Adaptive volume constraint algorithm for stress limit-based topology optimization

Structural topology optimization.- On basic properties of Michell's structures.- Validation of numerical method by analytical benchmarks and verification of exact solutions by numerical methods.- Introduction to shape and topology optimization.- Homogenization method for shape and topology optimization.- Level set method for shape and topology optimization.- Compliance minimization of two-material elastic structures.- Some notes on topology optimization of vibrating continuum structures.- Topology optimization of vibrating continuum structures for maximum values of simple and multiple eigenfrequencies and frequency gaps.- On optimum shape design and periodicity of band-gape beam structures.- Topological design for minimum dynamic compliance of continuum structures subjected to forced vibration.- Topological design for minimum sound emission from bi-material structures subjected to forced vibration.- Discrete material optimization of vibrating laminated composite plates for minimum sound emission.- Optimization of diffusive transport problems.- Fluid topology optimization: stokes and Navier-stokes models.- Topology optimization of coupled multi-physics problems.- Topology optimization based on the extended finite element method.- Topology optimization of meso- and nano-scale problems.- Topology optimization under uncertainty.- A brief review of numerical methods of structural topology optimization.- The free material design in planar elasticity.

The numerical method of stamp topological optimization taking into account fatigue strength is presented in the work. It is proposed to take into account the restrictions on the stress state in accordance with the curve of the dependence of the maximum stresses on the number of loading cycles in the ESO topological optimization method. An approach to the selection of the evolutionary coefficient with a step-by-step increase in the rejection coefficient is proposed when constructing an iterative scheme for the rejection of elements by the method of topological optimization. The calculation of the stamp optimal topology with a decrease in volume due to the removal and redistribution of material was carried out in the study. The new geometric model of the optimal topology stamp is based on the predicted distribution of elements with a minimum stress level. The verification calculation of the stress state of the stamp of optimal topology with an assessment of fatigue strength was carried out in the work. The numerical calculation was carried out using the finite element method in the Ansys software package. The minimized stamp volume decreased by 35% according to the calculation results. The results of the study can be further applied in the development of topological optimization methods and in the design of stamping tools of optimal topology.

In recent years, additive manufacturing has been gaining ground among traditional manufacturing methods in many different applications. This is mainly due to its ease of prototyping, material savings and above all the highly complex geometries that can be achieved. Despite its many advantages, the use of additive manufacturing in electrical machines has been limited. The lack of maturity of the manufacturing processes and the increase in losses when applying additive approaches to some parts, mainly stators, have led little implementation in the field of electrical machines. The geometric freedom offered by additive manufacturing paves the way for the use of novel optimisation techniques, such as topology optimisation. Traditionally, topology optimisation has not been widely used because the complex geometries obtained by these algorithms are not easily produced by traditional manufacturing methods. However, thanks to additive manufacturing, topology optimisation has started to be used, mainly for mechanical applications and it has demonstrated its ability to reduce weight without compromising mechanical stability in several cases. Nevertheless, topology optimisation for physics other than mechanical has not been thoroughly studied, let alone for the simultaneous optimisation of different physics. In view of the scenario described, this thesis investigates the benefits that additive manufacturing and topology optimisation can bring to the design of electrical machines. For the additive manufacturing of electrical machines, a thorough literature review is carried out on the application of this manufacturing approach to different parts of electrical machines, active and non-active. Two main case studies are presented: in the first, the rotor, the shaft, the stator and the housing of an aerospace actuator are manufactured by L-PBF in FeCoV and the assembled actuator is tested. In the second case, a rotor is manufactured in FeSi by LP- DED. Finally, not considered an additive manufacturing case study itself in this thesis, but two electrical conductor prototypes are manufactured in CuCr1Zr and an additional geometry is manufactured in AlSi10Mg by L-PBF. With regard to topology optimisation of electrical machines, a description of the main topology optimisation methods used is given and their application to electrical machine components is presented. In a similar way to additive manufacturing, two case studies are analysed. First, a novel multiphysics - mechanical and electromagnetic - topology optimisation method is presented, in which the rotor and the stator of a permanent magnet motor are optimised simultaneously. This method is compared with two methods found in the literature, SIMP and on-off. Secondly, another topology optimisation method is described and applied to an electrical conductor model. The proposed algorithm involves a multiphysics - thermal and electromagnetic - hybrid parametric topology optimisation approach. Two reduced length geometries and one full length prototype are built via additive manufacturing. Finally, conclusions regarding additive manufacturing and topology optimisation of electrical machines are drawn from the work presented in this thesis. Future lines of work for additive manufacturing and topology optimisation of electrical machines are also presented.

