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Record W3136975200 · doi:10.23977/jemm.2021.060101

Optimization Design of the Support Plate of Large-scale Split Jack Multifunctional Rescue Attachments

2021· article· en· W3136975200 on OpenAlex
Ning Cheng, Jiehua Wang, Xinlei Ye, Shibo Li, Tao Jiang

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Engineering Mechanics and Machinery · 2021
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsRigidity (electromagnetism)Finite element methodStructural engineeringMinificationEngineeringMathematical optimizationMathematics

Abstract

fetched live from OpenAlex

Aiming at the problem of low strength and low rigidity of the support plate of the large-scale split jack multifunctional rescue attachment, a simulation model of the attachment is established based on the working principle of the split jack rescue attachment. The limit working condition is used as the input condition, and the finite element analysis is carried out on the support plate of the split jack rescue attachment. Based on the response surface method and multi - objective genetic algorithm, the main size parameters of the support plate are selected as the design parameters, and the maximum equivalent stress, maximum deformation and mass minimization are the optimization goals, and the optimization model of the support plate is established. Optimize its structure. The result shows that the strength and rigidity of the support plate are improved without increasing the mass.

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: none
Teacher disagreement score0.732
Threshold uncertainty score0.229

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 head0.011
GPT teacher head0.244
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