Using Machine Learning for Sustainable Concrete Material Selection and Optimization in Building Design

Qian Meng; Haoran Xu; Jingwen He

doi:10.70393/6a6374616d.323530

OPEN ACCESS |Research Article ||1 January 2025

Using Machine Learning for Sustainable Concrete Material Selection and Optimization in Building Design

Qian Meng

University of Technology Sydney

mengqian519@gmail.com

School of Architecture and Design, University of Technology Sydney, Sydney, Australia, 2007, mengqian519@gmail.com.

Haoran Xu

Columbia University

hx2304@columbia.edu

Graduate School of Architecture, Planning and Preservation, Columbia University, New York, 10027, USA, hx2304@columbia.edu.

Jingwen He

Washington University in St. Louis

jingwenhe@wustl.edu

Samfox School of Architecture, Washington University in St. Louis, California, USA, 94608, jingwenhe@wustl.edu.

* Corresponding Author³: Jingwen He, E-Mail: jingwenhe@wustl.edu

Publication

Accepted Unknow ; Published 2025 January 1

Journal of Computer Technology and Applied Mathematics, 2025, 2(1), 3007-4126.

Abstract

This paper explores the application of machine learning (ML) in the selection and optimization of concrete materials for sustainable building design. It discusses how AI-driven platforms, such as Concrete Copilot and SmartMix, are revolutionizing concrete mix design by improving performance, reducing costs, and minimizing environmental impact. By leveraging ML techniques, these platforms enable real-time optimization of concrete ingredients, enhancing both resource efficiency and sustainability. The paper highlights the potential of machine learning to drive innovation in the concrete industry, contributing to the development of greener, more efficient building materials for future construction projects.

Keywords

Machine Learning , Sustainable Concrete , Material Optimization , Building Design .

Metadata

DOI:

10.70393/6a6374616d.323530

ARK:

ark:/40704/JCTAM.v2n1a02

Pages: 8-14

References: 35

Disciplines: Machine Learning

Subjects: Computer Application Technology

Cite This Article

APA Style

Meng, Q., Xu, H. & He, J. (2025). Using machine learning for sustainable concrete material selection and optimization in building design. Journal of Computer Technology and Applied Mathematics, 2(1), 8-14. https://doi.org/10.70393/6a6374616d.323530

Acknowledgments

The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.

FUNDING

Not applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not applicable.

DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

INFORMED CONSENT STATEMENT

Not applicable.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHOR CONTRIBUTIONS

Not applicable.

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