Time-Stepped Finite-Element Modeling of Three-Phase Transformer for Electromagnetic Transient Emulation on FPGA
Bibliographic record
Abstract
The finite-element analysis is a powerful method to obtain detailed insight into the operation of any electromagnetic equipment. However, the required computational power to solve a finite-element modeled power equipment is so heavy that most Newton-Raphson-method-based algorithms can barely achieve real-time simulation. The low latency and hardware parallelism of the field programmable gate array (FPGA) provides a path forward. In this paper, a parallel and deeply pipelined adaptive transmission-line modeling method with preconditioned conjugate gradient solver is designed in hardware and implemented on two Xilinx R XCVU37P FPGAs for the finite-element modeling of a three-phase transformer. The accuracy of the transformer solver under both current excited and voltage-excited conditions of the transformer was validated against the commercial FE simulation tool.
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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 | 0.001 |
| 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) | 0.001 | 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".