A Review of Reliability Analysis for Water Quality in Water Distribution Systems
Notice bibliographique
Résumé
A review of reliability research for water distribution systems demonstrates that, to date, little is currently available characterizing water quality reliability indices.The incidence of micro-organism-caused outbreaks of waterborne disease demonstrates a number of causes, most of which are the result of water treatment system deficiencies.However, the basis for a change in this situation is projected as a result of the increasing age of distribution system components, increasing urban populations, per capita water demands, and deterioration of water distribution infrastructure.Although there is no universal agreement on how to define, or measure, the reliability of a water distribution system, this Chapter reviews the alternatives for characterizing reliability, demonstrating some of the strengths and weaknesses, and provides areas of future research.conditions.This means that for a reliable water supply system, water must be (i) available on demand, (ii) delivered at a sufficient pressure for proper use, and (iii) safe in terms of quality.Although reliability of a water supply system in general is a measure of performance in terms of the three factors indicated, undesirable events/failure will occur which will cause a decline or interruption in system performance.The reliability of a water supply system can be considered under three types of failure: mechanical, hydraulic and water quality failure.Mechanical failures, also termed component failures, may, for example, be pipe breakage, pump failure, power outages, or control valve failure.Changes in demand or in pressure head may result in hydraulic failures.These failures may be due to, for example, old pipes with varying roughness, inadequacy in pipe size due to increased water demands, insufficient pumping capacity, and insufficient in-system storage capacity.Water quality failure may be defined as occurrences where the concentrations of contaminants exceed the maximum contaminant level (MCL) defined by water quality standards.The major concern for water quality failure is the adverse effect on the health of humans.Due to the importance of water supply systems for the needs of society and for industrial growth, reliability studies have become of increasing importance for water distribution systems where considerations of planning, design and operations are integrated.However, quantifying the reliability of a water supply system continues to be a major problem.For confident decision-making, a set of meaningful and appropriate reliability measures need to be defined, wherein all the measures must be computationally feasible.Reviews of the literature by Mays (1996) and Engelhardt et al. (2000) revealed that that there is no universal agreement on how to define, or measure, the reliability of a water distribution system.This Chapter reviews the alternatives for characterizing reliability, demonstrating some of the strengths and weaknesses, and provides areas of future research. Reliability IndexAlthough no single measure of reliability is universally accepted, alternatives have been suggested depending on the purpose of the reliability study.Published alternative measures include:1. Index of Potential to Meet Critical Events.If a system can satisfy demand under a defined set of contingencies, for example, the
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,003 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,003 |
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 ».