Seismic Performance Quantification of Reinforced Concrete Shear Walls with Different End Configurations: Experimental Assessment and Data-driven Performance Models
Bibliographic record
Abstract
Well-detailed reinforced concrete (RC) shear walls did not achieve the expected seismic performance in the 2011 Christchurch earthquake as per the Canterbury earthquake royal commission report. Similarly, RC shear walls showed low seismic performance in the 2010 Maule earthquake. The two major seismic events intrigued this research dissertation, where six half-scaled RC shear walls were constructed and tested. The six walls were split into two phases, each phase had different end configurations (i.e., rectangular, flanged, and boundary elements). Phase II RC walls had 2.4 times the vertical reinforcement ratio of Phase I walls. The walls were detailed as per CSA A23.3-19, and they were tested laterally under a quasi-static cyclic fully-reversed loading while maintaining a constant axial load through the full test of the walls. The overall seismic performance of the six walls is evaluated in Chapters 2 and 3 in terms of their load-displacement relationships, crack patterns, displacement ductility capacities, stiffness degradation trends, curvature profiles, end strains, energy dissipation capabilities, and equivalent viscous damping ratios. In addition, damage states are specified according to the Federal Emergency Management Assessment (FEMA P58) guidelines. The results came in agreement with the Canterbury earthquake royal commission report, where the test walls with low vertical reinforcement ratios showed lower-than-expected seismic performance due to the concentration of their plastic hinges at the primary crack locations. Moreover, the results validated the Christchurch (2011) and Maule (2010) earthquake findings as concentrating the rebars at the end zones and providing adequate confinement enhanced the seismic performance of the test walls, which was the case for Phase II flanged and boundary element walls. The displacement ductility variations of the test walls inspired the work of Chapter 4, where the objective is to develop a data-driven expression for RC shear walls to better quantify their displacement ductility capacities. In this respect, an analytical model is developed and experimentally validated using several RC walls. The analytical model is then used to generate a dataset of RC walls with a wide range of geometrical configurations and design parameters, including cross-sectional properties, aspect ratios, axial loads, vertical reinforcement ratio, and concrete compressive strengths. This dataset is utilized to develop two data-driven prediction expressions for the displacement ductility of RC walls with rectangular and flanged/boundary element end configurations. The developed data-driven expressions accurately predicted the displacement ductility of such walls and they should be adopted by relevant building codes and design standards, instead of assigning a single ductility-related modification factor for all ductile RC shear walls, as per the 2020 National Building Code of Canada. Several researchers tested well-detailed Reinforced Masonry (RM) shear walls and the results concluded that RM shear walls showed high seismic performance similar to that of RC shear walls. This intrigued the research efforts presented in Chapter 5, where a comparative analysis is performed between the six RC walls tested in this dissertation and three RM walls tested in a previous experimental program. The analysis focuses on comparing the seismic performance of both wall systems in terms of their crack patterns, load-displacement envelopes, curvature profiles, displacement ductility, normalized periods, and equivalent viscous damping ratios. In addition, an economic assessment is performed to compare such RC and RM shear walls using their total rebar weights and the total construction costs. Overall, RM shear walls achieved an acceptable seismic performance coupled with low rebar weights and low construction costs when compared to their RC counterparts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".