Publications

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Interactions between individuals, both economic and social, are increasingly mediated by technological systems. Such platforms facilitate interactions by controlling and regularizing access, while extracting rent from users. The relatively recent idea of two-sided markets has given insights into the distinctive economic features of such arrangements, arising from network effects and the power of the platform operator. Simplifications required to obtain analytical results, while leading to basic understanding, prevent us from posing many important questions. For example we would like to understand how platforms can be secured when the costs and benefits of security differ greatly across users and operators, and when the vulnerabilities of particular designs may only be revealed after they are in wide use. We define an agent-based model that removes many constraints limiting existing analyses (such as uniformity of users, free and perfect information), allowing insights into a much larger class of real systems. © 2012 Springer-Verlag.

Difficulties in adequately characterising food supply chain topologies contribute major uncertainty to risk assessments of the food sector. The capability to trace contaminated foods forward (to consumers) and back (to providers) is needed for rapid recalls during food contamination events. The objective of this work is to develop an approach for risk mitigation that protects us from an attack on the food distribution system. This paper presents a general methodology for the stochastic mapping of fresh produce supply chains and an application to a single, relatively simple case - edible sprouts in one region. The case study demonstrates how mapping the network topology and modeling the potential relationships allows users to determine the likely contaminant pathways and sources of contamination. The stochastic network representation improves the ability to explicitly incorporate uncertainties and identify vulnerabilities. Copyright © 2012 Inderscience Enterprises Ltd.

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Cigarette smoking presented the most significant public health challenge in the United States in the 20th Century and remains the single most preventable cause of morbidity and mortality in this country. A number of System Dynamics models exist that inform tobacco control policies. We reviewed them and discuss their contributions. We developed a theory of the societal lifecycle of smoking, using a parsimonious set of feedback loops to capture historical trends and explore future scenarios. Previous work did not explain the long-term historical patterns of smoking behaviors. Much of it used stock-and-flow to represent the decline in prevalence in the recent past. With noted exceptions, information feedbacks were not embedded in these models. We present and discuss our feedback-rich conceptual model and illustrate the results of a series of simulations. A formal analysis shows phenomena composed of different phases of behavior with specific dominant feedbacks associated with each phase. We discuss the implications of our society's current phase, and conclude with simulations of what-if scenarios. Because System Dynamics models must contain information feedback to be able to anticipate tipping points and to help identify policies that exploit leverage in a complex system, we expanded this body of work to provide an endogenous representation of the century-long societal lifecycle of smoking.

Changes in climate can lead to instabilities in physical and economic systems, particularly in regions with marginal resources. Global climate models indicate increasing global mean temperatures over the decades to come and uncertainty in the local to national impacts means perceived risks will drive planning decisions. Agent-based models provide one of the few ways to evaluate the potential changes in behavior in coupled social-physical systems and to quantify and compare risks. The current generation of climate impact analyses provides estimates of the economic cost of climate change for a limited set of climate scenarios that account for a small subset of the dynamics and uncertainties. To better understand the risk to national security, the next generation of risk assessment models must represent global stresses, population vulnerability to those stresses, and the uncertainty in population responses and outcomes that could have a significant impact on U.S. national security.

Current protection strategies against insider adversaries are expensive, intrusive, not systematically implemented, and operate independently; too often, these strategies are defeated. The authors discuss the development of methods for a systems-based approach to insider security. To investigate insider evolution within an organization, they use system dynamics to develop a preliminary model of the employee life cycle that defines and analyzes the employee population's interactions with insider security protection strategies. The authors exercised the model for an example scenario that focused on human resources and personnel security activitiesspecifically, prehiring screening and security clearance processes. The model provides a framework for understanding important interactions, interdependencies, and gaps in insider protection strategies. This work provides the basis for developing an integrated systems-based process for buildingthat is, designing, evaluating, and operatinga system for effective insider security. © 2009 IEEE.

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The telecommunication network is recognized by the federal government as one of the critical national infrastructures that must be maintained and protected against debilitating attacks. We have previously shown how failures in the telecommunication network can quickly lead to telecommunication congestion and to extended delays in successful call completion. However, even if the telecom network remains fully operational, the special telecommunication demands that materialize at times of emergencies, and dynamically change based on subscriber behavior, can also adversely affect the performance of the overall telecommunication network. The Network Simulation Modeling and Analysis Research Tool (N-SMART) has been developed by Bell Labs as part of its work with the National Infrastructure Simulation and Analysis Center. This center is a joint program at Sandia National Laboratories and Los Alamos National Laboratory, funded and managed by the Department of Homeland Security's (DHS) Preparedness Directorate. N-SMART is a discrete event (call level) telecom model that simulates capacities, blocking levels, retrials, and time to complete calls for both wireline and wireless networks. N-SMART supports the capability of simulating subscriber reattempt behaviour under various scenarios. Using this capability we show how the network can be adversely impacted by sudden changes in subscriber behavior. We also explore potential solutions and ways of mitigating those impacts.

