Volume 12, Issue 4 (2023)
Naqshejahan 2023, 12(4): 116-141 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Jokar R, Maleki M. Investigating the effect of Voronoi shell parametric design on improving daylight efficiency in an office building in Shiraz. Naqshejahan 2023; 12 (4) :116-141
URL: http://bsnt.modares.ac.ir/article-2-65524-en.html
URL: http://bsnt.modares.ac.ir/article-2-65524-en.html
1- MSc Student, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran.
2- Assistant Professor, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran. , mo.maleki@basu.ac.ir
2- Assistant Professor, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran. , mo.maleki@basu.ac.ir
Abstract: (1510 Views)
Aims: The main purpose of this article is to investigate the performance and impact of the building shell on natural lighting components and radiation reception, as components affecting the quality of the interior space, through designing a shell with Voronoi algorithm.
Methods: For this purpose, using the genetic algorithm and taking into account the Useful Daylight Illumination and the Total Radiation, optimal configurations are presented from among the design options of the shell, which is based on the Voronoi algorithm. The working method has been multi-objective optimization using NSGA-II and linear modeling in the Rhino platform and Grasshopper plugin using environmental analysis tools such as Energy Plus and Radiance for numerical calculations. Also, skins are analyzed in three cases: 1-an infilled wall without the second skin, 2-using horizontal louvers, and 3- Voronoi skin as the second skin.
Findings: It has been indicated that with Voronoi skin, the amount of average Useful Daylight Illuminance has increased by 63.86% compared to the case without the second skin, and by 21.02% compared to the case using horizontal louvers the second skin. Also, by this design idea, the amount of total solar radiation decreases by 63.86% compared to the case without the second shell and decreases by 15.38% compared to the issue of using horizontal louvers as the second shell.
Conclusion: The designed shell resulting from the optimization process and the use of Voronoi geometry has a good performance in improving the Useful Daylight Illuminance and reducing the amount of sunlight.
Methods: For this purpose, using the genetic algorithm and taking into account the Useful Daylight Illumination and the Total Radiation, optimal configurations are presented from among the design options of the shell, which is based on the Voronoi algorithm. The working method has been multi-objective optimization using NSGA-II and linear modeling in the Rhino platform and Grasshopper plugin using environmental analysis tools such as Energy Plus and Radiance for numerical calculations. Also, skins are analyzed in three cases: 1-an infilled wall without the second skin, 2-using horizontal louvers, and 3- Voronoi skin as the second skin.
Findings: It has been indicated that with Voronoi skin, the amount of average Useful Daylight Illuminance has increased by 63.86% compared to the case without the second skin, and by 21.02% compared to the case using horizontal louvers the second skin. Also, by this design idea, the amount of total solar radiation decreases by 63.86% compared to the case without the second shell and decreases by 15.38% compared to the issue of using horizontal louvers as the second shell.
Conclusion: The designed shell resulting from the optimization process and the use of Voronoi geometry has a good performance in improving the Useful Daylight Illuminance and reducing the amount of sunlight.
Keywords: daylight, parametric design, office space, multi-objective optimization, genetic algorithm, contemporary architecture, sustainability, new technologies.
