Machine Learning and AI-Driven Innovations in Concrete Technology and Construction Materials

Dear Colleagues,

The rapid evolution of machine learning (ML) and artificial intelligence (AI) is transforming the field of civil engineering, especially in terms of concrete technology and construction materials. These technologies offer innovative solutions addressing long-standing challenges related to sustainability, durability, cost-effectiveness, and performance optimization. By leveraging big data, smart sensors, and predictive modeling, AI-driven approaches enable researchers and practitioners to optimize concrete mix designs, forecast structural behavior, and ensure long-term material resilience under diverse environmental and loading conditions.

This Special Issue, entitled “Machine Learning and AI-Driven Innovations in Concrete Technology and Construction Materials”, seeks to gather original research, case studies, and reviews that showcase how AI and ML can enhance civil engineering practices. It emphasizes both theoretical developments and practical applications, providing a comprehensive overview of the digital revolution shaping the future of sustainable construction.

Areas of interest include, but are not limited to, the following topics:

• AI-based optimization of concrete mix design and performance prediction;
• Application of ML in strength, durability, and sustainability assessment of construction materials;
• Real-time structural health monitoring using AI, IoT, and smart sensors;
• Digital twins for construction materials and structural systems;
• Big data analytics in material science and construction engineering;
• Predictive modeling of life-cycle performance and sustainability;
• Integration of ML/AI with nanotechnology and advanced material design;
• AI-assisted quality control and defect detection in manufacturing processes;
• Automated construction processes and robotics in civil engineering;
• Case studies on AI-driven approaches in sustainable buildings and infrastructure;
• Policy, standardization, and education challenges in adopting AI in construction.

By presenting interdisciplinary research from around the globe, this Special Issue aims to highlight the pivotal role of digital intelligence in advancing civil engineering materials and practices, bridging the gap between innovation, sustainability, and real-world implementation.

Dr. Radu Muntean
Guest Editor

Moutaman M. Abbas
Guest Editor Assistant
Email: moutaman.abbas@unitbv.ro
Affiliation: Department of Civil Engineering, Transilvania University of Brasov, 500036 Brasov, Romania
Website: https://scholar.google.com/citations?user=rtbOhwwAAAAJ&hl=en&oi=ao
Interests: sustainability; supplementary cementitious materials; concrete; AI-driven concrete technology

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 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.

• machine learning in concrete technology
• artificial intelligence in construction materials
• sustainable building materials
• durability and life-cycle performance
• digital twins and smart sensors
• structural health monitoring
• big data analytics in civil engineering
• mix design optimization
• predictive modeling
• AI-driven sustainability