Dynamic analysis of structures with uncertain properties.
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Bibliographic record
Abstract
The properties of engineering structures are variable by nature. This variation affects considerably the dynamic response of structures and this is overlooked in traditional deterministic analysis. The incorporation of statistical variability of structural properties in analysis has been a topic of considerable research for the last thirty years. The determination of statistical measures of a desired response variable, such as the natural frequencies, maximum displacement, or stresses has been a primary goal of this study. The objective of this research work is to determine the quantitative effect of uncertainties on the dynamic response of a structure with uncertain parameters through different methods. Three different approaches are used in this work: (i) the perturbation method, which addresses the problem analytically by assuming small variation in the structural properties; (ii) the Monte Carlo simulation, which treats the problem numerically and predicts accurate stochastic response; (iii) the mixed method, which is a compromise between the Monte Carlo simulation and the perturbation method. These three types of methods are implemented within a deterministic finite element code (CALFEM) to solve a stochastic eigenvalue problem associated to structural dynamics. In addition, the mixed method is applied to the dynamic analysis of a multistory building with uncertain stiffness subjected to an earthquake excitation. The response statistics obtained from this method are compared with the Monte Carlo simulation results. From this investigation, it is found that there may be a significant variation in the response variables for the associated uncertainties with the structural properties. The main concern of this study is to explore the various techniques for the treatment of uncertainties of dynamic systems such as material and geometric variation.Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .B35. Source: Masters Abstracts International, Volume: 42-02, page: 0634. Advisers: Faouzi Ghrib, Murty K. S. Madugula. Thesis (M.A.Sc.)--University of Windsor (Canada), 2003.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it