Cyclic Performance of a Piston Based Self-Centering Bracing System
Bibliographic record
Abstract
The major difficulties faced with traditional structural bracing systems against seismic loading include compression buckling and permanent residual deformation under seismic loading. Once buckling occurs, the strength and stiffness of a brace gets significantly reduced and the stiffness degrades rapidly in subsequent load cycles. A significant number of researches have been conducted in resolving this issue and various ideas have been proposed and developed for the industry, e.g. buckling restrained brace, cast steel yielding fuse, SCED, MANSIDE, and RHDB braces, etc. Unfortunately, most of these solutions are expensive and complicated to construct. Authors here have proposed a novel approach in addressing this issue using a modification of a device commonly seen in mechanical systems, which is a cylinder-piston assembly. In this system, stiffness and re-centering are contributed by shape memory alloy ties. This study investigates the behavior of this innovative Piston Based Self-Centering (PBSC) bracing system in finite element environment. Utilizing this assembly, a brace member is able to carry large magnitude of tensile and compression loading without buckling. Furthermore, this brace is able to re-center after large nonlinear deformation. This paper presents the results of the analytical investigation carried out in ABAQUS software using finite element method. The load deformation hysteresis was determined and a flag shaped hysteresis was achieved, which indicates good re-centering capability of the proposed system.
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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".