Simulation models can improve decisions meant to control the consequences of disruptions to critical infrastructures. We describe a dynamic flow model on networks purposed to inform analyses by those concerned about consequences of disruptions to infrastructures and to help policy makers design robust mitigations. We conceptualize the adaptive responses of infrastructure networks to perturbations as market transactions and business decisions of operators. We approximate commodity flows in these networks by a diffusion equation, with nonlinearities introduced to model capacity limits. To illustrate the behavior and scalability of the model, we show its application first on two simple networks, then on petroleum infrastructure in the United States, where we analyze the effects of a hypothesized earthquake.
Peste des Petits Ruminants (PPR) is an infectious disease affecting goats and sheep. PPR has a mortality rate of 80% and a morbidity rate of 100% in naïve herds. This disease is currently of concern to Afghani goat and sheep herders as conditions in Afghanistan are conducive to the disease becoming an epidemic. PPR is similar to Rinderpest, but is not as well studied. There is a lack of empirical data on how the disease spreads or effective large-scale mitigation strategies. We developed a herd-level, event-driven model of PPR, using memoryless state transitions, to study how the virus propagates through a herd, and to identify effective control strategies for disparate herd configurations and environments. This model allows us to perform Sensitivity Analyses (SA) on environmental and disease parameters for which we do not have empirical data and to simulate the effectiveness of various control strategies. We find that reducing the amount of time from the identification of PPR in a herd to the vaccination of the herd will radically reduce the number of deaths that result from PPR. The goal of this model is to give policy makers a tool to develop effective containment strategies for managing outbreaks of PPR.
Within the Department of Homeland Security (DHS), the Office of Cyber and Infrastructure Analysis (OCIA)'s National Infrastructure Simulation and Analysis Center (NISAC) develops capabilities to support the DHS mission and the resilience of the Nation’s critical infrastructure. At Sandia National Laboratories, under DHS/OCIA direction, NISAC is developing models of financial sector dependence on communications. This capability is designed to improve DHS's ability to assess potential impacts of communication disruptions to major financial services and the effectiveness of possible mitigations. This report summarizes findings and recommendations from the application of that capability as part of the FY2016 NISAC program plan.
We applied modeling and simulation to examine the real-world tradeoffs between developingcountry public-health improvement and the need to improve the identification, tracking, and security of agents with bio-weapons potential. Traditionally, the international community has applied facility-focused strategies for improving biosecurity and biosafety. This work examines how system-level assessments and improvements can foster biosecurity and biosafety. We modeled medical laboratory resources and capabilities to identify scenarios where biosurveillance goals are transparently aligned with public health needs, and resource are distributed in a way that maximizes their ability to serve patients while minimizing security a nd safety risks. Our modeling platform simulates key processes involved in healthcare system operation, such as sample collection, transport, and analysis at medical laboratories. The research reported here extends the prior art by provided two key compone nts for comparative performance assessment: a model of patient interaction dynamics, and the capability to perform uncertainty quantification. In addition, we have outlined a process for incorporating quantitative biosecurity and biosafety risk measures. Two test problems were used to exercise these research products examine (a) Systemic effects of technological innovation and (b) Right -sizing of laboratory networks.
The Integrated Human Futures Project provides a set of analytical and quantitative modeling and simulation tools that help explore the links among human social, economic, and ecological conditions, human resilience, conflict, and peace, and allows users to simulate tradeoffs and consequences associated with different future development and mitigation scenarios. In the current study, we integrate five distinct modeling platforms to simulate the potential risk of social unrest in Egypt resulting from the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile in Ethiopia. The five platforms simulate hydrology, agriculture, economy, human ecology, and human psychology/behavior, and show how impacts derived from development initiatives in one sector (e.g., hydrology) might ripple through to affect other sectors and how development and security concerns may be triggered across the region. This approach evaluates potential consequences, intended and unintended, associated with strategic policy actions that span the development-security nexus at the national, regional, and international levels. Model results are not intended to provide explicit predictions, but rather to provide system-level insight for policy makers into the dynamics among these interacting sectors, and to demonstrate an approach to evaluating short- and long-term policy trade-offs across different policy domains and stakeholders. The GERD project is critical to government-planned development efforts in Ethiopia but is expected to reduce downstream freshwater availability in the Nile Basin, fueling fears of negative social and economic impacts that could threaten stability and security in Egypt. We tested these hypotheses and came to the following preliminary conclusions. First, the GERD will have an important short-term impact on water availability, food production, and hydropower production in Egypt, depending on the short- term reservoir fill rate. Second, the GERD will have a very small impact on water availability in the Nile Basin over the longer term. Depending on the GERD fill rate, short-term (e.g., within its first 5 years of operation) annual losses in Egyptian food production may peak briefly at 25 percent. Long-term (e.g., 15 to 30 year) cumulative losses in Egypt's food production may be less than 3 percent regardless of the fill rate, with the GERD having essentially no impact on projected annual food production in Egypt about 25 years after opening. For the quick fill rates, the short-term losses may be sufficient to create an important decrease in overall household health among the general population, which, along with other economic stressors and different strategies employed by the government, could lead to social unrest. Third, and perhaps most importantly, our modeling suggests that the GERD's effect on Egypt's food and water resources is small when compared to the effect of projected Egyptian population and economic growth (and the concomitant increase in water consumption). The latter dominating factors are exacerbated in the modeling by natural climate variability and may be further exacerbated by climate change. Our modeling suggests that these growth dynamics combine to create long-term water scarcity in Egypt, regardless of the Ethiopian project. All else being equal, filling strategies that employ slow fill rates for the GERD (e.g., 8 to 13 years) may mitigate the risks in future scenarios for Egypt somewhat, but no policy or action regarding the GERD is likely to significantly alleviate the projected water scarcity in Egypt's Nile Basin. However, general beliefs among the Egyptian populace regarding the GERD as a major contributing factor for scarcities in Egypt could make Ethiopia a scapegoat for Egyptian grievances -- contributing to social unrest in Egypt and generating undesirable (and unnecessary) tension between these two countries. Such tension could threaten the constructive relationships between Egypt and Ethiopia that are vital to maintaining stability and security within and between their respective regional spheres of influence, Middle East and North Africa, and the Horn of Africa.
