Hybrid Simulation Testing of Normal and High-Strength RC Shear Walls in Nuclear Facilities under Ground Motion Sequences
Bibliographic record
Abstract
Reinforced concrete (RC) shear walls are widely used as a seismic force–resisting system in nuclear facilities. Such walls are designed to be relatively thick with a few openings for radiation shielding as well as for blast and fire protection. These geometrical requirements typically result in low-aspect-ratio walls with high reinforcement ratios that are provided by two or more mats, leading to complex construction activities and high construction costs. The use of high-strength reinforcement (HSR) has the potential to address such constructability and economic issues by reducing the required steel areas and rebar congestion. However, because relevant nuclear design standards restrict the use of HSR in their safety-related structures, most previous experimental studies to date focused on investigating the seismic performance of nuclear low-aspect-ratio RC shear walls when only normal-strength reinforcement (NSR) was used. To tackle this knowledge gap, the current study utilizes the pseudodynamic hybrid simulation testing technique to experimentally compare the performance of nuclear low-aspect-ratio RC shear walls with HSR and NSR when subjected to ground motion sequences. In this respect, two RC shear walls (i.e., W1-NSR and W2-HSR) with an aspect ratio of 0.83 were tested, where both walls were designed to have a similar lateral strength; however, Wall W2-HSR had a reduced reinforcement ratio of 1.23% compared with Wall W1-NSR, which had a reinforcement ratio of 2.20%. The two walls were subjected to several ground motion records to investigate their force-displacement responses, lateral strengths, ductility, stiffnesses, deformation capacities, cracking patterns, rebar strains, and failure modes. A numerical model was then developed and experimentally validated to simulate the response of the two test walls under such ground motion records. The results show that both walls achieved similar ultimate strength values; however, relevant nuclear design standards were not able to accurately estimate these values for Wall W2-HSR. In addition, although Wall W2-HSR had wider cracks relative to Wall W1-NSR during all ground motion sequences, the former wall achieved a high displacement ductility value without any premature brittle shear failure. The experimental results presented in the current study are expected to facilitate the adoption of HSR in low-aspect-ratio RC shear walls within nuclear construction practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".