Characterization of an airflow network model by sensitivity analysis: parameter screening, fixing, prioritizing and mapping
Authors:
Open Access
- 2 January 2016
- journal article
- research article
- Published by Taylor & Francis in Journal of Building Performance Simulation
- Vol. 10 (1) , 17-36
Abstract
Due to the over-parameterized models in detailed thermal simulation programs, modellers undertaking validation or calibration studies, where the model output is compared against field measurements, face difficulties in determining those parameters which are primarily responsible for observed differences. Where sensitivity studies are undertaken, the Morris method is commonly applied to identify the most influential parameters. They are often accompanied by uncertainty analysis using Monte Carlo simulations to generate confidence bounds around the predictions. This paper sets out a more rigorous approach to sensitivity analysis (SA) based on a global SA method with three stages: factor screening, factor prioritizing and fixing, and factor mapping. The method is applied to a detailed empirical validation data set obtained within IEA ECB Annex 58, with the focus of the study on the airflow network, a simulation program sub-model which is subject to large uncertainties in its inputs.Keywords
This publication has 39 references indexed in Scilit:
- Evaluation of a multi-stage guided search approach for the calibration of building energy simulation modelsEnergy and Buildings, 2015
- A methodology for identifying the influence of design variations on building energy performanceJournal of Building Performance Simulation, 2013
- Decision making under uncertainty in the retrofit analysis of the UK housing stock: Implications for the Green DealEnergy and Buildings, 2013
- Overview of pressure coefficient data in building energy simulation and airflow network programsBuilding and Environment, 2009
- Uncertainty and Sensitivity Analysis for Building Energy RatingJournal of Building Physics, 2009
- An effective screening design for sensitivity analysis of large modelsEnvironmental Modelling & Software, 2007
- Sensitivity analysis when model outputs are functionsReliability Engineering & System Safety, 2006
- Sensitivity analysis and validation of buildings' thermal models using adjoint-code methodEnergy and Buildings, 2000
- The use of graph theory in the sensitivity analysis of the model output: a second order screening methodReliability Engineering & System Safety, 1999
- The future of distributed models: Model calibration and uncertainty predictionHydrological Processes, 1992