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Record W2175413619 · doi:10.1115/gt2008-50948

Design Procedure of a Novel Micro-Turbine Low NOx Conical Wire-Mesh Duct Burner

2008· article· en· W2175413619 on OpenAlexaff
Omar Ramadan, Jérôme Gauthier, Patrick M. Hughes, Robert Brandon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsCombustorNOxCombustionProcess engineeringDuct (anatomy)Mechanical engineeringTurbineAutomotive engineeringElectricity generationCogenerationWaste managementEngineeringEnvironmental sciencePower (physics)Chemistry

Abstract

fetched live from OpenAlex

Nowadays, air pollution and climate change have become a global environmental problem. As a result, government regulations worldwide are becoming increasingly stringent. This has led to an urgent need to develop new designs and methods for improving combustion systems to minimize the production of toxic emissions, such as nitrogen oxides. Micro-turbine based cogeneration units are one of the interesting alternatives for combined electrical power and heat generation (CHP). Micro-turbine CHP technology still needs to be developed to increase efficiency, heat-to-power ratio and improve operating flexibility. This can all be obtained by adding a duct burner to the CHP unit. This paper documents the design process for a novel low NOx conical wire-mesh duct burner for the development of a more efficient micro-cogeneration unit. This burner provides the thermal energy necessary to raise the micro-turbine exhaust gases temperature to increase the heat recovery capability. The duct burner implements both lean premixed and surface combustion techniques to achieve low NOx and CO emission levels. The design process includes a set of preliminary design procedures relating the use of empirical and semi-empirical models. The preliminary design procedures were verified and validated for key components, such as the duct burner premixer, using Laser sheet illumination technique (LSI). The LSI was used to study the mixing process inside the premixer fitted with different swirlers. The designed duct burner was successfully operated in a blue flame mode over a wide range of conditions with NOx emissions of less than 5 ppmv and CO emissions of less than 10 ppmv (corrected to 15% O2).

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 score0.657
Threshold uncertainty score0.469

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 head0.019
GPT teacher head0.210
Teacher spread0.192 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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