Submission Deadline: 28 February 2026 View: 451 Submit to Special Issue
Prof. Xiao-Yong Wang
Email: wxbrave@kangwon.ac.kr
Affiliation: Departmentof Architectural Engineering,Kangwon National University, Gangwon, 24341, Korea
Research Interests: Sustainable concrete materials, performance prediction, numerical analysis
Prof. Ki-Bong Park
Email: kbpark@kangwon.ac.kr
Affiliation: Departmentof Architectural Engineering,Kangwon National University, Gangwon, 24341, Korea
Research Interests: High strength concrete, finite element method, artificial neural networks
With mounting global pressure to achieve carbon neutrality, the construction industry must transition toward sustainable and environmentally responsible practices. A critical component of this transformation lies in the development and deployment of low-carbon construction materials, such as eco-efficient concrete, recycled composites, geopolymers, and alternative binders. Traditional experimental approaches to material development and structural performance assessment, though foundational, often suffer from high costs and long lead times.
In contrast, computational modeling and simulation ranging from material-scale hydration models to full-scale structural analyses offer efficient, scalable, and predictive alternatives. Coupled with recent advances in artificial intelligence, digital twins, multi-physics modeling, and life cycle assessment, these tools enable high-throughput material screening, optimization of performance and sustainability, and even real-time decision support in construction processes.
This Special issue seeks to gather cutting-edge research on computational modeling, simulation, and optimization techniques for designing and assessing sustainable construction materials and systems. It aims to highlight multiscale and multidisciplinary approaches that integrate material science, structural engineering, environmental modeling, and computational intelligence.
The Special issue welcomes both methodological innovations and application-driven studies addressing the design, durability, carbon footprint, structural behavior, and lifecycle performance of sustainable construction solutions. Emphasis will be placed on the integration of modeling approaches across scales, from nano/microstructure prediction to full structural performance, as well as cross-disciplinary advances that couple AI, physics-based modeling, and digital construction technologies.
Suggested topics include, but are not limited to:
·Multiscale modeling of hydration, microstructure, and long-term durability in cement-based systems
·Finite element, discrete element, and mesh-free methods for sustainable materials and structures
·Coupled thermo-hydro-mechanical-chemical (THMC) simulations for green building materials
·Data-driven modeling: machine learning and hybrid models for property prediction and material design
·Optimization algorithms (e.g., NSGA-II, genetic algorithms, surrogate models) for low-carbon mix and structural design
·Digital twin and IoT-enabled modeling frameworks for smart construction monitoring
·Structural simulation and design under environmental constraints (e.g., carbon budget, embodied energy)
·Integrated life cycle analysis and carbon footprint modeling of construction processes
·AI-enhanced building information modeling (BIM) for sustainability assessment
·Simulation of recycled aggregate, geopolymer, and bio-based materials
·Predictive maintenance and deterioration modeling of low-carbon infrastructures
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