Purpose:The objective of this investigation is to study prosthodontics and internal components resistance to the masticatory stress and considering different force directions by using Finite Element Method analysis (FEM). The structural materials of the components are usually Titanium alloy grade 4 or 5 and thus, guarantee the integration of the fixture in the bone due to the osteointegration phenomena. Even if the long-term dental implant survival rate is easy to be obtained and confirmed by numerous researches, the related clinical success, due to the alteration of the mechanical and prosthodontics components is still controversial.Methods:By applying engineering systems of investigations like FEM and Von Mises analyses, it has been investigated how dental implant material was held against the masticatory strength during the dynamic masticatory cycles. A three-dimensional system involved fixture, abutment and the connection screws, which were created and analyzed. The elastic features of the materials used in the study were taken from recent literature data.Results:Data revealed a different response for both types of devices, although implant neck and dental abutment showed better results for all conditions of loading while the abutment screw represented aweak point of the system.Conclusion:The data of this virtual model showed all the features of different prosthetic retention systems under the masticatory load. Clinicians should find better prosthetic balance in order to better distribute the stress over the component and to guarantee patients’ clinical long-term results.

The objective of this investigation was to analyze the mechanical features of two different prosthetic retention devices. By applying engineering tools like the finite element method (FEM) and Von Mises analyses, we investigated how dental implant devices hold out against masticatory strength during chewing cycles. Two common dental implant overdenture retention systems were analyzed and then compared with a universal—common dental abutment. The Equator® attachment system and the Locator® arrangement were processed using the FEM Ansys® Workbench. The elastic features of the materials used in the study were taken from recent literature. Results revealed different responses for both the devices, and both systems guaranteed a perfect fit over the axial load. However, the different design and shape involves the customized use of each device for a typical clinical condition of applying overdenture systems over dental implants. The data from this virtual model showed different features and mechanical behaviors of the overdenture prosthodontics attachments. A three-dimensional system involved the fixture, abutment, and passant screws of three different dental implants that were created and analyzed. Clinicians should find the best prosthetic balance to better distribute the stress over the component, and to guarantee the patients clinical long-term results.

The objective of the present investigation was to evaluate how dental implant positioning can influence the masticatory stress distribution over screwed mandibular prosthodontics restoration and over the surrounding bone tissue. Moreover, the dental implant components and overdenture bar strengths under masticatory cycles have been investigated in order to evaluate possible screw and prosthesis breakage. A “virtual jaw” model and 3D dental implant were reproduced to realise finite element analysis in order to underline the parameters and the mechanical characteristics of the bone and of the dental implants connected to the overdenture bar. The distribution of a nonspecific chewing phase, analysing the overall load on the fixtures of the lower jaw, was performed. The study investigating frontal and horizontal planes and vertical directions of occlusal forces showed how position and perspective of fixtures strongly influenced the stress distribution and the consequent jawbone tissue remodelling. Prostheses elements such as cantilever, passing screws, and dental implants are strictly related to the correct selection of dental implant position. This study suggested a virtual method to guide the surgeon in the choice of implant number, position, diameter, and length, and cantilever length and shape, and to evaluate the prospective stress distribution of chewing strengths for a correct prosthesis rehabilitation.

Objective The purpose of this investigation is to highlight the technical components of a new kind of screw-retained dental implant prosthesis. The hypothesis is whether the OT Bridge (Rhein 83 S.R.L.; Bologna, Italy) system could be applied without secondary screw in the “all-on-four” retention system, thanks to the presence of an internal seeger. Materials and Methods By using engineering device such as finite element method (FEM) and von Mises investigation, it has been studied how the fixed prosthodontics for full-arch retention can be influenced by the presence of the screw for stabilizing it. Results In a dental implant, one model with four different configurations of the full-arch prosthesis retainer and the seeger has been investigated and then examined in contrast with or without the passant screw for locking the system. The experiments of this virtual study highlighted different features and mechanical behaviors of prosthodontic attachments. Conclusion The first two configurations, respectively those in which there are four and three connection screws, are safe and predictable. Therefore, the presence of the seeger significantly improves the stability and the retention of the whole prosthesis.

Titanium dental implants have had new competitors in recent years, such as fixtures made of zirconia, which promise better aesthetics. The purpose of this study is to evaluate their mechanical performance in silico (Finite Element Analysis). The investigation was performed on a single tooth Patent™ Dental Implant (Zircon Medical®, Altendorf, Switzerland) in two configurations: without offset (Test I) and with offset (Test II, 1.5 mm within the cortical bone). The Patent Implant system consists of two components: the implant with integrated abutment and the fibreglass post. The components of the dental implants were tested using a compression load of 400 N along the implant axis. The results showed that the chewing load generates stress distribution on the bone, therefore, the offset configuration should be avoided.

In recent years, thanks to the development of additive manufacturing techniques, pros-thetic surgery has reached increasingly cutting-edge levels, revolutionizing the clinical course of patients suffering from joint arthritis, rheumatoid arthritis, post-traumatic arthrosis, etc. This work aims to evaluate the best materials for prosthetic surgery in hip implants from a tribological and mechanical point of view by using a machine-learning algorithm coupling with multi-body modeling and Finite Element Method (FEM) simulations. The innovative aspect is represented by the use of machine learning for the creation of a humanoid model in a multibody software environment that aimed to evaluate the load and rotation condition at the hip joint. After the boundary conditions have been defined, a Finite Element (FE) model of the hip implant has been created. The material properties and the information on the tribological behavior of the material couplings under investigation have been obtained from literature studies. The wear process has been investigated through the implementation of the Archard’s wear law in the FE model. The results of the FE simulation show that the best wear behavior has been obtained by CoCr alloy/UHMWPE coupling with a volume loss due to a wear of 0.004 μm3 at the end of the simulation of ten sitting cycles. After the best pairs in terms of wear has been established, a topology optimization of the whole hip implant structure has been performed. The results show that, after the optimization process, it was possible to reduce implant mass making the implant 28.12% more lightweight with respect to the original one.

The aim of this paper is the development of a 7-DOF (Degrees Of Freedom) mathematical model of an IndyCar and the implementation of an Artificial Neural Network in order to predict the optimal setup parameters of the car, reducing time and costs for race teams. The mathematical model is created by using MATLABTM and Simulink software starting from a telemetry acquisition at the Houston circuit and is based on Vertical Vehicle Dynamic equations. The optimal setup parameters have been predicted through an Artificial Neural Network (ANN) by using the NFTOOL Toolbox of MATLABTM software. ANN is implemented in a Quarter Car model, firstly, in order to train the network and predict the parameters able to reduce tire deflection and suspension travel in the time domain and the resonance peaks amplitude in the frequency domain. Then, it is implemented in the 7-DOF model in order to predict the best setup parameters able to reduce body movements and the weight transfers of the car.

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