In the laser powder bed fusion process (PBF-LB), components are built up incrementally by locally melting metal powder with a laser beam. This process leads to inhomogeneous material properties of the manufactured components. By integrating these specific material properties into a topology optimization algorithm, product developers can be supported in the early phases of the product development process, such as design finding. For this purpose, a topology optimization method was developed, which takes the inhomogeneous material properties of components fabricated in the PBF-LB process into account. The complex pore architecture in PBF-LB components was studied with micro-computed tomography (µCT). Thereby, three characteristic regions of different porosity were identified and analyzed. The effective stiffness in each of these regions was determined by means of resonant ultrasonic spectroscopy (RUS) as well as finite element analysis. Afterward, the effective stiffness is iteratively considered in the developed topology optimization method. The resulting design proposals of two optimization cases were analyzed and compared to design proposals derived from a standard topology optimization. To evaluate the developed topology optimization method, the derived design proposals were additionally manufactured in the PBF-LB process, and the characteristic pore architecture was analyzed by means of µCT.

With the rapid advancement of computing technology, mathematical modeling and computer simulations have become common and standard methods for design of complex systems. To exercise these models intelligently and eliminate the burden of manual iteration, manipulating inputs and reviewing outputs, optimization strategies are applied in a simulation-based design environment. In reality, the knowledge that engineers have about the design problem is imperfect and incomplete, uncertainty always exists in simulation-based design. The conventional deterministic optimization techniques do not consider the impact of such uncertainties. If the system responses driving the design decisions are very sensitive to these uncertainties, serious problems might confront the designer. Performance of the actual system may differ greatly from expected optimum performance. Again, if the design solution is near one or more constraint boundaries, then even slight uncertainties or changes in the operating environment could produce failed, unsafe designs, and/or result in substantial performance degradation. In recent years, the concept of reliability and robust design has become very popular. Probabilistic design analysis and statistical modeling allow the identification of designs that qualify as not only feasible, but as consistently feasible in the face of uncertainty. Reliability based topology optimization (RBTO) extends the reliability notion to the area of structural topology optimization. Although reliability based design optimization (RBDO) is a well established research area, very few work has been presented in the area of RBTO. In this study, we give an overview of the various works done in the field of RBTO. Ever since Bendsoe and Kikuchi introduced the topology optimization using a homogenization method, many topology optimization methods have been developed for the both linear and nonlinear structures. Traditional topology optimization methods drive the topology of a structure to an optimum design based on the constraint on mass. Kharmanda et al. introduced reliability constraints in deterministic topology optimization problem. They proposed a heuristic strategy that aims to reduce mass while improving the reliability level of the structure without greatly increasing its weight. But the limit state function used by them was not based on failure criteria for the structure. Their formulation considered uncertainty with respect to ∗Design Automation Laboratory †Advisor geometrical dimension and applied load only. Also their reliability analysis seems to be independent of the boundary and loading condition, so their results showed similar values for the uncertain variables for different structures. Tovar et al. have developed the Hybrid Cellular Automaton (HCA) method for structural synthesis of continuum material where the state of each cell is defined by both density and strain energy. In Agarwal, a decoupled RBDO approach is employed such that the topology optimization is separate from the reliability analysis. Patel et al. showed the use of RBTO using the gradient free Hybrid Cellular Automata (HCA) method. Their formulation incorporates uncertainty with respect to material property also. They considered limit state function based on failure modes on the output displacements. This study aims at giving a comparative study on these methods. It points out the advantages and disadvantages of the methods, and their significance in the field of RBTO. As large numbers of design variables are associated with continuum topology optimization problems, RBTO methods are inherently computationally expensive because of additional required system analysis associate with RBDO. Based on the observations, this study presents an efficient method for incorporating reliability analysis in topology optimization.

