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Three-dimensional indentation test system for observing the distribution of internal mechanical properties in materials

2024· article· en· W4402313107 on OpenAlex

Why this work is in the frame

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fundA Canadian funder is recorded on the work.
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

VenuePrecision Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsnot available
FundersJapan Science and Technology AgencySwine Innovation Porc
KeywordsIndentationMaterials scienceInternal stressDistribution (mathematics)Composite materialMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

This paper describes the development of a three-dimensional (3D) indentation test system capable of observing the distribution of mechanical properties in structural materials. Serial sectioning with destructive treatment has traditionally been used as a method for observing microstructure within materials in three dimensions. The serial sectioning methods using precision cutting has attracted particular attention as it enables the observation of large sample volumes. However, those methods can only observe the microstructure as image, not the mechanical properties such as hardness and elastic modulus. To measure the 3D distribution of the mechanical properties of the material, it is effective to combine repeated cutting and indentation tests on each cutting surface. Morever, combining the image observation and mechanical property tests could allow a more sophisticated analysis of the interior of material. To implement this method, we have constructed an indentation test system on a precision machine using a Berkovich indenter, micro-force sensor, and micro-movement stage. In order to achieve a 3D indentation test, it is considered necessary to unify the measurement positions in the depth direction. Furthermore, the unloading rate needs to be controlled in order to carry out stable indentation tests. Therefore, we propose a method of 3D indentation test that can precisely control the maximum depth of indentation and unloading speed. In this paper, we devise a method for driving the constructed system and a method for obtaining data and confirm the accuracy of these methods by experiment. In addition, we determine indentation depth and unloading speed which are suitable for our method by performing indentation tests on a block for ultra-microhardness. Finally, we practice 3D indentation test in which the cutting and indentation tests are repeated on specimens with different mechanical properties in the depth direction. Experimental results show that our indentation test system is appropriate to measure three-dimensional mechanical properties inside the material. • The system was devised to enable indentation test on the precision machining. • The system allowed repeatable indentation tests on the cutting surface. • The indentation test system was built using a piezoelectric stage and force sensor. • This indentation test system could control indentation depth and unloading speed.

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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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.214
Teacher spread0.192 · 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