سازگاری حرارتی به عنوان شاخص نهایی سنجش کیفیت سایه اندازی سایبانهای خارجی نمونه مورد مطالعه : ساختمان مسکونی در شیراز

طرح تفضیلی شیراز، ضوابط و مقررات شهرسازی و ساختمانی، مهندسان مشاور برنامه ریز، شهر ساز و معمار شهر و خانه، 1393. ASHRAE 55-2010: American Society of Heating, Refrigerating and Air-Conditioning Engineers, Atlanta.

Thermal Environmental Conditions for Human Occupancy. ASHRAE 55 (2010) ASHRAE Standard 55-2010.

ASHRAE 14-2014: American Society of Heating, Ventilating, and Air Conditioning Engineers (ASHRAE).

Guideline 14-2014, Measurement of Energy and Demand Savings; Technical Report; American Society of Heating, Ventilating, and Air Conditioning Engineers: Atlanta, GA, USA, 2014.

ASHRAE 14-2002: American Society of Heating, Refrigeration and Air Conditioning Engineers, ASHRAE Guideline 14-2002 for Measurement of Energy and Demand Savings, , Atlanta, GA.

Amini R, Ghaffarianhoseini A, Ghaffarianhoseini A, Berardi U. Numerical investigation of indoor thermal comfort and air quality for a multi-purpose hall with various shading and glazing ratios. Thermal Science and Engineering Progress. 2021 May 1;22:100812.

Andelkovic AS, Mujan I, Dakić S. Experimental validation of a EnergyPlus model: Application of a multi-storey naturally ventilated double skin façade. Energy and Buildings. 2016 Apr 15;118:27-36.

Arbab M, Rahbar M, Arbab M. A Comparative Study of Artificial Intelligence Models for Predicting Interior Illuminance. Applied Artificial Intelligence. 2021 Apr 16;35(5):373-92.

Asadi E, da Silva MG, Antunes CH, Dias L, Glicksman L. Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application. Energy Build 2014;81:444–56.

Ascione F, Bianco N, Mauro GM, Vanoli GP. A new comprehensive framework for the multi-objective optimization of building energy design: Harlequin. Appl Energy 2019;241:331–61.

Baldinelli G. Double skin façades for warm climate regions: Analysis of a solution with an integrated movable shading system. 2009, Building and Environment 44(6):1107-1118 doi:10.1016/j.buildenv.2008.08.005

Bessoudo M, Tzempelikos A, Athienitis AK, Zmeureanu R. Indoor thermal environmental conditions near glazed facades with shading devices–Part I: Experiments and building thermal model. Building and environment. 2010 Nov 1;45(11):2506-16. https://doi.org/10.1016/j.buildenv.2010.05.013.

Calama-Gonzalez CM, Suárez R, León-Rodríguez ÁL. Thermal comfort prediction of the existing housing stock in southern Spain through calibrated and validated parameterized simulation models. Energy and Buildings. 2022 Jan 1;254:111562. Calixto-Aguirre I, Huelsz G, Barrios G, Cruz-Salas MV. Validation of thermal simulations of a non-air-conditioned office building in different seasonal, occupancy and ventilation conditions. Journal of Building Engineering. 2021 Dec 1;44:102922.

Carletti C, Sciurpi F, Pierangioli L, Asdrubali F, Pisello AL, Bianchi F, Sambuco S, Guattari C. Thermal and lighting effects of an external venetian blind: Experimental analysis in a full scale test room. Building and Environment. 2016 Sep 1;106:45-56.https://doi.org/10.1016/j.buildenv.2016.06.017.

Carlucci S, Cattarin G, Causone F, Pagliano L. Multi-objective optimization of a nearly zero-energy building based on thermal and visual discomfort minimization using a non-dominated sorting genetic algorithm (NSGA-II). Energy Build 2015;104:378–94.

Chatzikonstantinou I, Sariyildiz S, Bittermann MS. Conceptual airport terminal design using evolutionary computation. In: 2015 IEEE congress on evolutionary computation; 2015. p. 2245–52.

Cho J, Yoo C, Kim Y. Viability of exterior shading devices for high-rise residential buildings: Case study for cooling energy saving and economic feasibility analysis. Energy and Buildings. 2014 Oct 1;82:771-85.

Chollet F. Keras [WWW Document]. GitHub. URL https://github. com/fchollet/keras. 2015.

Chua KJ, Chou SK. Evaluating the performance of shading devices and glazing types to promote energy efficiency of residential buildings. InBuilding Simulation 2010 Sep (Vol. 3, No. 3, pp. 181-194). Springer Berlin Heidelberg.https://doi.org/10.1007/s12273-010-0007-2.