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Concepts from Complexity Science are valuable and allow a simulation approach for critical infrastructures that is flexible and has wide ranging applications.

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The fast and unrelenting spread of wireless telecommunication devices has changed the landscape of the telecommunication world, as we know it. Today we find that most users have access to both wireline and wireless communication devices. This widespread availability of alternate modes of communication is adding, on one hand, to a redundancy in networks, yet, on the other hand, has cross network impacts during overloads and disruptions. This being the case, it behooves network designers and service providers to understand how this redundancy works so that it can be better utilized in emergency conditions where the need for redundancy is critical. In this paper, we examine the scope of this redundancy as expressed by telecommunications availability to users under different failure scenarios. We quantify the interaction of wireline and wireless networks during network failures and traffic overloads. Developed as part of a Department of Homeland Security Infrastructure Protection (DHS IP) project, the Network Simulation Modeling and Analysis Research Tool (N-SMART) was used to perform this study. The product of close technical collaboration between the National Infrastructure Simulation and Analysis Center (NISAC) and Lucent Technologies, N-SMART supports detailed wireline and wireless network simulations and detailed user calling behavior.

The Global Energy Futures Model (GEFM) is a demand-based, gross domestic product (GDP)-driven, dynamic simulation tool that provides an integrated framework to model key aspects of energy, nuclear-materials storage and disposition, environmental effluents from fossil and non fossil energy and global nuclear-materials management. Based entirely on public source data, it links oil, natural gas, coal, nuclear and renewable energy dynamically to greenhouse-gas emissions and 12 other measures of environmental impact. It includes historical data from 1990 to 2000, is benchmarked to the DOE/EIA/IEO 2001 [5] Reference Case for 2000 to 2020, and extrapolates energy demand through the year 2050. The GEFM is globally integrated, and breaks out five regions of the world: United States of America (USA), the Peoples Republic of China (China), the former Soviet Union (FSU), the Organization for Economic Cooperation and Development (OECD) nations excluding the USA (other industrialized countries), and the rest of the world (ROW) (essentially the developing world). The GEFM allows the user to examine a very wide range of ''what if'' scenarios through 2050 and to view the potential effects across widely dispersed, but interrelated areas. The authors believe that this high-level learning tool will help to stimulate public policy debate on energy, environment, economic and national security issues.

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Surface and groundwater resources do not recognize political boundaries. Where nature and boundary cross, tension over shared water resources can erupt. Such tension is exacerbated in regions where demand approaches or exceeds sustainable supplies of water. Establishing equitable management strategies can help prevent and resolve conflict over shared water resources. This paper describes a methodology for addressing transboundary water issues predicated on the integration of monitoring and modeling within a framework of cooperation. Cooperative monitoring begins with agreement by international scientists and/or policy makers on transboundary monitoring goals and strategies; it leads to the process of obtaining and sharing agreed-upon information among parties with the purpose of providing verifiable and secure data. Cooperative modeling is the process by which the parties jointly interpret the data, forecast future events and trends, and quantify cause and effect relationships. Together, cooperative monitoring and modeling allow for the development and assessment of alternative management and remediation strategies that could form the basis of regional watershed agreements or treaties. An example of how this multifaceted approach might be used to manage a shared water resource is presented for the Kura River basin in the Caucasus.

The authors reconceptualize macro modified invasion percolation (MMIP) at the near pore (NP) scale and apply it to simulate the non-wetting phase invasion experiments of Glass et al [in review] conducted in macro-heterogeneous porous media. For experiments where viscous forces were non-negligible, they redefine the total pore filling pressure to include viscous losses within the invading phase as well as the viscous influence to decrease randomness imposed by capillary forces at the front. NP-MMIP exhibits the complex invasion order seen experimentally with characteristic alternations between periods of gravity stabilized and destabilized invasion growth controlled by capillary barriers. The breaching of these barriers and subsequent pore scale fingering of the non-wetting phase is represented extremely well as is the saturation field evolution, and total volume invaded.

The authors designed and conducted experiments in a heterogeneous sand pack where gravity-destabilized nonwetting phase invasion (CO{sub 2} and TCE) could be recorded using high resolution light transmission methods. The heterogeneity structure was designed to be reminiscent of fluvial channel lag cut-and-fill architecture and contain a series of capillary barriers. As invasion progressed, nonwetting phase structure developed a series of fingers and pools; behind the growing front they found nonwetting phase saturation to pulsate in certain regions when viscous forces were low. Through a scale analysis, they derive a series of length scales that describe finger diameter, pool height and width, and regions where pulsation occurs within a heterogeneous porous medium. In all cases, they find that the intrinsic pore scale nature of the invasion process and resulting structure must be incorporated into the analysis to explain experimental results. The authors propose a simple macro-scale structural growth model that assembles length scales for sub-structures to delineate nonwetting phase migration from a source into a heterogeneous domain. For such a model applied at the field scale for DNAPL migration, they expect capillary and gravity forces within the complex subsurface lithology to play the primary roles with viscous forces forming a perturbation on the inviscid phase structure.