Multi-Objective Optimization and Machine Learning in Sustainable Concrete Development
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Materials, and Repair & Renovation".
Deadline for manuscript submissions: 10 January 2027 | Viewed by 1
Special Issue Editors
Interests: optimization algorithms; machine learning for sustainable materials; AI for civil engineering; predictive modelling for material properties; AI for healthcare and industrial applications; foundation models; explainable AI
Interests: metaheuristic optimization; flood susceptibility mapping; artificial intelligence; computer learning and pattern recognition
Interests: low-carbon materials; sustainable concrete; cementitious composites; geopolymer; alkali-activated materials; waste materials valorization; nanomaterials; machine learning in civil engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The growing demand for low-carbon, durable, and high-performance construction materials has accelerated the development of sustainable concrete. At the same time, the increasing complexity of concrete mixture design requires advanced tools capable of balancing multiple and often conflicting objectives, such as mechanical performance, durability, cost, workability, and environmental impact. In this context, multi-objective optimization and machine learning have emerged as powerful approaches for improving concrete design, predicting material behavior, and supporting data-driven decision-making in construction materials development.
This Special Issue aims to gather original research articles, review papers, case studies, and state-of-the-art contributions related to the application of optimization techniques, machine learning, and artificial intelligence in sustainable concrete development. Topics may include material proportioning, performance prediction, lifecycle assessment, durability enhancement, waste valorization, image-based analysis, classification, materials characterization, explainable AI, and intelligent design approaches for sustainable concrete. Contributions addressing both theoretical advances and practical applications in sustainable concrete technology, cement-based composites, and structural behavior are highly welcome.
Suggested topics include, but are not limited to, the following:
- Sustainable concrete materials;
- Low-carbon and green concrete;
- Multi-objective optimization in concrete mix design;
- Machine learning for concrete property prediction and classification;
- Explainable artificial intelligence in concrete research;
- Image processing for concrete analysis;
- AI-based microstructural analysis of cementitious materials;
- Structural behavior of sustainable concrete;
- AI-driven durability and service-life assessment;
- Optimization of cost, strength, and carbon footprint;
- Recycled aggregate concrete;
- Supplementary cementitious materials;
- Waste-based and circular concrete materials;
- Data-driven modeling of cement-based composites;
- Lifecycle assessment and sustainability evaluation;
- Hybrid optimization algorithms in concrete engineering;
- Digitalization and intelligent systems in concrete technology.
Dr. Radhwan A.A. Saleh
Dr. Mustafa Ghaleb
Dr. Amin Al-Fakih
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sustainable concrete
- low-carbon materials
- multi-objective optimization
- machine learning and explainable AI
- concrete mix design
- cementitious composites
- geopolymer
- durability
- life cycle assessment
- nanomaterials
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