Article Type: Original Research |
Subject:
Highperformance Architecture
Received: 2022/09/21 | Accepted: 2022/12/20 | Published: 2023/01/1
Received: 2022/09/21 | Accepted: 2022/12/20 | Published: 2023/01/1
References
1. Karakoç E , Çağdaş G. Adaptive Architecture Based on Environmental Performance: An Advanced Intelligent Façade (AIF) Module. Gazi University Journal of Science. 2021, 34.3: 630-650. https://doi.org/10.35378/gujs.725902 [Article] [DOI]
2. Yuan Y, et al. Bionic building energy efficiency and bionic green architecture: A review. Renewable and sustainable energy reviews. 2017, 74: 771-787. https://doi.org/10.1016/j.rser.2017.03.004 [Article] [DOI]
3. Oxman R. Digital architecture as a challenge for design pedagogy: theory, knowledge, models and medium. Design studies. 2008, 29.2: 99-120. https://doi.org/10.1016/j.destud.2007.12.003 [Article] [DOI]
5. Zhang B T. Hypernetworks: A molecular evolutionary architecture for cognitive learning and memory. IEEE computational intelligence magazine, 2008, 3.3: 49-63. https://10.1109/MCI.2008.926615 [Article] [DOI]
6. Norouzi N, Shabak M, Embi MR, Khan TH. The architect, the client and effective communication in architectural design practice. Procedia-Social and Behavioral Sciences. 2015 Jan 27;172:635-42. https://doi.org/10.1016/j.sbspro.2015.01.413 [Article] [DOI]
7. Wang J, Xu C, Zhang J, Zhong R. Big data analytics for intelligent manufacturing systems: A review. Journal of Manufacturing Systems. 2022 Jan 1;62:738-52. https://doi.org/10.1016/j.jmsy.2021.03.005 [Article] [DOI]
8. Mergel I, Edelmann N, Haug N. Defining digital transformation: Results from expert interviews. Government information quarterly. 2019, 36.4: 101385. https://doi.org/10.1016/j.giq.2019.06.002 [Article] [DOI]
9. Rolvink A, Van De Straat R, Coenders J. Parametric structural design and beyond. International Journal of Architectural Computing. 2010, 8.3: 319-336. https://doi.org/10.1260/1478-0771.8.3.3 [Article] [DOI]
10. Labib R. Trade-off method to assess the interaction between light shelves and complex ceiling forms for optimized daylighting performance. Advances in Building Energy Research. 2015,9(2), 224-237. https://doi.org/10.1080/17512549.2015.1014838 [Article] [DOI]
11. Eltaweel A; Yuehong S U. Parametric design and daylighting: A literature review. Renewable and Sustainable Energy Reviews. 2017, 73: 1086-1103. https://doi.org/10.1016/j.rser.2017.02.011
12. Evins R. A review of computational optimization methods applied to sustainable building design. Renewable and sustainable energy reviews. 2013, 22: 230-245. https://doi.org/10.1016/j.rser.2013.02.004 [Article] [DOI]
13. Kornuta D, Abbud-Madrid A, Atkinson J, Barr J, Barnhard G, Bienhoff D, Blair B, Clark V, Cyrus J, DeWitt B, Dreyer C. Commercial lunar propellant architecture: A collaborative study of lunar propellant production. Reach. 2019 Mar 1;13:100026. https://doi.org/10.1016/j.reach.2019.100026 [Article] [DOI]
14. Heydarian A, Carneiro JP, Gerber D, Becerik-Gerber B, Hayes T, Wood W. Immersive virtual environments versus physical built environments: A benchmarking study for building design and user-built environment explorations. Automation in Construction. 2015 Jun 1;54:116-26. https://doi.org/10.1016/j.autcon.2015.03.020 [Article] [DOI]
15. Roudsari MS, Pak M. Ladybug: A parametric environmental plugin for grasshopper to help designers create an environmentally-conscious design. Paper 122 presented at the Proceedings of the 13th International IBPSA Conference Held in Lyon, France Aug. 2013. https://doi.org/10.26868/25222708.2013.2499 [Article] [DOI]
16. Nguyen A, Reiter S, Rigo P. A review on simulation-based optimization methods applied to building performance analysis. Applied Energy. 2014, 113, 1043-1058. https://doi.org/10.1016/j.apenergy.2013.08.061 [Article] [DOI]
