Energy Efficiency and Building’s Envelope: An Integrated Approach to High-Performance Architecture

Mansourimajoumerd, Parinaz; Bazazzadeh, Hassan; Mahdavinejad, Mohammadjavad; Nia, Sepideh Nik

doi:10.1007/978-3-031-20995-6_3

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…The building sector is a major contributor to global energy consumption and greenhouse gas emissions, accounting for nearly 40% of total energy usage and 36% of CO 2 emissions worldwide [18]. As urbanization accelerates and the impacts of climate change intensify, optimizing energy performance in architectural design has become a pressing priority to reduce the environmental footprint of buildings [19][20][21][22][23][24]. However, conventional design methods relying on human expertise and trial-and-error approaches face inherent limitations in exploring the vast, complex design space and uncovering optimal energy-efficient solutions [24][25][26][27][28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Harnessing Deep Learning and Reinforcement Learning Synergy as a Form of Strategic Energy Optimization in Architectural Design: A Case Study in Famagusta, North Cyprus

Karimi,

Adibhesami,

Hoseinzadeh

et al. 2024

Buildings

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This study introduces a novel framework that leverages artificial intelligence (AI), specifically deep learning and reinforcement learning, to enhance energy efficiency in architectural design. The goal is to identify architectural arrangements that maximize energy efficiency. The complexity of these models is acknowledged, and an in-depth analysis of model selection, their inherent complexity, and the hyperparameters that govern their operation is conducted. This study validates the scalability of these models by comparing them with traditional optimization techniques like genetic algorithms and simulated annealing. The proposed system exhibits superior scalability, adaptability, and computational efficiency. This research study also explores the ethical and societal implications of integrating AI with architectural design, including potential impacts on human creativity, public welfare, and personal privacy. This study acknowledges it is in its preliminary stage and identifies its potential limitations, setting the stage for future research to enhance and expand the effectiveness of the proposed methodology. The findings indicate that the model can steer the architectural field towards sustainability, with a demonstrated reduction in energy usage of up to 20%. This study also conducts a thorough analysis of the ethical implications of AI in architecture, emphasizing the balance between technological advancement and human creativity. In summary, this research study presents a groundbreaking approach to energy-efficient architectural design using AI, with promising results and wide-ranging applicability. It also thoughtfully addresses the ethical considerations and potential societal impacts of this technological integration.

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Section: Introductionmentioning

confidence: 99%

Harnessing Deep Learning and Reinforcement Learning Synergy as a Form of Strategic Energy Optimization in Architectural Design: A Case Study in Famagusta, North Cyprus

Karimi,

Adibhesami,

Hoseinzadeh

et al. 2024

Buildings

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“…The building industry significantly contributes to global warming, prompting various suggested alternatives to mitigate its impact on the environment. However, comprehensive building development and redevelopment plans in different countries exacerbate construction-related issues, particularly with building demolition (2,3).…”

Section: Introductionmentioning

confidence: 99%

A review on concrete recycling

Sara Shomal Zadeh,

Navid Joushideh,

Behrokh Bahrami

et al. 2023

World J. Adv. Res. Rev.

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Concrete is one the most used material in construction. Considering its capacity to harden upon water contact, solidification, and acquisition of full strength, concrete becomes capable of withstanding significant stress. Over the past century, concrete structures have gained immense popularity and found extensive application in diverse architectural project. This prominence places concrete at the forefront of contemporary design and high-performance structure construction, due to its inherent structural benefits. Consequently, concrete production has witnessed a surge, facilitated by on-site production methods and straightforward construction processes. However, this heightened production has led to a significant generation of concrete waste, reaching up to 80 percent of the original produced volume in some regions worldwide. Recognizing the environmental implications, the reduction of concrete waste through recycling has emerged as a sustainable approach. Extensive research has been conducted to explore methods such as concrete recycling and the incorporation of other waste construction materials into concrete, thereby investigating their effects on concrete properties. This comprehensive review delves into the various material mixtures employed and their implications on the application of recycled concrete.

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Energy Efficiency and Building’s Envelope: An Integrated Approach to High-Performance Architecture

Cited by 2 publications

References 26 publications

Harnessing Deep Learning and Reinforcement Learning Synergy as a Form of Strategic Energy Optimization in Architectural Design: A Case Study in Famagusta, North Cyprus

Harnessing Deep Learning and Reinforcement Learning Synergy as a Form of Strategic Energy Optimization in Architectural Design: A Case Study in Famagusta, North Cyprus

A review on concrete recycling

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