Identification of multiple joint dynamics using the inverse receptance coupling method
Bibliographic record
Abstract
A lot of effort has been put into accurately modelling virtual prototypes prior to physical building of structures, in order to minimize cost and time while improving performance. However, there are often significant discrepancies between the dynamics of virtual prototypes and actual physical structures, which are mainly caused by improper joint dynamics modelling and assumptions. To overcome these challenges, we propose a method for the identification of multiple joints in structures using the inverse receptance coupling method. This method enables the determination of the joint properties by finding the differences between the measured receptances of the assembled structures and the simulated receptances obtained from rigidly coupled substructures. The receptances are obtained either through the finite element model or experimental modal measurements. The only measurements required in the proposed identification method are measurements on the translational degrees of freedom of the substructures and assembled structure. Knowing the joint’s dynamic properties allows for the prediction of behavior of a new assembled structure that uses the same joint configuration, without the necessity of direct measurements on the structure.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".