17. Machairas V, Tsangrassoulis A, Axarli K. Algorithms for optimization of building design: A review. Renewable and Sustainable Energy Reviews. 2014, 31, 101-112. https://doi.org/10.1016/j.rser.2013.11.036 [Article] [DOI]
18. Arosha G, Richard H.A model based on Biomimicry to enhance the ecologically sustainable design, Architectural Science Review. 2012, 55:3, 224-235. https://doi:10.1080/00038628.2012.709406 [Article] [DOI]
19. Amoruso FM, Dietrich U, Schuetze T. Integrated BIM-parametric workflow-based analysis of daylight improvement for sustainable renovation of an exemplary apartment in Seoul, Korea. Sustainability. 2019, 11.9: 2699. https://doi.org/10.3390/su11092699 [Article] [DOI]
20. Machairas V, Tsangrassoulis A, Axarli K. Algorithms for optimization of building design: A review. Renewable and sustainable energy reviews. 2014, 31: 101-112. https://doi.org/10.1016/j.rser.2013.11.036 [Article] [DOI]
21. Elbeltagi E, Hegazy T, Grierson D. Comparison among five evolutionary-based optimization algorithms. Advanced engineering informatics. 2005, 19(1), 43-53. https://doi.org/10.1016/j.aei.2005.01.004 [Article] [DOI]
22. Chumachenko D, Meniailov I, Bazilevych K, Kuznetsova Y, Chumachenko T. Development of an intelligent agent-based model of the epidemic process of syphilis. In2019 IEEE 14th international conference on computer sciences and information technologies (CSIT) 2019 Sep 17 (Vol. 1, pp. 42-45). IEEE. https://10.1109/STC-CSIT.2019.8929749 [Article]
23. Zhang Z, Zhou H, Ma J, Xiong L, Ren S, Sun M, Wu H, Jiang S. Space deployable bistable composite structures with C-cross section based on machine learning and multi-objective optimization. Composite Structures. 2022 Oct 1;297:115983. https://doi.org/10.1016/j.compstruct.2022.115983 [Article] [DOI]
24. Murgul V, Vatin N, Zayats I. The role of the solar light quantity in the architectural forming of buildings. Procedia Engineering. 2015 Jan 1;117:819-24. https://doi.org/10.1016/j.proeng.2015.08.146 [Article] [DOI]
25. Moazzeni MH, Ghiabaklou Z. Investigating the influence of light shelf geometry parameters on daylight performance and visual comfort, a case study of educational space in Tehran, Iran. Buildings. 2016 Jul 13;6(3):26. https://doi.org/10.3390/buildings6030026 [Article] [DOI]
26. Lami IM, Mecca B. Assessing social sustainability for achieving sustainable architecture. Sustainability. 2020 ,13(1), 142. https://doi.org/10.3390/su13010142 [Article] [DOI]
27. Chang MC, Shih SG. A hybrid approach of dynamic programming and genetic algorithm for multi-criteria optimization on sustainable architecture design. Computer-Aided Design and Applications. 2015 May 4;12(3):310-9. https://doi.org/10.1080/16864360.2014.981460 [Article] [DOI]
28. Cheng S, Yunsong H, Han F. Multi-objective building form optimization method based on GANN-BIM model. Next Generation Building. 2015, 2.1. https://doi:10.7480/ngb.2.1.1517 [Article] [DOI]
29. Jalali Z. Optimization of Office Building Façade Using Genetic Algorithm With sustainability and BIM Integration Approach. Master's thesis in Architectural Technology, Faculty of Architecture, University of Tehran. 2017 ]Persian[ https://doi.org/10.1080/23744731.2019.1624095
30. Bahdad AAS, Fadzil, S F S, Taib N. Optimization of daylight performance based on controllable light-shelf parameters using genetic algorithms in the tropical climate of Malaysia. Journal of Daylighting. 2020, 7(1), 122-136. https://dx.doi.org/10.15627/jd.2020.10 [Article] [DOI]
31. Ziaee N, Vakilinezhad R. Multi-objective optimization of daylight performance and thermal comfort in classrooms with light-shelves: Case studies in Tehran and Sari, Iran. Energy and Buildings. 2022 Jan 1;254:111590. https://doi.org/10.1016/j.enbuild.2021.111590 [Article] [DOI]
32. Xue P, Mak CM, Cheung HD. The effects of daylighting and human behavior on luminous comfort in residential buildings: A questionnaire survey. Building and Environment. 2014 Nov 1;81:51-9. https://doi.org/10.1016/j.buildenv.2014.06.011 [Article] [DOI]
