Finite Element Modeling of Setar, a Stringed Musical Instrument
Bibliographic record
Abstract
This paper introduces a finite element model of Setar, a Persian long-necked lute. Setar is modeled as a transfer function between the imposed force on the bridge and the near-field resulted sound. Numerical modeling of stringed musical instruments is a computationally challenging task which has always been done with extreme simplifications. Phenomena such as fluid-structure interaction, composite structure, preload effect and infinite boundary are considered in this model. The cycle of Software used in here is CATIA, HyperMesh, Nastran, and HyperGraph. The frequency response between the force of string and generated sound in near field are obtained, taking into account the fluid inside and outside of the soundbox. This model is useful to predict the effect of modification in specific parts to the sound generated by the instrument. The numerical results have excellent agreement with the experimental ones. The modeling procedure can be extended to other musical instruments as well as less complicated problems such as passenger compartment of vehicles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".