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Record W190618549 · doi:10.7907/zbg7-z526

Impulse of a Single-Pulse Detonation Tube

2002· article· en· W190618549 on OpenAlexaboutno aff
E. Wintenberger, Joanna M. Austin, Marcia A. Cooper, Scott I. Jackson, J. E. Shepherd

Bibliographic record

VenueCaltechAUTHORS (California Institute of Technology) · 2002
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsImpulse (physics)DetonationComputer sciencePropulsionAeronauticsExplosive materialAerospace engineeringEngineeringPhysicsHistory

Abstract

fetched live from OpenAlex

This report describes experimental and numerical investigations on pulse detonation tubes carried out in the Explosion Dynamics Laboratory at Caltech during 1999-2002. The goal of this work was to develop a database on impulse measurements using direct ballistic measurement of impulse; and to develop a model based on simple gas dynamic principles that could be used to predict impulse for a wide range of fuels and initial conditions. At the time we started this work, there was a great deal of conflicting information regarding the values of impulse that could be obtained. Our goal was to clarify this situation and to develop a better understanding of the factors that controlled impulse generation in a pulse detonation tube - the simplest version of a pulse detonation engine. Since we began this project, many groups from throughout the world have made impulse models, carried out new numerical studies, and made direct experimental measurements of impulse. The work of these researchers has been invaluable to us as we refined and tested our ideas against their data and ours. We would like to acknowledge discussions with Fred Schauer (AFRL, USA), Chris Brophy (NPS,USA), K. Kailasanath (NRL, USA), R. Santoro (PSU, USA), Andrew Higgins (McGill University), Paul Harris (DREV, Canada), and E. Daniau (ENSMA - France). In particular, we thank Fred Schauer for generously sharing his data with us. We initially began preparing this report in 2000 and it went through a number of revisions with portions being presented at the Joint Propulsion Conference in the summer of 2001. Subsequently, the material underwent further revision and additions in preparation for journal publication and the orginal report was significantly out of date. We have chosen to replace the original text with preprints of our journal articles and retained the appendices to the original report. The material in Parts II and III consist of preprints of revised versions (accepted for publications) of two papers submitted to the Journal of Propulsion and Power in the winter of 2001-2002. The Appendices contain additional details about the modeling, details on the experimental setup, tabulated data from the experiments, and tabulated results of model computations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.018
GPT teacher head0.215
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2002
Admission routes1
Has abstractyes

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