939 resultados para Risk-based maintenance
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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is unproductive. A risk-based decision support system (DSS) that reduces the amount of time spent on inspection has been presented. The risk-based DSS uses the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of occurrence of these risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost and the cumulative effect of failure is determined through probability analysis. The model optimizes the cost of pipeline operations by reducing subjectivity in selecting a specific inspection method, identifying and prioritizing the right pipeline segment for inspection and maintenance, deriving budget allocation, providing guidance to deploy the right mix labor for inspection and maintenance, planning emergency preparation, and deriving logical insurance plan. The proposed methodology also helps derive inspection and maintenance policy for the entire pipeline system, suggest design, operational philosophy, and construction methodology for new pipelines.
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Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.
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Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.
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After a series of major storms over the last 20 years, the state of financing for U.S. natural disaster insurance has undergone substantial disruptions causing many federal and state backed programs against residential property damage to become severally underfunded. In order to regain actuarial soundness, policy makers have proposed a shift to a system that reflects risk-based pricing for property insurance. We examine survey responses from 1394 single-family homeowners in the state of Florida for support of several natural disaster mitigation policy reforms. Utilizing a partial proportional odds model we test for effects of location, risk perception, socio-economic and housing characteristics on support for policy reforms. Our findings suggest residents across the state, not just risk-prone homeowners, support the current subsidized model. We also examine several other policy questions from the survey to verify our initial results. Finally, the implications of our findings are discussed to provide inputs to policymakers.
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Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.
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For products sold with warranty, preventive maintenance actions by manufacturers and/or buyers have an impact on the total costs for both parties. This paper develops a framework to study preventive maintenance actions when items are sold under warranty and reviews the models that have appeared in the literature. It then develops a new model and carries out its analysis.
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In this study, we examine an important factor that affects consumers' acceptance of business-to-commerce (B2C) electronic commerce - perceived risk. The objective of this paper is to examine the definition of perceived risk in the context of B2C electronic commerce. The paper highlights the importance of perceived risk and the interwoven relation between perceived risk and trust. It discusses the problem of defining perceived risk in prior B2C research. This study proposes a new classification of consumers' perceived risk based on sources. It highlights the importance of identifying the sources of consumer's risk perceptions in addition to the consequences dimensions. Two focus group discussion sessions were conducted to verify the proposed classification. Results indicate that Internet consumers perceive three sources of risk in B2C electronic commerce: technology, vendor, and product. © 2003 Elsevier B.V. All rights reserved.
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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia
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OBJECTIVE: To assess the health risk of exposure to benzene for a community affected by a fuel leak. METHODS: Data regarding the fuel leak accident with, which occurred in the Brasilia, Federal District, were obtained from the Fuel Distributor reports provided to the environmental authority. Information about the affected population (22 individuals) was obtained from focal groups of eight individuals. Length of exposure and water benzene concentration were estimated through a groundwater flow model associated with a benzene propagation model. The risk assessment was conducted according to the Agency for Toxic Substances and Disease Registry methodology. RESULTS: A high risk perception related to the health consequences of the accident was evident in the affected community (22 individuals), probably due to the lack of assistance and a poor risk communication from government authorities and the polluting agent. The community had been exposed to unsafe levels of benzene (> 5 µg/L) since December 2001, five months before they reported the leak. The mean benzene level in drinking water (72.2 µg/L) was higher than that obtained by the Fuel Distributer using the Risk Based Corrective Action methodology (17.2 µg/L).The estimated benzene intake from the consumption of water and food reached a maximum of 0.0091 µg/kg bw/day (5 x 10-7 cancer risk per 106 individuals). The level of benzene in water vapor while showering reached 7.5 µg/m3 for children (1 per 104 cancer risk). Total cancer risk ranged from 110 to 200 per 106 individuals. CONCLUSIONS: The population affected by the fuel leak was exposed to benzene levels that might have represented a health risk. Local government authorities need to develop better strategies to respond rapidly to these types of accidents to protect the health of the affected population and the environment.
