Integration of network flow modelling and computational fluid dynamics to simulate contaminant transport and behaviour in the indoor environment

Aizaz Aamir Samuel, Paul Strachan

Research output: Contribution to journalArticle

Abstract

The flow of air from one room to another may be approximated by network flow models which consider the bulk flow of air. Such models can predict inter-zone air distributions but cannot predict intra-zone air flow conditions. Computational fluid dynamics, on the other hand, can be used to predict intra-room air flows with a high degree of accuracy provided sufficient care is taken in specification of boundary conditions, initial conditions and grid definition. Contaminant transport and behavior prediction models are supported by both modeling techniques. To overcome shortcomings of the individual techniques, both methods are combined within an integrated modeling framework. The methodology for prediction of contaminant concentration uses three solution procedures in addition to CFD. These involve the setting up and solution of contaminant distribution and transport equations (a sparse linear system), the setting up and solution of air flow equations (a non-linear system) and the setting up and solution of building thermal equations (a sparse non-linear system). This paper presents a method to integrate these approaches in order to accurately predict both inter- and intra-room air flows and contaminant distributions.

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Contaminant Transport
Network Flow
Computational Fluid Dynamics
Computational fluid dynamics
Impurities
Air
Modeling
Predict
Nonlinear Systems
Nonlinear systems
Integrated Modeling
Three Solutions
Sparse Linear Systems
Transport Equation
Prediction Model
Initial conditions
Linear systems
Integrate
Specification
Sufficient

Keywords

  • computational fluid dynamics
  • CFD
  • airflow
  • pollutant
  • multizone modeling

Cite this

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title = "Integration of network flow modelling and computational fluid dynamics to simulate contaminant transport and behaviour in the indoor environment",
abstract = "The flow of air from one room to another may be approximated by network flow models which consider the bulk flow of air. Such models can predict inter-zone air distributions but cannot predict intra-zone air flow conditions. Computational fluid dynamics, on the other hand, can be used to predict intra-room air flows with a high degree of accuracy provided sufficient care is taken in specification of boundary conditions, initial conditions and grid definition. Contaminant transport and behavior prediction models are supported by both modeling techniques. To overcome shortcomings of the individual techniques, both methods are combined within an integrated modeling framework. The methodology for prediction of contaminant concentration uses three solution procedures in addition to CFD. These involve the setting up and solution of contaminant distribution and transport equations (a sparse linear system), the setting up and solution of air flow equations (a non-linear system) and the setting up and solution of building thermal equations (a sparse non-linear system). This paper presents a method to integrate these approaches in order to accurately predict both inter- and intra-room air flows and contaminant distributions.",
keywords = "computational fluid dynamics, CFD, airflow, pollutant, multizone modeling",
author = "Samuel, {Aizaz Aamir} and Paul Strachan",
year = "2008",
month = "1",
language = "English",
volume = "114",
pages = "250--258",
journal = "American Society of Heating Refrigerating and Air Conditioning Engineers (ASHRAE) Transactions",
issn = "0001-2505",
publisher = "Amer. Soc. Heating, Ref. Air-Conditoning Eng. Inc.",

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AU - Samuel, Aizaz Aamir

AU - Strachan, Paul

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N2 - The flow of air from one room to another may be approximated by network flow models which consider the bulk flow of air. Such models can predict inter-zone air distributions but cannot predict intra-zone air flow conditions. Computational fluid dynamics, on the other hand, can be used to predict intra-room air flows with a high degree of accuracy provided sufficient care is taken in specification of boundary conditions, initial conditions and grid definition. Contaminant transport and behavior prediction models are supported by both modeling techniques. To overcome shortcomings of the individual techniques, both methods are combined within an integrated modeling framework. The methodology for prediction of contaminant concentration uses three solution procedures in addition to CFD. These involve the setting up and solution of contaminant distribution and transport equations (a sparse linear system), the setting up and solution of air flow equations (a non-linear system) and the setting up and solution of building thermal equations (a sparse non-linear system). This paper presents a method to integrate these approaches in order to accurately predict both inter- and intra-room air flows and contaminant distributions.

AB - The flow of air from one room to another may be approximated by network flow models which consider the bulk flow of air. Such models can predict inter-zone air distributions but cannot predict intra-zone air flow conditions. Computational fluid dynamics, on the other hand, can be used to predict intra-room air flows with a high degree of accuracy provided sufficient care is taken in specification of boundary conditions, initial conditions and grid definition. Contaminant transport and behavior prediction models are supported by both modeling techniques. To overcome shortcomings of the individual techniques, both methods are combined within an integrated modeling framework. The methodology for prediction of contaminant concentration uses three solution procedures in addition to CFD. These involve the setting up and solution of contaminant distribution and transport equations (a sparse linear system), the setting up and solution of air flow equations (a non-linear system) and the setting up and solution of building thermal equations (a sparse non-linear system). This paper presents a method to integrate these approaches in order to accurately predict both inter- and intra-room air flows and contaminant distributions.

KW - computational fluid dynamics

KW - CFD

KW - airflow

KW - pollutant

KW - multizone modeling

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JO - American Society of Heating Refrigerating and Air Conditioning Engineers (ASHRAE) Transactions

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JF - American Society of Heating Refrigerating and Air Conditioning Engineers (ASHRAE) Transactions

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