Experimental Study on the Deflagration to Detonation Transition of Hydrogen Mixture under Elevated Pressure and Temperature Conditions
Bibliographic record
Abstract
Article Experimental Study on the Deflagration to Detonation Transition of Hydrogen Mixture under Elevated Pressure and Temperature Conditions Xiao Yu, Long Jin, Linyan Wang, Navjot Sandhu, and Ming Zheng * Department of Mechanical, Automotive and Materials Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON N9B 3P4, Canada * Correspondence: mzheng@uwindsor.ca Received: 26 March 2025; Revised: 7 April 2025; Accepted: 14 April 2025; Published: 24 April 2025 Abstract: In this paper, the deflagration to detonation transition (DDT) process of a hydrogen-air mixture is investigated using a small tube with an inner diameter of 11.1 mm. A rapid compression machine (RCM) is utilized to compress the mixture, attaining high pressure and temperature to resemble engine applications. Both piezoelectric pressure transducers and ion sensors are used to detect the flame front, calculating the flame propagation speed. The background absolute pressure before DDT is adjusted from 20 kPa to 810 kPa via a combination of charging pressure and RCM compression, while the background temperature is adjusted from 296 K to 460 K with spark timing adjustment after the compression process of RCM. It is observed that background pressure is an important parameter that decides the existence of a successful DDT process, while background temperature offers a limited contribution to accelerating the flame speed within 1 m tube length.
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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) | 0.000 | 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".