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Record W2023175571 · doi:10.1115/gt2013-94076

A New Inlet Distortion and Pressure Loss Based Design of an Intake System for Stationary Gas Turbines

2013· article· en· W2023175571 on OpenAlexaff
J.L. Rodríguez, S. Klumpp, Thomas Biesinger, James O’Brien, Tobias Danninger

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsSiemens (Canada)
FundersSiemens
KeywordsGas compressorInletTurbineAxial compressorComputational fluid dynamicsDiffuser (optics)NozzleMarine engineeringMechanical engineeringEngineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a new design for a Compressor Inlet Manifold (CIM) for a land-based power generation Gas Turbine (turbine). The CIM is the component of the Inlet System (IS) that is directly connected to the turbine via the Compressor Inlet Case (CIC). The design philosophy is to use low fidelity but fast and automated CFD (Computational Fluid Dynamics) for design iterations and then confirm the design with detailed higher accuracy CFD before proceeding to engine tests. New design features include contouring the wall to minimize areas of flow separation and associated unsteadiness and losses, and improvement of the flow quality into the compressor. The CIM in a land-based turbine acts as a nozzle whereas the inlet of an aircraft acts as a diffuser. The flow also enters the CIM at 90 deg to the engine axis. This leads to a pair of counter rotating vortices at the compressor inlet. Three main sources of flow distortions at the face of the compressor are identified: flow separations at outer walls of the IS and CIM struts and the counter rotating vortices. The higher accuracy CFD analysis including the complete IS, CIM and the first compressor stage, simulates the effect of these distortions on the compressor front stage at design conditions. A range of inlet distortion parameters are used to evaluate the inlet design. The well known DC60 based criterion derived from aircraft engines and other less known but published parameters are able to give an indication of how the compressor surge margin of stationary gas turbines is affected.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score0.238

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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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