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Record W4393323210 · doi:10.1051/e3sconf/202450701064

Effect of Ambient temperature on the plastic products using the finite element method

2024· article· en· W4393323210 on OpenAlexaff
Lavish Kansal, Laith H. Alzubaidi, A B Gurulakshmi, G. Karuna, Shilpa Pahwa, Karabi Kalita Das

Bibliographic record

VenueE3S Web of Conferences · 2024
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsFinite element methodMaterials scienceComposite materialStructural engineeringEngineering

Abstract

fetched live from OpenAlex

The escalating use of plastic products alongside rising ambient temperatures has intensified concerns regarding their performance under diverse thermal conditions. This paper delves into the intricate relationship between plastic materials, ambient temperature fluctuations, and resulting stresses. Various grades of plastic materials are subjected to distinct ambient temperatures to elucidate stress generation—a pivotal aspect in plastic product design. Leveraging the finite element method, a comprehensive analysis is conducted to design and assess a plastic product under specified loads and ambient temperatures. The study encompasses the evaluation of equivalent stresses, normal and shear stresses, and deformations. Ultimately, the research culminates in the development and analysis of a thermally stable plastic product, offering valuable insights for robust design practices amidst evolving environmental conditions.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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