Publications

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Competition is fierce and often the first to act has an advantage, especially in environments where there are excess resources. However, expanding quickly to absorb excess resources creates requirements that might be unmet in future conditions of scarcity. Different patterns of scarcity call for different strategies. We define a model of interacting specialists (entities) to analyze which sizing strategies are most successful in environments subjected to frequent periods of scarcity. We require entities to compete for a common resource whose scarcity changes periodically, then study the viability of entities following three different strategies through scarcity episodes of varying duration and intensity. The three sizing strategies are: aggressive, moderate, and conservative. Aggressive strategies are most effective when the episodes of scarcity are shorter and moderate; conversely, conservative strategies are most effective in cases of longer or more severe scarcity. © 2012 Springer-Verlag.

Complex adaptive systems (CAS) modeling has become a common tool to study the behavioral dynamics of agents in a broad range of disciplines from ecology to economics. Many modelers have studied structure's importance for a system in equilibrium, while others study the effects of perturbations on system dynamics. There is a notable absence of work on the effects of agent interaction pathways on perturbation dynamics. We present an agent-based CAS model of a competitive economic environment. We use this model to study the perturbation dynamics of simple structures by introducing a series of disruptive events and observing key system metrics. Then, we generate more complex networks by combining the simple component structures and analyze the resulting dynamics. We find the local network structure of a perturbed node to be a valuable indicator of the system response. © 2012 Springer-Verlag.

International forces in Afghanistan have experienced difficulties in developing constructive engagements with the Afghan population, an experience familiar to a wide range of international agencies working in underdeveloped and developing nations around the world. Recently, forces have begun deploying Female Engagement Teams, female military units who engage directly with women in occupied communities, resulting inmore positive relationships with those communities as a whole. In this paper, we explore the hypothesis that the structure of community-based social networks strongly contributes to the effectiveness of the Female Engagement Team strategy, specifically considering gender-based differences in network community structure. We find that the ability to address both female and male network components provides a superior ability to affect opinions in the network, and can provide an effective means of counteracting influences from opposition forces. © 2012 Springer-Verlag.

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Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

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Infrastructures are networks of dynamically interacting systems designed for the flow of information, energy, and materials. Under certain circumstances, disturbances from a targeted attack or natural disasters can cause cascading failures within and between infrastructures that result in significant service losses and long recovery times. Reliable interdependency models that can capture such multi-network cascading do not exist. The research reported here has extended Sandia's infrastructure modeling capabilities by: (1) addressing interdependencies among networks, (2) incorporating adaptive behavioral models into the network models, and (3) providing mechanisms for evaluating vulnerability to targeted attack and unforeseen disruptions. We have applied these capabilities to evaluate the robustness of various systems, and to identify factors that control the scale and duration of disruption. This capability lays the foundation for developing advanced system security solutions that encompass both external shocks and internal dynamics.

Complex Adaptive Systems of Systems, or CASoS, are vastly complex eco-socio-economic-technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to highly-saturated interdependencies and allied vulnerabilities to cascades in associated systems. The Phoenix initiative approaches this high-impact problem space as engineers, devising interventions (problem solutions) that influence CASoS to achieve specific aspirations. CASoS embody the world's biggest problems and greatest opportunities: applications to real world problems are the driving force of our effort. We are developing engineering theory and practice together to create a discipline that is grounded in reality, extends our understanding of how CASoS behave, and allows us to better control those behaviors. Through application to real-world problems, Phoenix is evolving CASoS Engineering principles while growing a community of practice and the CASoS engineers to populate it.

Complex Adaptive Systems of Systems, or CASoS, are vastly complex ecological, sociological, economic and/or technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to pervasive interdependencies and attendant vulnerabilities to cascades in associated systems. Phoenix was initiated to address this high-impact problem space as engineers. Our overarching goals are maximizing security, maximizing health, and minimizing risk. We design interventions, or problem solutions, that influence CASoS to achieve specific aspirations. Through application to real-world problems, Phoenix is evolving the principles and discipline of CASoS Engineering while growing a community of practice and the CASoS engineers to populate it. Both grounded in reality and working to extend our understanding and control of that reality, Phoenix is at the same time a solution within a CASoS and a CASoS itself.

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The objectives of this presentation are: (1) To determine if healthcare settings serve as intensive transmission environments for influenza epidemics, increasing effects on communities; (2) To determine which mitigation strategies are best for use in healthcare settings and in communities to limit influenza epidemic effects; and (3) To determine which mitigation strategies are best to prevent illness in healthcare workers.

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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.

Loki-Infect 3 is a desktop application intended for use by community-level decision makers. It allows rapid construction of small-scale studies of emerging or hypothetical infectious diseases in their communities and evaluation of the potential effectiveness of various containment strategies. It was designed with an emphasis on modularity, portability, and ease of use. Our goal is to make this program freely available to community workers across the world.

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We develop a parsimonious model of the interbank payment system. The model incorporates an endogenous instruction arrival process, a scale-free topology of payments between banks, a fixed total liquidity which limits banks' capacity to process arriving instructions, and a global market that distributes liquidity. We find that at low liquidity the system becomes congested and payment settlement loses correlation with payment instruction arrival, becoming coupled across the network. The onset of congestion is evidently related to the relative values of three characteristic times: the time for banks' net position to return to 0, the time for a bank to exhaust its liquidity endowment, and the liquidity market relaxation time. In the congested regime settlement takes place in cascades having a characteristic length scale. A global liquidity market substantially attenuates congestion, requiring only a small fraction of the payment-induced liquidity flow to achieve strong beneficial effects. © 2007 Elsevier B.V. All rights reserved.

