Arti cial intelligence in concrete technology: a comprehensive review of simulation, modeling, and performance enhancement

REVIEWS ON ADVANCED MATERIALS SCIENCE, cilt.1, sa.1, ss.1-20, 2026 (Hakemli Dergi)

Concrete is a crucial construction material glob-

ally; nevertheless, increasing demands for superior me-

chanical performance, durability, and sustainability have

prompted the integration of modern technologies in con-

crete engineering. Arti cial intelligence (AI) has developed

as a transformative methodology, providing prediction,

optimization, and computational modeling capabilities that

surpass traditional experimental and analytical techniques.

This research rigorously analyzes AI-driven advancements

in concrete technology, emphasizing simulation, modeling,

and techniques for performance enhancement. Principal AI

technologies, such as machine learning, deep learning,

neural networks, and hybrid computational techniques, are

assessed for their capacity to forecast mechanical charac-

teristics, durability, workability, and long-term performance

under diverse environmental and loading situations. Appli-

cations in mix design optimization, sustainability evalua-

tion, and life cycle analysis illustrate AI’s capacity to reduce

environmental impacts, enhance material utilization, and

bolster structure resilience. Challenges like restricted

data availability, model interpretability, generalization

concerns, and computing requirements are examined, along

with solutions for enhancing reliability and practical use.

The results underscore AI’s pivotal function in the develop-

ment of intelligent, e cient, durable, and environmentally

sustainable concrete construction, o ering direction for

researchers and practitioners in creating high-performance

and sustainable infrastructure.