Sunday, June 28, 2020

UQSay #12


The twelfth UQSay seminar on Uncertainty Quantification and related topics, organized by L2S, MSSMAT, and EDF R&D, will take place online on Thursday afternoon, July 9, 2020.

14h–15h — Roberto Miorelli (CEA Paris-Saclay LIST) — [slides]

Metamodels and Statistical Tools Applied to Non-destructive Testing Problems

In the last decades, the non-destructive testing (NDT) research community has greatly increased its interest on statistical methods. This interest was driven by the community willingness to provide efficient solutions to NDT problems and push further the use of simulation to better design NDT inspection systems and procedures.

This research brought to the developments of new solutions to carry out sensitivity analysis, compute model assisted probability of detection, perform flaw(s) detection, flaw(s) characterization and probe optimization. Toward this end, the use of metamodels (also known as surrogate models) have been widely exploited for different NDT physics (ultrasound testing, eddy current testing, infrared thermography, etc.) with promising results. More recently, the NDT community is focussing on providing advanced simulation tools for performance estimation under uncertainties. One of the main area of interest of this research turns concerns the estimation of uncertainties for flaw(s) detection, characterization, and optimization problems. These developments have been particularly boosted and supported by the recent achievements in the field of machine learning that provide a plethora of algorithms and tools suitable for solving many different NDT problems.

This talk provides an overview on the use of metamodel tools and statistical methods applied to NDT problems developed at CEA LIST. A set of test cases that are matter of interest in the industrial domain are detailed and discussed. Moreover, some insights on the choices done to satisfy the different constraints imposed by the industrial domain are provided too.

Joint work with Christophe Reboud and Pierre Calmon.

PDF abstract: uqsay12_abstract_rmiorelli.pdf.

Organizers: Julien Bect (L2S), Emmanuel Vazquez (L2S), Didier Clouteau (MSSMAT), Filippo Gatti (MSSMAT), Fernando Lopez Caballero (MSSMAT), Bertrand Iooss (EDF R&D).

Practical details: the seminar will be held online using Microsoft Teams.

If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay group on Teams, simply send an email and you will be invited. Please specify which email address the invitation must be sent to (this has to be the address associated with your Teams account).

You will find the link to the seminar on the "General" UQSay channel on Teams, approximately 15 minutes before the beginning.

The technical side of things: you can use Teams either directly from you web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.

Wednesday, June 17, 2020

UQSay #11


The eleventh UQSay seminar on Uncertainty Quantification and related topics, organized by L2S, MSSMAT, and EDF R&D, will take place online on Thursday afternoon, June 25, 2020.

14h–15h — Guilhem Lavabre (EM2C) — [slides]

Dimension reduction and surrogate-modelling for uncertain auto-igniting flame simulations

Numerical simulations have become a backbone of research and industrial design, but few are as expensive as high-fidelity combustion simulations. These combine unsteady turbulent flow and chemistry computations, meaning a few tens of transport equations on meshes of several million nodes. As a result, such simulations can cost up to several millions of CPU-hours.

Alas, all this computational complexity does not shield the results from uncertainty as many sources of variability remain. To name a few: model calibration, operating conditions, exact composition of complex fuels, geometric variability of combustion chambers…

In this context, very sample-efficient methods are needed to make uncertainty propagation even affordable.

This presentation will focus on proposing methods to propagate chemical and experimental uncertainties in simulations of an auto-igniting flame. A toy-problem subject to similar physical phenomena will be introduced. It will be used to implement some uncertain dimension reduction methods. Different surrogate modelling approaches will then be tested and compared to put forward an affordable and relevant design of experiment for this problem.

Joint work with Olivier Gicquel and Ronan Vicquelin.

PDF abstract with illustrations: uqsay11_abstract_glavabre.pdf.

Organizers: Julien Bect (L2S), Emmanuel Vazquez (L2S), Didier Clouteau (MSSMAT), Filippo Gatti (MSSMAT), Fernando Lopez Caballero (MSSMAT), Bertrand Iooss (EDF R&D).

Practical details: the seminar will be held online using Microsoft Teams.

If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay channel on Teams, simply send an email and you will be invited. You will find the link to the seminar on this channel, approximately 15 minutes before the beginning.

The technical side of things: you can use Teams either directly from you web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.

Thursday, June 11, 2020

The show must go on

Dear colleagues, friends, UQ lovers,

There will be two more UQSay talks before the "summer break":

June 25 — Guilhem Lavabre
Dimension reduction and surrogate-modelling for uncertain auto-igniting flame simulations

July 9 — Roberto Miorelli
Metamodels and statistical tools applied to non-destructive testing problems

Save the dates!

Practical details: the seminar will be held online using Microsoft Teams.

If you want to attend these seminars (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay channel on Teams, simply to send an email and you will be invited. You will find the link to the seminar on this channel, approximately 15 minutes before the beginning.

