Advanced Methods for Estimating Mechanical Properties, Constructional and Performance of Fiber-Reinforced Concrete Materials
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Construction and Building Materials".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 1718
Special Issue Editor
Interests: machine learning; data science; data-driven methods; optimization; seismic design; innovative building materials; retrofitting buildings
Special Issue Information
Dear Colleagues,
Nowadays, artificial intelligence, specifically machine learning methods, can help to provide a surrogate prediction model for estimating the mechanical properties, performance and stability of concrete materials such as high-performance concrete, ultra-high-performance concrete, and alkali-activated ultra-high-performance concrete. Moreover, these data-driven techniques have the potential to be used by civil engineer/designers in various types of structures, bridges, and infrastructures. However, understanding numerous fundamental mechanisms in this field continues to pose a challenge, and the lack of industrial applications remains prevalent, highlighting the gap between theoretical research and real-world implementation in this area.
This Special Issue aims to focus on recent advancements, developments, and emerging trends related to machine learning methods for predicting mechanical properties of both fresh and hardened-state concrete material, long-term performance on the compressive or (tensile) strength of concrete material, and durability of eco-friendly cementitious materials with reduced carbon emissions. We welcome submissions of original research papers and review articles. Topics of interest include, but are not limited to:
- Innovative Ensemble Machine Learning Model;
- Data-Driven Techniques;
- High-Performance Concrete (HPC);
- Ultra-High-Performance Concrete (UHPC);
- Alkali-Activated Ultra-High-Performance Concrete (AA-UHPC);
- Green Concrete;
- Advancements in Concrete Materials;
- Fiber-Reinforced Concrete;
- Fiber-Reinforced Concrete Beam;
- Recycling and Upcycling in Building Materials;
- Smart and Responsive Materials for Building;
- Biocompatible and Biodegradable Building Materials;
- Low-Carbon Footprint Materials;
- Nano and Micro Technologies in Construction Materials;
- Fire-Resistant and Flame-Retardant Concrete Materials;
- Natural-Fiber-Reinforced Composites;
- 3D Printing in Construction;
- Durability and Longevity of Concrete Materials.
Dr. Farzin Kazemi
Guest Editor
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Keywords
- machine learning method
- data science
- data-driven techniques
- mechanical properties
- concrete materials
- fiber-reinforced concrete
- fiber-reinforced concrete beam
- optimization algorithms
- construction and building materials
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