MétaCan
Menu
Back to cohort
Record W1936890805 · doi:10.1504/ijvd.2015.071088

Comparison of load transfer index (U<SUP align="right">*</SUP>) with conventional stress analysis in vehicle structure design evaluation

2015· article· en· W1936890805 on OpenAlex

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

VenueInternational Journal of Vehicle Design · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsStress (linguistics)Index (typography)Transfer functionRackStructural engineeringStiffnessTransfer (computing)EngineeringFunction (biology)Automotive engineeringComputer scienceMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The load transfer index (U*), is a relatively new concept compared to its counterpart of structural stress analysis. The U*index characterises the internal stiffness distributions, which indicates the load transferring function of the prospective structure. Although the U* index and stress values have been proven to be useful indices in design, a systematic comparison between the conventional stress analysis and the loads transfer analysis (based on U*index) is lacking. In this study, using a component of the parcel rack from multiple passenger vehicles as an example, we demonstrate the unique capability of U*, indicating the load transferring function. We further show how the combination of the load index U* and the stress distributions provides a comprehensive understanding of the structure's response to various loading conditions. More importantly, we will discuss how the U* can provide unique guidelines for structure design with the purpose of improving the load transfer capacity and reducing the weight.

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)0.001
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 score0.520
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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