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Record W2592392671

ON THE 2D SIMPLIFICATION OF 3D CEMENTLESS HIP STEM NUMERICAL MODELS

2018· article· en· W2592392671 on OpenAlexaff
M. Reimeringer

Bibliographic record

VenueEspace ÉTS (ETS) · 2018
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsInertiaMoment of inertiaVariable (mathematics)Cortical boneMoment (physics)Constant (computer programming)Intersection (aeronautics)Finite element methodTransversal (combinatorics)Cancellous boneSecond moment of areaMechanicsGeometryMathematicsComputer scienceStructural engineeringMathematical analysisPhysicsEngineeringClassical mechanics
DOInot available

Abstract

fetched live from OpenAlex

Introduction Finite element (FE) models are commonly used to analyse the mechanical behaviour of the bone under different conditions. They provide detail information but they can be numerically expensive and this limits their use in cases where large or numerous simulations are required. On the other hand, 2D models show less computational cost but the precision of results depends on the approach used for the simplification. Three 2D approaches are commonly used: models without side-plate (WOSP)[1]; models with variable thickness side-plate and constant cortical thickness (SPCT)[2]; models with side-plate and variable cortical thickness (SPVT)[3]. The aim of this study is to determine which 2D approach reproduces best the FE results obtained with a 3D model involving hip stems. Methods The 2D models were generated by the intersection of the 3D model with the stem symmetry plane. Three approaches were considered to assure 3D-2D correspondence: 1) consider variable thickness for the cortical elements so that their transversal area moment of inertia equals the cross-sectional area moment of inertia from the 3D model (model WOSP); 2) include an additional side-plate with variable thickness to match the area moment of inertia from the 3D model, and consider constant thickness for the cortical bone elements (model SPCT); 3) include the side-plate but consider variable thickness for the cortical bone elements, derived from the 3D model (model SPVT). In all cases, the cancellous bone and stem elements had variable thickness computed so that their transversal area moment of inertia was equal to the cross-sectional area moment of inertia measured in the 3D model. This was done at different levels (Fig.1), providing a thickness distribution for the 2D elements. FE analyses were carried out for the static loading condition simulating stair climbing[4]. All materials were defined as linear isotropic and homogeneous. The post-operative situation where bone ingrowth is achieved was considered, resulting in bonded contact between the bone and the implant. The comparison between the 2D and 3D models was done based on three physical quantities: the Von Mises stresses (σVM); the strain energy density ( U ) and the interfacial shear stress (t) along the stem-bone interface. Results Fig.2 shows the σVM, U and t distributions for the 3D model and in the three 2D models. In general, the values for the three physical quantities were under estimated in all 2D models although the differences were small. However, the maximum values of σVM and U were larger in the 2D models than in the 3D model, whereas maximum t values were under estimated. Discussion It is possible to use 2D simplifications based on the stem symmetry plane to perform FE analyses when large number of simulations is needed or when the computational cost needs to be limited. In this way, a side-plate with variable thickness should be considered to obtain close results to the 3D model, while cortical bone thickness can be kept constant and cancellous bone thickness is varied. For figures/tables, please contact authors directly.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.506

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 studies0.0000.000
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 head0.035
GPT teacher head0.278
Teacher spread0.243 · 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 designNot applicable
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".

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Citations0
Published2018
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