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001-es BibID:BIBFORM115533
035-os BibID:(cikkazonosító)1513 (WoS)001094064100001 (Scopus)85175156241
Első szerző:Rashwan, Alkentar (topology optimization) (mechanical engineer)
Cím:Optimization of Additively Manufactured and Lattice-Structured Hip Implants Using the Linear Regression Algorithm from the Scikit-Learn Library / Alkentar Rashwan, Mankovits Tamás
Dátum:2023
ISSN:2073-4352
Megjegyzések:As the name implies, patient-specific latticed hip implants vary in design depending on the properties required by the patient to serve as a valid suitable organ. Unit cells are typically built based on a 3D design of beams, and the properties of unit cells change depending on their geometries, which, in turn, are defined by two main parameters: beam length and beam thickness. Due to the continuous increase in the complexity of the unit cells` designs and their reactions against different loads, the call for machine learning techniques is inevitable to help explore the parameters of the unit cells that can build lattice structures with specific desirable properties. In this study, a machine learning technique is used to predict the best defining parameters (length and thickness) to create a latticed design with a set of required properties (mainly porosity). The data (porosity, mass, and latticed area) from the properties of three unit-cell types, applied to the latticed part of a hip implant design, were collected based on the random length and thickness for three unit-cell types. Using the linear regression algorithm (a supervised machine learning method) from the scikit-learn library, a machine learning model was developed to predict the value of the porosity for the lattice structures based on the length and thickness as input data. The number of samples needed to generate an accurate result for each type of unit cell is also discussed.
Tárgyszavak:Műszaki tudományok Anyagtudományok és technológiák idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
machine learning
unit cells
finite element analysis
optimization
hip implant
Megjelenés:Crystals. - 13 : 10 (2023), p. 1-12. -
További szerzők:Mankovits Tamás (1981-) (gépészmérnök)
Internet cím:Szerző által megadott URL
DOI
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2.

001-es BibID:BIBFORM106241
035-os BibID:(cikkazonosító)113 (Scopus)85146637408 (WoS)000914644000001
Első szerző:Rashwan, Alkentar (topology optimization) (mechanical engineer)
Cím:Effects of Pore Size Parameters of Titanium Additively Manufactured Lattice Structures on the Osseointegration Process in Orthopedic Applications : A Comprehensive Review / Rashwan Alkentar, Nikolaos Kladovasilakis, Dimitrios Tzetzis, Tamás Mankovits
Dátum:2023
ISSN:2073-4352
Megjegyzések:Architected materials are increasingly applied in form of lattice structures to biomedical implant design for the purpose of optimizing the implant`s biomechanical properties. Since the porous design of the lattice structures affects the resulting properties of the implant, its parameters are being investigated by numerous research articles. The design-related parameters of the unit cells for a strutarchitected material are mainly the pore size and the strut thickness. Until today, researchers have not been able to decide on the perfect values of the unit cell parameters for the osseointegration process and tissue regeneration. Based on in vivo and in vitro experiments conducted in the field, researchers have suggested a range of values for the parameters of the lattice structures where osseointegration is in acceptable status. The present study presents a comprehensive review of the research carried out until today, experimenting and proposing the optimum unit cell parameters to generate the most suitable lattice structure for the osseointegration procedure presented in orthopedic applications. Additional recommendations, research gaps, and instructions to improve the selection process of the unit cell parameters are also discussed.
Tárgyszavak:Műszaki tudományok Anyagtudományok és technológiák idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
architected materials
lattice structures
additive manufacturing
optimization
osseointegration
Megjelenés:Crystals. - 13 : 1 (2023), p. 1-16. -
További szerzők:Kladovasilakis, Nikolaos Tzetzis, Dimitrios Mankovits Tamás (1981-) (gépészmérnök)
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
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