A review of sustainability assessment of geopolymer concrete through AI-based life cycle analysis

• Published in: AI in Civil Engineering Vol. 4; no. 1; p. 3
• Main Authors: Ramesh, V., Muthramu, B., Rebekhal, D.
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.12.2025; Springer; Springer Nature B.V
• Subjects: Artificial Intelligence; Cement; Civil Engineering; Concrete; Datasets; Ecological footprint; Emissions (Pollution); Energy consumption; Engineering; Environmental sustainability; Green buildings; Information management; Natural resources; Raw materials; Review; Sustainability; United States; United States; Sustainable construction; Neural networks; Alternative cementitious materials; Life cycle analysis; AI-based optimization; Geopolymer concrete; Machine learning; Artificial intelligence; Environmental impact; Sustainability assessment; Carbon footprint; Eco-friendly building materials
• ISSN: 2097-0943; 2730-5392; 2730-5392
• DOI: 10.1007/s43503-024-00045-3

Geopolymer concrete is acknowledged as a sustainable alternative to conventional Portland cement concrete owing to its ability to reduce carbon emissions and reutilize industrial by-products. This paper reviews the application of Artificial Intelligence-based Life Cycle Analysis (LCA) techniques in the sustainability assessment of geopolymer concrete. The assessment covers the entire life cycle of geopolymer concrete, spanning from the extraction of raw materials to its ultimate disposal, with a particular focus on its environmental, economic, and social impacts. The incorporation of AI techniques into the LCA process offers notable advantages, such as the efficient management of large datasets, enhancement of data quality, prediction of environmental impacts, and facilitation of informed decision-making. Key sustainability metrics to be considered include environmental impacts such as carbon footprint and energy consumption, economic factors like cost-effectiveness, as well as social implications. The amalgamation of AI within the LCA framework provides a comprehensive and efficient approach to evaluating the sustainability of geopolymer concrete, thereby facilitating its application in sustainable construction practices.