Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes

The construction industry is a major contributor to carbon emissions and resource depletion. This thesis advances sustainable construction by integrating solid waste recycling, advanced construction materials, 3D concrete printing, machine learning, optimisation techniques, and life cycle assessment...

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Main Author: Wang, Yufei
Format: Thesis
Published: Curtin University 2025
Online Access:http://hdl.handle.net/20.500.11937/98102
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author Wang, Yufei
author_facet Wang, Yufei
author_sort Wang, Yufei
building Curtin Institutional Repository
collection Online Access
description The construction industry is a major contributor to carbon emissions and resource depletion. This thesis advances sustainable construction by integrating solid waste recycling, advanced construction materials, 3D concrete printing, machine learning, optimisation techniques, and life cycle assessment. By developing predictive models, optimisation strategies, and environmental evaluations, this research enhances material efficiency and mitigates environmental impact. The findings provide a scientific foundation for transitioning towards resilient, sustainable, and circular construction practices.
first_indexed 2025-11-14T11:49:55Z
format Thesis
id curtin-20.500.11937-98102
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T11:49:55Z
publishDate 2025
publisher Curtin University
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-981022025-07-17T03:43:30Z Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes Wang, Yufei The construction industry is a major contributor to carbon emissions and resource depletion. This thesis advances sustainable construction by integrating solid waste recycling, advanced construction materials, 3D concrete printing, machine learning, optimisation techniques, and life cycle assessment. By developing predictive models, optimisation strategies, and environmental evaluations, this research enhances material efficiency and mitigates environmental impact. The findings provide a scientific foundation for transitioning towards resilient, sustainable, and circular construction practices. 2025 Thesis http://hdl.handle.net/20.500.11937/98102 Curtin University restricted
spellingShingle Wang, Yufei
Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes
title Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes
title_full Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes
title_fullStr Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes
title_full_unstemmed Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes
title_short Artificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastes
title_sort artificial-intelligence based multi-objective optimisation for concrete incorporating solid wastes
url http://hdl.handle.net/20.500.11937/98102