Show simple item record

dc.contributor.authorWang, Yufei
dc.contributor.supervisorXiangyu Wangen_US
dc.contributor.supervisorShengping Lien_US
dc.contributor.supervisorJunbo Sunen_US
dc.date.accessioned2025-07-17T03:43:30Z
dc.date.available2025-07-17T03:43:30Z
dc.date.issued2025en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/98102
dc.description.abstract

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.

en_US
dc.publisherCurtin Universityen_US
dc.titleArtificial-intelligence Based Multi-objective Optimisation for Concrete Incorporating Solid Wastesen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Design and the Built Environmenten_US
curtin.accessStatusFulltext not availableen_US
curtin.facultyHumanitiesen_US
curtin.contributor.orcidWang, Yufei [0000-0001-6690-7068]en_US
dc.date.embargoEnd2027-07-07


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record