Boundary Element Method Analysis of Multi-Conductor Systems Made of Thin Conductors in 2-D
Bibliographic record
Abstract
In this paper, the Boundary Element Method is used to build 2-D magnetic-harmonic models for multi-conductor systems made of thin conductors. The presented BEM models are much more computationally efficient than the equivalent Finite Element Method models. The proposed models allows the computations of the field quantities and of the circuit parameters of the multi-conductor system. Two approaches are presented, i) the shell approach, for cases where the current density varies across the thickness of the conductor, and ii) the strip approach, for cases where the current density is uniform across the thickness of the conductor. It is demonstrated that the strip approach leads to a significant simplification of the calculations. Voltages and currents are included directly in the system variables and outputs, respectively, avoiding the need for additional post-processing steps. The efficiency of the proposed models is important in cases including a large number of conductors, especially if frequency sweeps are required.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".