Modeling Urban Scenarios & Experiments: Fort Indiantown Gap Data Collections Summary and Analysis

Daniel E. Archer, Mark S. Bandstra, Gregory G. Davidson, Steven L. Cleveland, Irakli Garishvili, Donald E. Hornback, Jeffrey O. Johnson, M. S. Lance McLean, Andrew D. Nicholson, Bruce W. Patton, Douglas E. Peplow, Alexander A. Plionis, Brian J. Quiter, Will R. Ray, Andrew J. Rowe, Mathew W. Swinney, Michael J. Willis

Research output: Book/ReportCommissioned report

Abstract

This report summarizes experimental radiation detector, contextual sensor, weather, and global positioning system (GPS) data collected to inform and validate a comprehensive, operational radiation transport modeling framework to evaluate radiation detector system and algorithm performance. This framework will be used to study the influence of systematic effects (such as geometry, background activity, background variability, environmental shielding, etc.) on detector responses and algorithm performance using synthetic time series data. This work consists of performing data collection campaigns at a canonical, controlled environment for complete radiological characterization to help construct and benchmark a high-fidelity model with quantified system geometries, detector response functions, and source terms for background and threat objects. This data also provides an archival, benchmark dataset that can be used by the radiation detection community. The data reported here spans four data collection campaigns conducted between May 2015 and September 2016.
Original languageEnglish
Place of PublicationUnited States
DOIs
StatePublished - 2017

Keywords

  • 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY

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