakland (Nelson investment in research—most visibly through the establish-
and Lang, 2007). In general, our population will be older ment of the National Aeronautics and Space Administration
and more diverse than previous decades, adding to the social (NASA)—and education. The National Defense Education
vulnerabilities of metropolitan areas. Act of 1958 dramatically increased federal investment in
To accommodate the next 100 million people, 70 million education and made technological innovation and education
housing units will need to be added to the current stock of into national-security issues (Alter, 2011).
125 million; 40 million are likely to be new housing units, It is well known that disasters are focusing events
while the remaining 30 million are likely to replace dam- for public policy agenda setting, adoption, and change
aged or demolished units on existing property (Nelson and (Birkland, 1997). The September 11, 2001, terrorist attacks
Lang, 2007). Also, to accommodate these growing mega- put man-made threats at the forefront of disaster policy
economies, 100 billion square feet of nonresidential space making, management, and program implementation. Sep-
will likely be added; 30 billion of which is likely to be new tember 11 has also been described by some as the major
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46 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
Community Resilience
focusing event that significantly expanded the size and scope
of the federal government as well as its debt (Stone, 2010).
Drawing upon the research literature of several social
Similarly, Hurricane Katrina has been another focusing event
science disciplines, Norris et al. (2008) define community
for hazard and disaster management policy and program
resilience as a process linking a network of adaptive capaci-
implementation. To some extent, it has reversed some of the
ties in “economic development, social capital, information
trends started after September 11, but disaster recovery and
and communication, and community competence.” To build
mitigation have yet to regain their former status as officially
collective resilience, they recommend that “communities
preferred disaster policy responses (Waugh, 2006).
must reduce risk and resource inequities, engage local
For earthquake engineering research and seismic policy
people in mitigation, create organizational linkages, boost
making, adoption, and change in the United States, the 1971
and protect social supports, and plan for not having a plan,
San Fernando earthquake has been the most recent and salient
which requires flexibility, decision-making skills, and trusted
focusing event. It led to the formation of the California
sources of information that function in the face of unknowns”
Seismic Safety Commission in 1975 and the passage of the
(Norris et al., 2008). To achieve earthquake resilience, we,
National Earthquake Hazards Reduction Act in 1997 and
as earthquake engineering researchers and professionals,
the formation of NEHRP thereafter (Birkland, 1997). But,
need to look beyond earthquakes to other disasters, and even
was the 1971 earthquake or any other more recent U.S. earth-
outside of disasters, to understand how our work fits in and
quake a sputnik moment for the United States? The pairing
how to link our work with other initiatives to build adaptive
of the 1994 Northridge and 1995 Kobe earthquakes may
capacities and incite resiliency-related policy and actions.
well have been a sputnik moment for Japan. The tremendous
In 2006, earthquake professionals and public policy ad-
human loss, economic consequences, and, in some cases,
vocates joined forces to develop a set of policy recommenda-
surprising causes and levels of damage to structures and
tions for enhancing the resiliency of existing buildings, new
infrastructure all contributed to Japan’s major investment in
buildings, and lifelines in San Francisco (SPUR, 2009). The
earthquake engineering and disaster management research,
San Francisco Planning and Urban Research Association’s
education, and policy reform over the past decade. Will we
(SPUR’s) “Resilient City Initiative” chose to analyze the “ex-
have to wait until a major catastrophic urban earthquake
pected” earthquake, rather than the “extreme” event, because it
strikes the United States causing unprecedented human and
is a large event that can reasonably be expected to occur once
economic losses to have our sputnik moment in earthquake
during the useful life of structures and lifeline systems in the
engineering research, practice, and policy reform?
city. It also defined a set of performance goals—as target states
If some of the underlying motivations of a sputnik mo-
of recovery within hours, days, and months following the
ment stem from shock as well as a sense of being surpassed,
expected earthquake—in terms of four community clusters:
then is there any way for our earthquake professional com-
critical response facilities and support systems; emergency
munity to better communicate the lessons from Chile versus
housing and support systems; housing and neighborhood
Haiti and other disasters around the world to compel a more
infrastructure; and community recovery (SPUR, 2009).
focused policy and investment in earthquake engineering and
Lacking a theoretical model or set of quantifiable mea-
risk reduction research, education, and action? What can we
sures of community resilience, SPUR relied on expert opinion
learn from the biomedical, high-tech, and “green” engineer-
to set the target states of recovery for San Francisco’s build-
ing movements, as examples, which may have recently had,
ings and infrastructure and to assess the current performance
or may currently be a part of sputnik moments, in which
status of the cluster elements. For example, SPUR set a target
policy makers and private investors are motivated to take
goal to have 95 percent of residences available for “shelter-in-
action in ways that earthquake preparedness has not been
place” by their inhabitants within 24 hours after an expected
able to do with the same growth trajectory and enthusiasm?
earthquake; it also estimated that it would take 36 months for
the current housing stock to be available for “shelter-in-place”
Ideas for Transformative Earthquake Engineering in 95 percent of residences. But, is 95 percent an appropri-
Research and Solutions ate target for ensuring an efficient and effective recovery in
the city’s housing sector following an expected earthquake?
The remainder of this paper presents ideas to help
Does San Francisco really need to achieve all the performance
foster workshop discussions on transformative earthquake
targets defined by SPUR to be resilient following an expected
engineering research and on achieving earthquake-resilient
earthquake? Which target should be worked on first, second,
communities. It is organized around four dimensions: com-
and so forth? And, given all the competing community needs,
munity resilience, pre-event prediction and planning, design
when is the most appropriate time to promote an earthquake
of infrastructure, and post-event response and recovery. Par-
resiliency policy agenda?
ticular emphasis is given to community-level ideas that might
There is tremendous need for networked facilities and
utilize the networked facilities and cyberinfrastructure of the
cyberinfrastructure in support of basic and applied research
George E. Brown, Jr. Network for Earthquake Engineering
on community resilience. This includes:
Simulation (NEES).
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47
APPENDIX B
• Developing an observatory network to measure, interdependency and how these affect building func-
monitor, and model the earthquake vulnerability and tionality, time required to recover various levels of
resilience of communities, including communities’ building functionality, and other economic and social
adaptive capacities across many physical, social, eco- resilience factors.
nomic, and institutional dimensions. Clearer defini- • Developing aggregate inventories and models of
tions, metrics, and timescales are needed to establish community or regional risk/resiliency that can be
a baseline of resilience and to measure resilience used in mitigation, land use planning, and emergency
progress and effectiveness on an urban scale. planning. Local building and planning review pro-
• Collectively mapping and modeling the individual cesses and emergency management practices need
and organizational motivations to promote earth- tools to assess the incremental changes in community
quake resilience, the feasibility and cost of resilience risk/resiliency over time caused by new construction,
actions, and the removal of barriers and building of redevelopment, and implementation of different
capacities to achieve successful implementation. mitigation policies and programs. Real estate prop-
Community resilience depends in large part on our erty valuation and insurance pricing also need better
ability to better link and “sell” physical resilience methods to more fully reflect risk and resilience in
with environmental, economic, social, and even risk transfer transactions. Within current decision
institutional resilience motivations and causes. frameworks and practices, redevelopment of a low-
• Developing the quantitative models or methods density, low-rise, but structurally vulnerable neigh-
that prioritize and define when public action and borhood into a high-density, high-rise development
subsidy are needed (and how much) to fund seismic is likely to be viewed as a lowering of earthquake
rehabilitation of certain building or infrastructure risk and an increase in economic value to the com-
types, groups, or systems that are essential to a com- munity. But is it really? Tools that more accurately
munity’s resilience capacity versus ones that can be value the aggregation of risk across neighborhoods,
left to market forces, attrition, and private investment incremental changes in community resiliency, effects
to address. of aging and densification of the urban environment
• Developing a network of community-based earth- and accumulation of risk over time, and the dynamics
quake resiliency pilot projects to apply earthquake of adaptive capacity of a community post-disaster are
engineering research and other knowledge to reduce needed.
risk, promote risk awareness, and improve commu- • Developing models of the effects of institutional
nity resilience capacity. Understanding and develop- practices and governance on community resilience
ing effective, alternative methods and approaches to in terms of the preparedness, recovery, and adaptive
building local resilience capacity are needed because capacities. This includes modeling the effects of
earthquake-prone communities have varying cul- building and land use planning regulatory regimes,
tures, knowledge, skills, and institutional capacities. emergency decision-making processes, institutional
leadership and improvisational capacities, and post-
disaster financing and recovery management policies.
Pre-Event Prediction and Planning
To date, much of the pre-event research and practice
Design of Infrastructure
has focused on estimating the physical damage to individual
structures and lifeline systems, creating inventories and sce- Achieving community resilience will require enhanced
narios for damage and loss estimation, and preparing gov- efforts to upgrade the immense inventory of existing struc-
ernment institutions for disaster response. Ideas for “opera- tures and lifelines to be more earthquake-resilient and a
tionalizing” a vision of community-level resiliency include: broader understanding of resiliency-based performance
objectives for building and lifeline design and construction.
• Developing more robust earthquake forecasting and Ideas include:
scenario tools that address multiple resiliency per-
formance objectives and focus on community-level • Developing enhanced methods for evaluating and
resilience impacts and outcomes. retrofitting existing buildings and lifeline systems.
