ENDORSING PARTNERS

Engineering Infrastructure for
resilience and growth

The following are confirmed contributors to the ...
http://www.sandia.gov/CasosEngineering

Engineering Infrastructure for
Resilience and Growth
Theresa Brown
Sandia National...
Infrastructures as Complex Adaptive Systems (CAS)
 A CAS is a system in which the structure modifies
to enable success in...
What is changing in the infrastructure environment?
 Climate (temperature,





precipitation)
Population (growth,
re...
Engineering Future Infrastructure

Modified from Brown et al., 2011

ISNGI
October 2013

5
Engineering Infrastructure for Resilience to Climate Change

 Are there structural changes to national infrastructures th...
What kinds of structural changes are possible?
 Networks and Network Theory Insights
‒ Greater connectivity makes network...
Climate – Water – Energy- Food
Climate
Rainfall/Runoff Watershed Modeling
Recharge
Groundwater
Modeling

Runoff
River/Rese...
Changes in Precipitation -Temporal and Spatial Scaling
Projected changes in precipitation from global
models with uncertai...
Water Availability
Physical boundaries for hydrology (watersheds)
can be used to evaluate regional water supply

Projected...
Structural Characteristics of Regional Water Supply
• Emerged/Evolving
•
•
•

•

Population centers developed near major s...
Reactive - Consequence Management
Aging – incremental upgrades to some; next
generation equipment for others
Natural Disas...
Are there structural changes that could increase
water supply resilience?
 Manage by emergence and
control (Choi et al 20...
Understanding How Structure Influences Risks:
requires dynamic or iterative solutions

Going beyond water
resilience - req...
What capabilities do we need in order to better design for
resilience and growth?
 Better understanding through modeling ...
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SMART International Symposium for Next Generation Infrastructure: Engineering Infrastructures for Resilience and Growth

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A presentation conducted by Dr Theresa Brown Distinguished Member of Technical Staff, Sandia National Laboratories, United States of America. Presented on Tuesday the 1st of October 2013

Civil infrastructure and its impact on societies can tell us different stories Infrastructures are complex, adaptive, systems of systems. We have engineered their elements, but their topology emerges and changes over time as population grows and moves and as we learn how they fail
and can be protected from failure.  As we expand our modelling capability to better anticipate and improve our understanding of these systems we tend to focus on
optimization of their performance to increase efficiency and reduce costs. Over the past decade, we’ve expanded
the use of models to evaluate risks to infrastructures. 
Modelling is expanding to support the goal of resilient design for future infrastructures under the stresses of a
changing global climate, population growth, evolving demand and geologic conditions. This discussion explores the innovations in modelling and analysis needed to support engineering designs that improve system resilience to a wide range of future stresses and natural disasters.

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SMART International Symposium for Next Generation Infrastructure: Engineering Infrastructures for Resilience and Growth