33. Wang S, Yi YK, Liu N. Multi-objective optimization (MOO) for high-rise residential buildings’ layout centered on daylight, visual, and outdoor thermal metrics in China. Building and Environment. 2021 Nov 1;205:108263. https://doi.org/10.1016/j.buildenv.2021.108263 [Article] [DOI]
34. Yazyeva SB, Mayatskaya IA. Eco-sustainable architecture and comfortable living environment. InIOP Conference Series: Materials Science and Engineering 2021 Feb 1 (Vol. 1083, No. 1, p. 012018). IOP Publishing. https://doi:10.1088/1757-899X/1083/1/012018 [Article] [DOI]
35. Bardhan R, Debnath R. Daylight Performance of a Naturally Ventilated Building as parameter for Energy Management. Energy Procedia. 2016,90: 382–394. https://doi.org/10.1016/j.egypro.2016.11.205 [Article] [DOI]
36. Chen K W, Janssen P, Schlueter A. Multi-objective optimization of building form, envelope and cooling system for improved building energy performance, Autom. Constr., vol. 2016.94. https://doi.org/10.1016/j.autcon.2018.07.002 [Article] [DOI]
37. Kirimtat A, Koyunbaba BK, Chatzikonstantinou I, Sariyildiz S, Suganthan PN. Multi-objective optimization for shading devices in buildings by using evolutionary algorithms. In2016 IEEE Congress on Evolutionary Computation (CEC) 2016 Jul 24 (pp. 3917-3924). IEEE. https://10.1109/CEC.2016.7744286 [Article] [DOI]
38. Ahmadi J, Mahdavinejad M, Asadi S. Folded double-skin façade (DSF): in-depth evaluation of fold influence on the thermal and flow performance in naturally ventilated channels. International Journal of Sustainable Energy. 2021 Jun 16:1-30. https://doi.org/10.1080/14786451.2021.1941019
39. Lakhdari K, Sriti L, Painter B. Parametric optimization of daylight, thermal and energy performance of middle school classrooms, case of hot and dry regions. Building and Environment. 2021, 204, 108173. https://doi.org/10.1016/j.buildenv.2021.108173 [Article] [DOI]
40. Schwartz Y, Raslan R, Mumovic D. Implementing multi-objective genetic algorithm for life cycle carbon footprint and life cycle cost minimization: A building refurbishment case study. Energy. 2016, 97, 58-68. https://doi.org/10.1016/j.energy.2015.11.056 [Article] [DOI]
41. Ahmed MM, Abel-Rahman AK, Ali AH. Development of intelligent façade based on outdoor environment and indoor thermal comfort. Procedia technology. 2015 Jan 1;19:742-9. https://doi.org/10.1016/j.protcy.2015.02.105 [Article] [DOI]
42. Anton I, Tănase D. Informed geometries. Parametric modelling and energy analysis in early stages of design. Energy Procedia. 2016 Jan 1;85:9-16. https://doi.org/10.1016/j.egypro.2015.12.269 [Article] [DOI]
43. Burger S. South Australian Health and Medical Research Institute (Sahmri). https://doi.org/10.52842/conf.acadia.2014.201 [Article] [DOI]
44. Ahmadi J, Mahdavinejad M, Larsen OK, Zhang C, Zarkesh A, Asadi S. Evaluating the different boundary conditions to simulate airflow and heat transfer in Double-Skin Facade. In Building Simulation 2022 May;15(5):799-815. Tsinghua University Press. https://doi.org/10.1007/s12273-021-0824-5 [Article] [DOI]
45. Hosseini SM, Mohammadi M, Schröder T, Guerra-Santin O. Bio-inspired interactive kinetic façade: Using dynamic transitory-sensitive area to improve multiple occupants’ visual comfort. Frontiers of Architectural Research. 2021 Dec 1;10(4):821-37. https://doi.org/10.1016/j.foar.2021.07.004 [Article] [DOI]
46. Lartigue B, Lasternas B, Loftness V. Multi-objective optimization of building envelope for energy consumption and daylight. Indoor and built environment. 2014 Feb;23(1):70-80. https://doi.org/10.1177/1420326X13480224 [Article] [DOI]
47. Michael A, Heracleous C. Assessment of natural lighting performance and visual comfort of educational architecture in Southern Europe: The case of typical educational school premises in Cyprus. Energy and buildings. 2017 Apr 1;140:443-57. https://doi.org/10.1016/j.enbuild.2016.12.087 [Article] [DOI]