• Developing more holistic models of individual build- These methods need to reliably model the expected
ing risk/resiliency that extend structural simulations responses of existing buildings and lifelines to differ-
and performance testing to integrate information ent levels of ground motions and multiple resiliency
on soil and foundation interaction, non-structural performance objectives. Methods need to go beyond
systems, and lifeline systems with the structure and estimating the costs to retrofit toward developing
contents information and that model post-disaster more robust models that consider the full range of
building functionality and lifeline dependency and resiliency benefits and costs of different mitigation
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48 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
policy and financing strategies. These alternatives mental Design (LEED) program; architects and en-
need to think creatively of ways to reuse existing gineers developing green, adaptive, building “skins,”
stock, cost-effectively piggy-back on other rehabili- construction materials, and sensing networks; and
tation efforts, and incentivize and ease the burden of urban designers working on sustainable community
retrofitting existing stock. Current and future political standards and practices. Current efforts to build new
challenges are likely to include pressures to preserve “smart” buildings and cities could potentially benefit
historic and cultural integrity, and resistance to from the networked facilities and cyberinfrastructure
invest limited capital resources in seismic rehabilita- that the earthquake engineering community has devel-
tion projects. Concepts of a federal infrastructure oped in managing and processing the sensing data. In
bank might be expanded to include all seismically turn, earthquake engineering could potentially assist
vulnerable structures and infrastructure, and new in helping to develop better and more cost-effective
public-private financing mechanisms may need to be “sensing retrofits” of existing structures and lifeline
developed. Mechanisms to effectively communicate systems to be “smarter” and to better integrate disas-
the vulnerability of existing structures and lifeline ter resilience into the green building and sustainable
systems to owners, occupants, and policy makers community standards and practices. In November
to incite and reward action, such as an earthquake- 2010, the Green Building Council reached a major
resilience certification system, also need to be care- milestone in its short 10-year life span, having certi-
fully assessed. Sustained efforts to build consensus fied more than 1 billion square feet of commercial
for standards and actions to evaluate and retrofit building space (Koch, 2010). Since it was introduced
existing building and lifeline systems, develop in 2000, the Council’s LEED program has had more
guidelines, and transfer knowledge and technology than 36,000 commercial and 38,000 single-family
to building officials, owners, and engineers; utility homes participating in the program, of which 7,194
owners, operators, regulators, and engineers; and commercial projects and 8,611 homes have been com-
other policy and decision makers are also needed. pleted and certified as LEED compliant (Koch, 2010).
• Advancing performance-based earthquake engineer- Although the costs for becoming LEED certified may
ing for buildings, lifelines, geotechnical structures, be substantially lower than the costs for enhancing
and hazard defenses. Performance-based engineer- seismic performance, it is not a full explanation for
ing needs to take a broader look at the integrated the program’s comparative national and marketing
performance of a structure as well as the layers of successes. Minimizing damage and reducing the
substructures, lifeline systems, and surrounding com- deconstruct/construct cycles of development with
munity infrastructure that it depends upon. For ex- higher building performance levels should also be
ample, a 50-plus story residential high-rise is, in fact, considered as benefits in building valuation.
a neighborhood- or community-vertical, thus making
the lifeline conveyance and social resilience of a
Post-Event Response and Recovery
single structure. Even if the structure is deemed safe
following a disaster, lifeline disruptions may impact To date, much of the post-event research and practice
evacuations and render the structure uninhabitable has focused on estimating the physical damage and economic
with sealed windows and lack of elevator service, as losses caused by earthquakes and aiding government institu-
examples. tions in disaster response. Ideas for enhancing community-
• To have resilient communities, we cannot think of level capabilities to rapidly recover from disruption and
building-specific performance only. Community- adapt to changing conditions include:
level performance-based engineering models are
needed. These may require a systems approach to • Creating a more integrated multi-disciplinary net-
consider the complex interactions of lifeline systems, work and information management system to cap-
critical network vulnerability and dependencies, and ture, distill, integrate, and disseminate information
dependencies between physical, social, economic, about the geological, structural, institutional, and
and institutional sectors of a community, and to de- socioeconomic impacts of earthquakes, as well as
velop guidelines and “urban-level design standards” post-disaster response and recovery. This includes
for community-level performance. the creation and maintenance of a repository for post-
• Making seismic risk reduction and resilience an earthquake reconnaissance data.
integral part of many professional efforts to improve • Developing the next generation of post-disaster
the built environment, and building new alliances damage assessments. Post-disaster safety assessment
and coalitions with interest groups working on these programs are now well institutionalized in local
goals. This includes the Green Building Council and emergency management and building inspection
the Council’s Leadership in Energy and Environ- departments, with legal requirements, procedures,
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49
APPENDIX B
Acknowledgments
and training. The next generation of post-disaster
assessments might integrate the sensing networks
This paper was developed with the support of the
of “smart” buildings and lifeline systems to make
National Research Council and the organizers of Grand
it more quickly possible for emergency responders,
Challenges in Earthquake Engineering Research: A Com-
safety inspectors, and system operators, as well
munity Workshop. The ideas and opinions presented in this
as residential and commercial building occupants
paper are those of the author and also draw upon the work
themselves, to understand the post-disaster condi-
of the National Research Council’s Committee on National
tions of buildings or systems and resume occupancy
Earthquake Resilience—Research, Implementation, and
and operation safely or seek alternatives. The next
Outreach, of which the author was a member, and its final
generation of assessments could also take a more
report (NRC, 2011). In addition, the author acknowledges
holistic view of the disaster impacts and losses,
the work of members of the San Francisco Planning and
focusing on the economic and social elements as
Urban Research Association’s “Resilient City Initiative.” The
well as the built environment. Just like physical dam-
author also appreciates the suggestions and detailed review
age assessments, these socioeconomic, or resilience,
of this paper provided by workshop Co-chair Chris Poland
assessments need to be done quickly after a disaster,
and session moderator Arrietta Chakos; Liesel Ritchie for her
and also iteratively so that more-informed, and ap-
sharing of ideas; and Greg Deierlein and Reggie DesRoches
propriately timed, program and policy responses
(authors of companion papers for the workshop) for their
can be developed. Such assessments need to look at
helpful discussion while preparing the paper. Appreciation
the disaster-related losses, including the ripple ef-
is also extended to the conference Co-chairs, Greg Fenves
fects (i.e., lost wages, tax revenue, and income); the
and Chris Poland, and the NRC staff for their leadership and
spectrum of known available resource capital (both
efforts in organizing this workshop.
public and private wealth and disaster financing
resources) for response and recovery; social capital;
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hold, organizational, neighborhood, and regional SPUR (San Francisco Planning and Urban Research Association). 2009. The
levels). This is longitudinal research requiring sus- Resilient City: A New Framework for Thinking about Disaster Planning
in San Francisco. The Urbanist. Policy Initiative. San Francisco, CA.
tained efforts for 5 to 10 years and possibly even
Available at www.spur.org/policy/the-resilient-city.
longer, which does not fit well with existing research
funding models.
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50 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
Stone, D. 2010. Hail to the chiefs: The presidency has grown, and grown Waugh, W. L. 2006. The political costs of failure in the Katrina and Rita
and grown, into the most powerful, most impossible job in the world. disasters. The Annals of the American Academy of Political and Social
Newsweek. November 13. Science 604(March):10-25.
U.S. Census Bureau. 2000. Census of Housing. Available at www.census. White House. 2010. National Security Strategy. May 27. Washington,
gov/hhes/www/housing/census/historic/owner.html. DC. Available at www.whitehouse.gov/sites/default/files/rss_viewer/
U.S. Census Bureau. 2004. Statistical Abstract of the United States. Avail - national_security_strategy.pdf.
able at www.census.gov/prod/www/abs/statab2001_2005.html. White House. 2011. Remarks of President Barack Obama in State of the
U.S. Census Bureau. 2011. Census Bureau Home Page. Available at www. Union Address—As Prepared for Delivery. January 25. Available at
census.gov. www.whitehouse.gov/the-press-office/2011/01/25/remarks-president-
U.S. Department of Education. 2003. State and County Estimates of Low barack-obama-state-union-address.
Literacy. Institute of Education Sciences. Available at nces.ed.gov/naal/
estimates/StateEstimates.aspx.
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51
APPENDIX B
GRAND CHALLENGES IN LIFELINE EARTHQUAKE Water and wastewater systems support population growth,
ENGINEERING RESEARCH industrial growth, and public health. Power systems provide
lighting to homes, schools, and businesses and energize
Reginald DesRoches, PhD
communications. Transportation systems are the backbone
Professor and Associate Chair, School of Civil &
of mobility and commerce and connect communities. Tele-
Environmental Engineering
communications systems provide connectivity on the local,
Georgia Institute of Technology
national, and global scale.
Lifeline systems are the basis for producing and deliver-
Summary ing goods and services that are key to economic competitive-
ness, emergency response and recovery, and overall quality
Lifeline systems (transportation, water, waste disposal,
of life. Following an earthquake, lifeline systems provide a
electric power, gas and liquid fuels, and telecommunica-
critical link to communities and individuals, including water
tion) are intricately linked with the economic well-being,
for putting out fires, roads for evacuation and repopulation of
security, and social fabric of the communities they serve,
communities, and connectivity for emergency communica-
and the nation as a whole. The mitigation of earthquake
tions. The resilience of lifeline systems has a direct impact
risks for lifeline facilities presents a number of major chal-
on how quickly a community recovers from a disaster, as
lenges, primarily because of the vast inventory of facilities,
well as the resulting direct and indirect losses.
their wide range in scale and spatial distribution, the fact
that they are partially or completely buried and are there-
Challenges in Lifeline Earthquake Engineering
fore strongly influenced by soil-structure interaction, their
increasing interconnectedness, and their aging and deteriora-
The mitigation of earthquake hazards for lifeline
tion. These challenges will require a new set of research tools
facilities presents a number of major challenges, primar-
and approaches to adequately address them. The increasing
ily because of the vast inventory of facilities, their wide
access to high-speed computers, inexpensive sensors, new
range in scale and spatial distribution, the fact that they are
materials, improved remote sensing capabilities, and infra-
partially or completely buried and strongly influenced by
structure information modeling systems can form the basis
interactions with the surrounding soil, and their increasing
for a new paradigm for lifeline earthquake engineering in
interconnectedness. Because of their spatial distribution,
the areas of pre-event prediction and planning, design of the
they often cannot avoid crossing landslide areas, liquefaction
next-generation lifeline systems, post-event response, and
zones, or faults (Ha et al., 2010).
community resilience. Traditional approaches to lifeline
One of the challenges in the area of lifeline systems,
earthquake engineering have focused on component-level
when it comes to testing, modeling, or managing these
vulnerability and resilience. However, the next generation of
systems, is the vast range of scales. Testing or modeling
research will also have to consider issues related to the im-
of new innovative materials that might go into bridges or
pact of aging and deteriorating infrastructure, sustainability
pipelines could occur at the nano (10–9 m), micro (10–6 m),
considerations, increasing interdependency, and system-
or milli (10–3 m) level, while assessment of the transporta-
level performance. The current generation of the George E.
tion network or fuel distribution system occurs at the mega
Brown, Jr. Network for Earthquake Engineering Simulation
(10+6 m) scale. Multi-scale models required for lifeline
(NEES) was predicated on large-coupled testing equipment
systems involve trade-offs between the detail required for
and has led to significant progress in our understanding of
accuracy and the simplification needed for computational
how lifeline systems perform under earthquake loading.
efficiency (O’Rourke, 2010).
