Bibliographic record
Abstract
The operation of static power converters used in active filters can be simulated by means of widely available circuit simulation software packages such as PSpice. In these studies, converters are usually modeled as a set of real or idealized switches, which may result in long execution times and possible convergence problems, particularly in complex circuits. This paper proposes the use of macromodels to simulate active filters. The macromodels are based on converter switching functions rather than actual circuit components, and they are well suited for steady state and large signal transient analysis at the system level. In this approach, the converters are simulated as multiport networks avoiding the physical nonlinear micromodels associated with power switches. Computer memory and execution times required for the simulation of the power circuit are thereby significantly reduced. The procedure also allows rapid design of filter components, in particular passive elements such as inductors and capacitors. Complete examples of typical shunt filters are given to illustrate the effectiveness of the proposed models.
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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 | 0.000 | 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) | 0.002 | 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 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".