Aiming at the problems of a low material utilization rate and uneven stress distribution of cast-steel support joints in cable dome structures, topology optimization and additive manufacturing methods are used for optimization design and integrated manufacturing. First, the basic principle and calculation process of topology optimization are briefly introduced. Then, the initial model of the support joint is calculated and analyzed by using the universal software ANSYS Workbench 2020R2 and Altair OptiStruct, and the optimized joint is imported into Discovery Live to smooth the surface. The static behaviors of three types of joints (topology-optimized joints, joints after the smoothing treatment, and joints from practical engineering) are compared and analyzed. Finally, the joints are printed by using fused deposition modeling (FDM) technology and laser-based powder bed fusion (LBPBF) technology in additive manufacturing. The results show that the new support joint in the cable dome structure obtained by the topology optimization method has the advantages of a novel shape, a high material utilization rate, and a uniform stress distribution. Additive manufacturing technology can allow the manufacture of complex shape components with high precision and high speed. The combination of topology optimization and additive manufacturing effectively realizes the advanced design and integrated manufacturing of support joints for cable dome structures.

This paper deals with simultaneous topology and shape optimization of elastic contact problems. The structural optimization problem for an elastic contact problem is formulated. Shape as well as topological derivatives formulae of the cost functional are provided using material derivative and asymptotic expansion methods, respectively. These derivatives are employed to formulate necessary optimality condition for simultaneous shape and topology optimization and to calculate a descent direction in numerical algorithm. Level set based numerical algorithm for the solution of this optimization problem is proposed. Numerical examples are provided and discussed.

This paper presents an application of topology optimization and response surface method to optimize the geometry of a bicycle crank arm and the experimental validation of it. This is purposely to reduce the crank arm mass and create a preliminary design of a lightweight structure necessary for the high-performance bicycle development. A three-dimensional bike crank arm model was made in the SpaceClaim software followed by a static finite element analysis using ANSYS Workbench 2019 R1. A multiple cycling load was applied simultaneously in seven crank angles of 30, 45, 60, 90, 120, 135, and 150° relative to the horizontal position to create the multiple loads to the crank. From there, topology optimization was then conducted to investigate the effect of mass constraint, stress constraint, angle of cycling, and crank materials on the topological pattern result. To minimize stress concentration at corners, a shape optimization using the response surface method was conducted and obtained the final geometry. From the result, it is shown that both optimization methods not only successfully reduce the crank arm mass and provide several optimum design options but also are able to reduce the maximum stress in the crank arm up to 20% after the optimization process. The experimental validation using a newly developed wireless measurement system shows a considerable agreement to the numerical results.

During the last 20 years, structural optimization has become one of the most important topics of engineering applications. Design optimization of structure has been an interesting area of research in the field of engineering design for its ability to short the design cycle and to enhance product quality. Significant research activity has occurred in the area of structural optimization in the last decade. Especially for topology optimization of structure, many new theoretical, algorithmic, and computational contributions have resulted by researchers and engineers. Topology optimization is a powerful tool for global and multi-scale design of macrostructures, microstructures, and the cell of prescribed composite materials. The population based evolutionary algorithms have emerged as powerful mechanism for finding optimum solutions of complex optimization problems in engineering during the last two decades. Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation [1]. The thinking has wide application in various engineering fields, such as computer science, artificial intelligence, operations research. Genetic algorithm is another kind of bio-inspired optimization method and it is playing an increasingly important role in studies of complex adaptive systems. Its application ranges from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices and structures, such as aircraft turbines and integrated circuits [2]. Optimization of structures can be classified into three categories: sizing, shaping, and topology optimization. In the topology optimization, it is concerned with the structure members and connectivity between members. In general, it is easily represented by discrete variables rather than by those used for continuous optimization problems. Topology optimization is the most difficult and complex among three categories and it is special useful in developing innovative conceptual designs. Structural optimization, in particular the topology optimization, has been identified as one of the most challenging tasks in structural design. Various techniques and approaches have been established during the last two decades. Topology optimization usually referred to as layout optimization or general shape optimization [3]. It lets engineers get the optimal topology of structure or new configurations during product design phase, as they are implementing the design of the size