The next generation of NEES can build on this progress by
A second challenge related to the assessment of the
adapting the latest technological advances in other fields,
performance of lifeline systems is that many lifeline systems
such as wireless sensors, machine vision, remote sensing,
have a substantial number of pipelines, conduits, and compo-
and high-performance computing.
nents that are completely below ground (e.g., water supply,
gas and liquid fuel, electric power) or partially underground
Introduction: Lifelines—The Backbone of American (e.g., bridge or telecommunication tower foundations) and
Competitiveness are heavily influenced by soil-structure interaction, surface
faulting, and liquefaction. Hence, a distinguishing feature in
The United States is served by an increasingly complex
evaluating the performance of lifelines is establishing a thor-
array of critical infrastructure systems, sometimes referred
ough understanding of the complex soil-structure interaction.
to as lifeline systems. For the purposes of the paper, life-
A third and critical challenge related to lifeline systems
line systems include transportation, water, waste disposal,
is their vast spatial distribution and interdependency between
electric power, gas and liquid fuels, and telecommunication
lifeline systems—either by virtue of physical proximity or
systems. These systems are critical to our economic com-
via operational interaction. Damage to one infrastructure
petitiveness, national security, and overall quality of life.
component, such as a water main, can cascade into damage to
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52 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
a surrounding lifeline component, such as electrical or tele- capabilities, and building or bridge information model -
communications cables, because they are often co-located. ing (BIM or BrIM) systems can form the basis for a new
From an operational perspective, the dependency of lifelines paradigm for lifeline earthquake engineering in the areas
on each other complicates their coupled performance dur- of pre-event prediction and planning, design of the next-
ing an earthquake (Duenas-Osorio et al., 2007), as well as generation lifeline systems, post-event response, and com-
their post-event restoration. For example, electrical power munity resilience.
networks provide energy for pumping stations and control Although the current generation of NEES is predicated
equipment for transmission and distribution systems for oil on large-coupled testing equipment and has led to significant
and natural gas. progress in our understanding of how lifeline systems per-
A fourth challenge is the aging of lifeline systems. Many form under earthquake loading, the next generation of NEES
lifelines were designed and constructed 50-100 years ago can build on this progress by adapting the latest technological
without special attention to earthquake hazards and are de- advances in other fields, such as wireless sensors, machine
teriorating (ASCE, 2009). Moreover, many lifeline systems vision, remote sensing, and high-performance computing.
have demands placed on them that are much higher than they In addition, the coupling of seismic risk mitigation with
were originally designed to have. Many lifeline systems are other pressing global needs, such as sustainability, will re-
already damaged prior to an earthquake, which increases quire a different way of thinking about lifeline earthquake
their vulnerability. engineering. Sustainability, in this paper, is defined as the
ability to meet the needs of current and future generations
by being resilient, cost-effective, environmentally viable, and
Recent Advances in Lifeline Earthquake Engineering
socially equitable. Lifeline systems account for 69 percent
The field of lifeline earthquake engineering has experi- of the nation’s total energy use, and more than 50 percent of
enced significant progress over the past decade. Early studies greenhouse gas emissions are from lifeline systems, so their
in lifeline earthquake engineering focused on component continued efficient performance is critical for sustainable
behavior and typically used simple system models. They development (NRC, 2009).
often looked at the effects of earthquakes on the performance
of sub-components within each infrastructure system (e.g.,
Pre-Event Prediction and Planning
columns in a bridge). As more advanced experimental and
computational modeling facilities came online via the NEES Because earthquakes are low-probability, high-
program, the effects of larger systems (e.g., entire bridge) and consequence events, effective planning is critical to making
coupled soil-structure systems (e.g., pile-supported wharf) informed decisions given the risk and potential loses. One
were assessed (McCullough et al., 2007; Johnson et al., of the key tools in pre-event planning is the use of seismic
2008; Kim et al., 2009). Most recently, advances in model- risk assessment and loss estimation methodologies, which
ing and computation have led to the ability to study entire combines the systematic assessment of regional hazards with
systems (e.g., transportation networks, power networks, infrastructure inventories and vulnerability models through
etc.), including the local and regional economic impact of geographic information systems.
earthquake damage to lifeline systems (Kiremidjian et al., The performance of lifeline systems is strongly a func-
2007; Gedilkli et al., 2008; Padgett et al., 2009; Romero et tion of the seismic hazard and the geological conditions on
al., 2010; Shafieezadeh et al., 2011). which the lifeline systems are sited. Lifeline systems are
strongly affected by the peak ground deformation, which
often comes from surface faulting, landslides, and soil
Transformative Research in Lifeline Earthquake
liquefaction. Development of approaches to quantitatively
Engineering
predict various ground motion parameters, including peak
A new set of research tools is needed to adequately ad- ground displacement, will be important for understanding
dress the critical challenges noted above, namely the vast the performance of lifeline systems. This quantitative as-
range in scales, complex mix of soil-structure-equipment sessment has traditionally been performed using costly and
systems, interdependencies, and aging and deteriorating time-consuming approaches that are only typically done on a
lifeline systems. Modeling and managing interdependent local scale. The advent of advanced remote sensing products,
systems, such as electric power, water, gas, telecommunica- from air- and spaceborne sensors, now allows for the explora-
tions, and transportation systems require testing and simula - tion of land surface parameters (i.e., geology, temperature,
tion capabilities that can accommodate the many geographic moisture content) at different spatial scales, which may lead
and operational interfaces within a network, and among the to new approaches for quantifying soil conditions and prop-
different networks. erties (Yong et al., 2008).
The increasing access to high-speed computers, closed- One of the main challenges in regional risk assessment
form techniques for near-real-time network analysis, inex- is the lack of reliable and consistent inventory data. Research
pensive sensors, new materials, improved remote sensing is needed in finding better ways to acquire data on the vast
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53
APPENDIX B
inventories contained within a lifeline network. Although re- component (e.g., pipes, bridges, substations). Significant
searchers have effectively deployed remote sensing technolo- progress has been made in understanding the performance
gies following natural disasters (such as LiDAR), research is of the lifeline components using the current generation
needed in developing ways that these technologies can be ef- of NEES facilities (Johnson et al., 2008; O’Rouke, 2007;
fectively used in acquiring inventory data, including physical Abdoun et al., 2009; Ivey et al., 2010; Shafieezadeh et al.,
attributes of different lifeline systems and at different scales. 2011). However, additional work is needed in designing
Pre-event planning will require that we learn from past these systems, considering their role within a larger net-
earthquake events. This will require us to vastly improve work, the interdependent nature of lifeline systems, and the
post-earthquake information acquisition and management. trade-offs in terms of cost and safety associated with various
Comprehensive and consistent information on the earthquake design decisions. One critical tool for performing this type
hazard, geological conditions and responses, structural dam- of analysis is regional risk assessment programs, such as
age, and economic and social impacts observed in previous HAZUS or REDARS. These programs have traditionally
earthquakes are invaluable in planning for future events. This been used to assess and quantify risks; however, they can also
will provide unprecedented information on the performance be the foundation for design of infrastructure systems based
of individual lifelines but will also provide critical infor- on system performance. One key element that goes into
mation on the interaction among lifeline systems. A major these analyses is a fragility or vulnerability curve. Fragility
effort of the future NEES program should be to develop a curves are critical not only for comparing the relative vul-
comprehensive effort among professional, governmental, nerability of different systems, but also for serving as input
and academic institutions to systematically collect, share, to cost-benefit studies and life-cycle cost (LCC) analyses.
