Logiciel Persalys-Penstock pour l'estimation de la fiabilité des conduites forcées soumises à la corrosion : développements et applications

International audienceUn modèle mécano-probabiliste a été développé afin d'estimer la probabilité annuelle de défaillance d'un tronçon de conduite forcée soumis à des pertes d'épaisseur par corrosion. Ce modèle a été implémenté dans l'application dédiée Persalys-Penstock, qui utilise la librairie OpenTURNS et l'IHM Persalys. Après avoir décrit les principales fonctionnalités de l'application Persalys-Penstock, on expose quelques résultats obtenus sur la ruine par instabilité plastique (hors soudures) sur des plans d'expériences aléatoires de très grande dimension. Ces calculs permettent notamment d'estimer des quantiles de la probabilité annuelle de défaillance enveloppe. On présente également quelques études de sensibilité menées sur la ruine par rupture brutale ou mixte de défauts de type fissure (dans les soudures). Ces études permettent d'évaluer la dépendance de la probabilité annuelle de défaillance par rapport aux données d'entrée les plus influentes telles que le Facteur de Marge, la cinétique annuelle de corrosion, le niveau des contraintes résiduelles de soudage, la performance des Contrôles Non Destructifs mis en oeuvre à la construction et la dispersion des pertes d'épaisseur, la pression d'épreuve hydraulique réalisée à la mise en service de l'ouvrage

Robustness evaluation of the reliability of penstocks combining line sampling and neural networks

The objective of this work is to conduct robustness evaluations on the reliability assessment of penstocks using the info-gap framework. In order to improve the induced optimization searches, three original line sampling procedures are proposed in order to address the complex limit-state function on which the failure probability depends. The proposed algorithms are proven to be well suited for the search of the multiple roots involved in the line sampling technique. Then, a classification and a regression artificial neural network are combined for predicting the roots in order to reduce the computational time engendered by robustness evaluations

An info-gap framework for comparing epistemic uncertainty models in hybrid structural reliability analysis

International audienceThe main objective of this work is to study the effect of the choice of the input uncertainty model on robustness evaluations of probabilities of failure. Aleatory and epistemic uncertainty are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap theory, which is usually used to assess the robustness of a model to uncertainty, allows the<br&gtbounds on the failure probability obtained from different epistemic uncertainty models to be compared at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared considering the interval model, triangular and trapezoidal<br&gtpossibility distributions, the probabilistic uniform distribution and the paralellepiped convex model on two toy cases. A specific demand value, as introduced in the info-gap theory, is used as a value of information metric to quantify the gain of information on the probability of failure between a less informative uncertainty model and a more informative one

Robustness evaluation of the reliability of penstocks combining line sampling and neural networks

The objective of this work is to conduct robustness evaluations on the reliability assessment of penstocks using the info-gap framework. In order to improve the induced optimization searches, three original line sampling procedures are proposed in order to address the complex limit-state function on which the failure probability depends. The proposed algorithms are proven to be well suited for the search of the multiple roots involved in the line sampling technique. Then, a classification and a regression artificial neural network are combined for predicting the roots in order to reduce the computational time engendered by robustness evaluations

An info-gap framework for robustness assessment of epistemic uncertainty models in hybrid structural reliability analysis

The main objective of this work is to study the impact of the choice of input uncertainty models on robustness evaluations for probabilities of failure. Aleatory and epistemic uncertainties are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap method, which is usually used to assess the robustness of a model to uncertainty, allows to compare the bounds on the probability of failure obtained from different epistemic uncertainty models at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared for the interval model, the triangular and trapezoidal possibility distributions, the probabilistic uniform distribution and the parallelepiped convex model on two academic examples and one industrial use-case. A specific demand value, as introduced in the info-gap method, is used as a value of information metric to quantify the gain of information on the probability of failure between less informative uncertainty models and a more informative ones

An info-gap framework for robustness assessment of epistemic uncertainty models in hybrid structural reliability analysis

The main objective of this work is to study the impact of the choice of input uncertainty models on robustness evaluations for probabilities of failure. Aleatory and epistemic uncertainties are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap method, which is usually used to assess the robustness of a model to uncertainty, allows to compare the bounds on the probability of failure obtained from different epistemic uncertainty models at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared for the interval model, the triangular and trapezoidal possibility distributions, the probabilistic uniform distribution and the parallelepiped convex model on two academic examples and one industrial use-case. A specific demand value, as introduced in the info-gap method, is used as a value of information metric to quantify the gain of information on the probability of failure between less informative uncertainty models and a more informative ones

An info-gap framework for robustness assessment of epistemic uncertainty models in hybrid structural reliability analysis

The main objective of this work is to study the impact of the choice of input uncertainty models on robustness evaluations for probabilities of failure. Aleatory and epistemic uncertainties are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap method, which is usually used to assess the robustness of a model to uncertainty, allows to compare the bounds on the probability of failure obtained from different epistemic uncertainty models at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared for the interval model, the triangular and trapezoidal possibility distributions, the probabilistic uniform distribution and the parallelepiped convex model on two academic examples and one industrial use-case. A specific demand value, as introduced in the info-gap method, is used as a value of information metric to quantify the gain of information on the probability of failure between less informative uncertainty models and a more informative ones

Use of baclofen for the treatment of alcohol use disorders between 2014 and 2021 in France

IntroductionThe use of baclofen for the treatment of alcohol use disorders (AUD) in France has increased significantly between 2007 and 2013, initially through off-label prescription (1,2). In April 2014, temporary authorization for use (TAU) was granted, followed by marketing authorization (MA) in October 2018. It was also reported that high doses of baclofen had the potential for serious adverse effects (3). As a result, the maximum dose was limited to 80 mg/day in July 2017. We aimed to assess the impact of the medical authorization (MA) of baclofen for alcohol use disorder (AUD) on the number of newly treated patients in France between 2014 and 2021, and the impact of dose restrictions on baclofen dosage.MethodsA retrospective cohort study of patients newly treated with baclofen for AUD was conducted using data from the French National Health Data System. Characteristics of patients and treatments were described. Interrupted time-series analyses (ARIMA models) were performed to evaluate the effect of MA and dose limitation on baclofen treatment initiations and daily doses.ResultsBetween 2014 and 2021, 478,109 patients were newly treated with baclofen for AUD. A significant decline of initiations of baclofen was observed between 2014 (N=98,552) and 2015 (N=67,555), and a gradual decrease after 2016 (N=48 471 in 2021). The MA of baclofen for AUD did not have a statistically significant impact on the number of baclofen initiations for AUD. Before dose limitation, respectively 78.0% and 0.8% of daily doses were lower than 80mg and higher than 300mg, against 88.3% and 0.5% after July 2017.ConclusionSince the peak in 2014, baclofen use has been steadily decreasing and MA has not resulted in an increase in baclofen initiations for AUD. The part of patients with a dose greater than 300mg is low and has decreased over the period 2014-2021

Sea-level pressure conditions that characterized an epidemic year.

<p>A composite analysis was performed by separately averaging the SLP data for the years in which the highest (HIGH) and lowest (LOW) DF incidence were recorded in French Guiana. The contours (at 0.5°C intervals) show the HIGH minus the LOW differences in the SLP from July to December to illustrate the conditions that characterized a typical epidemic year. Filled-in areas indicate significant differences at the 5% confidence interval and were calculated using Student's <i>t</i>-test.</p