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Record W1990572422 · doi:10.5267/j.esm.2014.8.004

A new approach for investigation of damage zone properties in orthotropic materials

2014· article· en· W1990572422 on OpenAlexvenueno aff
Mahdi Fakoor, Mohammad Hossein Sabour, Nabi Mehri Khansari

Bibliographic record

VenueEngineering Solid Mechanics · 2014
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsOrthotropic materialMaterials scienceComposite materialStructural engineeringEngineeringFinite element method

Abstract

fetched live from OpenAlex

Article history: Received March 6, 2014 Accepted 23 August 2014 Available online 24 August 2014 Fracture phenomenon in orthotropic materials, generally associates with region called, “damaged zone” in crack tip vicinity. In quasi-brittle materials, this area is known as fracture process zone (FPZ). This area contains a multitude of microcracks, which cause difficulties in analytical process of the region. Also, energy waste in damaged zone can affect the material fracture properties. The characteristics of damaged zone should be considered to figure out the residual strength of composite materials. It also can help to predict the value or even the direction of crack growth of orthotropic materials. So far, several efforts have been made to determine the mechanical properties of this region, but none of them (due to the immense complexity of this region) can express the behavior of this region properly. Moreover, previous approach has not been verified by new experimental and numerical results, yet. In the present study, a new approach “damaged zone simulation (DZS)” is proposed based on the experimental and numerical data, for investigating the orthotropic damaged zone properties. Comparison with existing analytical data shows the capabilities of the presented approach. © 2014 Growing Science Ltd. All rights reserved.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score0.746

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 head0.014
GPT teacher head0.191
Teacher spread0.177 · 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 teacher head, 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

Citations4
Published2014
Admission routes1
Has abstractyes

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