The technical side of things: you can use Teams either directly from you web browser or using the "fat client" application, which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.

Wednesday, June 3, 2020

UQSay #10


The tenth UQSay seminar on Uncertainty Quantification and related topics, organized by L2S, MSSMAT, and EDF R&D, will take place online on Thursday afternoon, June 11, 2020.

14h–15h — Guillaume Perrin (CEA DIF) — [slides]

Point process-based approaches for the reliability analysis of complex systems

The conception of complex systems relies more and more on simulation. Numerical codes have therefore been introduced to optimize performance criteria for the system, but also to insure that undesirable events will not appear. Due to the presence of uncertainties on the inputs of the system, a probabilistic framework to the safety analysis of the system is generally considered. It generally relies on the estimation of the probability that a given real-valued output of the code does not exceed a specified threshold. This estimation may not be easy, as the numerical code can be very time-consuming and this probability may be very small (the system is supposed to be designed to operate in safe conditions).

In this presentation, we therefore propose an adaptive method to bound this probability with great confidence, while using as few code evaluations as possible. This method is based on the coupling of a particular Marked Poisson Process and the Gaussian process regression formalism. The interest of the proposed approach will finally be illustrated on a series of test cases.

Organizers: Julien Bect (L2S), Emmanuel Vazquez (L2S), Didier Clouteau (MSSMAT), Filippo Gatti (MSSMAT), Fernando Lopez Caballero (MSSMAT), Bertrand Iooss (EDF R&D).

Practical details: the seminar will be held online using Microsoft Teams.

If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay channel on Teams, simply to send an email and you will be invited. You will find the link to the seminar on this channel, approximately 15 minutes before the beginning.

The technical side of things: you can use Teams either directly from you web browser or using the "fat client" application, which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.

Thursday, May 21, 2020

UQSay #09


The ninth UQSay seminar on Uncertainty Quantification and related topics, organized by MSSMAT, L2S and EDF R&D, will take place online on Thursday afternoon, May 28, 2020.

14h–15h — Ludovic Chamoin (LMT ENS Paris-Saclay & IUF) — [slides]

Real-time data assimilation and control on mechanical systems under uncertainties

The work is placed into the framework of data assimilation and control in structural mechanics. It aims at developing new numerical tools in order to permit real-time and robust data assimilation and control that could then be used in various engineering activities. A specific targeted activity is the implementation of the DDDAS (Dynamic Data Driven Application System) technology in which a continuous exchange between simulation tools and experimental measurements is envisioned to the end of creating retroactive control loops on mechanical systems. In this context, and in order to take various uncertainty sources (modeling error, measurement noise…) into account, a powerful and general stochastic methodology with Bayesian inference is considered. However, a well-known drawback of such an approach is the computational complexity which makes real-time simulations and sequential assimilation some difficult tasks.

The presented work thus proposes to couple Bayesian inference with attractive and advanced numerical techniques so that real-time and sequential assimilation can be envisioned. First, PGD model reduction is introduced to facilitate the computation of the likelihood function, the uncertainty propagation through complex models, and the sampling of the posterior density. PGD builds a multi-parametric solution in an offline phase and leads to cost effective evaluation of the numerical model depending on parameters in the online inversion phase. Second, Transport Map sampling is investigated as a substitute to classical MCMC procedures for posterior sampling. It is shown that this technique leads to deterministic computations, with clear convergence criteria, and that it is particularly suited to sequential data assimilation. Here again, the use of PGD model reduction highly facilitates the process by recovering gradient and Hessian information in a straightforward manner. Third, and to increase robustness, on-the-fly correction of model bias is addressed in a stochastic context using data-based enrichment terms. Eventually, the synthesis of control laws in a stochastic context, using both PGD model reduction and dynamically updated model parameters, is investigated into the DDDAS framework in order to drive the physical system accordingly.

The overall methodology is applied and illustrated on specific test-cases dealing with 1the control of fusion welding processes or the management of mechanical tests on damageable concrete structures equipped with full-field measurements.

Joint work Paul-Baptiste Rubio and François Louf.

Refs: j.crme.2019.11.004, nme.6143, and s00466-018-1575-8.

PDF abstract: uqsay09_abstract_lchamoin.pdf.

Organizers: Julien Bect (L2S), Emmanuel Vazquez (L2S), Didier Clouteau (MSSMAT), Filippo Gatti (MSSMAT), Fernando Lopez Caballero (MSSMAT), Bertrand Iooss (EDF R&D).

Practical details: the seminar will be held online using Microsoft Teams.

If you want to attend this seminar (or any of the forthcoming online UQSay seminars), simply send an email to julien.bect@centralesupelec.fr and you will be invited to the UQSay channel on Teams. You will find the link to the seminar on this channel, approximately 15 minutes before the beginning.