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Stress exposure triggers cognitive and behavioral impairments that influence decision-making processes. Decisions under a context of uncertainty require complex reward-prediction processes that are known to be mediated by the mesocorticolimbic dopamine (DA) system in brain areas sensitive to the deleterious effects of chronic stress, in particular the orbitofrontal cortex (OFC). Using a decision-making task, we show that chronic stress biases risk-based decision-making to safer behaviors. This decision-making pattern is associated with an increased activation of the lateral part of the OFC and with morphological changes in pyramidal neurons specifically recruited by this task. Additionally, stress exposure induces a hypodopaminergic status accompanied by increased mRNA levels of the dopamine receptor type 2 (Drd2) in the OFC; importantly, treatment with a D2/D3 agonist quinpirole reverts the shift to safer behaviors induced by stress on risky decision-making. These results suggest that the brain mechanisms related to risk-based decision-making are altered after chronic stress, but can be modulated by manipulation of dopaminergic transmission.
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This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.
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This thesis focuses on theoretical asset pricing models and their empirical applications. I aim to investigate the following noteworthy problems: i) if the relationship between asset prices and investors' propensities to gamble and to fear disaster is time varying, ii) if the conflicting evidence for the firm and market level skewness can be explained by downside risk, Hi) if costly learning drives liquidity risk. Moreover, empirical tests support the above assumptions and provide novel findings in asset pricing, investment decisions, and firms' funding liquidity. The first chapter considers a partial equilibrium model where investors have heterogeneous propensities to gamble and fear disaster. Skewness preference represents the desire to gamble, while kurtosis aversion represents fear of extreme returns. Using US data from 1988 to 2012, my model demonstrates that in bad times, risk aversion is higher, more people fear disaster, and fewer people gamble, in contrast to good times. This leads to a new empirical finding: gambling preference has a greater impact on asset prices during market downturns than during booms. The second chapter consists of two essays. The first essay introduces a foramula based on conditional CAPM for decomposing the market skewness. We find that the major market upward and downward movements can be well preadicted by the asymmetric comovement of betas, which is characterized by an indicator called "Systematic Downside Risk" (SDR). We find that SDR can efafectively forecast future stock market movements and we obtain out-of-sample R-squares (compared with a strategy using historical mean) of more than 2.27% with monthly data. The second essay reconciles a well-known empirical fact: aggregating positively skewed firm returns leads to negatively skewed market return. We reconcile this fact through firms' greater response to negative maraket news than positive market news. We also propose several market return predictors, such as downside idiosyncratic skewness. The third chapter studies the funding liquidity risk based on a general equialibrium model which features two agents: one entrepreneur and one external investor. Only the investor needs to acquire information to estimate the unobservable fundamentals driving the economic outputs. The novelty is that information acquisition is more costly in bad times than in good times, i.e. counter-cyclical information cost, as supported by previous empirical evidence. Later we show that liquidity risks are principally driven by costly learning. Résumé Cette thèse présente des modèles théoriques dévaluation des actifs et leurs applications empiriques. Mon objectif est d'étudier les problèmes suivants: la relation entre l'évaluation des actifs et les tendances des investisseurs à parier et à crainadre le désastre varie selon le temps ; les indications contraires pour l'entreprise et l'asymétrie des niveaux de marché peuvent être expliquées par les risques de perte en cas de baisse; l'apprentissage coûteux augmente le risque de liquidité. En outre, des tests empiriques confirment les suppositions ci-dessus et fournissent de nouvelles découvertes en ce qui concerne l'évaluation des actifs, les décisions relatives aux investissements et la liquidité de financement des entreprises. Le premier chapitre examine un modèle d'équilibre où les investisseurs ont des tendances hétérogènes à parier et à craindre le désastre. La préférence asymétrique représente le désir de parier, alors que le kurtosis d'aversion représente la crainte du désastre. En utilisant les données des Etats-Unis de 1988 à 2012, mon modèle démontre que dans les mauvaises périodes, l'aversion du risque est plus grande, plus de gens craignent le désastre et moins de gens parient, conatrairement aux bonnes périodes. Ceci mène à une nouvelle découverte empirique: la préférence relative au pari a un plus grand impact sur les évaluations des actifs durant les ralentissements de marché que durant les booms économiques. Exploitant uniquement cette relation générera un revenu excédentaire annuel de 7,74% qui n'est pas expliqué par les modèles factoriels populaires. Le second chapitre comprend deux essais. Le premier essai introduit une foramule base sur le CAPM conditionnel pour décomposer l'asymétrie du marché. Nous avons découvert que les mouvements de hausses