Abstract

Teeth implant suffeers from stress sheildin and mismatch of bio-mechanical properties, such as weight and stifness. Multi-objective optimization. In order to design better implant, topology optimization of multi-objective function is used in this work. Weighted sum functions are offer a single function to be addressed and optimized which ease finding extremum and feasible design for the various functions that make this single multi-objective function. In this paper, a genetic algorithm is used to determine optimal weights of the three-objective function that used, which are minimizing compliance, minimizing local stress, and minimizing norm function of local stress. This multi-objective function is used to design the optimal shape of dental implant for minimal stress shielding in the jaw. Stress shielding problem is solved by designing the implant’s compliance to match the compliance of the original missing tooth. two stress minimization function has been examined, which is local stress and norm function. Conditions of the design was matching the stiffness of implant which made from titanium with original replaced tooth and setting volume fraction of topology optimization to be 40% of original design problem to offer weight matching. Results shows feasible design. Strain based fatigue simulation shows considerably low difference between non-optimized implant and optimized implant.

Highlights

  • To get the valid mechanical design for the certain application, practically there are several conflicting aspects to be considered

  • Our goal in this paper is to give design procedure of a multiobjective function by identifying best weights of the sum function based on shape and design target, using genetic algorithm; such multi-objective function will be used in Topographic based optimization design methods

  • Solid Isotropic Material with Penalization (SIMP) is a scheme apply for discretized design domain to find smooth optimal structure in which, material properties set to be constant for the discretized domain.[21, 22] the existence of building block which is set in what so-called density function composed of material existence ρ of conditioned power multiply by mechanical properties

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Summary

Introduction

To get the valid mechanical design for the certain application, practically there are several conflicting aspects to be considered. To get a solution for which, the design variables and constraint, satisfy the design criterion in the best way of minimum triage of all needed or desired aspects; multi-objective optimization gives such opportunity. The direct use of GA is not applicable for large number of element problem, for topology optimization such that, practically, topography to be optimized are complicated in nature, making finding valid design with orthodox method a difficult task. GA is adopted as global optimization solver to select the best weighting for sum multi-objective function. It can be selected using an evolutionary algorithm with predetermined sets by initialization of GA. To locate a solution for which, the design variables and constraint, satisfy the design criterion in the best way of minimum triage of all needed or desired aspects; multi-objective optimization gives such opportunity. Bendsoe [20] studied Solid Isotropic Material with Penalization (SIMP) based on Taylors work

Compliance and Stress based objective functions
Multi-objective function for structural optimization examples
Findings
Conclusions
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