Multi-Objective Performance Evaluation Framework for Integrated Fiber-Reinforced Shading Systems

Salman Oukati Sadegh; Emad Tabadkani; Mahmoud Oukati Sadegh

doi:10.15627/jd.2025.7

Author(s)

Salman Oukati Sadegh Department of Architecture, Built environment and Construction engineering,Politecnico di Milano,Italy

Emad Tabadkani Department of Architecture, Built environment and Construction engineering,Politecnico di Milano,Italy

Mahmoud Oukati Sadegh Faculty of Electrical and Computer Engineering, University of Sistan and Baluchestan,,Iran

Abstract

Shading systems are associated by their ability to control various factors such as energy consumption, visual comfort, and natural ventilation. To fulfill such economic, environmental, and social requirements, the use of integrated modular fiber-Reinforced Concrete (FRC) shading systems has become popular in recent years. While being more environmentally friendly, Fiber-reinforced concrete panels are also associated with lower costs. However, designing such systems are often associated with onerous time-consuming processes which has impacted their market uptake. To support designers since the early design phase, this research proposes an integrated systemic framework. The proposed framework benefits from integrating Multi-objective Evolutionary Algorithms (MOEAs). Such algorithms have proven to address conflicting parameters effectively while providing a range of different solutions to problems. Furthermore, the proposed framework incorporates the use of Pareto-front and Ranking method to better support decision making. Moreover, case study validates the efficacy of the framework in daylighting performance evaluation of an integrated modular FRC shading device for an office room. Finally, the results indicate that the proposed framework can provide a variety of optimal solutions to conflicting goals and further support performance evaluation of an integrated modular fiber-reinforced shading system.

Publication Details

Page(s) 111-124

DOI 10.15627/jd.2025.7

Published Journal: Journal of Daylighting, Volume: 12, Issue: 1, Year: 2025

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Keywords

Shading system, Fiber-Reinforced concrete, Integrated modular panels, Building performance

References

Agency I.E. .2013 .. , : .

Al-Masrani S.M.,Al-Obaidi K.M. .2019 .Dynamic shading systems: A review of design parameters, platforms and evaluation strategies. Autom Constr, 102 : .

R.C.G.M. Loonen M.,Trčka D.,Cóstola J.L.M.,Hensen J.L.M. .2013 .Climate adaptive building shells: State-of-the-art and future challenges. Renewable and Sustainable Energy Reviews, 25 : 483-493.

Sadineni S.B.,Madala S.,Boehm R.F. .2011 .Passive building energy savings: A review of building envelope components. Renewable and Sustainable Energy Reviews, 15 : 3617-3631.

Mirzabeigi S.,Razkenari M. .2022 .Design optimization of urban typologies: A framework for evaluating building energy performance and outdoor thermal comfort. Sustain Cities Soc, 76 : 103515.

Hershcovich C.,Rinsky V.,M. Laufer, V. .2021 .Thermal performance of sculptured tiles for building envelopes. Build Environ, 197 : 107809.

Grobman Y.J.,Y. Elimelech, Y.J. .2016 .Microclimate on building envelopes: testing geometry manipulations as an approach for increasing building envelopes' thermal performance. Archit Sci Rev, 59 : 269-278.

Gohl N.,Loose A.,Stark S.,Drück H. .2014 .Development of multifunctional building components (MultiKomp)-Comparison of different concepts. Energy Procedia, 48 : 1365-1373.

Kirimtat A.,Koyunbaba B.K.,Sariyildiz S. .2016 .Review of simulation modeling for shading devices in buildings. Renewable and Sustainable Energy Reviews, 53 : 23-49.

Wen S.,Hu X.,Xue P.,Lai D. .2023 .Comparing the performance of four shading strategies based on a multi-objective genetic algorithm: A case study in a university library. Journal of Building Engineering, 63 : 105532.

Kirimtat A.,Krejcar O.,Ekici B.,Tasgetiren M.F. .2019 ., Multi-objective energy and daylight optimization of amorphous shading devices in buildings. Solar Energy, 185 : 100-111.

J.M.L. Gagne M. .2010 .Andersen, Multi-objective façade optimization for daylighting design using a genetic algorithm. August, : 110-117.

Vera S.,Uribe D.,Bustamante W. .2017 .Optimization of a fixed exterior complex fenestration system considering visual comfort and energy performance criteria. Build Environ, 113 : 163-174.

