Artificial intelligence algorithms, simulation tools and software for optimization of adaptive facades: A systematic literature review

被引:0
作者
Ozluk, Resul [1 ]
Aydin, Fatih [2 ]
Yildiz, Yusuf [1 ]
机构
[1] Balikesir Univ, Dept Architecture, Balikesir, Turkiye
[2] Balikesir Univ, Dept Comp Engn, Balikesir, Turkiye
关键词
Adaptive facades; Energy performance; User comfort; Systematic literature review; Artificial intelligence algorithms; Simulation tools; BUILDING PERFORMANCE SIMULATION; ENERGY MANAGEMENT-SYSTEM; MULTIOBJECTIVE OPTIMIZATION; MIXED-INTEGER; SHADING SYSTEM; GLAZED FACADE; DAYLIGHT PERFORMANCE; MATHEMATICAL-MODEL; CONTROL STRATEGIES; THERMAL COMFORT;
D O I
10.1016/j.jobe.2025.112566
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In an increasingly digital world, many methods such as AI algorithms, simulation tools, and software are used for performance-based optimization of adaptive facades, and rapid developments are taking place in these areas. Currently, although there are many studies on these topics, they are not yet fully understood and addressed holistically. To fill this gap, this paper conducted a comprehensive review of these researches. In order to accomplish this objective, a bibliometric approach has been conducted with studies published between 2000 and 2023 to systematically analyze the literature on these topics. Using the systematic literature review, the case study location, case study building types, AF movement typologies, sustainability aspects, objectives of the studies and design parameters to achieve these objectives are investigated within the study scope. As a result, among the artificial intelligence algorithms used to optimize the performance of adaptive facades and their typologies, GAs (GA, NSGA-2, MOGA, MOEA) were found as the most widely used algorithms. Furthermore, the common software, simulation and modelling tools required in optimization process are Grasshopper, EnergyPlus and RhinoGrasshopper, respectively. Finally, this review paper will make a general database for current and emerging AI algorithms and tools used in optimization of adaptive fa & ccedil;ade.
引用
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页数:30
相关论文
共 238 条
[1]  
Ababneh M., 2006, J COMPUT SCI-NETH, V2, DOI [10.3844/jcssp.2006.82.85, DOI 10.3844/JCSSP.2006.82.85]
[2]   Experimental Study of Operating Conditions and Integration of Thermoelectric Materials in Facade Systems [J].
Aksamija, Ajla ;
Aksamija, Zlatan ;
Counihan, Chris ;
Brown, Dylan ;
Upadhyaya, Meenakshi .
FRONTIERS IN ENERGY RESEARCH, 2019, 7 (FEB)
[3]  
Alammar A, 2022, PROCEEDINGS OF THE 2022 ANNUAL MODELING AND SIMULATION CONFERENCE (ANNSIM'22), P656, DOI 10.23919/ANNSIM55834.2022.9859413
[4]   Genetic algorithms: theory, genetic operators, solutions, and applications [J].
Alhijawi, Bushra ;
Awajan, Arafat .
EVOLUTIONARY INTELLIGENCE, 2024, 17 (03) :1245-1256
[5]   An internal assessment of the thermal comfort and daylighting conditions of a naturally ventilated building with an active glazed facade in a temperate climate [J].
Altan, H. ;
Ward, I. ;
Mohelnikova, J. ;
Vajkay, F. .
ENERGY AND BUILDINGS, 2009, 41 (01) :36-50
[6]  
Amani N., 2024, Hybrid Adv, V6, DOI [10.1016/j.hybadv.2024.100236, DOI 10.1016/J.HYBADV.2024.100236]
[7]   Multi-Skin Adaptive Ventilated Facade: A Review [J].
Andreeva, Darya ;
Nemova, Darya ;
Kotov, Evgeny .
ENERGIES, 2022, 15 (09)
[8]  
[Anonymous], 2021, Energy Efficiency 2021 - Executive Summary
[9]   Design, fabrication and computational simulation of a bio-kinetic facade inspired by the mechanism of the Lupinus Succulentus plant for daylight and energy efficiency [J].
Anzaniyan, Elmira ;
Alaghmandan, Matin ;
Koohsari, Ayda Montaser .
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT, 2022, 28 (10) :1456-1471
[10]  
Araujo T., 2021, Parametric Design and Experimental Tests with Bimetal, DOI 10.