and archive information on the effects of significant earth- Although cost-benefit analyses are often conducted for
quakes, including on the built and natural infrastructures, scenario events or deterministic analyses, probabilistic cost-
society, and the economy. The information will need to be benefit analyses are more appropriate for evaluation of the
stored, presented, and made available in structured electronic anticipated return on investment in a novel high-performance
data management systems. Moreover, the data management system, by considering the risk associated with damage and
systems should be designed with input from the communities cost due to potential seismic damage. Additionally, LCC
that they are intended to serve. analyses provide an effective approach for characterizing the
The use of regional seismic risk assessment is key to lifetime investment in a system. Models often incorporate
pre-event planning for various lifeline systems under condi- costs associated with construction, maintenance, upgrade,
tions of uncertainty. For example, detailed information on and at times deconstruction (Frangopol et al., 1997). The
the performance of the bridges in a transportation network, LCC models can be enhanced to also include costs associ-
coupled with traffic flow models, can inform decision makers ated with lifetime exposure to natural hazards (Chang and
on the most critical bridges for retrofit, and which routes Shinozuka, 1996). Such models offer viable approaches for
would best serve as evacuation routes following an earth- evaluating the relative performance of different structural
quake (Padgett et al., 2010). Significant progress has been systems. Given the increased emphasis on sustainability, the
made in understanding the seismic performance of lifeline next generation of LCC models can also include aspects of
components (e.g., bridges) via component and large-scale environmental impacts (both in terms of materials usage and
testing and analysis; however, much less is known about the construction, and deconstruction resulting from earthquake
operability of these components, and the system as a whole, damage) and weigh them against resilience. For example,
as a function of various levels of damage. The use of sen- although greater material investment is often required to
sors and data management systems would better allow us make infrastructure systems more resilient, this may make
to develop critical relationships between physical damage, them less sustainable. Conducting this systems-level design
spatio-temporal correlations, and operability. will require access to data on both structural parameters
Finally, as infrastructure systems continue to age and de- (e.g., bridge configuration), environmental, and operational
teriorate, it will be necessary to quantify the in situ condition data (such as traffic flows). One research challenge will be
of these systems so that we can properly assess the increased how to design our infrastructure systems using an “inverse-
vulnerability under earthquake loading. A dense network of problem” paradigm. For example, a goal in design might be
sensors, coupled with advanced prognostic algorithms, will to have power and telecommunications restored within four
enable the assessment of in situ conditions, which will allow hours of an earthquake event. Using this information as a
for better predictions of the expected seismic performance constraint, the systems (and subsystems) can be designed to
(Kim et al., 2006; Lynch and Loh, 2006; Glaser et al., 2007). achieve these targets.
The next generation of BIM or BrIM systems will
provide unprecedented information that can be used in the
Performance-Based Design of Lifeline Systems
performance-based seismic design community (Holness,
The earthquake performance of a lifeline system is 2 008). Building information modeling and associated
often closely correlated with the performance of a lifeline d ata acquisition sensors (e.g., 3-D scanning and map -
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70 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
A BUILT ENVIRONMENT FROM FOSSIL CARBON photosynthesis. For the energy economy, we all realize that
coal and petroleum and natural gas consist of chemically
John W. Halloran
reduced carbon and reduced hydrogen from ancient biomass.
Professor, Department of Materials Science and Engineering
Coal and oil are residues of the tissues of green creatures. It is
University of Michigan
clear that burning fossil-carbon returns to today’s atmosphere
the CO2 that was removed by photosynthesis eons ago.
Transformative Materials We do not often consider that our built environment is
also predominantly created from fossils. Cement is made
These white papers are intended to stimulate discus-
from carbonate limestone, consisting of ancient carbon
sion in this Workshop on Grand Challenges in Earthquake
dioxide chemically combined with calcium oxide in fossil
Engineering Research. I am a materials engineer with no
shells. Limestone is one of our planet’s great reservoirs of
expertise at all in earthquake engineering, so what can I
geo-sequestered carbon dioxide, removed from the air long
possibly have to say that could, in some way, stimulate the
ago. The reactivity of Portland cements come from the alka-
discussions of the experts at this workshop? This workshop
line chemical CaO, which is readily available because lime-
seeks “transformative solutions” for an earthquake-resilient
stone fossil rocks are abundant, and the CaO can be obtained
society involving, among other important issues, the design
by simple heating of CaCO3. However, this liberates about a
of the physical infrastructure. I will address points relating
ton of CO2 per ton of cement. This is fossil-CO2, returned to
to the design of the infrastructure, in terms of the most basic
the atmosphere after being sequestered as a solid. Limestone-
materials from which we build our infrastructure. I hope to
based cement—the mainstay of the built environment—is
address transformational change in infrastructural materials
not sustainable.
that could make our society more resilient not only to the
Steel is cheap because we have enormous deposits of
sudden shaking of the ground, but also to the gradual chang-
iron oxide ore. These iron ores are a kind of geochemical
ing of the climate. If you seek a change in the infrastructure
fossil that accumulated during the Great Oxygenation Event
large enough to be considered transformational for earth-
2 billion years ago, as insoluble ferric oxide formed from
quake resilience, can you also make the change large enough
oxygen produced by photosynthesis. Red iron oxide is a res-
to make a fundamental change in sustainability?
ervoir of the oxygen exhaled by ancient green creatures. We
I want to attempt to stimulate discussion not only on how
smelt iron ore using carbon from coal, so that carbon fossil-
to use steel and concrete to make us less vulnerable to shock,
ized for 300 million years combines with oxygen fossilized
but also to make us less vulnerable to climate change. I hope
for 2,000 million years to flood our current atmosphere with
to be provocative to the point of being outrageous, because
CO2. Every ton of steel is associated with about 1.5 tons of
I want you to think about abandoning steel and concrete. I
fossil-CO2 liberated in the modern atmosphere. We could, at
am going to suggest designing a built environment with more
some cost, capture and sequester the CO2 from limekilns and
resilient, lighter, stronger, and more sustainable materials
blast furnaces, or we could choose to smelt iron ore without
based on fossil carbon.
carbothermic reduction. I prefer to consider a different way
T he phrase “sustainable materials based on fossil
to use fossil resources, both in the energy economy and the
carbon”—seems like an oxymoron. To explain this, I must
built environment. We need something besides steel to resist
back up. Fossil resources are obviously not renewable, so are
tensile forces, and something besides concrete for resisting
not sustainable in the very long run. But in the shorter run,
compression.
the limit to sustainability is not the supply of fossil resources
In this white paper, I consider using the fossil-hydrogen
but the damage the fossil resources do to our climate. The
for energy, and the fossil-carbon for durable materials, an
element of particular concern is fossil-carbon, which was
approach called HECAM—Hydrogen Energy and Carbon
removed from the ancient atmosphere by living creatures and
Materials. This involves simple pyrolysis of coal, oil, or gas
stored as fossil-CO2 in carbonate rocks and as reduced fossil-
to extract fossil-hydrogen for use as a clean fuel. The fossil-
carbon in hydrocarbons like gas, oil, and coal. The difficulty
carbon is left in the condensed state, as solid carbon or as
is that industrial society liberates the fossil carbon to the
carbon-rich resins. Production of enough fossil-hydrogen to
atmosphere at rates much faster than contemporary photo-
satisfy the needs of the energy economy creates a very large
synthesis can deal with it. It is more sustainable to use fossil
amount of solid carbon and carbon-rich resins, which can
resources without liberating fossil-CO2. Can this be done?
satisfy the needs of the built environment.
A Modern World Based on Fossil Life
Fossil Hydrogen for Energy, Fossil Carbon for Materials
Modern industrial society enjoys prosperity in large part
Fossil fuels and building materials are the substances
because we are using great storehouses of materials fossil-
that our Industrial Society uses in gigatonne quantities. To
ized from ancient life. As the term “fossil fuels” implies,
continue to exploit our fossil resources, and still avoid cli-
much of our energy economy exploits the fossil residue of
mate change, we could stop burning fossil-carbon as fuel and
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APPENDIX B
stop burning limestone for lime. Coal, petroleum, and gas are Petroleum as a hydrogen ore offers about 40 percent of
used as “hydrogen ores” for energy and “carbon ores” for its HHV from hydrogen, and is an exceptionally versatile
materials, as presented in more detail previously (Halloran, carbon ore. The petrochemical industry exists to manipulate
2007). Note that this necessarily means that only a fraction the C/H ratio of many products producing many structural
of the fossil fuel is available for energy. This fraction ranges materials. Indeed carbon fibers—the premier high-strength
from about 60 percent for natural gas to about 20 percent for composite reinforcement—are manufactured from petro-
coal. This might seem like we are “wasting” 40 percent of leum pitch. Fabricated carbons—the model for masonry-
the gas or 80 percent of the coal—but it is wasted only if a like carbon-building materials—are manufactured from
valuable co-product cannot be found. If the solid carbon is petroleum coke.
used as a building material, the residual carbon could have Coal, with an elemental formulation around CH0.7, is the
more value as a solid than it did as a fuel. leanest hydrogen ore (but the richest carbon ore). When coal
Natural gas is a rich hydrogen ore, offering about 60 per- is heated in the absence of air (pyrolyzed), it partially melts
cent of its high heating value (HHV) from hydrogen combus- to a viscous liquid (metaplast). Hydrogen and hydrocarbon
tion. It is a relatively lean carbon ore, and if the hydrogen is gases evolve, which swells the viscous metaplast into foam.
liberated by simple thermal decomposition: CH4 = 2H2 + C. In metallurgical coke, the metaplast solidifies as a spongy
The solid carbon is deposited from the vapor. Such vapor- cellular solid. Coke is about as strong as ordinary Portland
deposited carbons are usually sooty nanoparticles, such as cement concrete (OPC), but only about one-third the density
carbon black, which might be of limited use in the built of OPC. A stronger, denser solid carbon can be obtained by
environment. However, it may be possible to engineer controlling the foaming during pyrolysis by various methods,
new processes to produce very high strength and high- or by pulverizing the coke and forming a carbon-bonded-
value vapor-deposited carbons, such as fibers, nanotubes, carbon with coal tar pitch (a resin from coal pyrolysis).
of pyrolyic carbons (Halloran, 2008). Pyrolytic carbon has Wiratmoko has demonstrated that these pitch-bonded cokes,
exceptional strength. Vapor-derived carbon fibers could be similar to conventional carbon masonry, can be 3-10 times
very strong. Carbon nanotubes, which are very promising, as strong at OPC, and stronger that high strength concrete
are made from the vapor phase, and the large-scale decom- or fired clay brick, at less than half the density of OPC
position of millions of tons of hydrocarbon vapors might and 60 percent the density of clay brick (Wiratmoko and
provide a path for mass production. Halloran, 2009). Like petroleum pitch, coal tar pitch can be
An independent path for methane-rich hydrocarbon used as a precursor for carbon fibers.
