Hydro-ROM - Reduced order models of hydraulic protection systems for extreme water hazards (n. 2022PXYYK5)
Type
PRIN 2022, D.D. n. 104 del 2 febbraio 2022
CUP
C53D23001800006
Principal Investigator
Antonia Larese De Tetto (Università degli Studi di Padova - Dipartimento di Matematica "Tullio Levi Civita")
Other research units
UO1 - Antonia LARESE DE TETTO - Università degli Studi di PADOVA
UO2 - Damiano PASETTO - Università "Ca' Foscari" VENEZIA
Duration
28/09/2023 - 28/02/2026
Description
In the last decades we have observed a rapid growth of extreme hydrological events, such as floods and rock/debris or mud flows affecting more and more frequently our lives. Existing scenario predictions are confirming that this tendency will keep worsening in the near future. Our levees, dams, check dams, and flood control structures have mostly been conceived based on design criteria that did not consider the actual frequency and intensity of extreme hydrological occurrences. This means that, in many cases, we are not aware of the real conditions of an operating hydraulic structure and cannot predict its response to unforeseen events, preventing timely planning of adequate retrofitting interventions. The detailed physical description of these hydraulic systems must take into account the mutual interaction between the fluid phase and the deformable boundary of the structures. The numerical simulation of these coupled systems is extremely computationally demanding, thus limiting their practical application to real system monitoring. The goal of the project is the creation of reduced order models for Digital Twins (DT) for hydraulic and protection structures under hydrological hazards such as floods and debris flows. The DT must be able to predict the structure response in real-time to adapt to the fast-flowing measurement data. The groundbreaking idea that allows to achieve the needed speed is to combine Data Assimilation (DA) and Reduced Order Models (ROMs) to design machine learning echniques for complex and accurate high fidelity DTs. ROMs will capture the relevant features of the real process, while guaranteeing the computational efficiency for quasi real time applications. DAs will continuously correct and optimize the ROMs by the seamless flow of monitoring data during operational conditions, resulting in a modeling system classifiable within the framework of physics-informed machine learning.
The starting point is represented by the work of the team on complex three dimensional high fidelity numerical models (full order models -FOMs), to solve fluid-structure and fluid-soil problems able to simulate accurately the 3 dimensional interaction between the flow field (e.g. due to floods, intense sediment transport and debris flows or rapid rock movements), and/or the surrounding soil and the hydraulic or protection structure. This expertise on FOMs is complemented by the expertise in developing ROMs and DAs for nonlinear models as well as uncertainty quantification.
Activities
Postdoc 1 - Eleonora Spricigo
Postdoc 2 - Deependra Kumar
HYDROROM WORKSHOP: "Approximating the response of complex hydrological systems: from theory to real-world applications", June 3rd 2025, Venice
https://www.unive.it/data/agenda/9/101822
Plenary (A. Larese) at YAMC 2025, Padova
Plenary (A. Larese) at COMPSAFE: 4th International Conference on Computational Engineering and Science for Safety and Environmental Problems (COMPSAFE), Kobe, Japan https://www.compsafe2025.org;
Plenary (A. Larese) at HICOMP: 1st Hellenic Ialian Workshop in Computational Mechanics (HICOMP), 19-21 June 2025 Rodos, Greece https://www.hicomp2025.org/content/invited-speakers;
Keynote Speaker (A. Larese), 4th International Workshop on Advances in Computational Mechanics (IWACOM), 09.2024 Fukuoka, Japan https://www.jsces.org/IWACOM/4th/
Invited speaker, International Conference on Modern Materials and Technologies,CIMTEC,
Montecatini, Italy https://2024.cimtec-congress.org/track-e ;
Presentations at COUPLED 2025 -
Towards a surrogate model for debris flow events
E. Spricigo * , K. Deependra , M. Putti , D. Pasetto , A. Larese
Partitioned MPM-FEM Coupling Strategy to Simulate Granular Mass Flows Impacting Flexible Protective Structures V. Singer * , A. Larese , K. Bletzinger , R. Wüchner
A Fractal RBF Approach for Enhanced Surrogate Modeling of a Debris Flow
D. Kumar * , E. Spricigo , M. Putti , D. Pasetto , A. Larese
Presentation at SIMAI 2025 -
A Fractal RBF Approach for Enhanced Surrogate Modeling of a Granular Flows
D. Kumar * , E. Spricigo , M. Putti , D. Pasetto , A. Larese
Related publications
1. Dehghan-Souraki, D, Chasco, U., Zorrilla, R., Bladé i Castellet, E., and Larese, A., Three-
Dimensional Finite Element Modeling of Thermal Stratification in the Riba-Roja Reservoir Confluence: A Fluid–Thermal Multiphysics Approach, Water, 17(5),674, (2025)
https://doi.org/10.3390/w17050674
2.Moreno-Martinez, L. Wüchner, R., Larese, A., A mixed stabilized MPM formulation for
incompressible hyperelastic materials using Variational Subgrid-Scales Computer Meth-
ods in Applied Mechanics and Engineering (2025) Volume 435, 15 February 2025, 117621
https://doi.org/10.1016/j.cma.2024.117621
3.Dehghan-Souraki, D., López-Gómez,D., Bladé-Castellet, E., Larese, A., Sanz-Ramos, M.,
Optimizing sediment transport models by using the Monte Carlo simulation and deep
neural network (DNN): A case study of the Riba-Roja reservoir, Environmental Modelling
& Software, 175 (2024) https://doi.org/10.1016/j.envsoft.2024.105979
