Failure analysis of a 316L stainless steel femoral orthopedic implant
Bibliographic record
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 10 6 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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".