Modeling the photodegradation of large mode area Yb-doped fiber power amplifiers
Bibliographic record
Abstract
Photodarkening is presently a major concern for the long term reliability and efficiency of high power Yb-doped fiber lasers and amplifiers. This phenomenon has been associated with the formation of color centers in the fiber core of single-clad and large mode area Yb-doped fibers. However, its origin is still not well understood and to date no comprehensive model that could predict the lifetime of Yb-doped fiber-based devices has been put forward. A semi-empirical approach seems at the moment the best way to gain a better understanding of the growth behavior of photo-induced losses in Yb-doped fibers in the presence of both photodarkening and photobleaching processes. A rate equation describing the activation and deactivation of color centers involving stretched exponential functions has been developed. For this approach to be effective and reliable, a minimum of parameters is used, four to describe photodarkening and three for photobleaching. A large mode area Yb-doped fiber fabricated at INO using the MCVD process has been characterized. By properly choosing the initial pumping conditions, each parameter of the stretched exponential functions has been measured separately from the others. The model has then been used to simulate the power decay from a 1 kW, 10 ns-pulse, 100 kHz Yd-doped LMA fiber power amplifier. We show that the photodarkening behavior predicted by the model is in good agreement with the experimental results over more than 6000 hours. Such a model is general in its application but the stretched exponential parameters are unique to the type of fiber tested. The model will be a useful characterization tool for developing photodarkening-resistant fibers and for evaluating the lifetime of Yb-doped fiber-based devices affected by photodegradation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".