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Record W2222870790 · doi:10.1016/j.csefa.2015.12.001

Failure analysis of a 316L stainless steel femoral orthopedic implant

2016· article· en· W2222870790 on OpenAlexafffund
Benjamin Gervais, Aurélian Vadean, Maxime Raison, Myriam Brochu

Bibliographic record

VenueCase Studies in Engineering Failure Analysis · 2016
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsPolytechnique MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersFonds de recherche du Québec – Nature et technologiesPolytechnique Montréal
KeywordsMaterials scienceImplantImplant failureFemurCompression (physics)Structural engineeringFinite element methodStress (linguistics)Orthopedic surgeryFatigue testingFailure mechanismComposite materialDurabilityForensic engineeringOrthodonticsEngineeringSurgeryMedicine

Abstract

fetched live from OpenAlex

ABSTRACT: This study presents a failure analysis of a femoral orthopedic implant. This implant is a locking compression plate that was fixed to a broken femur using two types of screws: locking and compression screws. The study elucidates the causes of an in situ premature failure of the plate and screws. Chemical analysis, hardness tests, and microstructural analysis confirmed that the implant was manufactured from cold-worked stainless steel 316L. The macro and micro fractographic analyses revealed that the failure mechanism was high-cycle fatigue and that the implant underwent approximately 10⁶ loading cycles before failure. A finite element analysis of the assembly indicated that the crack initiation sites are located in the region where the highest stresses are observed. This numerical analysis confirmed that walking induces the loading condition needed for this specific failure. According to this loading condition and to the material properties, the stress amplitude that initiated and propagated the crack is estimated to be in the range of 400 MPa. Several considerations, both mechanical and medical, are discussed in order to explain the failure and to improve the system durability. From an engineering perspective, implant geometry and installation procedure could be optimized in order to reduce the stress concentrations that developed near the crack origin.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.005
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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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.

Study designObservational
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

Citations71
Published2016
Admission routes2
Has abstractyes

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