Concrete Structures Modeling: An Automated Model Discovery Framework
Public support
Provider
Czech Science Foundation
Programme
Standard projects
Call for proposals
SGA0202600001
Main participants
České vysoké učení technické v Praze / Fakulta stavební
Contest type
VS - Public tender
Contract ID
26-23871S
Alternative language
Project name in Czech
Concrete Structures Modeling: An Automated Model Discovery Framework
Annotation in Czech
The project aims to develop an advanced framework for simulating concrete behavior using autonomous model learning techniques. The idea is to integrate Physics-Informed Neural Networks (PINNs) with the Lattice Discrete Particle Model (LDPM) to overcome traditional limitations in constitutive modeling. Utilizing machine learning and experimental data, the framework seeks to dynamically adapt and optimize models, enhancing the accuracy and efficiency of concrete structure simulations. The interdisciplinary approach combines insights from mechanics, machine learning, and material science to create robust, interpretable models. The project will utilize an open-access dataset for training and validation, with a focus on ensuring the models' applicability in real-world engineering scenarios. Ultimately, this research aims to improve the design and durability of concrete structures, contributing to advancements in computational mechanics and structural engineering.
Scientific branches
R&D category
ZV - Basic research
OECD FORD - main branch
20102 - Construction engineering, Municipal and structural engineering
OECD FORD - secondary branch
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OECD FORD - another secondary branch
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CEP - equivalent branches <br>(according to the <a href="http://www.vyzkum.cz/storage/att/E6EF7938F0E854BAE520AC119FB22E8D/Prevodnik_oboru_Frascati.pdf">converter</a>)
GB - Agricultural machines and construction<br>JM - Structural engineering
Solution timeline
Realization period - beginning
Jan 1, 2026
Realization period - end
Dec 31, 2028
Project status
Z - Beginning multi-year project
Latest support payment
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Data delivery to CEP
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data delivery code
CEP26-GA0-GA-R
Data delivery date
Apr 29, 2026
Finance
Total approved costs
6,372 thou. CZK
Public financial support
6,372 thou. CZK
Other public sources
0 thou. CZK
Non public and foreign sources
0 thou. CZK