MétaCan
Menu
Back to cohort
Record W2072818950 · doi:10.1115/imece2014-37385

Investigation and Improvement of Thermal Efficiency of Hypersonic Scramjet

2014· article· en· W2072818950 on OpenAlexaff
Mohammad A. Hossain, Md. Taibur Rahman, Mohammad Ikthair Hossain Soiket, Sarzina Hossain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsScramjetCombustorHypersonic speedThermal efficiencySpecific impulsePropulsionRamjetOverall pressure ratioAerospace engineeringExergy efficiencyThermalMaterials scienceRocket engineExergyCombustionWork (physics)Total air temperatureMechanical engineeringMechanicsEngineeringThermodynamicsProcess engineeringPhysicsGas compressorChemistry

Abstract

fetched live from OpenAlex

This work is focused on investigation of thermal efficiency of a Hypersonic scramjet engine and propose some improvement of thermal efficiency based on thermodynamic and fluid flow analysis. Thermal management system is one of the main research fields in scramjet design. As it has no moving parts, the total thermal efficiency depends on inlet conditions, conditions of combustor exit and conditions of the engine exit. A combustor exit condition dictates the velocity and temperature after combustion. we concentrate our focus on this section. The first part of the paper, we tried to describe the fundamental exergy relationship for scramjet and we developed the relation of exergy distribution and exergy delivery rate. From an extensive literature review, we have found the relations between fluid velocity, pressure and temperature, which is described in the later part of the paper. Our main focus is to develop a combined relation of thermal efficiency in terms of engine exit velocity, temperature and air-fuel ratio. Different characteristic parameters such as overall efficiency, thermal efficiency, specific impulse have been determined at different inlet temperature ratio or the cycle static temperature ratio (T3/T0) and an optimum inlet temperature ratio is proposed for maximum overall efficiency.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.139

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations5
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicComputational Fluid Dynamics and AerodynamicsFrench-language works237,207