Évaluation des risques

Dans le domaine de la gestion des risques, l'évaluation des risques est l'ensemble des méthodes consistant à calculer la criticité (pertinence et gravité) des dangers. Elle vise outre à les quantifier, à qualifier les dangers (qui doivent donc préalablement avoir été identifiés). Elle se base sur . Dans ce domaine, on se restreint à l'étude du risque aryétique, c'est-à-dire en ne considérant que les événements à conséquences négatives. Dans la mesure du possible on s'attache à obtenir des indices de risque (ou quotient de risque) traduits en valeurs chiffrées, pour classer en les hiérarchisant les risques afin de pouvoir prioriser les mesures à prendre pour réduire les risques et/ou atténuer leurs conséquences ou rendre le risque acceptable. On parle d'évaluation chiffrée du risque, ou en anglais quantitative risk assessment (QRA). Cette analyse, historiquement utilisée dans l'industrie nucléaire et aéronautique, est devenue indispensable dans le monde pétrolier à la suite de la ca

Quantum-based approach for laboratory risk assessment and decision-making

Ruoxing Liao

With the rising focus on academic safety, there has been an effort to improve the academic safety climate and develop lab-specific risk assessment tools. Despite the progress made in recent years, there is still a deficit of reliable data statistics on safety events and risk assessment in academia, making it difficult to perform full-scale analysis. Moreover, the rapid turnover of personnel and the highly dynamic research tasks in a laboratory environment impede the implementation of classical and well-established risk management strategies, which are usually time-consuming and resource-intensive. Laboratory safety management is always challenging due to lack of data and effective methods. The end of safety management is usually the selection of risk mitigation measures. In the laboratory risk management process, decisions are often made through discussion and compromise. In this regard, it would be beneficial to provide a tool that can support in resource allocation and prioritization of actions. The goal of this project is to develop a decision support tool to assist in the selection of optimal and appropriate preventive or corrective measures in the lab safety management process. The use of decision tools such as Multi-Criteria Decision Making (MCDM) can effectively abstract complex laboratory management problems into a decision framework. This study focuses on the ranking process of competitive corrective measures. Combining the results of interviews and questionnaires, five evaluation criteria were proposed for the normative process of multi-criteria decision making. They are: Residual Risk, Risk reduction, Personnel reliability, Technical reliability, and Cost. classical methods TOPSIS and WSM have been evaluated during the study, and emerging quantum decision making methods have been explored. All three methods are used to simulate the laboratory safety decision making process, and they all present good consistency. Different weighting methods have also been applied to the model and two case studies have been conducted. The first case study is designed to construct the model and verify its feasibility, and the second model is used to investigate the process of group decision making. By applying different MCDM methods, the obtained results are discussed and compared to verify the stability and accuracy of the model. The approach proposed in this research is a promising tool. It offers the possibility to be compatible with different MCDM methods and risk assessment methods, and the proposed decision model could be used as a decision support system to help lab managers make better decisions, or it can provide a neutral point of view as an aid. Future work may include fine-tuning the model. In the following stage, decision criteria should be precisely defined, and corresponding quantitative formulas should be proposed to serve the flexible and dynamic laboratory environment.

2022

Risk assessment of pedestrian crossings: a stochastic video-based analysis

Adrien Nicolet

Although pedestrian crossings are supposed to guarantee safety, accidents are still frequent. Prior to implementing any measures to address this issue, the safety of the pedestrian crossing must be assessed. Various indices estimating the safety of pedestrian crossings have been developed. They quantify spatio-temporal distance, potential collision severity or kinetic energy on impact. Computing these indices requires accurate and reliable trajectory data which can be extracted from videos thanks to computer vision algorithms. Like any measurement technology, this process produces imperfections and uncertainty in its output. These errors and uncertainties are scarcely considered in the current index definitions. This project aims to integrate these different measurement uncertainties into the calculation of such indices. Instead of computing a single deterministic value for each index, we propose a methodology providing the index probability distribution under various uncertainties. Further- more, we investigate the influence of each uncertainty on the index distribution. The feasibility and reliability of this method are verified by applying it to an empirical data set. The methodology is validated by comparing the results to state-of-the-art conflict analysis. We observe that the outcome of the indices is strongly conditioned by the quality of the data, in particular the smoothness of the trajectories.

2020

Quantum-based approach for laboratory risk assessment and decision-making

Ruoxing Liao

2022

GIS-based hazard and risk assessment of transportation infrastructure

Quantum-based approach for laboratory risk assessment and decision-making

Risk assessment of pedestrian crossings: a stochastic video-based analysis

Risk assessment of pedestrian crossings: a stochastic video-based analysis

GIS-based hazard and risk assessment of transportation infrastructure

Quantum-based approach for laboratory risk assessment and decision-making