Accession Number : ADA590764


Title :   Network Interdependency Modeling for Risk Assessment on Built Infrastructure Systems


Descriptive Note : Doctoral thesis


Corporate Author : AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT


Personal Author(s) : Valencia, Vhance V


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a590764.pdf


Report Date : Oct 2013


Pagination or Media Count : 179


Abstract : As modern infrastructures become more interconnected, the decision-making process becomes more difficult because of the increased complexity resulting from infrastructure interdependencies. Simulation and network modeling provide a way to understand system behavior as a result of interdependencies. One area within the asset management literature that is not well covered is infrastructure system decay and risks associated with that decay. This research presents an enhanced version of Haimes' input-output inoperability model (IIM) in the analysis of built infrastructure systems. Previous applications of the IIM characterized infrastructure at the national level utilizing large economic databases. This study develops a three-phased approach that takes component level data stored within geographic information systems (GIS) to provide a metric for network interdependency across a municipal level infrastructure. A multi-layered approach is proposed which leverages the layered data structure of GIS. Furthermore, Monte Carlo simulation using stochastic decay estimates shows how infrastructure risk as a result of interdependency effects changes over time. Such an analysis provides insight to infrastructure asset managers on the impact of policy and strategy decision-making regarding the maintenance and management of their infrastructure systems.


Descriptors :   *DECISION MAKING , *INFRASTRUCTURE , *RISK ANALYSIS , DATA BASES , DECAY , ECONOMICS , ESTIMATES , IMPACT , INFORMATION SYSTEMS , INPUT OUTPUT MODELS , MAINTENANCE , MANAGEMENT , MANAGEMENT PERSONNEL , MODELS , MONTE CARLO METHOD , MUNICIPALITIES , NETWORKS , RISK , SIMULATION , STOCHASTIC PROCESSES , STRATEGY , THESES


Subject Categories : Statistics and Probability
      Operations Research


Distribution Statement : APPROVED FOR PUBLIC RELEASE