A SYSTEMS RELIABILITY APPROACH TO MODELING OPERATIONAL RISKS IN COMPLEX ENGINEERED SYSTEMS
Notice bibliographique
Résumé
Since the beginning of the industrial revolution in the late 18th century, the cause of many serious accidents in hydrosystems engineering has shifted from natural causes to human and technology related causes as these systems get more complex. While natural disasters still account for a significant amount of human and material losses, man-made disasters are responsible for an increasingly large portion of the toll, especially in the safety critical domain such as Dam and Levee systems. The reliable performance of hydraulic flow-control systems such as dams, reservoirs, levees etc. depends on the time-varying demands placed upon it by hydrology, operating rules, the interactions among subsystem components, the vagaries of operator interventions and natural disturbances. In the past, engineers have concerned themselves with understanding how the component parts of dam systems operate individually and not how the components interact with one another. Contemporary engineering practices do not address many common causes of accidents and failures, which are unforeseen combinations of usual conditions. In recent decades, the most likely causes of failures associated with dams have more often had to do with sensor and control systems, human agency, and inadequate maintenance than with extreme loads such as floods and earthquakes. This thesis presents a new approach, which combines simulation, engineering reliability modeling, and systems engineering. The new approach seeks to explore the possibilities inherent in taking a systems perspective to modeling the reliability of flow-control functions in hydrosystems engineering. Thus, taking into account the interconnections and dependencies between different components of the system, changes over time in their state as well as the influence upon the system of organizational limitations, human errors and external disturbances. The proposed framework attempts to consider all the physical and functional interrelationships between the parts of the dam and reservoir, and to combine the analysis of the parts in their functional and spatial interrelationships in a unified structure. The method attempts to bring together the systems aspects of engineering and operational concerns in a way that emphasizes their interactions. The argument made in this thesis is that systems reliability approach to analyzing operational risks—precisely because it treats systems interactions—cannot be based on the decomposition, linear methods of contemporary practice. These methods cannot logically capture the interactions and feedback of complex systems. The proposed systems approach relies on understanding and accurately characterizing the complex interrelationships among different elements within an engineered system. The modeling framework allows for analysis of how structural changes in one part of a system might affect the behavior of the system as a whole, or how the system responds to emergent geophysical processes. The implementation of the proposed approach is presented in the context of two case studies of US and Canadian water projects: Wolf Creek Dam in Kentucky and the Lower Mattagami River Project in Northern Ontario.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».