طراحی مبتنی بر شبیه سازی در تحقیقات تجربی عملکرد ساختمان، مورد مطالعاتی: یک ساختمان اداری در تبریز

Anu, M. (1997). Introduction to modeling and simulation, Proceedings of the 29th conference on Winter simulation, p.7-13. https://dl.acm.org/doi/10.1145/268437.268440
Athienitis, A., O’Brien, W (ed.). (2015). Modeling, Design, and Optimisation of Net-Zero Energy Buildings Solar Heating and Cooling, pp.175-176
Attiaa, Sh., Hensenb, J. LM., Beltránc, L, & D. Herde, A. (2011). Selection criteria for building performance simulation tools: Contrasting architects’ and engineers’ needs, Journal of Building Performance Simulation, 5, 1-15. https://www.researchgate.net/publication/254220572_Selection_criteria_for_building_performance_simulation_tools_Contrasting_architects%27_and_engineers%27_needs
Attia, SH., Hamdy, A., O’Brien, W, & Carlucci, S. (2013). Assessing gaps and needs for integrating building performance optimisation tools in net zero energy buildings design, Energy and Buildings J, 60, 110 124.https://www.sciencedirect.com/science/article/abs/pii/S0378778813000339
Bánóczy, E., & Szeme, P.T. (2014). Simulation-based optimisation in energy efficiency retrofit for office building, IEEE/SICE (International Symposium on System integration), pp.222-227. https://www.semanticscholar.org/paper/Simulation-based-optimization-in-energy-efficiency-B%C3%A1n%C3%B3czy-Szemes/d69dc29d-137547dae424bd9b26fa776fc2b0a99d
Demanuele, C., Tweddell, T., & Davies, M. (2010). Bridging the gap between predicted and actual energy performance in schools, World renewable energy congress XI, pp. 25-30. https://www.researchgate.net/publication/267967366_Bridging_the_gap_between_predicted_and_actual_energy_performance_in_schools
DOE. Building Energy Software Tools Directory. https://www.buildingenergysoftwaretools.com/?__cf_chl_jschl_tk__=4BPRez0hLLilQcx52.STFbrn3LhbKMFnw3Qwth7xdWY-1636035545-0-gaNycGzNCJE
Dooley, K. (2002). Simulation research methods, Baum, J (ed.), Companion to Organizations, Blackwell, London, pp. 829-830
Farhanieh, B., & Sattari, S. (2006). Simulation of energy saving in Iranian buildings using integrative modelling for insulation, Renewable Energy, 31(4), 417-425. https://www.sciencedirect.com/science/article/abs/pii/S0960148105000844
Gaetani, I., Hoes, P.J., & Hensen, L. (2016). Occupant behavior in building energy simulation: towards a fit-forpurpose modeling strategy, Energy and Buildings, 121, 188 204.https://www.sciencedirect.com/science/article/abs/pii/S0378778816301918
Garg, H., & Sharma, S. P. (2013). Reliability–redundancy allocation problem of pharmaceutical plant, Journal of Engineering Science and Technology, 8(2), 190 – 198. https://www.researchgate.net/publication/250306537_Reliability_redundancy_allocation_problem_of_pharmaceutical_plant
Hensen, J., & Lamberts, L. (ed.), (2011). Introduction to building performance simulation for design and operation, pp. 1-14, spon press, London. https://www.researchgate.net/publication/270570789_Building_Performance_Simulation_for_Design_and_Operation
H. Hart, G. (2011). Saving energy by insulating pipe components: on steam & hot water distribution systems, ASHRAE J. 53(10), 42-48. https://www.researchgate.net/publication/294658495_Saving_Energy_by_Insulating_pipe_Components_On_Steam_Hot_Water_Distribution_Systems
Holland, J. (2000). Emergence: From Chaos to Order, pp.45-52, Oxford University Press.
