Dear Colleagues,
On behalf of the Journal of the Asian Concrete Federation (ACF Journal), we are pleased to announce a Special Issue on “Artificial Intelligence and Data-Driven Approaches in Concrete Structures and Materials.”
Artificial intelligence (AI), machine learning (ML), and data-driven methods are rapidly reshaping concrete engineering — from predicting the properties of cementitious materials and optimizing mixtures, to designing, assessing, and monitoring reinforced- and prestressed-concrete structures. As the ACF Journal enters a new chapter as an Engineering Village (EI) and Scopus-indexed publication, this Special Issue aims to consolidate the latest advances at the intersection of concrete science and engineering and artificial intelligence, while bridging classical experimental and mechanics-based research with emerging data-driven paradigms.
We invite original research papers, review articles, and invited contributions from researchers and practitioners across the Asian Concrete Federation member countries and worldwide.
Scope and Topics (including, but not limited to):
- Machine-/deep-learning prediction of concrete material properties, durability, and mixture optimization;
- Data-driven performance prediction and design of RC/PC members and systems (flexure, shear, bond and anchorage, walls, coupling beams, columns, joints), including data-driven calibration of code provisions;
- AI for structural health monitoring, defect/damage detection, and NDT signal/image interpretation;
- Hybrid and physics-informed modeling (surrogate models, PINNs, mechanistic–data hybrids);
- AI for sustainable and low-carbon concrete (SCMs, geopolymers, recycled aggregates, LCA-driven optimization);
- Generative AI, large language models, and digital-twin / automation tools for concrete engineering practice;
- Enabling experimental, numerical, and analytical studies that generate benchmark datasets and design models.
Conventional experimental and analytical studies that produce design models or datasets relevant to the above themes are explicitly welcome.
Submission Process
Authors are invited to submit through the journal’s submission portal, https://mc03.manuscriptcentral.com/acf (ScholarOne / Manuscript Central). During submission, please select the Special Issue category “AI & Data-Driven Concrete” (exact category label to be confirmed) from the dropdown menu. Manuscripts must be prepared in Microsoft Word (PDF is not accepted) following the journal’s Author’s Guide, and submitted as four files: a cover letter, a separate title page, a blinded full manuscript, and (optional) a list of at least three suggested reviewers. All submissions undergo double-blind peer review, and the journal is open access with no article-processing charges.
Important Dates
- Call for papers open: July 2026
- Full manuscript submission deadline: 31 December 2026
- Expected publication: 2027 (Vol. 13).
Should you have any questions, please contact the Guest Editors — Prof. Hyeon-Jong Hwang (hwanghj@snu.ac.kr) and Prof. Jang-Woon Baek (baekjw@khu.ac.kr) — or the editorial office (Prof. Zhenguo Shi, Managing Editor, zshi@hnu.edu.cn; editorial support acf2023.acf2023@gmail.com). We value your contributions and look forward to your submissions.
With warm regards,
Prof. Hyeon-Jong Hwang (Seoul National University, Korea) — Lead Guest Editor
Prof. Jang-Woon Baek (Kyung Hee University, Korea) — Co-Guest Editor
Prof. Caijun Shi (Hunan University) — Editor-in-Chief, ACF Journal