gases involves dehydrogenating the methane to ethylene: Although less than 20 percent of the HHV of coal comes
2CH4 = 2H2 + C2H4. Conversion to ethylene liberates only from the burning of the hydrogen, coal pyrolysis still can
half the hydrogen for fuel use, reducing the hydrogen energy be competitive for the manufacture of hydrogen for fuel.
yield to about 30 percent of the HHV of methane. However, Recently, Guerra conducted a thorough technoeconomic
the ethylene is a very useful material feedstock. It can be analysis of HECAM from coal, using a metallurgical coke
polymerized to polyethylene, the most important commodity plant as a model (Guerra, 2010). Hydrogen could be pro-
polymer. Polyethylene is mostly carbon (87 wt percent C). duced by coal pyrolysis with much less CO2 emission,
Perhaps it is more convenient to sequester the fossil-carbon compared to hydrogen from the standard method of steam
with some of the fossil-hydrogen as an easy-to-use white resin reforming of natural gas. The relative hydrogen cost depends
rather than as more difficult-to-use black elemental carbon. on the price of natural gas, the price of coal, and the market
We can consider the polyethylene route as “white HECAM,” value of the solid carbon co-product. Assuming that the solid
with the elemental carbon route as “black HECAM.” carbon could be manufactured as a product comparable to
Polyethylene from white HECAM could be very useful concrete masonry blocks, the hydrogen from coal pyrolysis is
in the built environment as a thermoplastic resin, the matrix cheaper if carbon masonry blocks would have about 80 per-
for fiber composites, or a binder for cementing aggregates. cent of market value of concrete blocks (based on 2007 coal
It should not be a difficult challenge to produce thermoset and gas prices).
grades, to replace hydraulic-setting concretes with chemi- Since the fossil-carbon is not burned in the HECAM pro-
cally setting composites. Moreover, if cost effective methods cess, the carbon dioxide emission is much lower. However,
can be found for producing ultrahigh molecular weight poly- much more coal has to be consumed for the same amount
ethylene (UHMWPE) fibers, we could envision construction of energy. This carbon, however, is not wasted, but rather
materials similar to the current SpectraTM or DyneemaTM put to productive use. Because HECAM combines energy
fibers, which are among the strongest of all manufactured and materials, comparisons of environmental impact are
materials. The tensile strength of these UHMWPE fibers more complicated. For one example (Halloran and Guerra,
are on the order of 2,400 MPa, more than 10 times higher 2011), we considered producing a certain quantity of energy
than the typical yield strength of grade 60 rebar steel. The (1 TJ) and a certain volume of building materials (185 cubic
density of steel is 8 times as large as polyethylene (PE), so meters). HECAM with hydrogen energy and carbon build-
ing materials emitted 47 tons of CO2 and required 236 m3 to
the specific strength can be 80 times better for UHWMPE.
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72 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
be removed by mining. Burning coal and using OPC for the States, carbon dioxide from power plants, steel mills, and
material emitted 150 tons of CO2 and required 245 m3 to be cement kilns is vented to the atmosphere at no monetary
removed from quarries and mines. cost to the manufacturer. It is likely in the future that climate
change abatement and greenhouse gas control will become a
concern for the building industry.
Can Carbon and Carbon-Rich Solids Be Used in the
Infrastructure?
Could Carbon-Rich Materials Be Better for Earthquake
The mechanical properties of carbons appear to be
Resilience?
favorable. For compression-resistors, carbons have been
made that offer significant advantages in strength and A non-specialist like me, at a workshop of experts like
strength/density ratio. Carbons are quite inert with respect to this, should not offer an opinion on this question. I simply
aqueous corrosion and should be durable. But of course the do not know. However, two of the strongest and lightest
properties of these carbons in real environments have never structural materials available for any type of engineering are
been tested. For tensile-resistors, carbon-fiber composites or carbon fibers and UHMWPE fibers, which are fossil-carbon
UHMWPE-fiber composites should be more than adequate, sequestering materials we contemplate for HECAM. The
because they should be stronger and much less dense than specific strength and specific stiffness of fiber composites
steel. Durability has yet to be demonstrated. Fire resistance based on fossil-carbon based materials should easily exceed
is an obvious issue. The ability to manufacture these mate- the requirements of structural steel. Masonry based on fossil-
rials in realistic volumes has yet to be demonstrated. An carbon might easily exceed the performance of ordinary
analogue to the setting of cement has not been demonstrated, Portland cement concrete, and could be stronger, lighter, and
although conventional chemical cross-linking appears to be more durable. Would this enable a more earthquake-resilient
viable. Construction methods using these materials have yet built infrastructure? Would it make a more environmentally
to be invented. sustainable infrastructure? I hope this is discussed in this
The cost of HECAM materials is not clearly defined, workshop.
largely because the materials cost is related to the value of
the energy co-product, in the same way that the energy cost
The 19th Century as a Guide for the 21th Century
is related to the value of the materials co-product. Guerra’s
preliminary analysis looks favorable, with each co-product When contemplating any grand challenge, it is useful to
subsidizing the other. Fundamentally, durable materials such look back into history. One hundred years ago, concrete and
as concrete and steel are worth much more per ton than coal, steel construction was still quite new. One hundred fifty years
and about the same as natural gas. Values in 2003 were about ago, structural steel was not available for construction. Two
$70/ton for OPC, $220/ton for rebar, $44/ton for coal, and hundred years ago, there was no modern cement. So let me
$88/ton for natural gas (Halloran, 2007). Carbon-rich solids go back two centuries, to 1811, and consider what was avail-
are lower in density (and stronger), so figuring on the basis able for the built environment. There was no structural steel
of volume suggests that converting some of the fossil fuels in 1811. Steel was then a very costly engineering material,
into construction materials should be economically feasible. used in swords and tools in relatively small quantities. Steel
But none of this has been demonstrated. was simply not available in the quantity and the cost needed
Similar carbon materials and composites are known for use as a structural material. There was no Portland cement
in aerospace technologies as high-performance, very high- concrete in 1811. Joseph Aspdin did not patent Portland
cost materials. Clearly aerospace-grade graphite fibers or cement until 1824.
SpectraTM fibers would not possibly be affordable in the But a great deal changed in a rather short time. In
tonnages required for infrastructure. For example, the tensile 1810, the Tickford Iron Bridge was built with cast iron, not
strength of about 1,400 MPa has been reported for carbon steel. By 1856, Bessemer had reduced the cost of steel, and
fibers produced from coal tar after relatively cheap process- Siemens had produced ductile steel plate. By 1872, steel was
ing (Halloran, 2007). These are not as strong as aerospace- used to build the Brooklyn Bridge. The Wainwright Build-
grade graphite fibers (5,600 MPa), but are comparable in ing in 1890 had the first steel framework. The first glass and
strength to the glass fibers now used in construction, which steel building (Peter Behrens’ AEG Turbine Factory Berlin)
have a tensile strength of 630 MPa as strands. So we must arrived in 1908. I.K. Brunel used Portland cement in his
stretch our imagination to envision construction-grade car- Thames Tunnel in 1828. Joseph Monier used steel-reinforced
bon fibers and UHMWPE fibers, perhaps not as strong but concrete in 1867, and the first concrete high-rise was built
not nearly as costly as aerospace grade. In the same sense, in Cincinnati in 1893. Perhaps a similar change can occur in
the steel used in rebar is not nearly the cost (or the quality) the 21st century, and perhaps our descendents will think us
of the steel used in aircraft landing gear. fools to burn useful materials like carbon.
Much will also depend on when (or if) there will be an
effective cost for CO2 emissions. At present in the United
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73
APPENDIX B
References Halloran, J. W., and Z. Guerra. 2011. Carbon building materials from coal
char: Durable materials for solid carbon sequestration to enable hydro -
Guerra, Z. 2010. Technoeconomic Analysis of the Co-Production of Hydro - gen production by coal pyrolysis. Pp. 61-71 in Materials Challenges in
gen Energy and Carbon Materials. Ph.D. Thesis, University of Michigan, Alternative and Renewable Energy: Ceramic Transactions, Vol. 224,
Ann Arbor. G. G. Wicks, J. Simon, R. Zidan, E. Lara-Curzio, T. Adams, J. Zayas, A.
Halloran, J. W. 2007. Carbon-neutral economy with fossil fuel-based Karkamkar, R. Sindelar, and B. Garcia-Diaz, eds. John Wiley & Sons,
hydrogen energy and carbon materials. Energy Policy 53:4839-4846. Inc., Hoboken, NJ.
Halloran, J. W. 2008. Extraction of hydrogen from fossil resources with Wiratmoko, A., and J. W. Halloran. 2009. Fabricated carbon from
production of solid carbon materials. International Journal of Hydrogen minimally-processed coke and coal tar pitch as a Carbon-Sequestering
Energy 33:2218-2224. Construction Material. Journal of Materials Science 34(8):2097-2100.
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74 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
UNCERTAINTY QUANTIFICATION AND EXASCALE equally drawn from a consideration of the stochastic forward
COMPUTING: OPPORTUNITIES AND CHALLENGES problem, or the stochastic optimization problem.
