Experimentally Verified Retrofit Combining Hybrid Solutions for Enhancing the Seismic Response of Multistory RC Structures
Bibliographic record
Abstract
ABSTRACT This experimental and numerical study proposes hybrid retrofit alternatives involving multiple contemporary techniques to upgrade the fundamental seismic response characteristics of multistory reinforced concrete frame (MSRCF) structures. The impact of thin high‐performance reinforced concrete (HPRC) jackets on the concrete framing system's seismic response is first investigated through shake table testing (STT). The performance of the HPRC‐retrofitted frame is then compared with another STT campaign conducted for fabric‐reinforced cementitious matrix (FRCM)–retrofitted frame. The STT results indicated that at the same input ground motion intensity that caused failure for the FRCM‐retrofitted frame, the curvature ductility and interstory drift ratio of the HPRC‐retrofitted specimen were reduced by 79% and 87%, respectively. Upon verifying the fiber‐based modeling technique of HPRC and FRCM alternatives through STT, the study probabilistically assesses the seismic performance of a benchmark MSRCF building considering different hybrid retrofit alternatives by combining each technique with a self‐centering energy dissipation (SCED) bracing system. Following a systematic seismic assessment framework, it is concluded that the performance‐cost index of the less disruptive HPRC‐SCED option exceeded that of the FRCM‐SCED by 36%, confirming its preference among the considered alternatives for upgrading the seismic response of MSRCF deficient in stiffness, strength, and ductility.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".