Non Destructive Evaluation of Containment Walls in Nuclear Power Plants

Two functions are regularly tested on the containment walls in order to anticipate a possible accident. The first is mechanical to resist at a possible internal over-pressure and the second is to prevent leakage. The reference accident LLOCA (Large Loss of Coolant Accident) is the rupture of a pipe in the primary circuit of a nuclear plant. In this case, the pressure and temperature can reach 5 bar and 180°C in 20 seconds. The national project ‘Non-destructive testing of the containment structures of nuclear plants’ aims at studying the non-destructive techniques capable to evaluate the concrete properties and its damaging or progression of cracks. This 4-year-project is segmented into two parts. The first consists in developing and selecting the most relevant NDEs (Non Destructive Evaluations) in the laboratory to reach these goals. These evaluations are developed in conditions representing the real conditions of the stresses generated during ten-yearly visits of the plants or those related to an accident. The second part consists in applying the selected techniques to two containment structures under pressure. The first (technique) is proposed by the ONERA (National Office for Aerospace Studies and Research of France) and the second is a mock-up of a containment wall on a 1/3 scale made by EDF (Electricity of France) within the VeRCoRs program. Communication bears on the part of the project that concerns the damaging and cracking follow-up. The tests are done in bending on 3 or 4 points in order to study the cracks’ generation, their propagation, as well as their opening and closing. The mostly ultrasonic techniques developed concern linear or non-linear acoustic: acoustic emission [1], LOCADIFF (Locating with diffuse ultrasound) [2], energy diffusion, surface waves velocity and attenuation, DAET (Dynamic Acousto-Elasticity Testing) [3]. The data contribute to providing the mapping of the parameters searched for, either in volume, in surface or globally. Image correlation is an important additional asset to validate the coherence of the data. The spatial normalization of the data allows proposing algorithms on the combination of the experimental data. The tests results are presented and they show the capacity and the limits of the evaluation of the volume, surface or global data. A data fusion procedure is associated with these results

Utilisation d'ondes de surface à l'aide de scanners acoustiques sans contact pour le contrôle non destructif de structures en béton

This work proposes a method for the non-destructive testing of concrete for civil engineering structures.This method is based on the emission and reception - when the surface wave has passed through the material - ofacoustic sonic and ultrasonic waves. The waves used in this thesis are surface waves, as they have the property ofpenetrating the material to a depth equal to their wavelength. The auscultation of concrete is done using twoscanners: a first scanner applying this method with high frequency waves was used to characterize the concreteskin, while a second scanner using low frequency waves, developed within the framework of this work, made itpossible to characterize a concrete over the thickness of an entire wall. In order to determine the capabilities andlimitations of this method for the non-destructive testing of concrete, several pathologies or environmentalconditions of concrete were simulated in the laboratory on test specimens. These specimens were then examinednon-destructively with acoustic scanners and destructively with material tests. The pathologies or conditions inquestion were leaching, delamination, micro/macrocracking of the concrete, and its state of saturation. Comparisonof the results allowed us to conclude that this method and these scanners are able to detect and determine the depthof a leaching of concrete, as well as for a delamination within concrete, to follow the evolution of a saturation frontwithin a limestone but not yet within a concrete, and to detect and follow the stress and micro-cracking as well asthe evolution of macro-cracks, in particular thanks to automated measurements carried out in situ on the VeRCoRsstructure.Ce travail propose une méthode acoustique de contrôle non destructif du béton pour les structures du génie civil. Les ondes utilisées dans cette thèse sont des ondes de surface, car elles ont la propriété de pénétrerle matériau sur une profondeur égale à leur longueur d’onde. L’auscultation du béton est faite à l’aide de deuxscanners : un premier scanner appliquant cette méthode avec des ondes hautes fréquences a été utilisé pourcaractériser la peau d’un béton, tandis qu’un second scanner utilisant des ondes basses fréquences, développé dansle cadre de ce travail, a permis de caractériser un béton sur l’épaisseur d’un mur entier. Afin de déterminer lescapacités et les limites de cette méthode pour le contrôle non destructif du béton, plusieurs pathologies ouconditions environnementales du béton ont été simulées en laboratoire sur des éprouvettes. Ces éprouvettes ontensuite été auscultées de manière non destructive avec les scanners acoustiques, puis de manière destructive avecdes tests matériau. Les pathologies ou conditions en question sont la lixiviation, la délamination, lamicro/macrofissuration du béton, et son état de saturation. La comparaison des résultats nous a permis de conclureque cette méthode et ces scanners sont capables de détecter et déterminer la profondeur d’une lixiviation du béton,de même que pour une délamination au sein de béton, de suivre l’évolution d’un front de saturation au sein d’uncalcaire mais pas encore au sein d’un béton, et de détecter et suivre la contrainte et la microfissuration ainsi quel’évolution de macro fissures, notamment grâce à des mesures automatisées effectuées in situ sur la structure deVeRCoRs

