Multi-objective optimization of external shading system using genetic algorithm based workflow to enhance energy efficiency of existing building envelope
A. OIKONOMIDIS (TU Delft - Architecture and the Built Environment)
Simona Bianchi – Mentor (TU Delft - Architectural Technology)
C. Andriotis – Mentor (TU Delft - Architectural Technology)
MJ de Haas – Coach (TU Delft - Theory, Territories & Transitions)
M. Meizoso Aguilar – Coach (TU Delft - Teachers of Practice / AE+T)
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Abstract
This master thesis rigorously explores the integration of a genetic algorithm-based workflow in the design and optimization of a passive fixed shading system utilizing ETFE cushion panels, with the objective of enhancing the thermal resilience of an existing building envelope. The case study focuses on a mid-rise office building located in the port of Athens, Greece. The central research question addressed is: "How can a genetic algorithm-based workflow be effectively employed in the multi-objective optimization of a shading system to improve the energy efficiency of an existing building envelope?"
To answer this question, the research investigates four interconnected domains: ETFE double skin structures, resilience quantification, multi-criteria decision-making approaches with genetic algorithms, and the analysis of the case study building facade system. The study centers on the preliminary design phase of the shading system, highlighting its potential as a retrofit solution for existing infrastructures challenged by rising temperatures.
The outcomes of this research include the development of a versatile workflow for evaluating the energy performance of existing buildings, facilitating interdisciplinary feedback within a design team, and applying multi-objective optimization to design problems. This work provides a comprehensive framework for integrating advanced computational methods in architectural design, thereby contributing to the improvement of building energy efficiency and thermal resilience.