Spatially-aware systems engineering design modeling applied to natural hazard vulnerability assessment

  • Authors:

  • Timothy J. Eveleigh;Thomas A. Mazzuchi;Shahram Sarkani

  • Affiliations:

  • Department of Engineering Management and Systems Engineering, School of Engineering and Applied Science, The George Washington University, 1176 G Street, NW, Washington, DC 20052;Department of Engineering Management and Systems Engineering, School of Engineering and Applied Science, The George Washington University, 1176 G Street, NW, Washington, DC 20052;Department of Engineering Management and Systems Engineering, School of Engineering and Applied Science, The George Washington University, 1176 G Street, NW, Washington, DC 20052

  • Venue:
  • Systems Engineering
  • Year:
  • 2007

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Abstract

Human socio-technical systems are particularly vulnerable to natural and manmade disasters that project vast physical effects on interdependent functional infrastructure. Many disciplines are trying to understand the complex interactions between the physical world and the systems at risk within it. Systems engineering design is directly concerned with relationships between requirements, functions, and the physical architecture that implements functions. This paper explores the use and advantages of systems engineering design modeling that has been made sensitive to the spatial effects of the physical world by using a geographic information system (GIS) to represent elements of the physical architecture. The paper begins with a description of the spatial context and geographic information systems technology. We review how the spatial context is presently manifested in systems engineering and design modeling and then describe how we combined a geospatial model with a systems engineering design model and explored the unique views that the combined conceptual models introduce. We present a process approach developed for the natural hazard vulnerability domain and discuss our findings to date and the challenges that resulted from mixing models of greatly different fidelity. We conclude by suggesting future work that is needed to further investigate spatially-aware systems engineering conceptual models. © 2007 Wiley Periodicals, Inc. Syst Eng 10: 187–202, 2007