The spaceborne turntable is a piece of precision optical equipment utilized for monitoring space information and facilitating laser communication. The measurement accuracy of optical instruments is correlated to some extent with the mechanical properties of the structure. Addressing the design challenge posed by the U-frame in the spaceborne optoelectronic tracking and pointing turntable, this paper proposes a multi-constraint topology optimization method utilizing Abaqus/CAE and TOSCA. This method offers insights for U-frame design and has undergone scientific validation. Initially, the empirical design structure is established, optimization design areas are defined, and the initial model undergoes pre-processing in Abaqus/CAE. Subsequently, conceptual and mathematical models for topology optimization are developed, with the objective of minimizing structural compliance (thereby maximizing stiffness), and including constraints related to volume fraction, first-order natural frequency, and stress. Utilizing TOSCA, the U-frame topology optimization design is finalized, resulting in an optimized conceptual model. A comparative analysis of the optimized design against the empirical design structure demonstrates a significant 27.53% reduction in maximum stress, enhanced static stiffness, an increase of 11.48% in the first natural frequency, and a 4.3% reduction in mass. Moreover, the turntable that utilizes the optimized design structure not only meets reliability requirements in spacecraft structural design but also provides a stable platform for precise optical load alignment. The static and dynamic performance of the optimized U-frame has been enhanced, effectively mitigating the impact of external excitation on optical instrument measurement accuracy and meeting the lightweight design requirements for the U-frame, thus demonstrating the efficacy of the topology optimization method. This research offers valuable insights into U-frame design for spaceborne optoelectronic tracking and pointing turntables and carries significant guiding implications.

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.

Historically, fluidic devices such as switches, amplifiers, and oscillators, have an advantage, compared with electronic devices, in terms of maintenance-free operation and operating life. Therefore, prior to the great progress in electronic technologies that has occurred during the past several decades, the structure and function of fluidic devices were the subject of extensive research. In particular, the structures of these fluidic devices are often composed of complicated flow channel layouts. Recently, fluidic devices are again attracting significant attention, stimulated by progress in the development of MEMS technologies. In this study, to develop an energy-efficient structure for a MEMS-scale fluidic device, we apply a topology optimization method to an optimal design problem for a steady state incompressible viscous flow field. We use a level set-based topology optimization method incorporating the concept of the phase field method for the topology optimization so that clear boundaries between the solid and fluid domains are expressed in the optimal configurations. To define the topology optimization problem for a fluid regime, the expressions of the primary and adjoint problems are formulated concretely, to minimize viscous energy dissipation. Moreover, to ensure the intended design outflow rate at a designated outlet, the optimization problem includes an outflow rate inequality constraint in this paper. Following the concept of the standard adjoint variable method, a stable optimization process that satisfies the outflow rate inequality constraint is achieved. Two numerical examples, one for two-terminal and the other for multi-terminal flow, are provided to demonstrate the usefulness of the proposed level set-based topology optimization method.

Random variable of thermo-mechanical coupling (TMC) structure is analyzed first, then the topology optimization model of TMC compliant mechanism is established. According to the uncertainty factors such as temperature, load, volume ratio and thermal expansion coefficient in the process of topology optimization, the robust reliability optimal design method is introduced into the topology optimization process. The various factors on the sensitivity of topology optimization process is analyzed, the best match between various factors is find out, which make the product has robust reliability for the change of the uncertainty. The residual analysis for the most sensitive factors is carried out. Finally the correctness and validity of the method is verified with an example. Introduction When we study the compliant mechanisms by adopting topological optimization method, we only need to give design domain and allocate input and output position, no need from the perspective of a known rigidity. The mechanism come from this method have a input and output relationship of optimized “force—displacement”, thus it attracts people’s attention. Topology optimization research is developing from certain topology optimization direction to reliable topology optimization direction. Jinqing Zhan proposed a reliable topology optimization method of compliant mechanism based on infrastructure method. KHARMANDA proposed a reliable topology optimization method. Zhaokun Li proposed a geometric nonlinear topology optimization research method based on reliable compliant mechanism. Their research turned out that the mechanism based on reliable topology optimization is more reasonable than the mechanism based on certain topology optimization. Yongcong Kuang build a level set function to design variable, stiffness minimization, and proposed corresponding optimization algorithm. Mingtao Cui established a monolithic compliant mechanism multi-target reliable topology optimization design dual mathematical model. This paper combines topology optimization process of compliant mechanism and robust reliability optimal design, analyzes the sensitivity of uncertainty random variables such as design domain’s size, external load and temperature in topology optimization process. Then get the best combination among these random variables. Random Variable Coupling Field Analysis Hot objects will produce thermal expansion, thus caused by the thermal deformation and displacement of combined action of mechanical load and temperature load structure called a hot solid coupling structure, the finite element balance equation :

