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A Multi-Entity Field Approximation to determine the source location of multiple atmospheric contaminant releases
Abstract In the event of an accidental or intentional contaminant release, it is imperative to locate the source of the contaminant for use in hazard prediction models. In some situations more than a single contaminant release will be present, which becomes a complicating factor when contaminants from these releases significantly overlap. Here we present a Lagrangian approach to determine the source locations of multiple contaminant releases. For this approach, we assume that the concentration field is approximated by a superposition of contaminant entities, where an entity is a discrete object; namely a puff for an instantaneous release and a plume for a continuous release. The state of each entity is inferred from surface observations of the contaminant, and extrapolation of each entity's state provides an estimate of the contaminant source locations. We call this method a Multi-Entity Field Approximation (MEFA) because together the entities' concentration fields sum to approximate the observed concentration field. In this work, we outline the MEFA process for both instantaneous and continuous contaminant releases using data from two FUSION Field Trial 2007 (FFT07) Trials where contaminant fields from multiple contaminant releases overlap close to the source location.
Highlights ► We adopt a state estimation approach to locate the source of multiple contaminant releases. ► This technique is called a Multi-Entity Field Approximation (MEFA). ► We determine and analyze each entity's state to infer the contaminant source information. ► We demonstrate the method for instantaneous and continuous release scenarios using FFT07 Trial data.
A Multi-Entity Field Approximation to determine the source location of multiple atmospheric contaminant releases
Abstract In the event of an accidental or intentional contaminant release, it is imperative to locate the source of the contaminant for use in hazard prediction models. In some situations more than a single contaminant release will be present, which becomes a complicating factor when contaminants from these releases significantly overlap. Here we present a Lagrangian approach to determine the source locations of multiple contaminant releases. For this approach, we assume that the concentration field is approximated by a superposition of contaminant entities, where an entity is a discrete object; namely a puff for an instantaneous release and a plume for a continuous release. The state of each entity is inferred from surface observations of the contaminant, and extrapolation of each entity's state provides an estimate of the contaminant source locations. We call this method a Multi-Entity Field Approximation (MEFA) because together the entities' concentration fields sum to approximate the observed concentration field. In this work, we outline the MEFA process for both instantaneous and continuous contaminant releases using data from two FUSION Field Trial 2007 (FFT07) Trials where contaminant fields from multiple contaminant releases overlap close to the source location.
Highlights ► We adopt a state estimation approach to locate the source of multiple contaminant releases. ► This technique is called a Multi-Entity Field Approximation (MEFA). ► We determine and analyze each entity's state to infer the contaminant source information. ► We demonstrate the method for instantaneous and continuous release scenarios using FFT07 Trial data.
A Multi-Entity Field Approximation to determine the source location of multiple atmospheric contaminant releases
Annunzio, Andrew J. (Autor:in) / Young, George S. (Autor:in) / Haupt, Sue Ellen (Autor:in)
Atmospheric Environment ; 62 ; 593-604
15.08.2012
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Source term estimation , Multi-Entity Field Approximation , Entity , Atmospheric transport and dispersion , FUSION Field Trial 2007 , Genetic Algorithm optimization , AT&D , Atmospheric Transport and Dispersion , AYH12 , Annunzio, Young and Haupt, 2012 , digiPIDS , Digital Photoionization Sensors , FFT07 , MEFA , SEFA , Single Entity Field Approximation , STE , Source Term Estimation
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