Use of surface waves with non-contact acoustic scanners for non-destructive testing of concrete structures

Ce travail propose une méthode acoustique de contrôle non destructif du béton pour les structures du génie civil. Les ondes utilisées dans cette thèse sont des ondes de surface, car elles ont la propriété de pénétrerle matériau sur une profondeur égale à leur longueur d’onde. L’auscultation du béton est faite à l’aide de deuxscanners : un premier scanner appliquant cette méthode avec des ondes hautes fréquences a été utilisé pourcaractériser la peau d’un béton, tandis qu’un second scanner utilisant des ondes basses fréquences, développé dansle cadre de ce travail, a permis de caractériser un béton sur l’épaisseur d’un mur entier. Afin de déterminer lescapacités et les limites de cette méthode pour le contrôle non destructif du béton, plusieurs pathologies ouconditions environnementales du béton ont été simulées en laboratoire sur des éprouvettes. Ces éprouvettes ontensuite été auscultées de manière non destructive avec les scanners acoustiques, puis de manière destructive avecdes tests matériau. Les pathologies ou conditions en question sont la lixiviation, la délamination, lamicro/macrofissuration du béton, et son état de saturation. La comparaison des résultats nous a permis de conclureque cette méthode et ces scanners sont capables de détecter et déterminer la profondeur d’une lixiviation du béton,de même que pour une délamination au sein de béton, de suivre l’évolution d’un front de saturation au sein d’uncalcaire mais pas encore au sein d’un béton, et de détecter et suivre la contrainte et la microfissuration ainsi quel’évolution de macro fissures, notamment grâce à des mesures automatisées effectuées in situ sur la structure deVeRCoRs.This work proposes a method for the non-destructive testing of concrete for civil engineering structures.This method is based on the emission and reception - when the surface wave has passed through the material - ofacoustic sonic and ultrasonic waves. The waves used in this thesis are surface waves, as they have the property ofpenetrating the material to a depth equal to their wavelength. The auscultation of concrete is done using twoscanners: a first scanner applying this method with high frequency waves was used to characterize the concreteskin, while a second scanner using low frequency waves, developed within the framework of this work, made itpossible to characterize a concrete over the thickness of an entire wall. In order to determine the capabilities andlimitations of this method for the non-destructive testing of concrete, several pathologies or environmentalconditions of concrete were simulated in the laboratory on test specimens. These specimens were then examinednon-destructively with acoustic scanners and destructively with material tests. The pathologies or conditions inquestion were leaching, delamination, micro/macrocracking of the concrete, and its state of saturation. Comparisonof the results allowed us to conclude that this method and these scanners are able to detect and determine the depthof a leaching of concrete, as well as for a delamination within concrete, to follow the evolution of a saturation frontwithin a limestone but not yet within a concrete, and to detect and follow the stress and micro-cracking as well asthe evolution of macro-cracks, in particular thanks to automated measurements carried out in situ on the VeRCoRsstructure

Predicting County-Level Overdose Death Rates Amid the Escalating Overdose Crisis in the United States: A Statistical Modeling Approach Predicting Deaths Through 2022

