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Record W4322100295 · doi:10.1061/jsendh.steng-11397

Fragility and Economic Evaluations of High-Strength Reinforced Concrete Shear Walls in Nuclear Power Plants

2023· article· en· W4322100295 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Structural Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSquatStructural engineeringFragilityReinforcementShear wallMaterials scienceCompressive strengthFlexural strengthGeotechnical engineeringStiffnessConsolidation (business)RebarComposite materialGeologyEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.217
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it