Uncertainty Propagation of Internal Heat Gains for Building Thermal Behaviour Assessment: Influence of Spatial Distribution
暂无分享,去创建一个
[1] E. Iso,et al. Measurement Uncertainty and Probability: Guide to the Expression of Uncertainty in Measurement , 1995 .
[2] Brian J. Williams,et al. Sensitivity analysis when model outputs are functions , 2006, Reliab. Eng. Syst. Saf..
[3] Andrea Saltelli,et al. An effective screening design for sensitivity analysis of large models , 2007, Environ. Model. Softw..
[4] Saltelli Andrea,et al. Global Sensitivity Analysis: The Primer , 2008 .
[5] P Pieter-Jan Hoes,et al. User behavior in whole building simulation , 2009 .
[6] Matieyendou Lamboni,et al. Multivariate global sensitivity analysis for dynamic crop models , 2009 .
[7] Ardeshir Mahdavi,et al. USER BEHAVIOR AND ENERGY PERFORMANCE IN BUILDINGS , 2009 .
[8] T. Nagai,et al. PROBABILISTIC APPROACH TO DETERMINATION OF INTERNAL HEAT GAINS IN OFFICE BUILDING FOR PEAK LOAD CALCULATIONS , 2013 .
[9] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[10] Pieter de Wilde,et al. The gap between predicted and measured energy performance of buildings: A framework for investigation , 2014 .
[11] Brian J. Polidoro,et al. CONTAM User Guide and Program Documentation Version 3.2 , 2015 .
[12] Cheol-Soo Park,et al. Different Occupant Modeling Approaches for Building Energy Prediction , 2016 .
[13] A. Mahdavi,et al. A SYSTEMATIC ASSESSMENT OF THE SENSITIVITY OF BUILDING PERFORMANCE SIMULATION RESULTS WITH REGARD TO OCCUPANCY-RELATED INPUT ASSUMPTIONS , 2016 .
[14] Wei Tian,et al. Spatial distribution of internal heat gains: A probabilistic representation and evaluation of its influence on cooling equipment sizing in large office buildings , 2017 .
[15] A. Mahdavi,et al. IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings , 2017 .
[16] Patrick Schalbart,et al. Energy Performance Contracting Methodology Based upon Simulation and Measurement , 2017 .
[17] Minna Sunikka-Blank,et al. The Influence of Variation in Occupancy Pattern on Domestic Energy Simulation Prediction: A Case Study in Shanghai , 2017 .
[18] Henrik Madsen,et al. On site characterisation of the overall heat loss coefficient: Comparison of different assessment methods by a blind validation exercise on a round robin test box , 2017 .
[19] Władysław Jakubiec,et al. Evaluation of measurement uncertainty – Monte Carlo method , 2017 .
[20] Franklin P. Mills,et al. Rethinking the role of occupant behavior in building energy performance: A review , 2018, Energy and Buildings.
[21] B. Ajib. Data-driven building thermal modeling using system identification for hybrid systems , 2018 .
[22] Dominique Marchio,et al. A comparison of methods for uncertainty and sensitivity analysis applied to the energy performance of new commercial buildings , 2018 .
[23] E. Ghisi,et al. A field study about gender and thermal comfort temperatures in office buildings , 2018, Energy and Buildings.
[24] Pieter de Wilde,et al. A review of uncertainty analysis in building energy assessment , 2018, Renewable and Sustainable Energy Reviews.
[25] T. Lawrence,et al. Thermal comfort evaluation in campus classrooms during room temperature adjustment corresponding to demand response , 2019, Building and Environment.