48. Omidfar A, Torghabehi OO, Buelow PV. Performance-based design of a self-standing building skin; A methodology to integrate structural and daylight performance in a form exploration process. InProceedings of IASS Annual Symposia 2014 Sep 19 (Vol. 2014, No. 16, pp. 1-8). International Association for Shell and Spatial Structures (IASS). DOI: 10.13140/2.1.1433.2167 [Article] [DOI]
49. Onubogu NO, Chong KK, Tan MH. Review of Active and Passive Daylighting Technologies for Sustainable Building. International Journal of Photoenergy. 2021 Oct 26;2021. https://doi:10.1155/2021/8802691 [Article] [DOI]
50. Goharian A, Mahdavinejad M. A novel approach to multi-apertures and multi-aspects ratio light pipe. Journal of Daylighting. 2020 Sep 16;7(2):186-200. https://doi.org/10.15627/jd.2020.17 [Article] [DOI]
51. Fallahtafti R, Mahdavinejad M. Window geometry impact on a room's wind comfort. Engineering, Construction and Architectural Management. 2021 Mar 24;28(9):2381-2410. https://doi.org/10.1108/ECAM-01-2020-0075 [Article] [DOI]
52. Zafarmandi S, Mahdavinejad M, Norford L, Matzarakis A. Analyzing Thermal Comfort Sensations in Semi-Outdoor Space on a University Campus: On-Site Measurements in Tehran’s Hot and Cold Seasons. Atmosphere. 2022 June 22;13, 1034. https://doi.org/10.3390/atmos13071034 [Article] [DOI]
53. Goharian A, Mahdavinejad M, Bemanian M, Daneshjoo K. Designerly optimization of devices (as reflectors) to improve daylight and scrutiny of the light-well’s configuration. Building Simulation. 2021 Oct 9 (pp. 1-24). Tsinghua University Press. https://doi.org/10.1007/s12273-021-0839-y [Article] [DOI]
54. Haghshenas M, Hadianpour M, Matzarakis A, Mahdavinejad M, Ansari M. Improving the suitability of selected thermal indices for predicting outdoor thermal sensation in Tehran. Sustainable Cities and Society. 2021 Jul 27:103205. https://doi.org/10.1016/j.scs.2021.103205
55. Javanroodi K, Nik VM, Mahdavinejad M. A novel design-based optimization framework for enhancing the energy efficiency of high-rise office buildings in urban areas. Sustainable Cities and Society. 2019; 49:101597. https://doi.org/10.1016/j.scs.2019.101597 [Article] [DOI]
56. Saadatjoo P, Mahdavinejad M, Zhang G, Vali K. Influence of permeability ratio on wind-driven ventilation and cooling load of mid-rise buildings. Sustainable Cities and Society. 2021 Jul 1;70:102894. https://doi.org/10.1016/j.scs.2021.102894 [Article] [DOI]
57. Shaeri J, Mahdavinejad M. Prediction Indoor Thermal Comfort in Traditional Houses of Shiraz with PMV/PPD model. International Journal of Ambient Energy. 2022 Jun 21. https://doi.org/10.1080/01430750.2022.2092774 [Article] [DOI]
58. Mahdavinejad M, Javanroodi K. Natural ventilation performance of ancient wind catchers, an experimental and analytical study–case studies: one-sided, two-sided and four-sided wind catchers. International journal of energy technology and policy, 2014 Jan 1;10(1):36-60. https://doi.org/10.1504/IJETP.2014.065036 [Article] [DOI]
59. Shaeri J, Mahdavinejad M, Pourghasemian MH. A new design to create natural ventilation in buildings: Wind chimney. Journal of Building Engineering. 2022 Aug 22:105041. https://doi.org/10.1016/j.jobe.2022.105041 [Article] [DOI]
60. Talaei M, Mahdavinejad M, Azari R, Prieto A, Sangin H. Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance. Journal of Building Engineering. 2021 Jun 5:102832. https://doi.org/10.1016/j.jobe.2021.102832 [Article] [DOI]
61. Talaei M, Mahdavinejad M, Azari R, Haghighi HM, Atashdast A. Thermal and energy performance of a user-responsive microalgae bioreactive façade for climate adaptability. Sustainable Energy Technologies and Assessments. 2022 Aug 1;52:101894. https://doi.org/10.1016/j.seta.2021.101894 [Article] [DOI]