Aims. U.S. overdose (OD) deaths continue to escalate but are characterized by geographic and temporal heterogeneity. We previously validated a predictive statistical model to predict county-level OD mortality nationally from 2013 to 2018. Herein, we aimed to: 1) validate our model’s performance at predicting county-level OD mortality in 2019 and 2020; 2) modify and validate our model to predict OD mortality in 2022. Methods. We evaluated our mixed effects negative binomial model’s performance at predicting county-level OD mortality in 2019 and 2020. Further, we modified our model which originally used data from the year X to predict OD deaths in the year X+1 to instead predict deaths in year X+3. We validated this modification for the years 2017 through 2019 and generated future-oriented predictions for 2022. Finally, to leverage available, albeit incomplete, 2020 OD mortality data, we also modified and validated our model to predict OD deaths in year X+2 and generated an alternative set of predictions for 2022. Results. Our original model continued to perform with similar efficacy in 2019 and 2020, remaining superior to a benchmark approach. Our modified X+3 model performed with similar efficacy as our original model, and we present predictions for 2022, including identification of counties most likely to experience highest OD mortality rates. There was a high correlation (Spearman’s ρ = 0.93) between the rank ordering of counties for our 2022 predictions using our X+3 and X+2 models. However, the X+3 model (which did not account for OD escalation during COVID) predicted only 62,000 deaths nationwide for 2022, whereas the X+2 model predicted over 87,000. Conclusion. We have predicted county-level overdose death rates for 2022 across the US. These predictions, made publicly available in our online application, can be used to identify counties at highest risk of high OD mortality and support evidence-based OD prevention planning

Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action.

The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the "risk assessment," "detection" or "prediction" of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices

Non Destructive Evaluation of Containment Walls in Nuclear Power Plants

Two functions are regularly tested on the containment walls in order to anticipate a possible accident. The first is mechanical to resist at a possible internal over-pressure and the second is to prevent leakage. The reference accident LLOCA (Large Loss of Coolant Accident) is the rupture of a pipe in the primary circuit of a nuclear plant. In this case, the pressure and temperature can reach 5 bar and 180°C in 20 seconds. The national project ‘Non-destructive testing of the containment structures of nuclear plants’ aims at studying the non-destructive techniques capable to evaluate the concrete properties and its damaging or progression of cracks. This 4-year-project is segmented into two parts. The first consists in developing and selecting the most relevant NDEs (Non Destructive Evaluations) in the laboratory to reach these goals. These evaluations are developed in conditions representing the real conditions of the stresses generated during ten-yearly visits of the plants or those related to an accident. The second part consists in applying the selected techniques to two containment structures under pressure. The first (technique) is proposed by the ONERA (National Office for Aerospace Studies and Research of France) and the second is a mock-up of a containment wall on a 1/3 scale made by EDF (Electricity of France) within the VeRCoRs program. Communication bears on the part of the project that concerns the damaging and cracking follow-up. The tests are done in bending on 3 or 4 points in order to study the cracks’ generation, their propagation, as well as their opening and closing. The mostly ultrasonic techniques developed concern linear or non-linear acoustic: acoustic emission [1], LOCADIFF (Locating with diffuse ultrasound) [2], energy diffusion, surface waves velocity and attenuation, DAET (Dynamic Acousto-Elasticity Testing) [3]. The data contribute to providing the mapping of the parameters searched for, either in volume, in surface or globally. Image correlation is an important additional asset to validate the coherence of the data. The spatial normalization of the data allows proposing algorithms on the combination of the experimental data. The tests results are presented and they show the capacity and the limits of the evaluation of the volume, surface or global data. A data fusion procedure is associated with these results.</p

Identifying counties at risk of high overdose mortality burden during the emerging fentanyl epidemic in the USA: a predictive statistical modelling study.