et de baisses majeures du marché peuvent être prédits par les mouvements communs des bêtas. Un inadicateur appelé Systematic Downside Risk, SDR (risque de ralentissement systématique) est créé pour caractériser cette asymétrie dans les mouvements communs des bêtas. Nous avons découvert que le risque de ralentissement systématique peut prévoir les prochains mouvements des marchés boursiers de manière efficace, et nous obtenons des carrés R hors échantillon (comparés avec une stratégie utilisant des moyens historiques) de plus de 2,272% avec des données mensuelles. Un investisseur qui évalue le marché en utilisant le risque de ralentissement systématique aurait obtenu une forte hausse du ratio de 0,206. Le second essai fait cadrer un fait empirique bien connu dans l'asymétrie des niveaux de march et d'entreprise, le total des revenus des entreprises positiveament asymétriques conduit à un revenu de marché négativement asymétrique. Nous décomposons l'asymétrie des revenus du marché au niveau de l'entreprise et faisons cadrer ce fait par une plus grande réaction des entreprises aux nouvelles négatives du marché qu'aux nouvelles positives du marché. Cette décomposition révélé plusieurs variables de revenus de marché efficaces tels que l'asymétrie caractéristique pondérée par la volatilité ainsi que l'asymétrie caractéristique de ralentissement. Le troisième chapitre fournit une nouvelle base théorique pour les problèmes de liquidité qui varient selon le temps au sein d'un environnement de marché incomplet. Nous proposons un modèle d'équilibre général avec deux agents: un entrepreneur et un investisseur externe. Seul l'investisseur a besoin de connaitre le véritable état de l'entreprise, par conséquent, les informations de paiement coutent de l'argent. La nouveauté est que l'acquisition de l'information coute plus cher durant les mauvaises périodes que durant les bonnes périodes, comme cela a été confirmé par de précédentes expériences. Lorsque la récession comamence, l'apprentissage coûteux fait augmenter les primes de liquidité causant un problème d'évaporation de liquidité, comme cela a été aussi confirmé par de précédentes expériences.
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To evaluate how young physicians in training perceive their patients' cardiovascular risk based on the medical charts and their clinical judgment. Cross sectional observational study. University outpatient clinic, Lausanne, Switzerland. Two hundred hypertensive patients and 50 non-hypertensive patients with at least one cardiovascular risk factor. Comparison of the absolute 10-year cardiovascular risk calculated by a computer program based on the Framingham score and adapted for physicians by the WHO/ISH with the perceived risk as assessed clinically by the physicians. Physicians underestimated the 10-year cardiovascular risk of their patients compared to that calculated with the Framingham score. Concordance between methods was 39% for hypertensive patients and 30% for non-hypertensive patients. Underestimation of cardiovascular risks for hypertensive patients was related to the fact they had a stabilized systolic blood pressure under 140 mm Hg (OR = 2.1 [1.1; 4.1]). These data show that young physicians in training often have an incorrect perception of the cardiovascular risk of their patients with a tendency to underestimate the risk. However, the calculated risk could also be slightly overestimated when applying the Framingham Heart Study model to a Swiss population. To implement a systematic evaluation of risk factors in primary care a greater emphasis should be placed on the teaching of cardiovascular risk evaluation and on the implementation of quality improvement programs.
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Given the significant impact the use of glucocorticoids can have on fracture risk independent of bone density, their use has been incorporated as one of the clinical risk factors for calculating the 10-year fracture risk in the World Health Organization's Fracture Risk Assessment Tool (FRAX(®)). Like the other clinical risk factors, the use of glucocorticoids is included as a dichotomous variable with use of steroids defined as past or present exposure of 3 months or more of use of a daily dose of 5 mg or more of prednisolone or equivalent. The purpose of this report is to give clinicians guidance on adjustments which should be made to the 10-year risk based on the dose, duration of use and mode of delivery of glucocorticoids preparations. A subcommittee of the International Society for Clinical Densitometry and International Osteoporosis Foundation joint Position Development Conference presented its findings to an expert panel and the following recommendations were selected. 1) There is a dose relationship between glucocorticoid use of greater than 3 months and fracture risk. The average dose exposure captured within FRAX(®) is likely to be a prednisone dose of 2.5-7.5 mg/day or its equivalent. Fracture probability is under-estimated when prednisone dose is greater than 7.5 mg/day and is over-estimated when the prednisone dose is less than 2.5 mg/day. 2) Frequent intermittent use of higher doses of glucocorticoids increases fracture risk. Because of the variability in dose and dosing schedule, quantification of this risk is not possible. 3) High dose inhaled glucocorticoids may be a risk factor for fracture. FRAX(®) may underestimate fracture probability in users of high dose inhaled glucocorticoids. 4) Appropriate glucocorticoid replacement in individuals with adrenal insufficiency has not been found to increase fracture risk. In such patients, use of glucocorticoids should not be included in FRAX(®) calculations.