Ciro GC, Dugardin F, Yalaoui F, Kelly R. A NSGA-II and NSGA-III comparison for solving an open shop scheduling problem with resource constraints. IFAC-PapersOnLine 2016; 49(12): 1272–7.

Coakley D, Raftery P, Molloy P. Calibration of whole building energy simulation models: detailed case study of a naturally ventilated building using hourly measured data, Proceedings First Building Simulation and Optimization Conference (2012) 57–64.

da Fonseca RW, Didoné EL, Pereira FO. Using artificial neural networks to predict the impact of daylighting on building final electric energy requirements. Energy and Buildings. 2013 Jun 1;61:31-8. doi: 10.1016/j.enbuild.2013.02.009. Dahanayake KK, Chow CL. Studying the potential of energy saving through vertical greenery systems: Using EnergyPlus simulation program. Energy and Buildings. 2017 Mar 1;138:47-59.doi:10.1016/j.enbuild.2016.12.002.

Deb K, Jain H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE Trans Evol Comput 2013;18(4):577–601.

Deb K, Pratap A, Agarwal S, Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 2002;6(2):182–97.

Eltaweel A, Su Y. (2017). Controlling venetian blinds based on parametric design; via implementing Grasshopper’s plugins: A case study of an office building in Cairo. Energy and Buildings, 139, 31–43.

doi:10.1016/j.enbuild.2016.12.075

Emmerich MT, Deutz AH. A tutorial on multiobjective optimization: fundamentals and evolutionary methods. Nat Comput 2018; 17(3):585–609.

Fang Y, Cho S. Design optimization of building geometry and fenestration for daylighting and energy performance. Solar Energy. 2019 Oct 1;191:7-18. doi: 10.1016/j.solener.2019.08.039.

Hall MR. 2010. Materials for Energy Efficiency and Thermal Comfort in Buildings. Woodhead Publishing Series in Energy, eBook ISBN: 9781845699277.

Hashemi N, Fayaz R, Sarshar M. Thermal behaviour of a ventilated double skin facade in hot arid climate, Energy and Buildings, Volume 42, Issue 10, 2010, Pages 1823-1832, ISSN 0378-7788.

https://doi.org/10.1016/j.enbuild.2010.05.019.

Hossain MU, Poon CS. Global warming potential and energy consumption of temporary works in building construction: A case study in Hong Kong. Building and Environment. 2018 Sep 1;142:171-9. https://doi.org/10.1016/j.buildenv.2018.06.026.

https://climatestudiodocs.com/docs/daylightLEEDOpt1.html

Jayathissa P, Luzzatto M, Schmidli J, Hofer J, Nagy Z, Schlueter A. Optimising building net energy demand with dynamic BIPV shading. Applied Energy. 2017 Sep 15;202:726-35.

https://doi.org/10.1016/j.apenergy.2017.05.083.

Karaman S, Ekici B, Cubukcuoglu C, Koyunbaba BK, Kahraman I. Design of rectangular façade modules through computational intelligence. In: 2017 IEEE congress on evolutionary computation; 2017. p. 1021–8.

Khoroshiltseva M, Slanzi D, Poli I. A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices. Applied energy. 2016 Dec 15;184:1400-10.

https://doi.org/10.1016/j.apenergy.2016.05.015

Kirimtat A, Koyunbaba BK, Chatzikonstantinou I, Sariyildiz S, Suganthan PN. Multi-objective optimization for shading devices in buildings by using evolutionary algorithms. 2016 IEEE Congress on Evolutionary Computation (CEC). doi:10.1109/cec.2016.7744286

Kirimtat A, Koyunbaba BK, Chatzikonstantinou I, Sariyildiz S. Review of simulation modeling for shading devices in buildings. Renew. Sustain. Energy Rev., vol. 53, pp. 23–49, Jan. 2016. doi: 10.1016/j.rser.2015.08.020.

Kirimtat A, Krejcar O, Ekici B, Tasgetiren MF. Multi-objective energy and daylight optimization of amorphous shading devices in buildings. Solar Energy. 2019 Jun 1;185:100-11.

Levy S, Steinberg DM. Computer experiments: a review. AStA Advances in Statistical Analysis. 2010 Dec;94(4):311-24. doi:10.1016/j.ress.2015.12.002

Lim YW, Kandar MZ, Ahmad MH, Ossen DR, Abdullah AM. Building façade design for daylighting quality in typical government office building. Building and Environment. 2012 Nov 1;57:194-204. https://doi.org/10.1016/j.buildenv.2012.04.015.

