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Record W2754164069 · doi:10.1177/0954407017724635

Demonstration of the effectiveness of <i>U</i> <sup>*</sup> -based design criteria on vehicle structural design

2017· article· en· W2754164069 on OpenAlex
Qingguo Wang, Khashayar Pejhan, Igor Telichev, Christine Wu

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

VenueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFunction (biology)Component (thermodynamics)Design methodsComputer scienceStructural engineeringEngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

A basic function of vehicle structures is bearing the load. To design high efficient vehicle structures, it is crucial to know how the applied forces are transferred in the structure. The U * index was introduced as the indicator of the main load path in the structure. U * -based design criteria were developed to promote the ability of the U * index theory for vehicle structural design. However, the effectiveness of these U * -based design criteria on improving the structural performance is still unknown. In this paper, an improved design of a vehicle component was proposed based on the U * governed design criteria. Compared to the original design, the weight of the modified structure is reduced by 10% while the maximum displacement and stress are declined by 5% and 26%, respectively. The paper proves that the application of the U * driven design criteria can effectively increase the structural performance.

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.256
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