An integrated modeling framework for infrastructure system-of-systems simulation

Design of future hard infrastructure must consider emergent behaviors from cross-system interdependencies. Understanding these interdependencies is challenging due to high levels of integration in high-performance systems and their operation as a collaborative system-of-systems managed by multiple organizations. Existing modeling frameworks have limitations for strategic planning either because important spatial structure attributes have been abstracted out or behavioral models are oriented to shorter-term analysis with a static network structure. This paper presents a formal modeling framework as a first step to integrating infrastructure system models in a system-of-systems simulation addressing these concerns. First, a graph-theoretic structural framework captures the spatial dimension of physical infrastructure. An element's simulation state includes location, parent, resource contents, and operational state properties. Second, a functional behavioral framework captures the temporal dimension of infrastructure operations at a level suitable for strategic analysis. Resource behaviors determine the flow of resources into or out of nodes and element behaviors modify other state including the network structure. Two application use cases illustrate the usefulness of the modeling framework in varying contexts. The first case applies the framework to future space exploration infrastructure with an emphasis on mobile system elements and discrete resource flows. The second case applies the framework to infrastructure investment in Saudi Arabia with an emphasis on immobile system elements aggregated at the city level and continuous resource flows. Finally, conclusions present future work planned for implementing the framework in a simulation software tool.American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Strategic Engineering Gaming for Improved Design and Interoperation of Infrastructure Systems

Large physical networks of interrelated infrastructure components support modern societies as a collaborative system with significant technical and social complexity. Design and evolution of infrastructure systems seeks to reduce wasted resources and maximize lifecycle value. Interdependencies between constituent systems call for an integrative approach to improve interoperation but many existing techniques rely on centralized development and emphasize technical aspects of design. This paper presents a simulation gaming approach to collaborative infrastructure system design leveraging the technical strengths of simulation models and the social strengths of multi-player engagement in a game execution. In a strategic engineering game, models representing each constituent infrastructure system share a common graph-theoretic modeling framework and are integrated using the HLA-Evolved standard for interoperable federated simulations. A prototype game instantiation based on a space-based resource economy supporting future space exploration is discussed with the objective of identifying how factors of game play influence insights to collaborative system design. Future work seeks to develop, execute, and evaluate the prototype game to further research the use of simulation games in supporting collaborative system design

A System-of-Systems Framework for Exploratory Analysis of Climate Change Impacts on Civil Infrastructure Resilience

Climate change has various chronic and acute impacts on civil infrastructure systems (CIS). A long-term assessment of resilience in CIS requires understanding the transformation of CIS caused by climate change stressors and adaptation decision-making behaviors of institutional agencies. In addition, resilience assessment for CIS includes significant uncertainty regarding future climate change scenarios and subsequent impacts. Thus, resilience analysis in CIS under climate change impacts need to capture complex adaptive behaviors and uncertainty in order to enable robust planning and decision making. This study presented a system-of-systems (SoS) framework for abstraction and integrated modeling of climate change stressors, physical infrastructure performance, and institutional actors’ decision making. The application of the proposed SoS framework was shown in an illustrative case study related to the impacts of sea level rise and subsequent saltwater intrusion on a water system. Through the use of the proposed SoS framework, various attributes, processes, and interactions related to physical infrastructure and actor’s decision making were abstracted and used in the creation of a computational simulation model. Then, the computational model was used to simulate various scenarios composed of sea level rise and adaptation approaches. Through an exploratory analysis approach, the simulated scenario landscape was used to identify robust adaptation pathways that lead to a greater system resilience under future uncertain sea level rise. The results of the illustrative case study highlight the various novel capabilities of the SoS framework: (i) abstraction of various attributes and processes that affect the long-term resilience of infrastructure under climate change; (ii) integrated modeling of CIS transformation based on simulating the adaptive decision-making processes, physical infrastructure performance, and climate change impacts; and (iii) exploratory analysis and identification of robust pathways for adaptation to climate change impacts

A System-of-Systems Framework for Exploratory Analysis of Climate Change Impacts on Civil Infrastructure Resilience

Climate change has various chronic and acute impacts on civil infrastructure systems (CIS). A long-term assessment of resilience in CIS requires understanding the transformation of CIS caused by climate change stressors and adaptation decision-making behaviors of institutional agencies. In addition, resilience assessment for CIS includes significant uncertainty regarding future climate change scenarios and subsequent impacts. Thus, resilience analysis in CIS under climate change impacts need to capture complex adaptive behaviors and uncertainty in order to enable robust planning and decision making. This study presented a system-of-systems (SoS) framework for abstraction and integrated modeling of climate change stressors, physical infrastructure performance, and institutional actors’ decision making. The application of the proposed SoS framework was shown in an illustrative case study related to the impacts of sea level rise and subsequent saltwater intrusion on a water system. Through the use of the proposed SoS framework, various attributes, processes, and interactions related to physical infrastructure and actor’s decision making were abstracted and used in the creation of a computational simulation model. Then, the computational model was used to simulate various scenarios composed of sea level rise and adaptation approaches. Through an exploratory analysis approach, the simulated scenario landscape was used to identify robust adaptation pathways that lead to a greater system resilience under future uncertain sea level rise. The results of the illustrative case study highlight the various novel capabilities of the SoS framework: (i) abstraction of various attributes and processes that affect the long-term resilience of infrastructure under climate change; (ii) integrated modeling of CIS transformation based on simulating the adaptive decision-making processes, physical infrastructure performance, and climate change impacts; and (iii) exploratory analysis and identification of robust pathways for adaptation to climate change impacts