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Executive SummaryIn Nepal, landslides are one of the major natural hazards after epidemics, killing over 100 persons per year. However, this figure is an underreported reflection of the actual impact that landslides have on livelihoods and food security in rural Nepal. With predictions of more intense rainfall patterns, landslide occurrence in the Himalayas is likely to increase and continue to be one of the major impediments to development. Due to the remoteness of many localities and lack of resources, responsibilities for disaster preparedness and response in mountain areas usually lie with the communities themselves. Everyday life is full of risk in mountains of Nepal. This is why mountain populations, as well as other populations living in harsh conditions have developed a number of coping strategies for dealing with adverse situations. Perhaps due to the dispersed and remote nature of landslides in Nepal, there have been few studies on vulnerability, coping- and mitigation strategies of landslide affected populations. There are also few recommendations available to guide authorities and populations how to reduce losses due to landslides in Nepal, and even less so, how to operationalize resilience and vulnerability.Many policy makers, international donors, NGOs and national authorities are currently asking what investments are needed to increase the so-called 'resilience' of mountain populations to deal with climate risks. However, mountain populations are already quite resilient to seasonal fluctuations, temperature variations, rainfall patterns and market prices. In spite of their resilience, they continue to live in places at risk due to high vulnerability caused by structural inequalities: access to land, resources, markets, education. This interdisciplinary thesis examines the concept of resilience by questioning its usefulness and validity as the current goal of international development and disaster risk reduction policies, its conceptual limitations and its possible scope of action. The goal of this study is two-fold: to better define and distinguish factors and relationships between resilience, vulnerability, capacities and risk; and to test and improve a participatory methodology for evaluating landslide risk that can serve as a guidance tool for improving community-based disaster risk reduction. The objective is to develop a simple methodology that can be used by NGOs, local authorities and communities to reduce losses from landslides.Through its six case studies in Central-Eastern Nepal, this study explores the relation between resilience, vulnerability and landslide risk based on interdisciplinary methods, including geological assessments of landslides, semi-structured interviews, focus groups and participatory risk mapping. For comparison, the study sites were chosen in Tehrathum, Sunsari and Dolakha Districts of Central/Eastern Nepal, to reflect a variety of landslide types, from chronic to acute, and a variety of communities, from very marginalized to very high status. The study uses the Sustainable Livelihoods Approach as its conceptual basis, which is based on the notion that access and rights to resources (natural, human/institutional, economic, environmental, physical) are the basis for coping with adversity, such as landslides. The study is also intended as a contribution to the growing literature and practices on Community Based Disaster Risk Reduction specifically adapted to landslide- prone areas.In addition to the six case studies, results include an indicator based methodology for assessing and measuring vulnerability and resilience, a composite risk assessment methodology, a typology of coping strategies and risk perceptions and a thorough analysis of the relation between risk, vulnerability and resilience. The methodology forassessing vulnerability, resilience and risk is relatively cost-effective and replicable in a low-data environment. Perhaps the major finding is that resilience is a process that defines a community's (or system's) capacity to rebound following adversity but it does not necessarily reduce vulnerability or risk, which requires addressing more structural issues related to poverty. Therefore, conclusions include a critical view of resilience as a main goal of international development and disaster risk reduction policies. It is a useful concept in the context of recovery after a disaster but it needs to be addressed in parallel with vulnerability and risk.This research was funded by an interdisciplinary grant (#26083591) from the Swiss National Science Foundation for the period 2009-2011 and a seed grant from the Faculty of Geosciences and Environment at the University of Lausanne in 2008.Résumé en françaisAu Népal, les glissements de terrain sont un des aléas les plus dévastateurs après les épidémies, causant 100 morts par an. Pourtant, ce chiffre est une