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Record W2103204315 · doi:10.5539/mas.v9n4p178

Finite Element Analysis’s Interrelationship Equation to Predict the Deflection of Rolled Homogeneous Armor Steel Plate Due to Explosion based on Different Explosive Masses and Plate Thicknesses

2015· article· en· W2103204315 on OpenAlexvenueno aff
Mohd Zaid Othman, Md Fuad Shah Koslan, Ahmad Mujahid Ahmad Zaidi

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
Fundersnot available
KeywordsExplosive materialArmourMaterials scienceHomogeneousFinite element methodDeflection (physics)Parametric statisticsStructural engineeringMechanicsExplosion weldingComposite materialPhysicsEngineeringClassical mechanicsMathematicsThermodynamicsChemistry

Abstract

fetched live from OpenAlex

This paper presents the interrelationship equation to predict the deformations of square rolled homogeneous armor steel plate subjected to spherical shape trinitrotoluene charge by using finite element analysis software i.e. AUTODYN 3D. The investigation starts by producing computer simulation process using AUTODYN 3D so that a set of experimental tests deformations’ data of rolled homogeneous armor steel plate from a published work can be used to validate the computer simulations outputs and good agreements are observed. Parametric studies are then performed on the design parameters of the explosive and the rolled homogeneous armor steel plate, where the mass of the explosive and the thickness of the rolled homogeneous amour steel plate are varied and analyzed by using the AUTODYN 3D computer simulations. Curve fitting method is then performed to produce the interrelationship equation that could be utilized by researchers as an initial prediction method in determining the deformation of rolled homogeneous armor steel plate subjected to explosive charge and the interrelation equation is valid and can be utilized for a standoff distance of 200 mm, plate’s thickness of 15 mm to 30 mm and explosive mass of 1.5 kg to 10 kg.

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)0.001
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 score0.504
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.040
GPT teacher head0.240
Teacher spread0.200 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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