62. Goharian A, Daneshjoo K, Mahdavinejad M, Yeganeh M. Voronoi geometry for building facade to manage direct sunbeams. Journal of Sustainable Architecture and Civil Engineering. 2022 Oct 26;31(2):109-24. https://doi.org/10.5755/j01.sace.31.2.30800 [Article] [DOI]
63. Shaeri J, Mahdavinejad M, Vakilinejad R, Bazazzadeh H, Monfared M. Effects of sea-breeze natural ventilation on thermal comfort in low-rise buildings with diverse atrium roof shapes in BWh regions. Case Studies in Thermal Engineering. 2022 Dec 16:102638. https://doi.org/10.1016/j.csite.2022.102638 [Article] [DOI]
64. Torabi M, Mahdavinejad M. Past and Future Trends on the Effects of Occupant Behaviour on Building Energy Consumption. J. Sustain. Archit. Civ. Eng. 2021 Oct 27;29(2) 83-101. https://doi.org/10.5755/j01.sace.29.2.28576 [Article] [DOI]
65. Zarkesh, A., mahyari, H., Mahdavinejad, M. An intelligent adaptive skin from a biomimetic approach for energy consumption reduction. Hoviatshahr, 2022. doi: 10.30495/hoviatshahr.2022.64865.12140 [Article] [DOI]
66. Latifi, M., Mahdavinejad, M. Contemporaryization of Isfahan Indigenous Housing Model based on Analysis of non-Morphic Relationships of Plan, Case Study: Jangjouian House. Journal of Iranian Architecture Studies, 2022. doi: 10.22052/jias.2022.245859.0 [Article] [DOI]
67. Arbab M, Mahdavinejad M, Bemanian M. A Mathematical Framework for Evaluation of Stagnation and Movement in Architectural Spaces, Case Studies: Iranian Traditional Houses. IJAUP 2022; 32(4). doi: 10.22068/ijaup.572 [Article] [DOI]
68. Askari A, Mahdavinejad M, Ansari M. Investigation of displacement ventilation performance under various room configurations using computational fluid dynamics simulation. Building Services Engineering Research and Technology. 2022 May 7;43(5):627–643. https://doi.org/10.1177/01436244221097312 [Article] [DOI]
69. Alilou M, Mahdavinejad M. The Effect of CCT on Vitality and Population Absorption in Urban Area: Case Study of the Safavi Bridge Urban Area in Karaj, Iran. Light & Engineering (Svetotekhnika), Moscow. 2022 Sep 1;30(5): 81-91. Available from: https://l-e-journal.com/en/journals/light-engineering-30-5/light-engineering-30-5-2022-paper-version/ [Article]
70. Hadianpour M, Mahdavinejad M, Bemanian M, Haghshenas M, Kordjamshidi M. Effects of windward and leeward wind directions on outdoor thermal and wind sensation in Tehran. Building and Environment. 2019 Mar 1;150:164-180. https://doi.org/10.1016/j.buildenv.2018.12.053 [Article] [DOI]
71. Hadianpour M, Mahdavinejad M, Bemanian M, Nasrollahi F. Seasonal differences of subjective thermal sensation and neutral temperature in an outdoor shaded space in Tehran, Iran. Sustainable Cities and Society, 2018 May 1; 39: 751-64. https://doi.org/10.1016/j.scs.2018.03.003 [Article] [DOI]
72. Heidari F, Mahdavinejad M, Werner LC, Roohabadi M, Sarmadi H. Biocomputational Architecture Based on Particle Physics. Front. Energy Res. 2021 July 08;9:620127. https://doi.org/10.3389/fenrg.2021.620127 [Article] [DOI]
73. Mahdavinejad M, Hosseini SA. Data mining and content analysis of the jury citations of the Pritzker Architecture prize (1977–2017). Journal of Architecture and Urbanism. 2019 Feb 1;43(1):71-90. https://doi.org/10.3846/jau.2019.5209 [Article] [DOI]
74. Maghsoud M, Nasr T. ITC-based Technologies and Green Strategy for Contemporization of Tehran Silo. Naqshejahan-Basic studies and New Technologies of Architecture and Planning. 2022 Mar 10;12(1):1-9. https://dorl.net/dor/20.1001.1.23224991.1401.12.1.2.2 [Article] [DOI]
75. Moshari M, Nazari S. Learning from Hidden Geometry of Forests and Wild-life Environment for Biophilic Regional Planning. Naqshejahan - Basic Studies and New Technologies of Architecture and Planning. 2020 Oct 10;10(3):183-191. https://dorl.net/dor/20.1001.1.23224991.1399.10.3.6.6 [Article] [DOI]
