A platform for research: civil engineering, architecture and urbanism
A Gaussian process emulator approach for rapid contaminant characterization with an integrated multizone-CFD model
Abstract This paper explores a Gaussian process emulator based approach for rapid Bayesian inference of contaminant source location and characteristics in an indoor environment. In the pre-event detection stage, the proposed approach represents transient contaminant fate and transport as a random function with multivariate Gaussian process prior. Hyper-parameters of the Gaussian process prior are inferred using a set of contaminant fate and transport simulation runs obtained at predefined source locations and characteristics. This paper uses an integrated multizone-CFD model to simulate contaminant fate and transport. Mean of the Gaussian process, conditional on the inferred hyper-parameters, is used as a computationally efficient statistical emulator of the multizone-CFD simulator. In the post event-detection stage, the Bayesian framework is used to infer the source location and characteristics using the contaminant concentration data obtained through a sensor network. The Gaussian process emulator of the contaminant fate and transport is used for Markov Chain Monte Carlo sampling to efficiently explore the posterior distribution of source location and characteristics. Efficacy of the proposed method is demonstrated for a hypothetical contaminant release through multiple sources in a single storey seven room building. The method is found to infer location and characteristics of the multiple sources accurately. The posterior distribution obtained using the proposed method is found to agree closely with the posterior distribution obtained by directly coupling the multizone-CFD simulator with the Markov Chain Monte Carlo sampling.
Highlights A Gaussian process emulator-based Bayesian framework for indoor source characterization is proposed. The method uses integrated multizone-CFD model for prediction of contaminant fate and transport. The method is developed for localization and characterization of possibly multiple sources. Efficacy of the method is demonstrated for hypothetical contaminant release in a seven room single-story building. The method significantly improves computational cost compared to direct-MCMC sampling with comparable accuracy.
A Gaussian process emulator approach for rapid contaminant characterization with an integrated multizone-CFD model
Abstract This paper explores a Gaussian process emulator based approach for rapid Bayesian inference of contaminant source location and characteristics in an indoor environment. In the pre-event detection stage, the proposed approach represents transient contaminant fate and transport as a random function with multivariate Gaussian process prior. Hyper-parameters of the Gaussian process prior are inferred using a set of contaminant fate and transport simulation runs obtained at predefined source locations and characteristics. This paper uses an integrated multizone-CFD model to simulate contaminant fate and transport. Mean of the Gaussian process, conditional on the inferred hyper-parameters, is used as a computationally efficient statistical emulator of the multizone-CFD simulator. In the post event-detection stage, the Bayesian framework is used to infer the source location and characteristics using the contaminant concentration data obtained through a sensor network. The Gaussian process emulator of the contaminant fate and transport is used for Markov Chain Monte Carlo sampling to efficiently explore the posterior distribution of source location and characteristics. Efficacy of the proposed method is demonstrated for a hypothetical contaminant release through multiple sources in a single storey seven room building. The method is found to infer location and characteristics of the multiple sources accurately. The posterior distribution obtained using the proposed method is found to agree closely with the posterior distribution obtained by directly coupling the multizone-CFD simulator with the Markov Chain Monte Carlo sampling.
Highlights A Gaussian process emulator-based Bayesian framework for indoor source characterization is proposed. The method uses integrated multizone-CFD model for prediction of contaminant fate and transport. The method is developed for localization and characterization of possibly multiple sources. Efficacy of the method is demonstrated for hypothetical contaminant release in a seven room single-story building. The method significantly improves computational cost compared to direct-MCMC sampling with comparable accuracy.
A Gaussian process emulator approach for rapid contaminant characterization with an integrated multizone-CFD model
Tagade, Piyush M. (author) / Jeong, Byeong-Min (author) / Choi, Han-Lim (author)
Building and Environment ; 70 ; 232-244
2013-08-13
13 pages
Article (Journal)
Electronic Resource
English
British Library Online Contents | 2013
|Contaminant ingress into multizone buildings: An analytical state-space approach
Online Contents | 2014
|Multizone Modeling Approaches to Contaminant-Based Design
British Library Online Contents | 2002
|Multizone Modeling Approaches to Contaminant-Based Design
British Library Conference Proceedings | 2002
|