FOR EARTHQUAKE ENGINEERING
Uncertainty Quantification: Opportunities and Challenges
Omar Ghattas
Departments of Mechanical Engineering and Geological
Perhaps the central challenge facing the field of com-
Sciences
putational science and engineering today is: how do we
Institute for Computational Engineering & Sciences
quantify uncertainties in the predictions of our large-scale
The University of Texas at Austin
simulations? For many societal grand challenges, the “single
point” deterministic predictions issued by most contempo-
Introduction rary large-scale simulations of complex systems are just a
first step: to be of value for decision making (optimal design,
In this white paper we consider opportunities to ex-
optimal allocation of resources, optimal control, etc.), they
tend large-scale simulation-based seismic hazard and risk
must be accompanied by the degree of confidence we have
analysis from its current reliance on deterministic earth -
in the predictions. This is particularly true in the field of
quake simulations to those based on stochastic models. The
earthquake engineering, which historically has been a leader
simulations we have in mind begin with dynamic rupture,
in its embrace of stochastic modeling. Indeed, Vision 2025,
proceed through seismic wave propagation in large regions,
American Society of Engineers’ (ASCE’s) vision for what
and ultimately couple to structural response of buildings,
it means to be a civil engineer in the world of the future, as-
bridges, and other critical infrastructure—so-called “rupture-
serts among other characteristics that civil engineers (must)
to-rafters” simulations. The deterministic forward problem
serve as . . . managers of risk and uncertainty caused by
alone—predicting structural response given rupture, earth,
natural events. . . . (ASCE, 2009). Once simulations are
and structural models—requires petascale computing, and is
endowed with quantified uncertainties, we can formally pose
receiving considerable attention (e.g., Cui et al., 2010). The
the decision-making problem as an optimization problem
inverse problem—given observations, infer parameters in
governed by stochastic partial differential equations (PDEs)
source, earth, or structural models—increases the computa-
(or other simulation models), with objective and/or constraint
tional complexity by several orders of magnitude. Finally, ex-
functions that take the form of, for example, expectations,
tending the framework to the stochastic setting—where un-
and decision variables that represent design or control
certainties in observations and parameters are quantified and
parameters (e.g., constitutive parameters, initial/boundary
propagated to yield uncertainties in predictions—demands
conditions, sources, geometry).
the next major prefix in supercomputing: the exascale.
Uncertainty quantification arises in three fundamental
Although the anticipated arrival of the age of exascale
ways in large-scale simulation:
computing near the end of this decade is expected to provide
the raw computing power needed to carry out stochastic
• Stochastic inverse problem: Estimation of probability
r upture-to-rafters simulations, the mere availability of
densities for uncertain parameters in large-scale sim-
O(1018) flops per second peak performance is insufficient,
ulations, given noisy observations or measurements.
by itself, to ensure success. There are two overarching chal-
• Stochastic forward problem: Forward propagation of
lenges: (1) can we overcome the curse of dimensionality
the parameter uncertainties through the simulation to
to make uncertainty quantification (UQ) for large-scale
issue stochastic predictions.
earthquake simulations tractable, even routine; and (2) can
• Stochastic optimization: Solution of the stochastic
we design efficient parallel algorithms for the deterministic
optimization problems that make use of statistics of
forward simulations at the heart of UQ that are capable of
these predictions as objectives and/or constraints.
scaling up to the expected million nodes of exascale systems,
and that also map well onto the thousand-threaded nodes
Although solution of stochastic inverse, forward, or
that will form those systems? These two questions are wide
optimization problems can be carried out today for smaller
open today; we must begin to address them now if we hope
models with a handful of uncertain parameters, these tasks
to overcome the challenges of UQ in time for the arrival of
are computationally intractable for complex systems char-
the exascale era.
acterized by large-scale simulations and high-dimensional
We illustrate several of the points in this white paper with
p arameter spaces using contemporary algorithms (see,
examples taken from wave propagation, which is just one
e.g., Oden et al., 2011). Moreover, existing methods suffer
component of the end-to-end rupture-to-rafters simulation,
from the curse of dimensionality: simply throwing more
but typically the most expensive (some comments are made
processors at these problems will not address the basic diffi-
on the other components). Moreover, we limit the discussion
culty. We need fundamentally new algorithms for estimation
of UQ to the stochastic inverse problem. Despite the narrow-
and propagation of, and optimization under, uncertainty in
ing of focus, the conclusions presented here could have been
large-scale simulations of complex systems.
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75
APPENDIX B
To focus our discussion, in the remainder of this section However, we are interested in not just point estimates of the
we will consider challenges and opportunities associated best-fit parameters, but also a complete statistical descrip-
with the first task above, that of solving stochastic inverse tion of all the parameter values that is consistent with the
problems, and employing Bayesian methods of statistical data. The Bayesian approach does this by reformulating
inference. This will be done in the context of the modeling the inverse problem as a problem in statistical inference,
of seismic wave propagation, which typically constitutes the incorporating uncertainties in the measurements, the forward
most expensive component in simulation-based rupture-to- model, and any prior information on the parameters. The
rafters seismic hazard assessment. solution of this inverse problem is the so-called “posterior”
The problem of estimating uncertain parameters in a probability densities of the parameters, which reflects the
simulation model from observations is fundamentally an in- degree of credibility we have in their values (Kaipio and
verse problem. The forward problem seeks to predict output Somersalo, 2005; Tarantola, 2005). Thus we are able to
observables, such as seismic ground motion at seismometer quantify the resulting uncertainty in the model parameters,
locations, given the parameters, such as the heterogeneous taking into account uncertainties in the data, model, and prior
elastic wave speeds and density throughout a region of inter- information. Note that the term “parameter” is used here in
est, by solving the governing equations, such as the elastic (or the broadest sense—indeed, Bayesian methods have been
poroelastic, or poroviscoelastoplastic) wave equations. The developed to infer uncertainties in the form of the model as
forward problem is usually well posed (the solution exists, is well (so-called structural uncertainties).
unique, and is stable to perturbations in inputs), causal (later- The Bayesian solution of the inverse problem proceeds
time solutions depend only on earlier time solutions), and as follows. Suppose the relationship between observable
local (the forward operator includes derivatives that couple outputs y and uncertain input parameters p is denoted by
nearby solutions in space and time). The inverse problem, y = f(p, e), where e represents noise due to measurement and/
on the other hand, reverses this relationship by seeking to or modeling errors. In other words, given the parameters p,
estimate uncertain (and site-specific) parameters from (in the function f(p) invokes the solution of the forward prob-
situ) measurements or observations. The great challenge of lem to yield y, the predictions of the observables. Suppose
also that we have the prior probability density πpr(p), which
solving inverse problems lies in the fact that they are usually
ill-posed, non-causal, and non-local: many different sets of encodes the confidence we have in prior information on
parameter values may be consistent with the data, and the in- the unknown parameters (i.e., independent of information
verse operator couples solution values across space and time. from the present observations), and the likelihood function
π(yobs|p), which describes the conditional probability that the
Non-uniqueness in the inverse problem stems in part
from the sparsity of data and the uncertainty in both measure- parameters p gave rise to the actual measurements yobs. Then
ments and the model itself, and in part from non-convexity Bayes’ theorem of inverse problems expresses the posterior
probability density of the parameters, πpost, given the data
of the parameter-to-observable map (i.e., the solution of the
forward problem to yield output observables, given input yobs, as the conditional probability
parameters). The popular approach to obtaining a unique
πpost (p) = π(p|yobs) = k πpr(p) π(yobs|p)
“solution” to the inverse problem is to formulate it as an opti- (1)
mization problem: minimize the misfit between observed and
predicted outputs in an appropriate norm while also minimiz- where k is a normalizing constant. The expression (1) pro-
ing a regularization term that penalizes unwanted features vides the statistical solution of the inverse problem as a
of the parameters. This is often called Occam’s approach: probability density for the model parameters p.
find the “simplest” set of parameters that is consistent with Although it is easy to write down expressions for the
the measured data. The inverse problem thus leads to a non- posterior probability density such as (1), making use of
linear optimization problem that is governed by the forward these expressions poses a challenge, because of the high
simulation model. When the forward model takes the form dimensionality of the posterior probability density (which is
of PDEs (as is the case with the wave propagation models a surface of dimension equal to the number of parameters)
considered here), the result is an optimization problem that and because the solution of the forward problem is required
is extremely large-scale in the state variables (displacements, at each point on this surface. Straightforward grid-based
stresses or strains, etc.), even when the number of inversion sampling is out of the question for anything other than a few
parameters is small. More generally, because of the hetero- parameters and inexpensive forward simulations. Special
geneity of the earth, the uncertain parameters are fields, and sampling techniques, such as Markov chain Monte Carlo
when discretized result in an inverse problem that is very (MCMC) methods, have been developed to generate sample
large scale in the inversion parameters as well. ensembles that typically require many fewer points than grid-
Estimation of parameters using the regularization ap- based sampling (Kaipio and Somersalo, 2005; Tarantola,
proach to inverse problems as described above will yield an 2005). Even so, MCMC approaches will become intractable
estimate of the “best” parameter values that simultaneously as the complexity of the forward simulations and the dimen-
fit the data and minimize the regularization penalty term. sion of the parameter spaces increase. When the parameters
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76 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
are a (suitably discretized) field (such as density or elastic iterations, for which the (formally dense, of dimension in the
wave speeds of a heterogeneous earth), and when the for- millions) Hessian matrix is never formed, and only its action
ward PDE requires many hours to solve on a supercomputer on a vector (which requires a forward/adjoint pair of solves)
for a single point in parameter space (such as seismic wave is required (Akçelik et al., 2005). These fast deterministic
propagation in large regions), the entire MCMC enterprise methods can be capitalized upon to accelerate sampling
of the posterior density πpost(p), via Langevin dynamics.
collapses dramatically.
