Within today＇s product development process, various FE-simulations （finite element） for the functional validation of the desired characteristics are made to avoid expensive testing with real components. Those simul...Within today＇s product development process, various FE-simulations （finite element） for the functional validation of the desired characteristics are made to avoid expensive testing with real components. Those simulations are performed with great effort for discretization, use of simulations conditions, like taking different non-linearities （i.e., material behavior, etc.） into account, to create meaningful results. Despite knowing the effects of deformations occurring during the production processes, always the non-deformed design model of a CAD-system （computer aided design） is used for the FE-simulations. It seems rather doubtful that further refinement of simulation methods makes sense, if the real manufactured geometry of the component is not considered for in the simulation. For an efficient exploit of the potential of simulation methods, an approach has been developed which offers a geometry model for simulation based on the existing CAD-model but with integrated production deviations as soon as a first prototype is at hand by adapting the FE-mesh to the real, 3D surface detected geometry.展开更多
Advanced engineering coatings offer a promising solution to enhance the longevity and performance of medical biomaterials in orthopaedic implants.This study hypothesises that diamond-like carbon(DLC)coatings exhibit d...Advanced engineering coatings offer a promising solution to enhance the longevity and performance of medical biomaterials in orthopaedic implants.This study hypothesises that diamond-like carbon(DLC)coatings exhibit distinct frictional performance based on substrate and counterface material.Three different DLC coatings were tested using a pin-on-plate test in four material combinations.Virgin and DLC-coated CoCrMo and Ti6Al4V pins were tested under sliding against UHMWPE and glass plates with simulated body fluid lubrication.Results revealed that coating composition significantly impacts frictional performance,with silicon-and oxygen-doped coatings showing great potential to minimise friction.Surprisingly,reducing contact pressure had either a neutral or somewhat negative effect.Future investigations will focus on long-term testing and lubrication analyses of these material combinations.展开更多
Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated(EHL)contacts.In this contribution,we demonstr...Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated(EHL)contacts.In this contribution,we demonstrate that machine learning(ML)and artificial intelligence(AI)approaches(support vector machines,Gaussian process regressions,and artificial neural networks)can predict relevant film parameters more efficiently and with higher accuracy and flexibility compared to sophisticated EHL simulations and analytically solvable proximity equations,respectively.For this purpose,we use data from EHL simulations based upon the full-system finite element(FE)solution and a Latin hypercube sampling.We verify that the original input data are required to train ML approaches to achieve coefficients of determination above 0.99.It is revealed that the architecture of artificial neural networks(neurons per layer and number of hidden layers)and activation functions influence the prediction accuracy.The impact of the number of training data is exemplified,and recommendations for a minimum database size are given.We ultimately demonstrate that artificial neural networks can predict the locally-resolved film thickness values over the contact domain 25-times faster than FE-based EHL simulations(R^(2) values above 0.999).We assume that this will boost the use of ML approaches to predict EHL parameters and traction losses in multibody system dynamics simulations.展开更多
文摘Within today＇s product development process, various FE-simulations （finite element） for the functional validation of the desired characteristics are made to avoid expensive testing with real components. Those simulations are performed with great effort for discretization, use of simulations conditions, like taking different non-linearities （i.e., material behavior, etc.） into account, to create meaningful results. Despite knowing the effects of deformations occurring during the production processes, always the non-deformed design model of a CAD-system （computer aided design） is used for the FE-simulations. It seems rather doubtful that further refinement of simulation methods makes sense, if the real manufactured geometry of the component is not considered for in the simulation. For an efficient exploit of the potential of simulation methods, an approach has been developed which offers a geometry model for simulation based on the existing CAD-model but with integrated production deviations as soon as a first prototype is at hand by adapting the FE-mesh to the real, 3D surface detected geometry.
基金This research was carried out under a project funded by the Czech Science Foundation,Grant No.22‐02154S and No.25‐15390SM.Marian greatly acknowledges the financial support from the Vicerrectoria Academica(VRA)of the Pontificia Universidad Catolica de Chile within the Programa de Insercion Academica(PIA).
文摘Advanced engineering coatings offer a promising solution to enhance the longevity and performance of medical biomaterials in orthopaedic implants.This study hypothesises that diamond-like carbon(DLC)coatings exhibit distinct frictional performance based on substrate and counterface material.Three different DLC coatings were tested using a pin-on-plate test in four material combinations.Virgin and DLC-coated CoCrMo and Ti6Al4V pins were tested under sliding against UHMWPE and glass plates with simulated body fluid lubrication.Results revealed that coating composition significantly impacts frictional performance,with silicon-and oxygen-doped coatings showing great potential to minimise friction.Surprisingly,reducing contact pressure had either a neutral or somewhat negative effect.Future investigations will focus on long-term testing and lubrication analyses of these material combinations.
基金support from Pontificia Universidad Católica de Chile.A.Rosenkranz gratefully acknowledges the financial support given by ANID(Chile)in the framework of the Fondecyt projects(Nos.11180121 and EQM190057)Additionally,A.Rosenkranz acknowledges the financial support given by the VID of the University of Chile within the project U-Moderniza(No.UM-04/19).
文摘Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated(EHL)contacts.In this contribution,we demonstrate that machine learning(ML)and artificial intelligence(AI)approaches(support vector machines,Gaussian process regressions,and artificial neural networks)can predict relevant film parameters more efficiently and with higher accuracy and flexibility compared to sophisticated EHL simulations and analytically solvable proximity equations,respectively.For this purpose,we use data from EHL simulations based upon the full-system finite element(FE)solution and a Latin hypercube sampling.We verify that the original input data are required to train ML approaches to achieve coefficients of determination above 0.99.It is revealed that the architecture of artificial neural networks(neurons per layer and number of hidden layers)and activation functions influence the prediction accuracy.The impact of the number of training data is exemplified,and recommendations for a minimum database size are given.We ultimately demonstrate that artificial neural networks can predict the locally-resolved film thickness values over the contact domain 25-times faster than FE-based EHL simulations(R^(2) values above 0.999).We assume that this will boost the use of ML approaches to predict EHL parameters and traction losses in multibody system dynamics simulations.