The current expansion of natural gas (NG) development in the United States requires an understanding of how this change will affect the natural gas industry, downstream consumers, and economic growth in order to promote effective planning and policy development. The impact of this expansion may propagate through the NG system and US economy via changes in manufacturing, electric power generation, transportation, commerce, and increased exports of liquefied natural gas. We conceptualize this problem as supply shock propagation that pushes the NG system and the economy away from its current state of infrastructure development and level of natural gas use. To illustrate this, the project developed two core modeling approaches. The first is an Agent-Based Modeling (ABM) approach which addresses shock propagation throughout the existing natural gas distribution system. The second approach uses a System Dynamics-based model to illustrate the feedback mechanisms related to finding new supplies of natural gas - notably shale gas - and how those mechanisms affect exploration investments in the natural gas market with respect to proven reserves. The ABM illustrates several stylized scenarios of large liquefied natural gas (LNG) exports from the U.S. The ABM preliminary results demonstrate that such scenario is likely to have substantial effects on NG prices and on pipeline capacity utilization. Our preliminary results indicate that the price of natural gas in the U.S. may rise by about 50% when the LNG exports represent 15% of the system-wide demand. The main findings of the System Dynamics model indicate that proven reserves for coalbed methane, conventional gas and now shale gas can be adequately modeled based on a combination of geologic, economic and technology-based variables. A base case scenario matches historical proven reserves data for these three types of natural gas. An environmental scenario, based on implementing a $50/tonne CO 2 tax results in less proven reserves being developed in the coming years while demand may decrease in the absence of acceptable substitutes, incentives or changes in consumer behavior. An increase in demand of 25% increases proven reserves being developed by a very small amount by the end of the forecast period of 2025.
Adaptation is believed to be a source of resilience in systems. It has been difficult to measure the contribution of adaptation to resilience, unlike other resilience mechanisms such as restoration and recovery. One difficulty comes from treating adaptation as a deus ex machina that is interjected after a disruption. This provides no basis for bounding possible adaptive responses. We can bracket the possible effects of adaptation when we recognize that it occurs continuously, and is in part responsible for the current system’s properties. In this way the dynamics of the system’s pre-disruption structure provides information about post-disruption adaptive reaction. Seen as an ongoing process, adaptation has been argued to produce “robust-yet-fragile” systems. Such systems perform well under historical stresses but become committed to specific features of those stresses in a way that makes them vulnerable to system-level collapse when those features change. In effect adaptation lessens the cost of disruptions within a certain historical range, at the expense of increased cost from disruptions outside that range. Historical adaptive responses leave a signature in the structure of the system. Studies of ecological networks have suggested structural metrics that pick out systemic resilience in the underlying ecosystems. If these metrics are generally reliable indicators of resilience they provide another strategy for gaging adaptive resilience. To progress in understanding how the process of adaptation and the property of resilience interrelate in infrastructure systems, we pose some specific questions: Does adaptation confer resilience?; Does it confer resilience to novel shocks as well, or does it tune the system to fragility?; Can structural features predict resilience to novel shocks?; Are there policies or constraints on the adaptive process that improve resilience?.
Complex adaptive systems are central to many persistent problems locally and globally. In cases where the effects of a policy play out slowly and propagate through interdependencies with other systems, the broader view and understanding gained from complex adaptive system analyses allow us to recognise the causal relationships involved and solve persistent system-level issues. This is particularly true with the risks due to climate change, economic crises, energy disruptions and food insecurity. Climate change and the challenge of addressing the resulting global risks provides a common set of problems on which to build a global community of practice that utilises earth systems' engineering approaches and sustainability goals to understand and resolve problems in complex adaptive systems of systems. Structural adaptation under environmental stress, simple rules for entity interactions and conditiondependent behaviours are key attributes of complex systems. These attributes provide the means for creating models that behave the way the real system does and for the same reasons, improving understanding and designing effective solutions. This paper presents general concepts for infrastructure adaptation and examples of successful applications of an expanded engineering process for complex systems of systems.
As with other large healthcare organizations, medical adverse events at the Department of Veterans Affairs (VA) facilities can expose patients to unforeseen negative risks. VHA leadership recognizes that properly handled disclosure of adverse events can minimize potential harm to patients and negative consequences for the effective functioning of the organization. The work documented here seeks to help improve the disclosure process by situating it within the broader theoretical framework of issues management, and to identify opportunities for process improvement through modeling disclosure and reactions to disclosure. The computational model will allow a variety of disclosure actions to be tested across a range of incident scenarios. Our conceptual model will be refined in collaboration with domain experts, especially by continuing to draw on insights from VA Study of the Communication of Adverse Large-Scale Events (SCALE) project researchers.