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Record W2333171785 · doi:10.1115/imece2002-32345

Finite Element Simulations of Joints Used in the Automotive Industry

2002· article· en· W2333171785 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

VenueManufacturing · 2002
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsGibson Energy (Canada)
Fundersnot available
KeywordsRivetAerospaceFinite element methodAutomotive industryComputer scienceSet (abstract data type)Variety (cybernetics)Mechanical engineeringEngineeringStructural engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Finite element-based simulations of vehicle body systems are an effective means of optimizing a design. However, body systems often consist of components from a variety of sources. Hence, accurate modeling requires a robust set of analysis functionality for joining such components. Joints—such as welds, bolts, rivets, clinches, and adhesives—present unique challenges to the analyst. Despite the critical influence joints have on functional performance, there is little information on best practices for modeling such connections. This paper presents a survey of some of the approaches available in ABAQUS, a general-purpose commercial finite element code, and discusses various applications of these techniques through a series of case studies. While the modeling techniques discussed in this paper have been motivated largely by automotive applications, they are also applicable to other areas such as aerospace structures.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.512

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 head0.044
GPT teacher head0.261
Teacher spread0.217 · 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