The central problem in scaling up the standard MCMC Long-time trajectories of the Langevin equation sample the
methods for large-scale forward simulations and high- posterior, and integrating the equation requires evaluation
dimensional parameter spaces is that this approach is of the gradient at each sample point. More importantly, the
purely black-box, i.e., it does not exploit the structure of the equation can be preconditioned by the inverse of the Hessian,
parameter-to-observable map f(p). The key to overcoming in which case its time discretization is akin to a stochastic
the curse of dimensionality, we believe, lies in effectively Newton method, permitting us to recruit many of the ideas
exploiting the structure of this map to implicitly or explicitly from deterministic large-scale Newton methods developed
reduce the dimension of both the parameter space as well over the past several decades.
as the state space. The motivation for doing so lies in the This stochastic Newton method has been applied to
fact that the data are often informative about just a fraction a nonlinear seismic inversion problem, with the medium
of modes of the parameter field, because of ill-posedness parameterized into 65 layers (Martin et al., In preparation).
Figure 1 indicates just O(102) samples are necessary to
of the inverse problem. Another way of saying this is that
the Jacobian of the parameter-to-observable map is typically adequately sample the (non-Gaussian) posterior density,
a compact operator, and thus can be represented effectively while a reference (non-derivative) MCMC method (Delayed
using a low-rank approximation—that is, it is sparse with Rejection Adaptive Metropolis) is nowhere near converged
after even O(105) samples. Moreover, the convergence of the
respect to some basis (Flath et al., 2011). The remaining
dimensions of parameter space that cannot be inferred from method appears to be independent of the problem dimen-
the data are typically informed by the prior; however, the sion when scaling from 65 to 1,000 parameters. Although
prior does not require solution of forward problems, and is the forward problem is still quite simple (wave propagation
thus cheap to compute. Compactness of the parameter-to- in a 1D layered medium), and the parameter dimension is
observable map suggests that the state space of the forward moderate (up to 1,000 parameters), this prototype example
problem can be reduced as well. A number of current ap- demonstrates the considerable speedups that can be had if
proaches to model reduction for stochastic inverse problems problem structure is exploited, as opposed to viewing the
show promise. These range from Gaussian process response simulation as a black box.
surface approximation of the parameter-to-observable map
(Kennedy and O’Hagan, 2001), to projection-type forward
Exascale Computing: Opportunities and Challenges
model reductions (Galbally et al., 2010; Lieberman et al.,
2010), to polynomial chaos approximations of the stochastic The advent of the age of petascale computing—and
forward problem (Narayanan and Zabaras, 2004; Ghanem the roadmap for the arrival of exascale computing around
and Doostan, 2006; Marzouk and Naim, 2009), to low-rank 2018—bring unprecedented opportunities to address soci-
approximation of the Hessian of the log-posterior (Flath et etal grand challenges in earthquake engineering, and more
al., 2011; Martin et al., In preparation). In the remainder of generally in such fields as biology, climate, energy, manu-
this section, as just one example of the above ideas, we illus- facturing, materials, and medicine (Oden et al., 2011). But
trate the dramatic speedups that can be achieved by exploit- the extraordinary complexity of the next generation of high-
ing derivative information of the parameter-to-observable performance computing systems—with hundreds of thou-
map, and in particular the properties of the Hessian. sands to millions of nodes, each having multiple processors,
Exploiting derivative information has been the key to each with multiple cores, heterogeneous processing units,
overcoming the curse of dimensionality in deterministic in- and deep memory hierarchies—presents tremendous chal-
verse and optimization problems (e.g., Akçelik et al., 2006), lenges for scientists and engineers seeking to harness their
and we believe it can play a similar critical role in stochastic raw power (Keyes, 2011). Two central challenges arise: how
inverse problems as well. Using modern adjoint techniques, do we create parallel algorithms and implementations that
gradients can be computed at a cost of a single linearized (1) scale up to and make effective use of distributed memory
systems with O(105-106) nodes and (2) exploit the power of
forward solve, as can actions of Hessians on vectors. These
tools, combined with specialized solvers that exploit the fact shared memory massively multi-threaded individual nodes?
that many ill-posed inverse problems have compact data mis- Although the first challenge cited is a classical difficulty,
fit operators, often permit solution of deterministic inverse we can at least capitalize on several decades of work on
problems in a dimension-independent (and typically small) constructing, scaling, analyzing, and applying parallel algo-
number of iterations. Deterministic inverse problems have rithms for distributed memory high-performance computing
been solved for millions of parameters and states in tens of systems. Seismic wave propagation, in particular, has had a
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77
APPENDIX B
Figure 1 Left: Comparison of number of points taken for sampling posterior density for a 65-dimensional seismic inverse problem to iden -
tify the distribution of elastic moduli for a layered medium, from reflected waves. DRAM (black), unpreconditioned Langevin (blue), and
Stochastic Newton (red) sampling methods are compared. Convergence indicator is multivariate potential scale reduction factor, for which a
value of unity indicates convergence. Stochastic Newton requires three orders of magnitude fewer sampling points than the other methods.
Right: Comparison of convergence of stochastic Newton method for 65 and 1,000 dimensions suggests dimension independence.
SOURCE: Courtesy of James Martin, University of Texas at Austin.
long history of being at the forefront of applications that can for inverse problems, in which the material model changes
exploit massively parallel supercomputing, as illustrated, for at each inverse iterations, resulting in a need to remesh re-
example, by recent Gordon Bell Prize finalists and winners peatedly. The results in Table 1 demonstrate that excellent
(Bao et al., 1996; Akçelik et al., 2003; Komatitsch et al., scalability on the largest contemporary supercomputers can
2003; Burstedde et al., 2008; Carrington et al., 2008; Cui et be achieved for the wave propagation solution, even when
al., 2010). To illustrate the strides that have been made and the taking meshing into account, by careful numerical algorithm
barriers that remain to be overcome, we provide scalability design and implementation. In this case, a high-order ap-
results for our new seismic wave propagation code. This code proximation in space (as needed to control dispersion errors)
solves the coupled acoustic-elastic wave equations in first combined with a discontinuous Galerkin formulation (which
order (velocity-strain) form using a discontinuous Galerkin provides stability and optimal convergence) together provide
spectral element method in space and explicit Runge Kutta a higher computation to communication ratio, facilitating
in time (Wilcox et al., 2010). The equations are solved in a
spherical earth model, with properties given by the Prelimi-
nary Reference Earth Model. The seismic source is a double
couple point source with a Ricker wavelet in time, with cen- Table 1 Strong scaling of discontinuous Galerkin spectral
tral frequency of 0.28 Hz. Sixth-order spectral elements are element seismic wave propagation code on the Cray XT-5
used, with at least 10 points per wavelength, resulting in 170 at ORNL (Jaguar), for a number of cores ranging from
million elements and 525 billion unknowns. Mesh generation 32K to 224K.
is carried out in parallel prior to wave propagation, to ensure
# proc meshing wave prop par eff
that the mesh respects material interfaces and resolves local cores time* (s) per step (s) wave Tflops
wavelengths. Table 1 depicts strong scaling of the global
32,460 6.32 12.76 1.00 25.6
seismic wave propagation code to the full size of the Cray 65,280 6.78 6.30 1.01 52.2
XT5 supercomputer (Jaguar) at Oak Ridge National Labora- 130,560 17.76 3.12 1.02 105.5
tory (ORNL). The results indicate excellent strong scalability 223,752 47.64 1.89 0.99 175.6
for the overall code (Burstedde et al., 2010). Note that mesh Meshing time is the time for parallel generation of the mesh (adapted to
generation costs about 25 time steps (tens of thousands that local wave speed) prior to wave propagation solution; wave prop per step
are typically required), so that the cost of mesh generation is is the runtime in seconds per time step of the wave propagation solve; par
eff wave is the parallel efficiency associated with strong scaling; and Tflops
negligible for any realistic simulation. Not only is online par-
is the double precision flop rate in teraflops/s.
allel mesh generation important for accessing large memory
SOURCE: Courtesy of Carsten Burstedde, Georg Stadler, and Lucas
and avoiding large input/output (I/O), but it becomes crucial Wilcox, University of Texas at Austin.
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78 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
better latency tolerance and scalability to O(105) cores, while alone on large clusters and supercomputers. This trend will
also resulting in dense local operations that ensure better only continue to accelerate.
cache performance. Explicit time integration avoids a global Current high-end GPUs are capable of a teraflop per
system solve, while the space filling curve-based ordering of second peak performance, which offers a spectacular two
the mesh results in better locality. orders of magnitude increase over conventional CPUs. The
However, if we consider full rupture-to-rafters simu- critical question, however, is: can this performance be ef-
lations beyond wave propagation, new and greater chal - fectively harnessed by scientists and engineers to acceler-
lenges arise. Rupture modeling may require dynamic ate their simulations? The new generation of many-core
mesh adaptivity to track the evolving rupture front, and and accelerated chips performs well on throughput-oriented
historically this has presented significant challenges on tasks, such as those supporting computer graphics, video
highly parallel systems. In recent work, we have designed gaming, and high-definition video. Unfortunately, a different
scalable dynamic mesh refinement and coarsening algo- picture emerges for scientific and engineering computations.
rithms that scale to several hundred thousand cores, present Although certain specialized computations (such as dense
little overhead relative to the PDE solution, and support matrix problems and those with high degrees of locality) map
complex geometry and high-order continuous/discontinuous well onto modern many-core processors and accelerators,
discretization (Burstedde et al., 2010). Although they have the mainstream of conventional scientific and engineering
not yet been applied to dynamic rupture modeling, we ex - simulations—including the important class of PDE solvers—
pect that the excellent scalability observed in Table 1 will be involve sparse operations, which are memory bandwidth-
retained. On the other hand, coupling of wave propagation bound, not throughput-bound. As a result, the large increases
with structural response presents much greater challenges, in the number of cores on a processor, which have occurred
because of the need to solve the structural dynamics equa - without a concomitant increase in memory bandwidth (be-
tions with an implicit method (earthquakes usually excite cause of the large cost and low demand from the consumer
structures in their low modes, for which explicit methods market), deliver little increase in performance. Indeed, sparse
are highly wasteful). Scalability of implicit solvers to hun - matrix computations often achieve just 1-2 percent of peak
dreds of thousands of cores and beyond remains extremely performance on modern GPUs (Bell and Garland, 2009).