76. Pakdehi SG, Salimi M, Rasoolzadeh M, Abbasi M. Influence of γ-Al2O3 nano particles on the properties of washcoats deposited on cordierite monoliths. Journal of Ceramic Processing Research. 2015 Oct 1;16(5):505-510. https://doi.org/10.36410/jcpr.2015.16.5.505 [Article] [DOI]
77. Pakdehi, S. G., Salimi, M., & Rasoolzadeh, M. (2014b). A review on decomposition of hydrazine and its kinetics as a novel approach for CO-free H2 production. Res Appl Mech Eng, 3, 21-25. Available from: https://d1wqtxts1xzle7.cloudfront.net [Article]
78. Saadatjoo P, Mahdavinejad M, Zarkesh A. Porosity Rendering in High-Performance Architecture: Wind-Driven Natural Ventilation and Porosity Distribution Patterns. Armanshahr Architecture & Urban Development, 2019; 12(26): 73-87. https://doi.org/10.22034/aaud.2019.89057 [Article] [DOI]
79. Saadatjoo P, Mahdavinejad M, Zhang G. A study on terraced apartments and their natural ventilation performance in hot and humid regions. Building Simulation. 2018 Apr 1;11(2):359-372. Tsinghua University Press. https://doi.org/10.1007/s12273-017-0407-7 [Article] [DOI]
80. Valitabar M. Mohammadjavad M. Henry S. Peiman P. A dynamic vertical shading optimisation to improve view, visual comfort and operational energy. Open House International. 2021 Jul 9;46(3):401-415. https://doi.org/10.1108/OHI-02-2021-0031 [Article] [DOI]
81. Tadayon K, Mahdavinejad M, Shahcheraghi A. Advanced mathematical algorithms to outline integrated architectural design process. Journal of Sustainable Architecture and Urban Design. 2021 Aug 23;9(1):1-12. https://doi.org/10.22061/JSAUD.2020.6603.1686 [Article] [DOI]
82. Pilechiha P. Optimization Methods and Algorithms in Architectural and Urban Design, Basic Mathematical Solutions. Naqshejahan - Basic Studies and New Technologies of Architecture and Planning. 2020 Oct 10;10(3):205-217. https://dorl.net/dor/20.1001.1.23224991.1399.10.3.4.4 [Article] [DOI]
83. Rahbar, M., MahdaviNejad, M., Bemanian, M., Davaie-Markazi, A. Artificial neural network for outlining and predicting environmental sustainable parameters. Journal of Sustainable Architecture and Urban Design, 2020; 7(2): 169-182. doi: 10.22061/jsaud.2019.4501.1333 [Article] [DOI]
84. Khatami S M. The Analysis of Buildings Façade’s Challenges and the Role of Effective Groups in its Formation in the City of Tehran. Naqshejahan - Basic Studies and New Technologies of Architecture and Planning. 2022 Sep 10; 12(3):63-78. https://dorl.net/dor/20.1001.1.23224991.1401.12.3.1.5 [Article] [DOI]
85. Rahbar M, Mahdavinejad M, Markazi A.H.D., Bemanian M. Architectural layout design through deep learning and agent-based modeling: A hybrid approach. Journal of Building Engineering. 2022 April15; 47, 103822. https://doi.org/10.1016/j.jobe.2021.103822 [Article] [DOI]
86. Rahbar M, Mahdavinejad M, Bemanian M, Davaie Markazi AH, Hovestadt L. Generating Synthetic Space Allocation Probability Layouts Based on Trained Conditional-GANs. Applied Artificial Intelligence. 2019 Jul 3;33(8):689-705. https://doi.org/10.1080/08839514.2019.1592919 [Article] [DOI]
87. Motalyi S, Heidari Sh. Breathing Wall Modeling to Absorb Indoor Pollutants in a Living Room of a House Inspired by the Buffer Zones of Traditional Architecture in Hot and Arid Climate of Iran Country. Naqshejahan - Basic studies and New Technologies of Architecture and Planning. 2018 Jun 10;8(1):1-7. https://dorl.net/dor/20.1001.1.23224991.1397.8.1.1.3 [Article] [DOI]
88. Haque AB, Bhushan B, Dhiman G. Conceptualizing smart city applications: Requirements, architecture, security issues, and emerging trends. Expert Systems. 2022 Jun;39(5):e12753. https://doi.org/10.1111/exsy.12753 [Article] [DOI]
89. Mahdavinejad, M. Discourse of High-Performance Architecture: A Method to Understand Contemporary Architecture. Hoviatshahr, 2017; 11(2): 53-67. Available from: https://hoviatshahr.srbiau.ac.ir/article_10930.html?lang=en [Article]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |