Seismic design of friction damped braced steel plane frames by energy methods
Bibliographic record
Abstract
The investigation described in this thesis represents the first known attempt to develop a simplified method for the seismic design of structures equipped with a novel friction damping system. The system has been shown experimentally to perform very well and is an exciting development in earthquake resistant design. The design of a building equipped with the friction damping system is achieved by determining the optimum slip load distribution to minimize structural response. A new efficient numerical modelling approach for the analysis and design of Friction Damped Braced Frames (FDBF) is presented. The hysteretic properties of the friction devices are derived theoretically and included in a Friction Damped Braced Frame Analysis Program (FDBFAP), which is adaptable to a microcomputer environment. The optimum slip load distribution is determined by minimizing a Relative Performance Index (RPI) derived from energy concepts. The steady-state response of a single storey friction damped structure subjected to sinusoidal ground motion is investigated analytically. Basic design information on the optimum slip load for the friction device is obtained. The parameters governing the optimum slip load, which minimizes the amplitude for any forcing frequency, are derived. The study indicates that the optimum slip load depends on the characteristics of the ground motion and of the structure. Using variational principles on a shear beam analogy, an optimum slip load distribution along the height of the structure is derived when the total amount of slip load is specified. It is shown that the optimum slip load is proportional to the slope of the deflected shape of the structure. The results of the study reveal that only a small improvement in the response is obtained by using this optimum distribution compared to the response obtained with a uniform distribution. Therefore the use of an optimum uniform distribution seems adequate for the design of friction damped structures. Taking into account the analytical results obtained, FDBFAP is then used in a parametric study which leads to the construction of a design slip load spectrum. The spectrum depends on the properties of the structure and ground motion anticipated at the construction site. It is believed that the availability of this design slip load spectrum will lead to a greater acceptance by the engineering profession of this new and innovative structural concept.
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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) | 0.001 | 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".