Supporting an integrated transportation infrastructure and public space design: A coupled simulation method for evaluating traffic pollution and microclimate

Traditional urban and transport infrastructure planning that emphasized motorized transport has fractured public space systems and worsened environmental quality, leading to a decrease in active travel. A novel multiscale simulation method for supporting an integrated transportation infrastructure and public space design is presented in this paper. This method couples a mesoscale agent-based traffic prediction model, traffic-related emission calculation, microclimate simulations, and human thermal comfort assessment. In addition, the effects of five urban design strategies on traffic pollution and pedestrian level microclimate are evaluated (i.e., a “two-fold” evaluation). A case study in Beijing, China, is presented utilizing the proposed urban modeling-design framework to support the assessment of a series of transport infrastructure and public space scenarios, including the Baseline scenario, a System-Internal Integration scenario, and two External Integration scenarios. The results indicate that the most effective way of achieving an environmentally- and pedestrian- friendly urban design is to concentrate on both the integration within the transport infrastructure and public space system and the mitigation of the system externalities (e.g., air pollution and heat exhaustion). It also demonstrates that the integrated blue-green approach is a promising way of improving local air quality, micro-climatic conditions, and human comfort

A System-of-Systems Framework for Exploratory Analysis of Climate Change Impacts on Civil Infrastructure Resilience

Climate change has various chronic and acute impacts on civil infrastructure systems (CIS). A long-term assessment of resilience in CIS requires understanding the transformation of CIS caused by climate change stressors and adaptation decision-making behaviors of institutional agencies. In addition, resilience assessment for CIS includes significant uncertainty regarding future climate change scenarios and subsequent impacts. Thus, resilience analysis in CIS under climate change impacts need to capture complex adaptive behaviors and uncertainty in order to enable robust planning and decision making. This study presented a system-of-systems (SoS) framework for abstraction and integrated modeling of climate change stressors, physical infrastructure performance, and institutional actors’ decision making. The application of the proposed SoS framework was shown in an illustrative case study related to the impacts of sea level rise and subsequent saltwater intrusion on a water system. Through the use of the proposed SoS framework, various attributes, processes, and interactions related to physical infrastructure and actor’s decision making were abstracted and used in the creation of a computational simulation model. Then, the computational model was used to simulate various scenarios composed of sea level rise and adaptation approaches. Through an exploratory analysis approach, the simulated scenario landscape was used to identify robust adaptation pathways that lead to a greater system resilience under future uncertain sea level rise. The results of the illustrative case study highlight the various novel capabilities of the SoS framework: (i) abstraction of various attributes and processes that affect the long-term resilience of infrastructure under climate change; (ii) integrated modeling of CIS transformation based on simulating the adaptive decision-making processes, physical infrastructure performance, and climate change impacts; and (iii) exploratory analysis and identification of robust pathways for adaptation to climate change impacts

Data-Driven Distributed Modeling, Operation, and Control of Electric Power Distribution Systems

The power distribution system is disorderly in design and implementation, chaotic in operation, large in scale, and complex in every way possible. Therefore, modeling, operating, and controlling the distribution system is incredibly challenging. It is required to find solutions to the multitude of challenges facing the distribution grid to transition towards a just and sustainable energy future for our society. The key to addressing distribution system challenges lies in unlocking the full potential of the distribution grid. The work in this dissertation is focused on finding methods to operate the distribution system in a reliable, cost-effective, and just manner. In this PhD dissertation, a new data-driven distributed ($D^3M$) framework using cellular computational networks has been developed to model power distribution systems. Its performance is validated on an IEEE test case. The results indicate a significant enhancement in accuracy and performance compared to the state-of-the-art centralized modeling approach. This dissertation also presents a new distributed and data-driven optimization method for volt-var control in power distribution systems. The framework is validated for voltage control on an IEEE test feeder. The results indicate that the system has improved performance compared to the state-of-the-art approach. The PhD dissertation also presents a design for a real-time power distribution system testbed. A new data-in-the-loop (DIL) simulation method has been developed and integrated into the testbed. The DIL method has been used to enhance the quality of the real-time simulations. The assets combined with the testbed include data, control, and hardware-in-the-loop infrastructure. The testbed is used to validate the performance of a distribution system with significant penetration of distributed energy resources