Fragility and Economic Evaluations of High-Strength Reinforced Concrete Shear Walls in Nuclear Power Plants
Notice bibliographique
Résumé
Recent research studies have investigated the use of high-strength materials in nuclear power plant structures to enhance the constructability of their massive squat RC shear walls. For example, high-strength reinforcement bars can significantly reduce the required steel areas, thus minimizing material/fabrication costs, reducing rebar congestion, facilitating concrete consolidation/placement, and simplifying quality control checks. High-strength concrete can also limit cracks and deflections because of its enhanced mechanical properties, including the elastic modulus and compression/tension strength. Despite the advantages of high-strength materials, the dynamic response of their squat nuclear shear walls has not yet been fully investigated when different design parameters are adopted. To address this, the current study focuses on developing fragility functions for squat RC shear walls with high-strength materials to evaluate their seismic response compared with their counterparts with normal-strength materials; the economic benefits of both material walls were also assessed. In this respect, a numerical model was developed and then validated using previous experimental programs that have been conducted on RC shear walls with different aspect ratios, vertical/horizontal web reinforcement ratios, yield/ultimate strengths of reinforcement, concrete compressive strengths, and axial load levels. Following the model development and validation, incremental dynamic analyses using 44 far-field ground motion records were performed to develop fragility functions for nine squat RC shear walls with normal- and high-strength materials at different damage states. These damage states were characterized by several performance indicators following relevant guidelines. The current study identified wall damage states based on (1) yielding of reinforcement bars, concrete crushing, shear failure, and reinforcement buckling/fracturing; and (2) crack widths (i.e., 0.5, 1.5, and 3 mm) calculated using the modified compression field theory. Several wall design parameters, including material strength, reinforcement spacing and axial load level, were investigated to quantify their influence on the seismic fragility of such squat RC walls. Finally, the economic benefits of using high-strength materials in nuclear power plants were evaluated by presenting direct comparisons between the walls in terms of their total rebar weights and the corresponding total construction costs. The results showed that the use of high-strength concrete and high-strength reinforcement with large spacing between the rebars can lead to early cracking of their walls, thus having a higher probability of exceedance values to damage relative to walls designed with normal-strength materials. The results demonstrate also that enhancements in seismic fragility coupled with low total construction costs can be attained by walls with normal-strength concrete and high-strength reinforcement. The current study facilitates the adoption of RC shear walls with high-strength materials in nuclear construction practice.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».