Bibliographic record
Abstract
Sensitivity and parametric analyses are powerful tools in assisting engineers to improve design, control and operation of mechanical systems. Sensitivity derivatives help designers to understand the behaviour of the system at hand and modify the design to achieve more satisfactory results. Moreover, these derivatives are beneficial in optimum design, optimal control algorithms, and parameter identification methods. In addition to all these applications, sensitivity derivatives can be used to develop methods for parametric analysis of multibody systems; the formulation of such a method is also described in this thesis. The thesis includes several sections: first, the sensitivity analysis of multibody systems is categorized into two groups: the inverse- and the forward-dynamics based problems. Next, an overview of the literature on different mathematical methods for calculation of the sensitivity derivatives is presented. Then, the dynamics parametric analysis problem is formulated. A parametric analysis method is presented, which relies on the interpretation of a linear space based on sensitivity derivatives. Further to the analysis mentioned above, a parametric analysis toolbox is created in the Simulink environment which complements the Multibody Toolbox (MuT) developed by the Canadian Space Agency. To illustrate the material,two problems are considered to apply the proposed sensitivity and parametric analyses approach on them. First, parametric analysis of contact/impact dynamics for a five-bar linkage is performed. The performance indicator is the pre-impact constrained motion space kinetic energy for contact/impact problems. The performance indicators of these contact/impact systems are related to characterizing the intensity of the contact transition during a change in topology. Second, a combined physical-virtual system is considered and effect of the variation of the inertial parameters of the virtual model on the joint torque variations of such a system is investigated. Simulation and experiments are performed using a setup that contains a physical device and a virtual dynamic system. Experimental results are compared to the simulation results.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".