Vol. 12 No. 1 (2026)
Articles

Multi-Objective Optimization of Facade Retrofit Solutions for Italian Residential Precast Concrete Buildings

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  • Neri Banti,
  • Cecilia Ciacci,
  • Vincenzo Di Naso,
  • Frida Bazzocchi
Neri Banti
Department of Civil and Environmental Engineering, University of Florence, Italy
Cecilia Ciacci
Department of Civil and Environmental Engineering, University of Florence, Italy
Vincenzo Di Naso
Department of Civil and Environmental Engineering, University of Florence, Italy
Frida Bazzocchi
Department of Civil and Environmental Engineering, University of Florence, Italy
DOI: https://doi.org/10.36253/tema-16959

Published 2025-12-05

Keywords

  • Residential building stock,
  • precast structure,
  • energy retrofit,
  • optimization,
  • BIM

Copyright (c) 2026 TEMA Technologies Engineering Materials Architecture

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The current European policies aim to obtain a significant reduction in CO2 emissions, targeting a carbon-free economy by 2050, and propose an extensive renovation plan for the residential building heritage. The majority of Italian residential buildings predates energy-saving regulations and are currently affected by several environmental issues. This paper proposes retrofitting measures for the external walls of an existing residential precast building dating back to the 1980s, located in the Province of Florence. Two different technological solutions have been evaluated for the redevelopment of facades, featuring recladding with a Vêture system and a rainscreen solution. The methodology of the research implements a BIM-based approach: the building was modelled in the Revit environment, while optimized facade layouts were generated using an algorithm developed in Grasshopper, considering various design parameters. As for the Vêture solution, the chosen configuration reduces the total number of panels installed, minimizing at the same time the use of special components. A similar approach has been adopted in the case of the rainscreen solution, but resorting to an optimization procedure through genetic algorithms. The solutions of interest have been hence selected in the Pareto front, considering the type and number of panels. The retrofit interventions explored improved the building’s energy label from F to E, also enhancing its aesthetic quality.