Liu S, Kwok YT, Lau KK, Chan PW, Ng E. Investigating the energy saving potential of applying shading panels on opaque façades: A case study for residential buildings in Hong Kong. Energy and Buildings. 2019 Jun 15;193:78-91. https://doi.org/10.1016/j.enbuild.2019.03.044.

Loeppky JL, Sacks J, Welch WJ. Choosing the sample size of a computer experiment: A practical guide. Technometrics. 2009 Nov 1;51(4):366-76. http://dx.doi.org/10.1198/TECH.2009.08040

Mandalaki M, Zervas K, Tsoutsos T, Vazakas A. Assessment of fixed shading devices with integrated PV for efficient energy use. Solar Energy. 2012 Sep 1;86(9):2561-75. doi:10.1016/j.solener.2012.05.026

Mangkuto RA, Feradi F, Putra RE, Atmodipoero RT, Favero F. (2018). Optimisation of daylight admission based on modifications of light shelf design parameters. Journal of Building Engineering, 18, 195–209. doi:10.1016/j.jobe.2018.03.007

Mangkuto RA, Koerniawan MD, Soelami FN. Daylight Annual Illuminance Investigation in Elementary School Classrooms for the Tropic of Lhokseumawe, Indonesia. Journal of Applied Science and Engineering. 2021 Jul;25(1):129-39.

Manzan M, Clarich A. FAST energy and daylight optimization of an office with fixed and movable shading devices. Building and Environment. 2017 Feb 15;113:175-84.https://doi.org/10.1016/j.buildenv.2016.09.035.

Marszal AJ, Heiselberg P, Bourrelle JS, Musall E, Voss K, Sartori I. Napolitano A. Zero Energy Building – A review of definitions and calculation methodologies, Energy and Buildings, Volume 43, Issue 4, 2011, Pages 971-979, ISSN 0378-7788. https://doi.org/10.1016/j.enbuild.2010.12.022.

Naderi E, Sajadi B, Behabadi MA, Naderi E. Multi-objective simulation-based optimization of controlled blind specifications to reduce energy consumption, and thermal and visual discomfort: Case studies in Iran. Building and Environment. 2020 Feb 1;169:106570. https://doi.org/10.1016/j.buildenv.2019.106570.

Pal SK, Takano A, Alanne K, Siren K. (2017). A life cycle approach to optimizing carbon footprint and costs of a residential building. Building and Environment, 123, 146–162.

https://doi.org/10.1016/j.buildenv.2017.06.051.

Park JH, Yun BY, Chang SJ, Wi S, Jeon J, Kim S. Impact of a passive retrofit shading system on educational building to improve thermal comfort and energy consumption. Energy and Buildings. 2020 Jun 1;216:109930.https://doi.org/10.1016/j.enbuild.2020.109930.

Pulido-Arcas JA, Rubio-Bellido C, Perez-Fargallo A, Oropeza-Perez I. 2020. Zero-Energy Buildings - New Approaches and Technologies, Net-Zero Energy Buildings: Principles and Applications (chapter 4). ISBN:978-1-78985-246-2. DOI:10.5772/intechopen.87727

Ramos Ruiz G, Fernandez Bandera C. Validation of calibrated energy models: Common errors. Energies. 2017 Oct 12;10(10):1587.

doi:10.3390/en10101587 Razmi A, Rahbar M, Bemanian M. PCA-ANN integrated NSGA-III framework for dormitory building design optimization: Energy efficiency, daylight, and thermal comfort. Appl. Energy, vol. 305, no. September 2021, p. 117828, Jan. 2022, doi: 10.1016/j.apenergy.2021.117828.

Salam A, El Hibaoui A, Saif A. A comparison of activation functions in multilayer neural network for predicting the production and consumption of electricity power. International Journal of Electrical and Computer Engineering (IJECE). 2021 Feb 1;11(1):163-70.

Samadi S, Noorzai E, Beltrán LO, Abbasi S. A computational approach for achieving optimum daylight inside buildings through automated kinetic shading systems. Frontiers of Architectural Research. 2020 Jun 1;9(2):335-49. https://doi.org/10.1016/j.foar.2019.10.004.

Sang Y, Zhao JR, Sun J, Chen B, Liu S. Experimental investigation and EnergyPlus-based model prediction of thermal behavior of building containing phase change material. Journal of Building Engineering. 2017 Jul 1;12:259-66. doi:10.1016/j.jobe.2017.06.011

Sghiouri H, Mezrhab A, Karkri M, Naji H. Shading devices optimization to enhance thermal comfort and energy performance of a residential building in Morocco. Journal of building Engineering. 2018 Jul 1;18:292-302.

