Providing Safety: Using Probabilistic or Deterministic Methods
Notice bibliographique
Résumé
The primary objective of a good engineering design or maintenance process is to provide safety with optimized resources. Most parameters and models used in engineering have uncertainty — some more so than others. Probabilistic assessments strive to account for these uncertainties explicitly while the deterministic methods account for uncertainties implicitly by using conservative inputs and safety factors. Deterministic methods are preferred by many due to their simplicity. However if inputs and safety factors are not defined prudently with explicit consideration for uncertainties and consequences they can lead to unsafe or unduly conservative solutions. The main objective in using reliability based methodologies is to provide consistent safety by explicitly accounting for uncertainties in a probabilistically quantified manner. Reliability methods also allow the articulation of the level of safety. This level of consistency in safety cannot be achieved in a deterministic analysis using safety factors because uncertainties are not accounted for explicitly and consequently the uncertainties lead to variable solutions. However safety factors can be calibrated using reliability methods so that more consistent safety levels can be assured when using deterministic methods. There is a relationship between the reliability level and the deterministic safety factors. This relationship between reliability levels and deterministic safety factors is examined both from a mathematical and practical perspective. Consequently it is shown that reliability based methods can be used to calibrate deterministic methods to improve the consistency of the safety level with due consideration to underlying uncertainties and consequences. This kind of calibration is used in other industries such as structural design and nuclear facilities. Providing more consistent safety enables optimization of maintenance activities which enables the safest system to be provided with available resources. Currently the pipeline industry uses deterministic methods with conservative inputs that are not based on risk or safety principles. Consequently there is a large variation in the inputs and safety factors used in the industry. Some examples of these are safety factors used in response to inline inspection that vary from the reciprocal of the design factor to 1.1 for all location classes. This paper shows that the maximum safety factor achievable for a given design is defined by the original design factor and the ratio between flow stress and yield strength. It also shows the inadequacy of using safety factors that are not risk based. The paper focuses on the importance of using a sound risk based rationale for appropriate safety factors in deterministic methods. A glossary of terms is provided at the end of the introduction.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,006 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
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 ».