Bakmohammadi P. .2020 .Optimization of the design of the primary school classrooms in terms of energy and daylight performance considering occupants' thermal and visual comfort. Energy Reports, 6 : 1590-1607.

Al-Masrani S.M.,Al-Obaidi K.M.,Zalin N.A.,Isma M.I.A. .2018 .Design optimisation of solar shading systems for tropical office buildings: Challenges and future trends. Solar Energy, 170 : 849-872.

Makhmalbaf .2018 .Building energy performance analysis of ultra-highperformance fiber-reinforced concrete (UHP-FRC) façade systems. Energy Build, 174 : 262-275.

F.R.G. de Sá A.,Silva A. .2020 .Tensile and flexural performance of concrete members reinforced with polypropylene fibers and GFRP bars. Compos Struct, 253 : 112784.

Wasim M.,Oliveira O.,Ngo T.D. .2022 .Structural performance of prefabricated glass fibre concrete floor panel versus compressed fibre cement floor panel for an optimised volumetric module- A case study. Journal of Building Engineering, 48 : 103819.

Raman .2023 .A review on the variation of mechanical properties of carbon fibrereinforced concrete. Constr Build Mater, 366 : 130173.

Zhang P.,Wang C.,Gao Z.,Wang F. .2023 .A review on fracture properties of steel fiber reinforced concrete. Journal of Building Engineering, 67 : 105975.

Monazami M.,Gupta R. .2022 .Investigation of mechanical behavior and fracture energy of fiber-reinforced concrete beams and panels. Cem Concr Compos, 133 : 104656.

G.B. Kim K.,Pilakoutas P.,Waldron P. .2009 .Finite element analysis of thin GFRC panels reinforced with FRP. Constr Build Mater, 23 : 930-942.

Evola G.,Gullo F.,Marletta L. .2017 .The role of shading devices to improve thermal and visual comfort in existing glazed buildings. Energy Procedia, 134 : 346-355.

Datta G. .2001 .Effect of fixed horizontal louver shading devices on thermal performance of building by TRNSYS simulation. Renew Energy, 23 : 497-507.

Mangkuto R.A.,Dewi D.K.,Herwandani A.A.,Koerniawan M.D. .2019 .Design optimisation of internal shading device in multiple scenarios: Case study in Bandung, Indonesia. Journal of Building Engineering, 24 : 100745.

Heidari A.,Taghipour M.,Yarmahmoodi Z. .2021 .The effect of fixed external shading devices on daylighting and thermal comfort in residential building. Journal of Daylighting, 8 : 165-180.

Krstić-Furundžić A.,Vujošević M.,Petrovski A. .2019 .Energy and environmental performance of the office building facade scenarios. Energy, 183 : 437-447.

A.K.K. Lau E.,Salleh C.H.,Lim M.Y.,Sulaiman M.Y. .2016 .Potential of shading devices and glazing configurations on cooling energy savings for high-rise office buildings in hot-humid climates: The case of Malaysia. International Journal of Sustainable Built Environment, 5 : 387-399.

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

Evangelisti L.,Guattari C.,Asdrubali F. .2020 .An experimental investigation of the thermal performance of a building solar shading device. Journal of Building Engineering, 28 : 101089.

Serralheiro M.I. .2017 .Methodology for service life prediction of architectural concrete facades. Constr Build Mater, 133 : 261-274.

Marie I.,Quiasrawi H. .2012 .Closed-loop recycling of recycled concrete aggregates. J Clean Prod, 37 : 243-248.

Zhou B.,Uchida Y. .2017 .Relationship between fiber orientation/distribution and post-cracking behaviour in ultra-high-performance fiber-reinforced concrete (UHPFRC). Cem Concr Compos, 83 : 66-75.

Feng J.,Yang F.,Qian S. .2021 .Improving the bond between polypropylene fiber and cement matrix by nano calcium carbonate modification. Constr Build Mater, 269 : 121249.

C.A. Nonato Da Silva J.,Ciambella J.A.O.,Barros I.G.,Costa I.G. .2020 .A multiscale model for optimizing the flexural capacity of FRC structural elements. Compos B Eng, 200 : 108325.

K.M. Nascimento P.H.,Ribeiro Borges A.L.,Christoforo T.H.,Panzera T.H.,Bai T.H. .2023 .Fiber-reinforced concrete (FRC) for civil engineering applications. , : 541-568.

Shen L.,Yao X.,Luzio G. Di,Jiang M. .2023 .Mix optimization of hybrid steel and polypropylene fiber-reinforced concrete for anti-thermal spalling. Journal of Building Engineering, 63 : 105409.

