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Record W2200491446 · doi:10.1115/omae2015-41432

Lateral Pressure Effects on the Ultimate Strength of Plates

2015· article· en· W2200491446 on OpenAlexaff
Lei Jiang, Shengming Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsMartec (Canada)
Fundersnot available
KeywordsStructural engineeringFinite element methodTransverse planeStress (linguistics)Submarine pipelineUltimate tensile strengthNonlinear systemMaterials scienceSensitivity (control systems)Plane (geometry)GeologyEngineeringGeotechnical engineeringComposite materialMathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

During the operations of ships and offshore structures in the ocean environment, these structures are subjected to combined lateral pressure and in-plane stresses. However, in today’s ship design and analysis procedures, the effects of the lateral pressure on the ultimate strength of these structures are often ignored. Previous studies have indicated that the lateral pressure could have a noticeable influence on the ultimate load carrying capacity of stiffened panels when they are subjected to combined longitudinal and transverse stresses. The purpose of this paper is to present a systematic numerical study to quantify the lateral pressure effects on the ultimate strength of plates. The sensitivity of the plate’s ultimate strength to lateral pressure is characterized as a function of the plate geometry, the pressure magnitude and the ratio of the in-plane stress components. The present numerical study is performed by using LR’s in-house nonlinear finite element program VAST and the newly development LR procedure for nonlinear structural mechanics analysis was followed. The results and findings from this study are detailed in this paper.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
Teacher spread0.206 · 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
Published2015
Admission routes1
Has abstractyes

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