Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend

The effective, economical, and safe design of engineering construction projects necessitates the use of advanced concrete technology. Due to the variety of conditions inherent in construction projects, engineers and concrete designers often find difficulties in choosing the best options, as extensive experimental validation is often associated with the consumption of time and resources. Predicting and optimizing real-life challenges in concrete technology can be completed in a faster and more efficient manner using artificial intelligence (AI) methods, as they offer a highly robust and practical approach. This resource is aimed specifically at guiding B. Tech students in utilizing AI techniques in concrete design, material characterization, and structural performance evaluation. It explores

the use of machine learning, meta-heuristic approaches, and hybrid models in the prediction of mechanical properties, optimization of concrete blend designs, and classification of material defects. Throughout the project development support process, students will be engaged in hands-on activities, utilizing AI tools and techniques in concrete-related datasets. Students will be required to understand the workings of various AI models and choose suitable algorithms to address specific issues related to concrete. The focus will be on developing predictive or optimization models. The aim is to enable students to design AI solutions to streamline the processes of design, analysis, and material selection related to advanced concrete technology, thereby allowing them to shift

from theoretical knowledge to more advanced practical skills.

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