During The Fifteenth International Conference on Computational Structures Technology (CST 2024) (https://www.civil-comp.info/2024/cst/), held from 4-6 September 2024 in Prague, Czech Republic, a special session titled “Data Science in Civil Engineering Materials” (CST-S1) took place. It was organized by Dr. S. Czarnecki and Prof. Łukasz Sadowski from Wroclaw University of Science and Technology, Poland.
The session focused on the application of data science and machine learning techniques in the analysis of civil engineering materials, highlighting their role in optimizing material selection, design, and durability assessment. Key topics included predictive modeling, decision support systems, and large dataset analysis from laboratory tests and field performance data.
One of the highlights of this session was a dedicated block on Reinforced Concrete Computational Modelling, held on Thursday, 5 September 2024, from 11:00 to 13:00. The session was chaired by Prof. Rami Hawileh, Prof. J.-W. Hong, and Dr. S. Czarnecki.
The presentations included:
- CST.14.1: Hardware Accelerated Python-Based Finite Element Analysis of Reinforced Concrete Member – H. Chung and H.-G. Kwak
- CST.14.2: Recent Trends in Using Artificial Intelligence in Evaluating Functional Properties of Industrial Concrete Floors – M. Moj, S. Czarnecki, Ł. Sadowski
- CST.14.3: Blast Responses of a Reinforced Concrete Slab Using the Arbitrary Lagrangian-Eulerian Method – T.H. Lee, D. Park, Y. Choi, Y. Lee, J.-W. Hong
The session attracted both researchers and industry professionals interested in cutting-edge techniques for material analysis and structural modeling in civil engineering.