BackgroundThe emergence of fentanyl around 2013 represented a new, deadly stage of the opioid epidemic in the USA. We aimed to develop a statistical regression approach to identify counties at the highest risk of high overdose mortality in the subsequent years by predicting annual county-level overdose death rates across the contiguous USA and to validate our approach against observed overdose mortality data collected between 2013 and 2018.MethodsWe fit mixed-effects negative binomial regression models to predict overdose death rates in the subsequent year for 2013-18 for all contiguous state counties in the USA (ie, excluding Alaska and Hawaii). We used publicly available county-level data related to health-care access, drug markets, socio-demographics, and the geographical spread of opioid overdose as model predictors. The crude number of county-level overdose deaths was extracted from restricted US Centers for Disease Control and Prevention mortality records. To predict county-level overdose rates for the year 201X: (1) a model was trained on county-level predictor data for the years 2010-201(X-2) paired with county-level overdose deaths for the year 2011-201(X-1); (2) county-level predictor data for the year 201(X-1) was fed into the model to predict the 201X county-level crude number of overdose deaths; and (3) the latter were converted to a population-adjusted rate. For comparison, we generated a benchmark set of predictions by applying the observed slope of change in overdose death rates in the previous year to 201(X-1) rates. To assess the predictive performance of the model, we compared predicted values (of both the model and benchmark) to observed values by (1) calculating the mean average error, root mean squared error, and Spearman's correlation coefficient and (2) assessing the proportion of counties in the top decile (10%) of overdose death rates that were correctly predicted as such. Finally, in a post-hoc analysis, we sought to identify variables with greatest predictive utility.FindingsBetween 2013 and 2018, among the 3106 US counties included, our modelling approach outperformed the benchmark strategy across all metrics. The observed average county-level overdose death rate rose from 11·8 per 100 000 people in 2013 to 15·4 in 2017 before falling to 14·6 in 2018. Our negative binomal modelling approach similarly identified an increasing trend, predicting an average 11·8 deaths per 100 000 in 2013, up to 15·1 in 2017, and increasing further to 16·4 in 2018. The benchmark model over-predicted average death rates each year, ranging from 13·0 per 100 000 in 2013 to 18·3 in 2018. Our modelling approach successfully ranked counties by overdose death rate identifying between 42% and 57% of counties in the top decile of overdose mortality (compared with 29% and 43% using the benchmark) each year and identified 194 of the 808 counties with emergent overdose outbreaks (ie, newly entered the top decile) across the study period, versus 31 using the benchmark. In the post-hoc analysis, we identified geospatial proximity of overdose in nearby counties, opioid prescription rate, presence of an urgent care facility, and several economic indicators as the variables with the greatest predictive utility.InterpretationOur model shows that a regression approach can effectively predict county-level overdose death rates and serve as a risk assessment tool to identify future high mortality counties throughout an emerging drug use epidemic.FundingNational Institute on Drug Abuse

Non destructive monitoring of mechanical stress in concrete for the survey of nuclear power plants

Session 2-1 - NDE and NDT for Civil Engineering, paper QNDE2019-6837, 3 pagesInternational audienceTo prevent consequences of damage in case of accident, some barriers of pre-stressed concrete are included in the nuclear power plant structures. Hence, to insure the nuclear security, it is important to control these structures. The nuclear accident induces pressure and temperature increases. This case is studied in a French Project involving eight academic and industrial laboratories with skills in NDE (Non-Destructive Evaluation) methods. In this paper, we focus on the synthesis for the results with different techniques in relation with the evolution of stress in the structure. Experiments tests have been conducted on slabs 0.5 m x 0.25 m x 0.12 m submitted to compressive load, for one concrete mix formulated to be representative of nuclear containment. In situ NDE measurements have been done during a test simulating nuclear accident. These experiments were realized on the Vercors mock-up which is a 1/3 scaled concrete power plant (? 16 m x h 30 m cylinder, with 0.40 m thick walls) submitted to internal pressure up to 4 bars. This study includes electromagnetic techniques such as radar, capacitive, resistivity, permeability and ultrasonic measurements (impact echo, ultrasonic pulse velocity for volume and surface waves, diffuse waves, coda wave interferometry, nonlinear acoustics, etc.). Good agreements are observed between laboratory and in situ measurements. Industrial and research perspectives are presented

Non Destructive Evaluation for containment monitoring

International audienc