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Record W3211594916 · doi:10.32920/ryerson.14656644.v1

Analytical and experimental investigation of the effects of the machining processes on the mechanical behaviour of carbon epoxy composite laminates

2021· preprint· en· W3211594916 on OpenAlexaff
Muhammad Umair Saleem

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsUniversité du Québec à Trois-RivièresToronto Metropolitan University
Fundersnot available
KeywordsMachiningMaterials scienceComposite materialSurface roughnessEpoxyComposite numberSurface finishSurface integrityThermographyCarbon fiber reinforced polymerComposite laminatesInfraredMetallurgy

Abstract

fetched live from OpenAlex

To join various components, drilling is the most frequently used machining process for carbon fiber-reinforced polymer (CFRP) composites. However, it induces various defects such as microcracks, resin degradation and fiber pull-out. In order to eliminate these problems, an appropriate machining process must be employed. Therefore, the main objective of this research is to conduct an analytical and experimental study to investigate the influence of the machining process on the mechanical behaviour of a CFRP structural component and assembly drilled with conventional (CM) and abrasive water-jet machining (AWJM) processes. All CFRP composite laminates did not demonstrate any prominent change in the mechanical properties during static tests. However, fatigue tests showed that the damage accumulation in conventional machining was higher than that in AWJM specimens. Thus, in the case of CM specimens the endurance limit was less than AWJM specimens. The difference in the mechanical behaviour of the composite laminates can be related to the initial surface integrity induced by the difference in the mechanism of material removal of each machining process. This difference in surface texture was responsible for the initiation of stress concentration sites as evident from infrared thermographic stress and thermal analysis. The heat dissipated from all laminates was also correlated to the damage accumulation. It was identified that the surface roughness criterion (Ra) used for the characterization of the surface roughness for metals was not suitable for composites as roughness values of all specimens were same, however different mechanical behaviour was observed. An IR thermographic damage criterion (TDC) was developed which related the temperature threshold area with damage evolution. TDC further confirms the superiority of AWJM compared to CM process. Further it was identified that AWJM process was less sensitive to the composite's stacking sequence compared to conventional machining. The main conclusion of this research is that the failure modes of composite structure parts and assembly are highly affected by the choice of the machining process. This study therefore confirms that the machining process has an important contribution for the design of composite parts and assembly in order to improve the service life of the machined composite structures.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.305

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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