Comparative Assessment of Fiber-Reinforced Polymer (FRP), Engineered Cementitious Composites (ECC), and Steel Frames for Retrofitting Masonry Walls Against In-Plane Seismic Actions
Bibliographic record
Abstract
The Masonry structures, despite their extensive historical utilization, frequently exhibit inherent brittleness, rendering them susceptible to cracking and structural failure when subjected to diverse loading conditions. In an effort to enhance understanding of masonry performance and provide significant contributions to the design and retrofitting of these structures, this research investigates the structural response of masonry walls under cyclic, concentrated transverse point loading, and monotonic loading conditions Finite Element Analysis (FEA). To mitigate in-plane cracks, three strengthening techniques Fiber Reinforced Polymer (FRP) sheets, Engineered Cementitious Composites (ECC), and steel frames were implemented, and their effectiveness was compared. The results indicated that FRP sheets provided superior crack control compared to the other two methods. Furthermore, a parametric study was conducted to evaluate different FRP sheet configurations under cyclic loading, assessing their impact on force-displacement behaviour, crack morphology, and peak load capacity. Among the tested configurations, the Case-1 (Diagonal configuration) FRP layout significantly enhanced seismic resistance by minimizing sliding failure and distributing stresses more efficiently, achieving an about 62% increase in peak force compared to the control model. The results also highlight that Case 1 possesses superior energy dissipation capacity, ductility, and stiffness retention and hence is the most effective strengthening technique for enhancing the seismic resilience of masonry walls. The findings of this study expected to play crucial role for optimizing masonry retrofitting strategies, contributing to the development of resilient and structurally efficient masonry walls for seismic-prone regions.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".