The technical side of things: you can use Teams either directly from you web browser or using the "fat client" application, which is available for most platforms (Windows, Linux, Mac, Android & iOS). We recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.

Thursday, January 30, 2020

UQSay #08

The eighth UQSay seminar on Uncertainty Quantification and related topics, organized by L2S, Anses, MSSMAT, and EDF R&D will take place on Thursday afternoon, February 27, 2020, at CentraleSupelec Paris-Saclay (Eiffel building, amphi V).

14h — David Makowski (INRAE) — [slides]

The role of uncertainty analysis in biological invasion risk analysis

Biological invasions have sometimes spectacular consequences on our environment. They can have impacts on agricultural production, on human health and sometimes even call into question the existence of certain economic sectors. In order to assess the risks of potentially harmful organisms and identify appropriate management measures, numerous risk analyses are carried out every year by scientists from various disciplines in different countries. However, the likelihood of entry, establishment, spread of a biological organism and its potential impact depend on many uncertain factors. In this presentation, I will describe the main approaches used to conduct uncertainty analyses in this area and discuss their relevance and limitations for decision support.

15h — Myriam Merad (UMR LAMSADE, PSL*, CNRS, Univ. Paris Dauphine) — [slides]

Considerations around the concepts of uncertainty, risk and decision making in safety, security, environment and health

Through several operational examples, we will discuss the links between risks, uncertainties and decisions and the effect of modeling processes on decision support.

References: see ResearchGate and the book "Expertise Under Scrutiny".

Organizers: Emmanuel Vazquez (L2S), Laurent Guillier (Anses) and Julien Bect (L2S).

Saturday, December 14, 2019

UQSay #07

The seventh UQSay seminar on Uncertainty Quantification and related topics, organized by L2S and MSSMAT, will take place on Thursday afternoon, January 16, 2020, at CentraleSupelec Paris-Saclay (Eiffel building, amphi III).

We will have two talks:

14h — Bertrand Iooss (EDF R&D / PRISME dept.) — [slides]

Iterative estimation in uncertainty and sensitivity analysis

While building and using numerical simulation models, uncertainty and sensitivity analysis are invaluable tools. In engineering studies, numerical model users and modellers have shown high interest in these techniques that require to run many times the simulation model with different values of the model inputs in order to compute statistical quantities of interest (QoI, i.e. mean, variance, quantiles, sensitivity indices…). In this talk we will focus on new issues relative to large scale numerical systems that simulate complex spatial and temporal evolutions. Indeed, the current practice consists in the storage of all the simulation results. Such a storage becoming quickly overwhelming, with the associated long read time that makes cpu time consuming the estimation of the QoI. One solution consists in avoiding this storage and in computing QoI on the fly (also called in-situ). It turns the problem to considering problems of iterative statistical estimation. The general mathematical and computational issues will be posed, and a particular attention will be paid to the estimation of quantiles (via an adaptation of the Robbins-Monro algorithm) and variance-based sensitivity indices (the so-called Sobol' indices).

Joint work with Yvan Fournier (EDF), Bruno Raffin (INRIA), Alejandro Ribés (EDF), Théophile Terraz (INRIA).

Refs: hal-01607479 and hal-02016828.

Related software: Melissa.

15h — Bruno Barracosa (EDF R&D / EFESE dept. and L2S) — [slides1 + slides2]

Bayesian Multi-objective Optimization with Noisy Evaluations using the Knowledge Gradient

We consider the problem of multi-objective optimization in the case where each objective is a stochastic black box that provides noisy evaluation results. More precisely, let f_1, ..., f_q be q real-valued objective functions defined on a search domain 𝕏 ⊂ ℝ^d, and assume that, for each x ∈ 𝕏, we can observe a noisy version of the objectives: Z_1 = f_1(x) + ε_1, ..., Z_q = f_q(x) + ε_q, where the ε_i's are zero-mean random variables. Our objective is to estimate the Pareto-optimal solutions of the problem: min f_1, ..., f_q.

We adopt a Bayesian optimization approach, which is a classical approach when the affordable number of evaluations is severely limited. In essence, Bayesian optimization consists in choosing a probabilistic model for the outputs Z_i and defining a sampling criterion to select evaluation points in the search domain 𝕏. Here, we propose to discuss the extension of the Knowledge Gradient approach of Frazier, Powell and Dayanik (INFORMS J. Comput., 21(4):599–613, 2009) to multi-objective problems with noisy evaluations. For instance, such an extension has been recently proposed by Astudillo and Frazier.

Joint work with Julien Bect (L2S), Héloïse Baraffe (EDF), Juliette Morin (EDF), Gilles Malarange (EDF) and Emmanuel Vazquez (L2S).

Organizers: Julien Bect (L2S) and Fernando Lopez Caballero (MSSMAT).