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Record W4411321179 · doi:10.4271/2025-01-0213

CFD Study of Lubrication Pump Starvation Due to Oil Pan Sloshing

2025· article· en· W4411321179 on OpenAlexaff
Shiyi Pan, Jing Liu, Wei Wang

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2025
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsSlosh dynamicsLubricationComputational fluid dynamicsStarvationMarine engineeringPetroleum engineeringMechanicsEnvironmental scienceMaterials scienceEngineeringMechanical engineeringPhysicsBiology

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Dynamic vehicle operation, such as acceleration, deceleration, and tilting, can cause severe oil sloshing in the engine oil pan. This can lead to oil starvation at the pickup tube, compromising lubrication pump performance, and potentially damaging engine components. This study presents a Computational Fluid Dynamics (CFD) multiphase model of an engine oil pan and a system of lubrication pumps, simulated using Simerics-MP+®. A series of numerical simulations are conducted at a given pump speed and extreme oil pan tilt angles or accelerations relevant to a high performance vehicle. Time-dependent oil distributions are visualized, and real-time oil flow rates are monitored at the pickup tubes to assess the impact of oil dynamics and pan position on pick-up tube starvation. This CFD model provides valuable insights into oil pan and pump behavior under extreme vehicle operation conditions, aiding in the design and optimization of lubrication systems to mitigate the risk of oil starvation and improve overall engine safety and performance.</div></div>

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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.

Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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