A comparative study on the seismic performance of long span Engineered Cementitious Composite (ECC) structures
Bibliographic record
Abstract
The strain hardening fiber reinforced concrete—generally known as the Engineered Cementitious Composite (ECC)—has rapidly gained the attention of researchers in recent years. However, most of the research on ECC is limited to material and member level, leaving a gap in the understanding of its behavior at the structural scale. Therefore, this study investigates the global seismic response of ECC structures and compares their performance with conventional reinforced concrete (RC) structures. For this purpose, a case study long span building structure (an aircraft hangar having a span length of 40 meters) is selected. Under the design-level gravity and lateral loads, its members are separately designed using the conventional RC and ECC. It is observed that for ECC members, the requirement of longitudinal steel is reduced by 30% when compared with the conventional RC members. Similarly, owing to an improved tensile behavior, the ECC members also exhibited a higher shear capacity than RC members, resulting in a significant reduction in the requirement of transverse reinforcement. The detailed inelastic finite element models for both design cases (RC and ECC) were subjected to the pushover analysis and nonlinear response history analysis (NLRHA) to assess their seismic performance. It is observed that (in terms of local and global seismic demands, structural damage, and ductile behavior) the performance of the ECC structure is significantly improved when compared to the conventional RC structure. The comparative cost analysis showed a reduction of 11.9% in the overall material cost of the ECC structure as compared to RC. These results show that ECC can be effectively used at the full structural level as an economic solution to ensure the ductile response and superior seismic performance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".