PRISM : Predictive Risk-Informed asset Strategic Management

Laurent Doyen

Laurent Doyen,
Assistant Professor in applied mathematics and especially in statistics and probability applied to reliability at University Grenoble Alpes, France.
laurent.doyen@univ-grenoble-alpes.fr

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Sophie Capdevielle

Sophie Capdevielle,
Assistant Professor in Civil Engineering at University Grenoble Alpes, France.

sophie.capdevielle@univ-grenoble-alpes.fr

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DESCRIPTION

The aim of this project is to develop decision support methods for the dynamic management of assets at risk in an uncertain context and in the presence of heterogeneous sources of information. The developed methods aim to integrate all the information (sensor data, control data, expert opinion, physical knowledge) into a stochastic model, and then use this surrogate knowledge model to develop predictive decision-making methods. One of the challenges of the project, in terms of AI, lies in the low-data context associated with risk issues, which requires introducing engineering knowledge, explainability and guaranteeing the decisions from the risk point of view. The project draws on a team of academics from a wide range of scientific fields, as well as established collaborations with industry, local authorities and operational technical services. These collaborations aim to help managing ageing critical infrastructures.


ACTIVITIES

  • PhD : « Taking into account different levels of information and the effect of maintenance in a multidimensional degradation process with a view to optimizing the monitoring and maintenance policy”, ongoing since September 2025.
  • M2 Internship + PhD on Fragility analysis of ageing assets subject to natural hazards: to begin in winter / spring 2026, currently recruiting.
  • Postdoc : "Considering deterioration in assessment of residual risk to protected infrastructures and systems », currently recruiting.
  • PhD : “Dialogue between micromechanics and probabilistic analyses for estimating the residual life of metallic structural elements under fatigue: application to hydraulic structures” financed by the industrial chair Medelia (Fondation Grenoble INP): to begin in Fall 2025.
  • Several internship positions will also be open during the chair duration
 

EVENTS

Presentation of the chair at the MIAI days, June 19 and 20, 2025, Grenoble


SELECTED LIST OF PUBLICATIONS : 

  • BOUH20] Bouhjiti D. E-M., Baroth J., Dufour F., Michel-Ponnelle S., Masson B., Stochastic Finite Elements Analysis of large concrete structures’ serviceability under Thermo-Hydro-Mechanical loads – Case of Nuclear Containment Buildings, Nuclear Engineering and Design, Vol. 370,110800, 2020.
  • [CAPD21] Capdevielle, S., Grange, S., Dufour, F., & Desprez, C. (2021). A shear warping kinematic enhancement for fiber beam elements with a damaging cross-section. Finite Elements in Analysis and Design, 195, 103559.
  • [CARL19] Carladous, S., Tacnet, J. M., Batton-Hubert, M., Dezert, J., & Marco, O. (2019). Managing protection in torrential mountain watersheds: A new conceptual integrated decision-aiding framework. Land Use Policy, 80, 464-479.
  • [CHAH21] Chahrour, N., Nasr, M., Tacnet, J. M., & Bérenguer, C. (2021). Deterioration modeling and maintenance assessment using physics-informed stochastic Petri nets: Application to torrent protection structures. Reliability Engineering & System Safety, 210, 107524.
  • [CHAH24a] Chahrour, N., Piton, G., Tacnet, J. M., & Bérenguer, C. (2024). A surrogate deterioration model of debris retention systems towards cost-effective maintenance strategies and increased protection efficacy. Engineering Structures, 300, 117202.
  • [CHAH24b]Chahrour, N., Bérenguer, C., & Tacnet, J. M. (2024). Incorporating cascading effects analysis in the maintenance policy assessment of torrent check dams against torrential floods. Reliability Engineering & System Safety, 243, 109875.
  • [LERO23] Leroy, M., Bérenguer, C., Doyen, L., & Gaudoin, O. (2023). Statistical inference for a Wiener‐based degradation model with imperfect maintenance actions under different observation schemes. Applied Stochastic Models in Business and Industry, 39(3), 352-371.
  • [LERO24] Leroy, M., Bérenguer, C., Doyen, L., & Gaudoin, O. (2024). Modelling and inference for a degradation process with partial maintenance effects. Quality and Reliability Engineering International, 40(7), 3729-3750.
  • [ROSS23] Rossat, D., Baroth, J., Briffaut, M., Dufour, F., Monteil, A., Masson, B., & Michel-Ponnelle, S. (2023). Bayesian updating for predictions of delayed strains of large concrete structures: influence of prior distribution. European Journal of Environmental and Civil Engineering, 27(4), 1763-1795.
  • [SAVI21] Savin, O., Baroth, J., Badina, C., Charbonnier, S., & Bérenguer, C. (2021). Damage due to start-stop cycles of turbine runners under high-cycle fatigue. International Journal of Fatigue, 153, 106458.
  • [WANG21] Wang, X., Gaudoin, O., Doyen, L., Bérenguer, C., & Xie, M. (2021). Modeling multivariate degradation processes with time‐variant covariates and imperfect maintenance effects. Applied Stochastic Models in Business and Industry, 37(3), 592-611.
Published on  September 17, 2025
Updated on September 17, 2025