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Record W4403515686 · doi:10.1115/1.4066898

A Multi-Scale Thermal-Mechanical Numerical Method for Mini-Channel Heat Exchanger Subjected to Fluid Pressure Loads

2024· article· en· W4403515686 on OpenAlex
Zirui Xu, Xiaoxu Zhang, Yin Tan, Jiyuan Bi, Ri Li, Xiongwei Yang, Qiuwang Wang, Ting Ma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueASME Journal of Heat and Mass Transfer · 2024
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsHeat exchangerMaterials scienceThermalScale (ratio)Fluid pressureMechanical engineeringMechanicsEnvironmental scienceComposite materialPetroleum engineeringGeologyEngineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract This study proposes a novel multi-scale numerical method for thermal-mechanical analysis of mini-channel heat exchangers (MCHEs) under internal fluid pressure and temperature loads. The method comprises a macro-scale model for global analysis and a meso-scale model for detailed submodel analysis, specifically focusing on the internal fluid pressure effects within the MCHEs. The macroscopic model divides the MCHE into cover plate and homogenized regions subjected to pressure and temperature loads. To incorporate internal pressures into the homogenized MCHE model, mathematical equations are formulated to convert internal fluid pressures into equivalent strain loads. Additionally, a novel equivalent thermal expansion method is introduced, integrating internal fluid pressure loads by prescribing equivalent thermal expansion coefficients alongside spatially-varying nodal temperature fields within the MCHE. The meso-scale models with detailed channel patterns are assigned to specific portions of the homogenized region. The integration of the mesoscale model into the macroscopic framework is achieved through the application of the submodel method. Comparisons between the equivalent and actual MCHE models show that the proposed equivalent method can provide accurate predictions for thermal-mechanical deformations and stresses, and significantly reduce the computational expenses.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.802

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 head0.016
GPT teacher head0.261
Teacher spread0.246 · 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