The objective of this investigation is to carry out the topology design optimization of the pickup suspension of high-speed optical pickups in DVD’s or CD ROM’s. The specific design target here is to increase the torsional eigenfrequency of the pickup as high as possible while keeping the focusing eigenfrequency between 25 Hz and 35 Hz, and the tracking eigenfrequency between 43 Hz and 57 Hz. These frequency ranges are set to meet other design constraints such as servo-controllability. A typical pickup consists of a bobbin having an optical lens and suspension plates to support it. Since the eigenfrequencies of the bobbin itself are in the order of 10 kHz, it can be modeled as a point mass when dealing with the low-frequency dynamic characteristics in consideration. These modeling techniques are verified in the previous researchers. In modeling the bobbin, we also consider its moments of inertia. In designing the suspension system, damping bond is usually applied to control the quality factors at the focusing and tracking frequencies. The location of the damping treatment on the suspension system may be determined by an optimization method, but this is not pursued in this work since the result by the earlier work can be applied to the present suspension system. Unlike static problems such as compliance minimization problems with single and multiple loads or compliant mechanism problems with single and multiple input/outputs, optimization problems involving eigenvalues suffer from mode-switching, which often causes serious difficulties in solution convergence. Mode-switching represents the phenomenon that eigenmodes are changed during the update of design variables. If the design target were simply to maximize a few lowest eigenfrequencies, the mode-switching problem would be handled rather easily. However, the present optimization problem is not the case because we must follow the eigenfrequencies of the specific modes such as tracking, focusing and twisting modes during the optimization process. To handle this situation satisfactorily, we should employ a technique to track the desired modes. In the present investigation, the desired modes are traced by means of the modal assurance criterion (MAC), which has been widely used in experimental modal analysis. For the pickup consisting of a bobbin and suspension plates, the present design goal can be achieved by optimizing the configuration of the suspension plates. To find an optimal plate configuration, we employ the topology optimization method, but the specific method employed here is the multiscale topology optimization method. In the multiscale optimization method, the density design variables are transformed into multiscaled design variables by a series of nonlinear and linear transformations. With the multiscale topology optimization method, the optimization can be completed more efficiently than the optimization by 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization 4-6 September 2002, Atlanta, Georgia AIAA 2002-5483 Copyright © 2002 by the author(s). Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. the standard single-scale direct density method. As an optimizer, the feasible direction method is employed to handle effectively multiple constraints on eigenfrequencies. By the present application of the topology optimization method, the twisting eigenfrequency has been maximized while the focusing and tracking eigenfrequencies are kept in the prescribed frequency range. The optimized suspension plate in the present work outperforms the designs improved from the existing rectangular bend-type plates.

The center of mass and the inertia tensor are important parameters characterizing the kinetic properties of many structural systems, e.g., the rotor, spacecraft, and aircraft. In these occasions, designs not consistent with the requirements on the center of mass and inertia tensor cannot be accepted. In this paper, mathematical models are established to carry out the topology optimization of continua considering the mass and inertia characteristics. Two numerical examples, one for minimizing the static compliance considering locations of the center of mass and the other for maximizing the fundamental eigenfrequency considering both locations of the center of mass and values of the inertia products, are presented to demonstrate that the requirements on mass and inertia characteristics could have a profound influence on the final optimized layouts in structural topology optimization problems. On the other hand, the mass and inertia characteristics can also be tuned by topology optimization methods. In the second numerical problem, the smooth minimum operator is used to approximate the fundamental eigenfrequency with the first 4 eigenfrequencies so that the possible non-differentiability of the repeated eigenfrequencies can be avoided. Due to its extreme importance in engineering practice, the work of this paper can be useful to carry out designs in accordance with the requirements on the mass and inertia characteristics under the framework of traditional density-based structural topology optimization methods.