TOPOLOGY OPTIMIZATION OF INTEGRATED COMBUSTION ENGINE PISTON USING FEA METHOD (CAE TOOLS)

This thesis aims at understanding and improving topology optimization techniques focusing on density-based level-set methods and geometrical nonlinearities. Central in this work are the numerical modeling of the mechanical response of a design and the consistency of the optimization process itself. Concerning the first topic, we investigate different means to improve the robustness of density-based numerical models including geometrical nonlinearities. The conventional approach (scaling the local material properties) can result in convergence problems due to excessive deformation in low-stiffness finite elements. To avoid excessive deformation, we combine the element connectivity parameterization method (adapting the connectivity between finite elements) with level-set-based topology optimization. Furthermore, we achieve greater robustness of analysis method using a second and improved approach called element deformation scaling. This approach eliminates the need for solving internal equilibrium equations (needed for the element connectivity parameterization method) via an explicit relation between the local internal and global external displacement field. The second focus of this thesis is on the optimization process of level-set-based topology optimization, and in particular its numerical consistency. We observe that signed-distance reinitialization of the level-set function affects the shape of a design in the optimization process. To minimize this effect, we propose a discrete level-set method that is based on an approximate Heaviside function and focusing on the implementation. Furthermore, we also propose a level-set-based topology optimization method using an exact Heaviside function and mathematical programming that effectively eliminates the need for reinitialization. We demonstrate that our density-based level-set method is closely related to conventional density-based topology optimization methods, while offering the advantage of more control over the geometrical complexity. On the other hand, we confirm that the dependence of the final result on the initial design which remains one of the big challenges for level-set-based topology optimization. The potential of the proposed level-set method is shown by applying it on problems with stress constraints and geometrical nonlinearities and performing manufacturing tolerant topology optimization. Finally, this thesis offers a review of level-set methods for structural topology optimization to identify and discuss the different approaches that are available in literature. We can distinguish between level-set methods by examination of their design parameterization, sensitivities, update procedures and regularization techniques. A level-set-based design parameterization offers the advantage of a crisp distinction between subdomains. For this reason, X-FEM approaches and conforming discretizations are an interesting option to retain the crisp nature of the level-set-based description of the design. Many level-set methods are combined with density-based numerical models and are, therefore, closely related to conventional density-based topology optimization methods. In particular, recently proposed projection methods have much in common with a level-set-based design description. The results of level-set-based TO methods often rely heavily on regularization techniques that introduce inconsistencies in the optimization process. Numerical consistency does not necessarily lead to the best search direction, but is essential to find a Karush-Kuhn-Tucker point of the discretized optimization problem.

In this thesis numerical methods combining evolutionary optimization algorithms and finite element analysis are developed and applied to problems in cardiac mechanics and structural optimization. In the first application finite element analysis is combined with a real encoded genetic algorithm to determine unknown material parameters in constitutive model for ventricular myocardium using an inverse approach. As a second application suppression of global instabilities in minimum-weight Michell structures is investigated. A real encoded genetic algorithm is combined with a finite element eigenvalue buckling analysis for suppressing global buckling associated with minimum-weight structures. A novel finite element based evolutionary algorithm is developed to determine optimal structural topologies for a 2D continuum. Finally, the topology optimization algorithm described above is modified to determine optimal structural topology for design domains composed of materials having different strengths in tension and compression (dual strength materials). Optimal topologies evolve through successive removal and admission of material based on the current strain energy distribution. Illustrative examples demonstrate the ability to determine optimal structural configuration for a dual strength material domain. Optimal topologies obtained using current scheme are shown to agree with minimum-volume layouts generated using analytic methods based on dual strength material optimality criteria.

A linear network is a type of wireless sensor network in which sparse nodes are deployed along a virtual line; for example, on streetlights or columns of a bridge, tunnel, and pipelines. The typical deployment of Linear Wireless Sensor Net-work (LWSN) creates an energy hole around the sink node since nodes near the sink nodes deplete their energy faster than others. Optimal network topology is one of the key factors that can help improve LWSN performance and lifetime. Finding optimal topology becomes tough in large network where total possible combinations is very high. We propose an Optimal Topology Generation (OpToGen) framework based on genetic algorithm for LWSN. Network deployment tools can use OpToGen to configure and deploy LWSNs. Through a discrete event simulator, we demonstrate that the use of genetic algorithm accomplishes fast convergence to optimal topologies as well as less computational overhead as compared to brute force search for optimal topology. We have evaluated OpToGen on the number of generations it took to achieve the best topology for various sized LWSNs. The trade-off between energy consumption and different network sizes is also reported.

