IGBT based HV pulse generator for high conductivity liquid food treatment
Bibliographic record
Abstract
Several investigations show that there is an effective process to break a microorganism's membrane using the pulsed electric field (PEF) in order to pasteurize liquid foods. Such pulsed electric fields are produced by high voltage, high peak current and fast rise-time pulses applied to a chamber with liquid passing through it. Due to the nature of the short pulses the processes is nonthermal; hence, it helps to save the nutritional values of the treated food as well as its taste. Thus PEF treatment is considered as a good alternative to the conventional pasteurization treatments that are thermal processes. The aim of this work is to study the effect of design parameters such as switch type, gate drive circuit, and circuit configuration on the output voltage rise and fall times using a newly developed solid state pulsed generator. The paper presents the results obtained from treating liquid samples whose electrical conductivities fall in the range of a variety of liquid foods, using a variable 0-6 kV, with 3μs flat-top pulses; and rise-time of 70-1000 ns. The peak current rating of the pulse generator 1500A, can sustain the heavy loading due to the high conductivities of the treated samples.
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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 | 0.000 |
| 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 | 0.001 |
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".