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This report describes a model Transport Processes Investigation (TPI) where field-scale vadose zone flow and transport processes are identified and verified through a systematic field investigation at a contaminated DOE site. The objective of the TPI is to help with formulating accurate conceptual models and aid in implementing rational and cost effective site specific characterization strategies at contaminated sites with diverse hydrogeologic settings. Central to the TPI are Transport Processes Characterization (TPC) tests that incorporate field surveys and large-scale infiltration experiments. Hypotheses are formulated based on observed pedogenic and hydrogeologic features as well as information provided by literature searches. The field and literature information is then used to optimize the design of one or more infiltration experiments to field test the hypothesis. Findings from the field surveys and infiltration experiments are then synthesized to formulate accurate flow and transport conceptual models. Here we document a TPI implemented in the glacial till vadose zone at the Fernald Environmental Management Project (FEMP) in Fernald, Ohio, a US Department of Energy (DOE) uranium processing site. As a result of this TPI, the flow and transport mechanisms were identified through visualization of dye stain within extensive macro pore and fracture networks which provided the means for the infiltrate to bypass potential aquatards. Such mechanisms are not addressed in current vadose zone modeling and are generally missed by classical characterization methods.

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An infiltration and dye transport experiment was conducted to visualize flow and transport processes in a heterogeneous, layered, sandy-gravelly fluvial deposit adjacent to Rio Bravo Boulevard in Albuquerque, NM. Water containing red dye followed by blue-green dye was ponded in a small horizontal zone ({approx}0.5 m x 0.5 m) above a vertical outcrop ({approx}4 m x 2.5 m). The red dye lagged behind the wetting front due to slight adsorption thus allowing both the wetting front and dye fronts to be observed in time at the outcrop face. After infiltration, vertical slices were excavated to the midpoint of the infiltrometer exposing the wetting front and dye distribution in a quasi three-dimensional manner. At small-scale, wetting front advancement was influenced by the multitude of local capillary barriers within the deposit. However at the scale of the experiment, the wetting front appeared smooth with significant lateral spreading {approx} twice that in the vertical, indicating a strong anisotropy due to the pronounced horizontal layering. The dye fronts exhibited appreciably more irregularity than the wetting front, as well as the influence of preferential flow features (a fracture) that moved the dye directly to the front, bypassing the fresh water between.

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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.

Critical Infrastructures are formed by a large number of components that interact within complex networks. As a rule, infrastructures contain strong feedbacks either explicitly through the action of hardware/software control, or implicitly through the action/reaction of people. Individual infrastructures influence others and grow, adapt, and thus evolve in response to their multifaceted physical, economic, cultural, and political environments. Simply put, critical infrastructures are complex adaptive systems. In the Advanced Modeling and Techniques Investigations (AMTI) subgroup of the National Infrastructure Simulation and Analysis Center (NISAC), we are studying infrastructures as complex adaptive systems. In one of AMTI's efforts, we are focusing on cascading failure as can occur with devastating results within and between infrastructures. Over the past year we have synthesized and extended the large variety of abstract cascade models developed in the field of complexity science and have started to apply them to specific infrastructures that might experience cascading failure. In this report we introduce our comprehensive model, Polynet, which simulates cascading failure over a wide range of network topologies, interaction rules, and adaptive responses as well as multiple interacting and growing networks. We first demonstrate Polynet for the classical Bac, Tang, and Wiesenfeld or BTW sand-pile in several network topologies. We then apply Polynet to two very different critical infrastructures: the high voltage electric power transmission system which relays electricity from generators to groups of distribution-level consumers, and Fedwire which is a Federal Reserve service for sending large-value payments between banks and other large financial institutions. For these two applications, we tailor interaction rules to represent appropriate unit behavior and consider the influence of random transactions within two stylized networks: a regular homogeneous array and a heterogeneous scale-free (fractal) network. For the stylized electric power grid, our initial simulations demonstrate that the addition of geographically unrestricted random transactions can eventually push a grid to cascading failure, thus supporting the hypothesis that actions of unrestrained power markets (without proper security coordination on market actions) can undermine large scale system stability. We also find that network topology greatly influences system robustness. Homogeneous networks that are 'fish-net' like can withstand many more transaction perturbations before cascading than can scale-free networks. Interestingly, when the homogeneous network finally cascades, it tends to fail in its entirety, while the scale-free tends to compartmentalize failure and thus leads to smaller, more restricted outages. In the case of stylized Fedwire, initial simulations show that as banks adaptively set their individual reserves in response to random transactions, the ratio of the total volume of transactions to individual reserves, or 'turnover ratio', increases with increasing volume. The removal of a bank from interaction within the network then creates a cascade, its speed of propagation increasing as the turnover ratio increases. We also find that propagation is accelerated by patterned transactions (as expected to occur within real markets) and in scale-free networks, by the 'attack' of the most highly connected bank. These results suggest that the time scale for intervention by the Federal Reserve to divert a cascade in Fedwire may be quite short. Ongoing work in our cascade analysis effort is building on both these specific stylized applications to enhance their fidelity as well as embracing new applications. We are implementing markets and additional network interactions (e.g., social, telecommunication, information gathering, and control) that can impose structured drives (perturbations) comparable to those seen in real systems. Understanding the interaction of multiple networks, their interdependencies, and in particular, the underlying mechanisms for their growth/evolution is paramount. With this understanding, appropriate public policy can be identified to guide the evolution of present infrastructures to withstand the demands and threats of the future.