  1. 1. ENDORSING PARTNERS Engineering Infrastructure for resilience and growth The following are confirmed contributors to the business and policy dialogue in Sydney: • Rick Sawers (National Australia Bank) • Nick Greiner (Chairman (Infrastructure NSW) Monday, 30th September 2013: Business & policy Dialogue Tuesday 1 October to Thursday, Dialogue 3rd October: Academic and Policy Presented by: Dr Theresa Brown, Distinguished Member of Technical Staff, Sandia National Laboratories, United States of America www.isngi.org www.isngi.org
  2. 2. http://www.sandia.gov/CasosEngineering Engineering Infrastructure for Resilience and Growth Theresa Brown Sandia National Laboratories ISNGI October 2013 2013-8202C Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.
  3. 3. Infrastructures as Complex Adaptive Systems (CAS)  A CAS is a system in which the structure modifies to enable success in its environment (Johnson et al. 2012) ‒ structure and behavior are products of all the perturbations the system has experienced and modifications it has implemented. ‒ certain structural characteristics emerge, hierarchical and modular, with simple rules for interaction among the elements  Infrastructures involve multiple interacting CAS or Complex Adaptive Systems of Systems (CASoS)  Successful adaptation to disruptions is a characteristic of resilience, but it can lead to highly optimized tolerance and robust-yet-fragile properties (Carlson and Doyle, 1999) ISNGI October 2013 3
  4. 4. What is changing in the infrastructure environment?  Climate (temperature,     precipitation) Population (growth, redistribution) Technology (transitional, transformational) Consumer Expectations (quality, reliability and/or cost of service) Economy  Changes in infrastructure   supply and demand (x, y, t) ‒ Capacity to meet demand ‒ Quality of service ‒ Costs Changes in society ‒ Productivity ‒ Population health and wealth Changes in risks ‒ Threats ‒ Vulnerabilities ‒ Consequences ISNGI October 2013 4
  5. 5. Engineering Future Infrastructure Modified from Brown et al., 2011 ISNGI October 2013 5
  6. 6. Engineering Infrastructure for Resilience to Climate Change  Are there structural changes to national infrastructures that will keep them resilient to the combination of possible stresses that could occur over the next 10 100 years? Changing Drought Frequency Increasing Weather-Related Power Outages ISNGI October 2013 6
  7. 7. What kinds of structural changes are possible?  Networks and Network Theory Insights ‒ Greater connectivity makes networks more robust to random, node or link failures ‒ Centralization allows greater control, creates potential single points of failure ‒ Distribution decreases impact of directed attack; less control  System Dynamics ‒ Balancing loops to prevent death spirals Climate change is not a random failure nor is it a directed attack; it is a long-term global change with large uncertainty in the impacts on regional and temporal climate variability and rates of change ISNGI October 2013 7
  8. 8. Climate – Water – Energy- Food Climate Rainfall/Runoff Watershed Modeling Recharge Groundwater Modeling Runoff River/Reservoir Routing Water Available Rights Water Water Demand Water Allocation Consequence Analysis Environmental Economic Damage Water Delivery Social ISNGI October 2013 8
  9. 9. Changes in Precipitation -Temporal and Spatial Scaling Projected changes in precipitation from global models with uncertainty To create a model of regional precipitation that includes realistic variability (spatially and temporally) 0.20 0.15 % Deviation from 2000-2009 Mean IPCC Ensemble of 53 Climate model runs transformed to exceedance probability. 0.10 0.05 0.00 -0.05 -0.10 -0.15 -0.20 2000 Based on Backus et al., 2010 and 2012 2010 2020 Year 2030 2040 2050 ISNGI October 2013 9
  10. 10. Water Availability Physical boundaries for hydrology (watersheds) can be used to evaluate regional water supply Projected minimum surface water availability by 2035 (summer demand adjusted for population growth : projected annual low flow conditions) Projected Changes population changes and changes in economic activity impact water demand Backus et al., 2010 Projected (sustainable) groundwater availability 2035 (pumping : recharge) Tidwell, 2013 ISNGI October 2013 10
  11. 11. Structural Characteristics of Regional Water Supply • Emerged/Evolving • • • • Population centers developed near major surface water features Population growth increases water demand and contamination; but provides economic power, growth and diversity Risk management/Infrastructure development – water irrigation and distribution systems, allocation rules, flood control features (dams, levees); storage; treatment; use of groundwater; crossbasin water diversion projects; control systems Technology and population growth drive expansion • Mix of natural and engineered elements • • • Storage (reservoirs, aquifers, tanks) influences resilience to supply perturbations  Duration and magnitude dependent  Changes risks Transportation networks (rivers, streams, pipes and pumps) Water Treatment (filtration, chemical) • Competing uses • Water for transportation (navigable locks and dams), ISNGI October 2013 11
  12. 12. Reactive - Consequence Management Aging – incremental upgrades to some; next generation equipment for others Natural Disaster – population displaced; desire to restore natural barriers and increase engineered barriers (design basis) sea walls for surge, dams for flooding, underground power lines Hurricane Katrina landfall, 8/29/2005 Source: NOAA Satellite Image Drought – prioritizing urban water use (taking it from prior appropriations for irrigation/ranching) Moving agriculture production Gradual moving population out of floodplains ISNGI October 2013 12
  13. 13. Are there structural changes that could increase water supply resilience?  Manage by emergence and control (Choi et al 2001) ‒ Identify regional water policy strategies that are robust to uncertainty ‒ Implement progressively and adjust ‒ Incentives that allow creative/innovative solutions and recognition of viable solutions ‒ Improve information for creating balancing loops ISNGI October 2013 13
  14. 14. Understanding How Structure Influences Risks: requires dynamic or iterative solutions Going beyond water resilience - requires expanding the boundaries to global interdependencies ISNGI October 2013 14
  15. 15. What capabilities do we need in order to better design for resilience and growth?  Better understanding through modeling and analysis processes that account for the dynamics of human-technical-natural systems     ‒ Causal relationships ‒ Condition dependent behavior ‒ Resource constraints ‒ Delays and the effects of delays on system viability and performance ‒ Policy effects on dynamics Explicitly represent and account for uncertainties Explicitly represent and account for risk reduction strategies Comparative analysis to identify solutions that are robust to uncertainty Decision maker confidence in the analysis and ability to implement the engineered solution  Evaluation and improvement ISNGI October 2013 15

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