In conventional level set methods, the slope of the level set function needs to be well controlled to maintain the numerical stability during the topology optimization process. One common solution is to regularize the level set function to be a signed distance function, which is usually achieved by periodically implementing the so called re-initialization scheme to force the level set function to gain the desired signed distance property. However, the re-initialization scheme will bring some unwanted drawbacks to the optimization process, such as zero level set drifting, time consuming etc. In addition, re-initialization is usually implemented outside the optimization loop, which will cause convergence issues. In this paper, a distance regularization functional is introduced to the structural topology optimization objective functional to ensure the signed distance property of the level set function near the structure boundaries. This functional can also keep the level set function to be constant-value at positions far away from the structural boundaries. The radial basis function (RBF) based parameterization technique together with the mathematical programming are utilized to improve the potential capability of handling multiple constraints for the topology optimization. The combination of these two techniques makes the level set based topology optimization be capable of handling complicated multi-constrained problems with higher numerical efficiency, leaving no compromise to multiple drawbacks. To demonstrate the validity of the proposed scheme, benchmark examples on minimum compliance structural optimization are employed. This type of problem is computed by the conventional level set method with the introduced distance regularization functional, the RBF based parametric level set and at last, the distance regularized RBF based parametric level set separately to demonstrate their differences.

A level set solution to the stress-based structural shape and topology optimization

By providing structural support and damping capacity, motor plates used in tower cranes effectively reduce vibrations stemming from the mass and operation of asynchronous motor assemblies, thereby improving overall performance. This study proposes a combined topology and thickness optimization strategy to minimize the weight of a motor plate used in tower cranes without compromising structural performance. In the first stage, topology optimization is conducted to achieve an optimal material distribution under predefined loading and boundary conditions. In the second stage, thickness optimization is performed to minimize mass while maintaining structural integrity, considering maximum equivalent stress and total deformation as primary constraints. Finite element analysis is used throughout the process to evaluate mechanical responses for each design iteration. Results indicate that the motor plate mass can be reduced by approximately 60 % without compromising safety limits, providing a substantial improvement in both material efficiency and mechanical performance. The final optimized model is validated and presented with graphical interpretations of stress, deformation, and mass variation against plate thickness.

As an increasing need for metal implant species and quantities in the clinical application, the demands of structure for the implants have been increased, accompanying the rapid development of 3D printing technology and the progress of medical combination with engineering also made it possible to fabricate complex implants. On this basis, the topology optimization of structure in the finite element analysis technique has been developed gradually, and the application of this technique has greatly improved the biomechanical properties of implants. This review introduces the applications of topology optimization technology in implant structure design, and summarizes the researches of topology optimization technique in the field of medical implant mainly on the department of maxillofacial surgery and orthopedics. In the field of orthopedics, topology optimization technique is most widely used, and in the structural design of joint prosthesis, internal fixation and spinal implant, the obvious progress was obtained in both theory and practice. Finally, the paper put forward the prospect of the trend for the topology optimization design of metal implants in the future. Key words: Topology optimization; Implants; Maxillofacial surgery; Orthopedics.

This paper proposes a topology optimization method for a dielectric optical cloak that provides results that are perfectly free from intermediate materials, based on a level set boundary expression and the Finite Element Method. The finite element mesh is re-generated to fit the iso-surface of the level set function at every iterative step, to remove intermediate materials, so that the obtained optimal structure consists of only two materials, the dielectric material and air. First, the level set-based topology optimization is formulated and a topology optimization algorithm is proposed for the exact level set approach. Next, design requirements for the dielectric optimal cloak device are clarified and an objective functional for the design is formulated. The proposed method is then applied to a simple numerical problem to illustrate its effectiveness.

BackgroundTotal talar replacement is normally stable and satisfactory. We studied a rational scaffold talus model for each size range created through topology optimization (TO) and comparatively evaluated a topologically optimized scaffold bone talus model using a finite element analysis (FEA). We hypothesized that the rational scaffold would be more effective for application to the actual model than the topologically optimized scaffold.MethodsSize specification for the rational model was performed via TO and inner scaffold simplification. The load condition for worst-case selection reflected the peak point according to the ground reaction force tendency, and the load directions “plantar 10°” (P10), “dorsi 5°” (D5), and “dorsi 10°” (D10) were applied to select worst-case scenarios among the P10, D5, and D10 positions (total nine ranges) of respective size specifications. FEA was performed on each representative specification-standard model, reflecting a load of 5340 N. Among the small bone models selected as the worst-case, an arbitrary size was selected, and the validity of the standard model was evaluated. The standard model was applied to the rational structure during validity evaluation, and the TO model reflecting the internal structure derived by the TO of the arbitrary model was implemented.ResultIn worst-case selection, the highest peak von Mises stress (PVMS) was calculated from the minimum D5 model (532.11 MPa). Thereafter, FEA revealed peak von Mises stress levels of 218.01 MPa and 565.35 MPa in the rational and topologically optimized models, respectively, confirming that the rational model yielded lower peak von Mises stress. The weight of the minimum model was reduced from 1106 g to 965.4 g after weight reduction through rational scaffold application.ConclusionThe rational inner-scaffold-design method is safer than topologically optimized scaffold design, and three types of rational scaffold, according to each size range, confirmed that all sizes of the talus within the anatomical dimension could be covered, which was a valid result in the total talar replacement design. Accordingly, we conclude that an implant design meeting the clinical design requirements, including patient customization, weight reduction, and mechanical stability, should be possible by applying a rational inner scaffold without performing TO design. The scaffold model weight was lower than that of the solid model, and the safety was also verified through FEA.

The focus in this paper is to design a compact ultra-wideband self-complementary antenna (SCA) optimized for bandwidth constrained by size. The concept of frequency independent self-complementary geometries is applied to achieve the highest bandwidth possible, and a genetic algorithm (GA) optimization method is used to provide the optimal planar antenna topology and substrate design in an available finite space. An FDTD technique is used to fully analyze the complex antenna structures. It is demonstrated that a GA-optimized SCA can provide a wide bandwidth ratio of about 1:5 which occupies an area as small as /spl lambda//4/spl times//spl lambda//4 at the lowest frequency. An equally spaced alternate-leaves SCA on an optimized meta-substrate is also proposed that provides ultra-wideband bandwidth characteristics (bandwidth ratio 1:8) with as small dimensions as /spl lambda//3/spl times//spl lambda//3.

A constitutive theory, finite element formulation and topology optimization for anti-vibration rubber are presented. Many vibration isolators made of rubbers are operating under small oscillatory load superimposed on large static deformation. A~viscoelastic constitutive equation for rubber is proposed considering the influence of large static pre-deformation on the dynamic properties. The proposed model is derived through linearization of Simo's viscoelastic constitutive model and introduction of static deformation correction factor. And then the model is implemented in a finite element code to analyze the behavior of rubber elements under general loading conditions. Dynamic tests are performed in order to verify the model under multi-axial deformation. The computed results by the FEA code are compared with the experimental results and the suggested constitutive equation with static deformation correction factor shows good agreement with the test values. For the stability and low transmissibility of isolation systems, both static and dynamic performance must be concurrently considered in the design process. The continuum-based design sensitivity analyses (DSA) of both the static hyperelastic model and dynamic viscoelastic model are developed. And then the topology optimization methodology is used in order to generate the system layouts considering both the static and dynamic performance.

SummaryThis paper presents an alternative topology optimization method based on an efficient meshless smoothed particle hydrodynamics (SPH) algorithm. To currently calculate the objective compliance, the deficiencies in standard SPH method are eliminated by introducing corrective smoothed particle method and total Lagrangian formulation. The compliance is established relative to a designed density variable at each SPH particle which is updated by optimality criteria method. Topology optimization is realized by minimizing the compliance using a modified solid isotropic material with penalization approach. Some numerical examples of plane elastic structure are carried out and the results demonstrate the suitability and effectiveness of the proposed SPH method in the topology optimization problem. Copyright © 2016 John Wiley & Sons, Ltd.

Topology optimization of compliant mechanism and its support through a level set method

3D printed patient-specific fixation plates for the treatment of slipped capital femoral epiphysis: Topology optimization vs. conventional design

Lightweight lattice structure generation and topology optimization (TO) are common design methodologies. In order to further improve potential structural stiffness of lattice structures, a method combining the multi-topology lattice structure design based on unit-cell library with topology optimization is proposed to optimize the parts. First, a parametric modeling method to rapidly generate a large number of different types of lattice cells is presented. Then, the unit-cell library and its property space are constructed by calculating the effective mechanical properties via a computational homogenization methodology. Third, the template of compromise Decision Support Problem (cDSP) is applied to generate the optimization formulation. The selective filling function of unit cells and geometric parameter computation algorithm are subsequently given to obtain the optimum lightweight lattice structure with uniformly varying densities across the design space. Lastly, for validation purposes, the effectiveness and robustness of the optimized results are analyzed through finite element analysis (FEA) simulation.