Numerical Analysis of Propagation of Nonlinear Waves in Prestressed Solids
Bibliographic record
Abstract
The details of numerical algorithms implemented in CAE FIDESYS for the analysis of the propagation of nonlinear waves in elastic and viscoelastic bodies are discussed. It’s taken into account that waves propagation lead to new strains which superimpose on existing stresses (induced anisotropy) in the media. For the formulation of problem we used the theory of repeated superposition of large strains. The details of numerical algorithms for the analysis of the propagation of nonlinear waves in elastic and viscoelastic bodies are discussed. The implementation of the spectral element method for the nonlinear dynamic problems of elasticity under finite strains is considered. Some details of parallel computing on multicore and multiprocessor systems for the problems of nonlinear dynamic elasticity are presented. The results of numerical experiments obtained in CAE Fidesys are shown, in particular: the analysis of propagation of nonlinear shock wave; the analysis of propagation of surface waves; the dynamic processes related with the origination of a hole in a weakly compressible nonlinear-viscoelastic material.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".