Li Q.,Shi Z.,Zhao F.,Yu S.,K. Xie, S. .2023 .Mechanical performance evaluation of steel fiber-reinforced concrete (FRC) based on multi-mechanical indicators from split hopkinson pressure bar (SHPB) test. Journal of Building Engineering, 79 : 107898.

Mena-Alonso Á.,González D.C.,Mínguez J.,Vicente M.A. .2024 .Size effect on the flexural fatigue behavior of high-strength plain and fiber-reinforced concrete. Constr Build Mater, 411 : 134424.

Farhangi V.,Moradi M.J.,Daneshvar K.,Hajiloo H. .2024 .Application of artificial intelligence in predicting the residual mechanical properties of fiber reinforced concrete (FRC) after high temperatures. Constr Build Mater, 411 : 134609.

M.F. Leone .2021 .Advanced modelling and digital manufacturing: Parametric design tools for the optimization of UHPFRC (ultra highperformance Fiber reinforced concrete) shading panels. Autom Constr, 126 : 103650.

Whitley D.,Rana S.,Dzubera J.,Mathias K.E. .1996 .Evaluating evolutionary algorithms. Artif Intell, 85 : 245-276.

J.H. Holland, .1992 .Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. , : .

Jungjohann H. .2016 .Ontario Celebration Zone pavilion: a large pneumatic structure. Procedia Eng, 155 : 507-515.

Maulik U. .2000 .Genetic algorithm-based clustering technique. Pattern Recognit, 33 : 1455-1465.

Wright S. .1932 .The roles of mutation, inbreeding, crossbreeding, and. , : .

J.D. Schaffer ,TN .1985 .Some experiments in machine learning using vector evaluated genetic algorithms. , : .

Goldberg D.E.,Addison-Wesley Longman D.E. .1989 .. Optimization and Machine Learning, : .

Makki M.,Showkatbakhsh M.,Tabony A.,Weinstock M. .2019 .Evolutionary algorithms for generating urban morphology: Variations and multiple objectives. International Journal of Architectural Computing, 17 : 5-35.

Akbari M.,Asadi P.,M.K. Besharati Givi P.,UK P. .2014 .Artificial neural network and optimization. in: Advances in Friction-Stir Welding and Processing, : .

Ascione F.,Bianco N.,C. De Stasio G.M.,Mauro G.P.,Vanoli G.P.,Waltham G.P. .2018 .. in: Comprehensive Energy Systems, 5 : 827-854.

Zitzler E.,Citeseer E. .1999 .Evolutionary algorithms for multiobjective optimization: Methods and applications. , 63 : .

Wallacei .2021 .. accessed August 13, : .

Deb K.,Pratap A.,Agarwal S.,Meyarivan T. .2002 .A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6 : 182-197.

Adekanmbi O.A.,Olugbara O.O.,Adeyemo J. .2014 .A comparative study of state-of-the-art evolutionary multi-objective algorithms for optimal cropmix planning. International Journal of Agricultural Science and Technology, 2 : 8-16.

Deb K.,Mohan M.,Mishra S. .2005 .Evaluating the ϵ-domination based multiobjective evolutionary algorithm for a quick computation of Pareto-optimal solutions. Evol Comput, 13 : 501-525.

Sadegh S.O.,Gasparri E.,Brambilla A.,Globa A. .2022 .Kinetic facades: An evolutionary-based performance evaluation framework. Journal of Building Engineering, 53 : 104408.

EnergyPlus .2023 .. , : .

Samant S.,Sharples S. .2004 .Surface Reflectance Distributions and their Effect on Average Daylight Factor Values in Atrium Buildings. Archit Sci Rev, 47 : 177-181.

Bian Y.,Ma Y. .2017 .Analysis of daylight metrics of side-lit room in Canton, south China: A comparison between daylight autonomy and daylight factor. Energy Build, 138 : 347-354.

Nabil A.,Mardaljevic J. .2005 .Useful daylight illuminance: a new paradigm for assessing daylight in buildings. , 37 : 41-57.

Chang Y.,Bouzarkouna Z.,D. Z. .2015 .Devegowda, Multi-objective optimization for rapid and robust optimal oilfield development under geological uncertainty. Comput Geosci, 19 : 933-950.

Sivanandam S.N.,Deepa S.N. .2008 .Genetic algorithms. , : 15-37.