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References

  1. [1] ENEA (2024) La consistenza del parco immobiliare nazionale. ENEA, Rome. https://www.pubblicazioni.enea.it/le-pubblicazioni-enea/edizioni-enea/anno-2024/la-consistenza-del-parco-immobiliare-nazionale.html
  2. [2] Ciulla G, Galatioto A, Ricciu R (2016) Energy and economic analysis and feasibility of retrofit actions in Italian residential historical buildings. Energy Build 128:649–659. https://doi.org/10.1016/j.enbuild.2016.07.044
  3. [3] Ballarini I, Corrado V, Madonna F, Paduos S, Ravasio F (2017) Energy refurbishment of the Italian residential building stock: energy and cost analysis through the application of the building typology. Energy Policy 105:148–160. https://doi.org/10.1016/j.enpol.2017.02.026
  4. [4] Corrado V, Ballarini I (2016) Refurbishment trends of the residential building stock: Analysis of a regional pilot case in Italy. Energy Build 132:91–106. https://doi.org/10.1016/j.enbuild.2016.06.022
  5. [5] Pittau F, Malighetti LE, Iannaccone G, Masera G (2017) Prefabrication as Large-scale Efficient Strategy for the Energy Retrofit of the Housing Stock: An Italian Case Study. Procedia Eng 180:1160–1169. https://doi.org/10.1016/j.proeng.2017.04.276
  6. [6] Costanzo V, Nocera F, Detommaso M, Evola G (2024) Decarbonizing cities through electrification: A strategic study for densely built residential districts in Southern Italy. Sustain Cities Soc 113:105651. https://doi.org/10.1016/j.scs.2024.105651
  7. [7] Di Turi S, Stefanizzi P (2015) Energy analysis and refurbishment proposals for public housing in the city of Bari, Italy. Energy Policy 79:58–71. https://doi.org/10.1016/j.enpol.2015.01.016
  8. [8] Lucchi E, Agliata R (2023) HBIM-based workflow for the integration of advanced photovoltaic systems in historical buildings. J Cult Herit 64:301–314. https://doi.org/10.1016/j.culher.2023.10.015
  9. [9] Gigliarelli E, Calcerano F, Cessari L (2017) Heritage Numerical Simulation and Decision Support Systems: an Integrated Approach for Historical Buildings Retrofit. Energy Procedia 133:135–144. https://doi.org/10.1016/j.egypro.2017.09.379
  10. [10] Caterino N, Nuzzo I, Ianniello A, Varchetta G, Cosenza E (2021) A BIM-based decision-making framework for optimal seismic retrofit of existing buildings. Engineering Structures 242:112544. https://doi.org/10.1016/j.engstruct.2021.112544
  11. [11] Sanhudo L, Ramos NMM, Poças Martins J, Almeida RMSF, Barreira E, Simões ML, Cardoso V (2018) Building information modeling for energy retrofitting – A review. Renewable and Sustainable Energy Reviews 89:249–260. https://doi.org/10.1016/j.rser.2018.03.064
  12. [12] Angelo LD, Hajdukiewicz M, Seri F, Keane MM (2022) A novel BIM-based process workflow for building retrofit. J Build Eng 50:104163. https://doi.org/10.1016/j.jobe.2022.104163
  13. [13] Motalebi M, Rashidi A, Mahdi M (2022) Optimization and BIM-based lifecycle assessment integration for energy efficiency retrofit of buildings. J Build Eng 49:104022. https://doi.org/10.1016/j.jobe.2022.104022
  14. [14] McNeel & Associates (2025) Grasshopper for Revit. https://www.rhino3d.com/it/features/rhino-inside-revit/
  15. [15] Ahmad A, Bande L, Ahmed W, Young K, Jha M (2024) AI application in architecture in UAE: Application of an advanced optimized shading structure as a retrofit strategy of a midrise residential building façade in downtown Abu Dhabi. Energy and Buildings 325:114995. https://doi.org/10.1016/j.enbuild.2024.114995
  16. [16] Dastoum M, Sanchez Guevara C, Arranz B (2024) Efficient daylighting and thermal performance through tessellation of geometric patterns in building facade: A systematic review. Energy Sustain Dev 83:101563. https://doi.org/10.1016/j.esd.2024.101563
  17. [17] Ente Italiano di Normazione (2014) UNI/TS 11300-1 Prestazioni energetiche degli edifici. Parte 1: Determinazione del fabbisogno di energia termica dell’edificio per la climatizzazione estiva ed invernale. UNI, Italy
  18. [18] Governo Italiano (2015) Decreto Ministeriale 26 Giugno 2015. Applicazione delle Metodologie di calcolo delle prestazioni energetiche e definizione delle prescrizioni e dei requisiti minimi degli edifici. Gazzetta Ufficiale, Italia
  19. [19] Chiarugi A, Salmesi S, Sani T (1984) Strutture Ca-AB system per edificio multipiano. La prefabbricazione, pp 11–12
  20. [20] Ente Italiano di Normazione (2015) UNI 10351. Materiali e prodotti per l’edilizia. Proprietà termoigrometriche. Procedura per la scelta dei valori di progetto. UNI, Italy
  21. [21] Thornton Tomasetti (2025) Colibri Plugin for Grasshopper. http://core.thorntontomasetti.com/colibri-release/
  22. [22] Thornton Tomasetti (2025) DesignExplorer. https://www.thorntontomasetti.com/capability/design-explorer
  23. [23] Park HK, Ock JH (2015) Developing the preliminary cost estimate for the free-form building facade in conjunction with the panel optimization process. KSCE J Civ Eng 19:1214–1223. https://doi.org/10.1007/s12205-015-0671-y
  24. [24] Pasetti Monizza G, Di Blasio I, Matt DT (2024) Exploring applications of Computational Design techniques and design for manufacturability for costs reduction of prefabricated timber-based facades: The ‘LegnAttivo’ design prototype. Dev Built Environ 19:100489. https://doi.org/10.1016/j.dibe.2024.100489