Seismic Analysis and Design for Enhanced Performance of Nonstructural Components in Steel Buildings
Bibliographic record
Abstract
Large economic losses and downtime due to nonstructural damage in recent earthquakes have highlighted the need for improving the seismic performance of nonstructural components (NSCs). Recognizing this, many studies have focused on evaluating the seismic demands of NSCs supported on structures of various types. However, previous studies considered the supporting structure as a single-degree-of-freedom (SDOF) system or as a simplified multi-DOF frame. More advanced nonlinear modeling techniques able to capture damage-induced deterioration must be considered to arrive at more realistic estimates of the response of various structural system types. In addition, demand estimation methods must be complemented with appropriate design procedures that enable the reduction of seismic losses associated with NSCs. The first main objective of this thesis is to better quantify the seismic demands imposed on acceleration-sensitive components mounted in steel buildings with common lateral force resisting systems, including Special Concentrically Braced Frame (SCBF) and Special Moment Frame (SMF) structures. The second main objective focuses on developing a simplified performance-based design procedure centered on NSC losses. To achieve the first objective, eleven archetypes with varying heights and vibration properties are numerically modeled using state-of-the-art validated methods. Then, the absolute floor acceleration responses are used to generate floor acceleration spectra for various NSC damping and ductility levels. The thesis presents qualitative and quantitative aspects of the NSC demands, as well as practical formulas for relevant design parameters, including the ratio of peak floor acceleration (PFA) to peak ground acceleration (PGA), and the ratio of peak component acceleration (PCA) to PFA. The thesis proceeds with using FEMA P-58 procedures to develop a simplified NSC-loss-based design approach for SCBF structures. This approach is based on NSC loss spectra that allow in-advance selection of the design base shear coefficient so that acceptable exceedance probabilities can be met for multiple loss levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.002 | 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 teacher head, 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".