sous-estimation de l'impact réel de l'effet des glissements sur les moyens de subsistance et la sécurité alimentaire au Népal. Avec des prévisions de pluies plus intenses, l'occurrence des glissements dans les Himalayas augmente et présente un obstacle au développement. Du fait de l'éloignement et du manque de ressources dans les montagnes au Népal, la responsabilité de la préparation et la réponse aux catastrophes se trouve chez les communautés elles-mêmes. Le risque fait partie de la vie quotidienne dans les montagnes du Népal. C'est pourquoi les populations montagnardes, comme d'autres populations vivant dans des milieux contraignants, ont développé des stratégies pour faire face aux situations défavorables. Peu d'études existent sur la vulnérabilité, ceci étant probablement dû à l'éloignement et pourtant, les stratégies d'adaptation et de mitigation des populations touchées par des glissements au Népal existent.Beaucoup de décideurs politiques, bailleurs de fonds, ONG et autorités nationales se demandent quels investissements sont nécessaires afin d'augmenter la 'resilience' des populations de montagne pour faire face aux changements climatiques. Pourtant, ces populations sont déjà résilientes aux fluctuations des saisons, des variations de température, des pluies et des prix des marchés. En dépit de leur résilience, ils continuent de vivre dans des endroits à fort risque à cause des vulnérabilités créées par les inégalités structurelles : l'accès à la terre, aux ressources, aux marchés et à l'éducation. Cette thèse interdisciplinaire examine le concept de la résilience en mettant en cause son utilité et sa validité en tant que but actuel des politiques internationales de développement et de réduction des risques, ainsi que ses limitations conceptuelles et ses possibles champs d'action. Le but de cette étude est double : mieux définir et distinguer les facteurs et relations entre la résilience, la vulnérabilité, les capacités et le risque ; Et tester et améliorer une méthode participative pour évaluer le risque des glissements qui peut servir en tant qu'outil indicatif pour améliorer la réduction des risques des communautés. Le but est de développer une méthodologie simple qui peut être utilisée par des ONG, autorités locales et communautés pour réduire les pertes dues aux glissements.A travers les études de cas au centre-est du Népal, cette étude explore le rapport entre la résilience, la vulnérabilité et les glissements basée sur des méthodes interdisciplinaires ; Y sont inclus des évaluations géologiques des glissements, des entretiens semi-dirigés, des discussions de groupes et des cartes de risques participatives. Pour la comparaison, les zones d'études ont été sélectionnées dans les districts de Tehrathum, Sunsari et Dolakha dans le centre-est du Népal, afin de refléter différents types de glissements, de chroniques à urgents, ainsi que différentes communautés, variant de très marginalisées à très haut statut. Pour son cadre conceptuel, cette étude s'appuie sur l'approche de moyens de subsistance durable, qui est basée sur les notions d'accès et de droit aux ressources (naturelles, humaines/institutionnelles, économiques, environnementales, physiques) et qui sont le minimum pour faire face à des situations difficiles, comme des glissements. Cette étude se veut aussi une contribution à la littérature et aux pratiques en croissantes sur la réduction des risques communautaires, spécifiquement adaptées aux zones affectées par des glissements.En plus des six études de cas, les résultats incluent une méthodologie basée sur des indicateurs pour évaluer et mesurer la vulnérabilité et la résilience, une méthodologie sur le risque composé, une typologie de stratégies d'adaptation et perceptions des risques ainsi qu'une analyse fondamentale de la relation entre risque, vulnérabilité et résilience. Les méthodologies pour l'évaluation de la vulnérabilité, de la résilience et du risque sont relativement peu coûteuses et reproductibles dans des endroits avec peu de données disponibles. Le résultat probablement le plus pertinent est que la résilience est un processus qui définit la capacité d'une communauté (ou d'un système) à rebondir suite à une situation défavorable, mais qui ne réduit pas forcement la vulnérabilité ou le risque, et qui requiert une approche plus fondamentale s'adressant aux questions de pauvreté. Les conclusions incluent une vue critique de la résilience comme but principal des politiques internationales de développement et de réduction des risques. C'est un concept utile dans le contexte de la récupération après une catastrophe mais il doit être pris en compte au même titre que la vulnérabilité et le risque.Cette recherche a été financée par un fonds interdisciplinaire (#26083591) du Fonds National Suisse pour la période 2009-2011 et un fonds de préparation de recherches par la Faculté des Géosciences et Environnement à l'Université de Lausanne en 2008.