Jankovic, L. (2017). Designing Zero Carbon Buildings Using Dynamic Simulation Methods, second edition, Routledge, New York, pp.10-11
Kuo, W., & Prasad, V.R (2000). An annotated overview of system reliability optimisation. IEEE Transaction on Reliability, (49)2,176-187. https://ieeexplore.ieee.org/abstract/document/877336
Liang, X., Hong, T., Shen, G.Q. (2016). Occupancy data analytics and prediction: A case study, Building and Environment, 102,179-192. https://www.sciencedirect.com/science/article/abs/pii/S036013231630110X
Lund Jensen, R., & Kalyanova, O., Heiselberg, P. (2008). Modeling a naturally ventilated double skin façade with a building thermal simulation program, 8th Nordic symposium, Building physics. https://www.researchgate.net/publication/237464908_Modeling_a_Naturally_Ventilated_Double_Skin_Facade_with_a_Building_Thermal_Simulation_Program
Lusk, G. (2016). Computer simulation and the features of novel empirical data, Studies in History and Philosophy of Science, 56,145-152. https://www.sciencedirect.com/science/article/abs/pii/S0039368115001430
M. Samaan, M., Farag, O. & Khalil, M. (2018). Using simulation tools for optimizing cooling loads and daylighting levels in Egyptian campus buildings, Housing and Building National Research Center, (HBRC J),14, 79–92. https://www.sciencedirect.com/science/article/pii/S168740481600002X
Nguyen, A., Reiter, S. & Rigo, P. (2014). A Preview on simulation-based optimisation methods applied to building performance analysis, Applied Energy, pp. 1043-1058.https://www.sciencedirect.com/science/article/abs/pii/S0306261913007058
Niu, S. Pan, W., & Zhao, Y. (2016). A virtual reality integrated design approach to improving occupancy information integrity for closing the building energy performance gap, Sustainable Cities and Society, 27, 275-286. https://www.researchgate.net/publication/298897644_A_virtual_reality_integrated_design_approach_to_improving_occupancy_information_integrity_for_closing_the_building_energy_performance_gap
Panas, A., & Pantouvakis, J. P. (2010). Evaluating research methodology in construction productivity studies, The Built & Human Environment Review J, 3(1), 70. https://www.researchgate.net/publication/282715366_Evaluating_research_methodology_in_construction_productivity_studies
Peng, W., Yang, J., Wagner, F., & Mauzerall, D.L. (2017). Substantial air quality and climate co-benefits achievable now with sectoral mitigation strategies in China. Sci. Total Environ. 598, 1076–1084. https://www.sciencedirect.com/science/article/abs/pii/S0048969717308185
Suh,W J., Park, C. S, & Kim, D. W.(2011). Heuristic vs. meta-heuristic optimisation for energy performance of a post office building. Proceedings of the 12th conference of international building performance simulation association, pp. 704-711, Sydney: IBPSA.
Tian, Z., Zhang, X., Jin, X., Zhou, X., Si, B. & Shi, X. (2018). Towards adoption of building energy simulation and optimisation for passive building design: A survey and a review, Energy and Buildings J, 158, 1306-1316. https://www.sciencedirect.com/science/article/abs/pii/S0378778817317899
Tian, Z.C., Chen, W.Q., Tang, P., Wang, J.G, & Shi, X. (2015). Building Energy Optimisation Tools and Their Applicability in Architectural Conceptual Design Stage, Energy Procedia (78), 2572 – 2577. https://www.sciencedirect.com/science/article/pii/S1876610215020202
Wetter, M. (2009). GenOpt, Generic optimisation program - User manual, version 3.0.0. Technical report, LBNL-5419. s. l.: Lawrence Berkeley National Laboratory.
Wilde, P. De. (2014). The gap between predicted and measured energy performance of buildings: A framework for investigation, Automation in Construction, 41, 40-49. https://www.sciencedirect.com/science/article/abs/pii/S092658051400034X
X. W. Zou, P., & Alam, M. (2020). Closing the Building Energy Performance Gap Through Component Level Analysis and Stakeholder Collaborations. Energy & Buildings Journal, (224). https://www.sciencedirect.com/science/article/abs/pii/S0378778820307842
Yan, D., O ‘Brien, W., Hong T., Feng, X., Gunay, H.B., Tahmasebi, F., & Mahdavi, A. (2015). Occupant behavior modeling for building performance simulation: Current state and future challenges, Energy and Buildings, 107, 264-278. https://www.sciencedirect.com/science/article/abs/pii/S0378778815302164
Yoshino, H., Hong, T., & Nord, N., (2017). IEA EBC annex 53: Total energy use in buildings—Analysis and evaluation methods, Energy and Buildings, 152, 124-136. https://www.sciencedirect.com/science/article/abs/pii/S0378778817318716
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