Sherif A, El-Zafarany A, Arafa R. External perforated window Solar Screens: The effect of screen depth and perforation ratio on energy performance in extreme desert environments. Energy and Buildings, 52, 2012, pages1-10. doi:10.1016/j.enbuild.2012.05.025

Sima E, Chagolla-Aranda MA, Huelsz G, Tovar R, Alvarez G. Tree and neighboring buildings shading effects on the thermal performance of a house in a warm sub-humid climate. Building Simulation (2015), 8(6), 711–723. doi:10.1007/s12273-015-0247-2

Singh R, Lazarus IJ, Kishore VV. Uncertainty and sensitivity analyses of energy and visual performances of office building with external venetian blind shading in hot-dry climate. Applied energy. 2016 Dec 15;184:155-70. doi:10.1016/j.apenergy.2016.10.007

Stazi F, Marinelli S, Di Perna C, Munafò P. Comparison on solar shadings: Monitoring of the thermo-physical behaviour, assessment of the energy saving, thermal comfort, natural lighting and environmental impact. Solar Energy. 2014 Jul 1;105:512-28. doi:10.1016/j.solener.2014.04.005

Szandala T. Review and comparison of commonly used activation functions for deep neural networks. InBio-inspired neurocomputing 2021 (pp. 203-224). Springer, Singapore.

Tabadkani A, Valinejad Shoubi M, Soflaei F, Banihashemi S. Integrated parametric design of adaptive facades for user's visual comfort, Automation in Construction, Volume 106, 2019, 102857, ISSN 0926-5805, https://doi.org/10.1016/j.autcon.2019.102857.

Taveres-Cachat E, Lobaccaro G, Goia F, Chaudhary G. A methodology to improve the performance of PV integrated shading devices using multi-objective optimization. Applied energy. 2019 Aug 1;247:731-44. https://doi.org/10.1016/j.apenergy.2019.04.033.

TensorFlow Team. TensorFlow: Large-scale machine learning on heterogeneous systems.2015.

Tian W, Heo Y, De Wilde P, Li Z, Yan D, Park CS, Feng X, Augenbroe G. A review of uncertainty analysis in building energy assessment. Renewable and Sustainable Energy Reviews. 2018 Oct 1;93:285-301.doi:10.1016/j.rser.2018.05.029

Toutou A, Fikry M, Mohamed W. The parametric based optimization framework daylighting and energy performance in residential buildings in hot arid zone. Alexandria engineering journal. 2018 Dec 1;57(4):3595-608.

Valladares-Rendon LG, Lo SL. Passive shading strategies to reduce outdoor insolation and indoor cooling loads by using overhang devices on a building. InBuilding Simulation 2014 Dec (Vol. 7, No. 6, pp. 671-681). Springer Berlin Heidelberg.DOI 10.1007/s12273-014-0182-7

Valladares-Rendon LG, Schmid G, Lo SL. Review on energy savings by solar control techniques and optimal building orientation for the strategic placement of façade shading systems. Energy and Buildings. 2017 Apr 1;140:458-79. https://doi.org/10.1016/j.enbuild.2016.12.073.

Viana FA. A tutorial on Latin hypercube design of experiments. Quality and reliability engineering international. 2016 Jul;32(5):1975-85. doi:10.1002/qre.1924

Wagdy A, Fathy F, Altomonte S. Evaluating the daylighting performance of dynamic façades by using new annual climate-based metrics. PLEA 2016 (the 32nd Int. Conf. Passiv. Low Energy Archit., no. July, pp. 941–947, 2016.

Yeon S, Yu B, Seo B, Yoon Y, Lee KH. ANN based automatic slat angle control of venetian blind for minimized total load in an office building. Sol. Energy, vol. 180, no. January, pp. 133–145, 2019, doi: 10.1016/j.solener.2019.01.027.

Yi YK. Building facade multi-objective optimization for daylight and aesthetical perception. Building and Environment. 2019 Jun 1;156:178-90.

Yufka M, Ekici B, Cubukcuoglu C, Chatzikonstantinou I, Sariyildiz IS. Multi-Objective skylight optimization for a healthcare facility foyer space. In: 2017 IEEE congress on evolutionary computation; 2017. p. 1008–14.

Zhang F, Cheng L, Wu M, Xu X, Wang P, Liu Z. Performance analysis of two-stage thermoelectric generator model based on Latin hypercube sampling. Energy Conversion and Management. 2020 Oct 1;221:113159. doi:10.1016/j.enconman.2020.113159

Zhao J, Du Y. Multi-objective optimization design for windows and shading configuration considering energy consumption and thermal comfort: A case study for office building in different climatic regions of China. Solar Energy. 2020 Aug 1;206:997-1017

.https://doi.org/10.1016/j.solener.2020.05.090.