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


AKBULUT Z. F., Güler S., Arvas M. A., Osmanoğlu F., Kurucu M.

Reviews on Advanced Materials Science, cilt.65, sa.1, 2026 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 65 Sayı: 1
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1515/rams-2025-0240
  • Dergi Adı: Reviews on Advanced Materials Science
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals, Academic Search Ultimate (EBSCO)
  • Anahtar Kelimeler: artificial intelligence, computational modeling, concrete technology, performance enhancement, simulation
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

Concrete is a crucial construction material globally; nevertheless, increasing demands for superior mechanical performance, durability, and sustainability have prompted the integration of modern technologies in concrete engineering. Artificial 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 characteristics, durability, workability, and long-term performance under diverse environmental and loading situations. Applications in mix design optimization, sustainability evaluation, 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 development of intelligent, efficient, durable, and environmentally sustainable concrete construction, offering direction for researchers and practitioners in creating high-performance and sustainable infrastructure.