A Modified Multiport Two-Layer Network Equivalent for the Analysis of Electromagnetic Transients
Bibliographic record
Abstract
This paper presents a modified two-layer network equivalent (M-TLNE) that provides a simpler surface layer compared to the original two-layer network equivalent (TLNE) without scarifying accuracy. The M-TLNE further reduces computational time which is of significance for statistical analysis and real-time simulation of electromagnetic transients. The MTLNE is simple, inherently stable, and is adequately accurate for practical applications. This paper also presents a generalized methodology for developing the proposed M-TLNE, based on a low-order vector fitting and a nonlinear least square minimization. The developed methodology is applicable to single and multiport network equivalents for both single and multiphase systems. Applications of the M-TLNE to single and multiport systems are also presented in this paper and the accuracy of the proposed M-TLNE is verified based on comparing the results with those obtained from detailed simulations of the system in the PSCAD/EMTDC simulation environment. A comparison of the M-TLNE with the original TLNE and the frequency-dependant network equivalent is also presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".