challenging because of the global communication required Future peak performance increases will continue to come in
by effective preconditioners, though progress continues to the form of processors capable of massive hardware multi-
be made (Yang, 2006). Finally, adding nonlinear constitu- threading. It is now up to scientists and engineers to adapt
tive models or finite deformations into the soil or structural to this new architectural landscape; the results thus far have
behavior greatly increases parallel complexity, because of been decidedly mixed, with some regular problems able to
the need for dynamic load balancing and possibly local time achieve large speedups, but many sparse unstructured prob-
stepping. It is fair to say that the difficulties associated with lems unable to benefit.
scaling end-to-end rupture-to-rafters simulations are formi - Here we provide evidence of the excellent GPU perfor-
dable, but not insurmountable if present rates of progress mance that can be obtained by a hybrid parallel CPU-GPU
can be sustained (and accelerated). implementation of the discontinuous Galerkin spectral
On the other hand, the second challenge identified element seismic wave propagation code described above
above—exploiting massive on-chip multithreading—has (Burstedde et al., 2010). The mesh generation component
emerged in the past several years and presents new and perni- remains on the CPU, because of the complex, dynamic data
cious difficulties, particularly for PDE solvers. A sea change structures involved, while the wave propagation solution has
is under way in the design of the individual computer chips been mapped to the GPU, capitalizing on the local dense
that power high-end supercomputers (as well as scientific blocks that stem from high-order approximation. Table 2 pro-
workstations). These chips have exploded in complexity, and vides weak scaling results on the Longhorn GPU cluster at
now support multiple cores on multiple processors, with deep the Texas Advanced Computing Center (TACC), which con-
memory hierarchies and add-on accelerators such as graphic sists of 512 NVIDIA FX 5800 GPUs, each with 4GB graph-
processing units (GPUs). The parallelism within compute ics memory, and 512 Intel Nehalem quad core processors
nodes has grown remarkably in recent years, from the single connected by QDR InfiniBand interconnect. The combined
core processors of a half-decade ago to the hundreds of cores mesh generation–wave propagation code is scaled weakly
of modern GPUs and forthcoming many-core processors. from 8 to 478 CPUs/GPUs, while maintaining between 25K-
These changes have been driven by power and heat dissipa- 28K seventh-order elements per GPU (the adaptive nature
tion constraints, which have dictated that increased perfor- of mesh generation means we cannot precisely guarantee
mance cannot come from increasing the speed of individual a fixed number of elements). The largest problem has 12.3
cores, but rather by increasing the numbers of cores on a million elements and 67 billion unknowns. As can be seen
chip. As a result, computational scientists and engineers in- in the table, the scalability of the wave propagation code is
creasingly must contend with high degrees of fine-grained exceptional; parallel efficiency remains at 100 percent in
parallelism, even on their laptops and desktop systems, let weak scaling over the range of GPUs considered. Moreover,
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79
APPENDIX B
Table 2 Weak scaling of discontinuous Galerkin spectral element seismic wave propagation code on the Longhorn cluster at
TACC.
#GPUs #elem mesh (s) transf (s) wave prop par eff wave Tflops (s.p.)
8 224048 9.40 13.0 29.95 1.000 0.63
64 1778776 9.37 21.3 29.88 1.000 5.07
256 6302960 10.6 19.1 30.03 0.997 20.3
478 12270656 11.5 16.2 29.89 1.002 37.9
#elem is number of 7th-order spectral elements; mesh is time to generate the mesh on the CPU; tranf is the time to transfer the mesh and other initial data
from CPU to GPU memory; wave prop is the normalized runtime (in µsec per time step per average number of elements per GPU); par eff wave is the parallel
efficiency of the wave propagation solver in scaling weakly from 8 to 478 GPUs; and Tflops is the sustained single precision flop rate in teraflops/s. The wall-
clock time of the wave propagation solver is about 1 second per time step; meshing and transfer time are thus completely negligible for realistic simulations.
SOURCE: Courtesy of Tim Warburton and Lucas Wilcox.
the wave propagation solver sustains around 80 gigaflops/s rafters deterministic forward earthquake simulations map
(single precision), which is outstanding performance for an poorly to modern consumer-market-driven, throughput-
irregular, sparse (albeit high-order) PDE solver. oriented chips with their massively multithreaded accel-
Although these results bode well for scaling earthquake erators. Improvements in computer science techniques (e.g.,
simulations to future multi-petaflops systems with massively auto-parallelizing and auto-tuning compilers) are important
multi-threaded nodes, we must emphasize that high-order- but insufficient: this problem goes back to the underlying
discretized (which enhance local dense operations), explicit mathematical formulation and algorithms. Finally, even if we
(which maintain locality of operations) solvers are in the could exploit parallelism on modern and emerging systems at
sweet spot for GPUs. Implicit sparse solvers (as required in all levels, the algorithms at our disposal for UQ suffer from
structural dynamics) are another story altogether: the sparse the curse of dimensionality; entirely new algorithms that can
matrix-vector multiply alone (which is just the kernel of an scale to large numbers of uncertain parameters and expensive
iterative linear solver, and much more readily parallelizable underlying simulations are critically needed.
than the preconditioner) often sustains only 1-2 percent of It is imperative that we overcome the challenges of
peak performance in the most optimized of implementations designing algorithms and models for stochastic rupture-to-
(Bell and Garland, 2009). Adding nonlinear constitutive rafters simulations with high-dimensional random parameter
behavior and adaptivity for rupture dynamics further com- spaces that can scale on future exascale systems. Failure to
plicates matters. In these cases, the challenges of obtaining do so risks undermining the substantial investments being
good performance on GPU and like systems appear over- made by federal agencies to deploy multi-petaflops and
whelming, and will require a complete rethinking of how we exaflops systems. Moreover, the lost opportunities to harness
model, discretize, and solve the governing equations. the power of new computing systems will ultimately have
consequences many times more severe than mere hardware
costs. The future of computational earthquake engineer-
Conclusions
ing depends critically on our ability to continue riding the
The coming age of exascale supercomputing prom- exponentially growing curve of computing power, which is
ises to deliver the raw computing power that can facilitate now threatened by architectures that are hostile to the com-
data-driven, inversion-based, high-fidelity, high-resolution putational models and algorithms that have been favored.
rupture-to-rafters simulations that are equipped with quan- Never before has there been as wide a gap between the
tified uncertainties. This would pave the way to rational capabilities of computing systems and our ability to exploit
simulation-based decision making under uncertainty in such them. Nothing less than a complete rethinking of the entire
areas as design and retrofit of critical infrastructure in earth- end-to-end enterprise—beginning with the mathematical
quake-prone regions. However, making effective use of that formulations of stochastic problems, leading to the manner
in which they are approximated numerically, the design of
power is a grand challenge of the highest order, owing to the
the algorithms that carry out the numerical approximations,
extraordinary complexity of the next generation of computing
systems. Scalability of the entire end-to-end process—mesh and the software that implements these algorithms—is im-
generation, rupture modeling (including adaptive meshing), perative in order that we may exploit the radical changes in
seismic wave propagation, coupled structural response, and architecture with which we are presented, to carry out the
analysis of the outputs—is questionable on contemporary stochastic forward and inverse simulations that are essential
supercomputers, let alone future exascale systems with three for rational decision making. This white paper has provided
orders of magnitude more cores. Even worse, the sparse, several examples—in the context of forward and inverse
unstructured, implicit, and adaptive nature of rupture-to- seismic wave propagation—of the substantial speedups
OCR for page 80
80 GRAND CHALLENGES IN EARTHQUAKE ENGINEERING RESEARCH
that can be realized with new formulations, algorithms, and Cui, Y., K. B. Olsen, T. H. Jordan, K. Lee, J. Zhou, P. Small, D. Roten,
G. Ely, D.K. Panda, A. Chourasia, J. Levesque, S. M. Day, and P.
implementations. Significant work lies ahead to extend these
Maechling. 2010. Scalable earthquake simulation on petascale super-
and other ideas to the entire spectrum of computations under- computers. In SC10: Proceedings of the International Conference for
lying simulation-based seismic hazard and risk assessment. High Performance Computing, Networking, Storage, and Analysis,
ACM/IEEE.
Flath, H. P., L. C. Wilcox, V. Akçelik, J. Hill, B. Van Bloemen Waanders,
Acknowledgments and O. Ghattas. 2011. Fast algorithms for Bayesian uncertainty quan -
tification in large-scale linear inverse problems based on low-rank
Figure 1 is the work of James Martin; Table 1 is the work partial Hessian approximations. SIAM Journal on Scientific Computing
of Carsten Burstedde, Georg Stadler, and Lucas Wilcox; and 33(1):407-432.
Table 2 is the work of Tim Warburton and Lucas Wilcox. This Galbally, D., K. Fidkowski, K. Willcox, and O. Ghattas. 2010. Nonlinear
work was supported by AFOSR grant FA9550-09-1-0608, model reduction for uncertainty quantification in large-scale inverse
problems. International Journal for Numerical Methods in Engineering
NSF grants 0619078, 0724746, 0749334, and 1028889, and
81:1581-1608.
DOE grants DEFC02-06ER25782 and DE-FG02-08ER25860. Ghanem, R. G., and A. Doostan. 2006. On the construction and analysis of
stochastic models: Characterization and propagation of the errors asso-
ciated with limited data. Journal of Computational Physics 217:63-81.
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