Topology Optimization Techniques Research Articles

Additive Manufacturing of Sustainable Construction Materials and Form-finding Structures: A Review on Recent Progresses.

Recently, there has been an increasing interest on the sustainability advantage of 3D concrete printing (3DCP), where the original cement-based mixtures used for printing could be replaced or incorporated with environmental-friendly materials. The development in digital modeling and design tools also creates a new realm of form-finding architecture for 3DCP, which is based on topological optimization of volumetric mass and physical performance. This review provides a perspective of using different green cementitious materials, applications of structural optimization, and modularization methods for realizing sustainable construction with additive manufacturing. The fresh and hardened mechanical properties of various sustainable materials for extrusion-based 3D printing are presented, followed by discussions on different topology optimization techniques. The current state of global research and industrial applications in 3DCP, along with the development of sustainable construction materials, is also summarized. Finally, research and practical gaps identified in this review lead to several recommendations on material developments, digital design tool's prospects for 3DCP to achieve the sustainability goal.

Performance of 3D printed topologically optimized novel auxetic structures under compressive loading: experimental and FE analyses

The auxetic structures, because of their negative Poisson's ratio, have a lot of potential applications in the aerospace and automobile industry due to their exceptional mechanical properties under bending, shear, and compression loads. In this study, three novel auxetic structures were prepared by creating modifications in the existing ones found in the literature. The in-plane mechanical performance of the novel structures under uniaxial compression loads was evaluated using experimentally validated finite element analysis (FEA) models. Moreover, their deformation and collapse behavior was also examined. It was found that all of the new auxetic structures possess higher Young's modulus and energy absorption capacities as compared to the conventional re-entrant structure. To further enhance their aforementioned properties, a topology optimization technique, i.e., shape optimization, whose effect on the mechanical performance of auxetic structures is not yet explored, was applied to the conventional and the new structures. The mechanical properties of shape-optimized structures were found to be significantly better than the un-optimized structures. Hence, auxetic structures, with compressive properties superior to the traditional ones were developed in this research which are favorable for high load applications. The modifications made to conventional structures, as well as the shape optimization technique utilized in this research, can be used as a guideline to produce other high-performance auxetic structures.

How to design a more stable dental implant: A topology optimization approach.

The body shape design is one of the most influential factors in the success of dental implants. This study presents a strategy to design the geometrical features of a threaded implant. The topology optimization technique is applied to identify appropriate spaces in the implant body to be removed for bone growth. The exact shape, position, and dimensions of the spaces are determined using a finite element model. This model consists of a mandibular segment, implant, abutment, and crown. During the optimization process, some grooves and holes are created in the implant by removing redundant materials. Bone growth into these spaces causes mechanical locking between the implant and surrounding bone. The smoothing process is performed following the optimization to remove stress concentration. The results indicate that this design strategy reduces the maximum displacement of the implant by approximately 20%. Moreover, a reduction in the implant's volume and an increase in the contact area between the implant and bone are obtained. All mentioned issues would increase the stability and reduce the risk of implant loosening. Finally, using conventional production methods, the optimal implant was produced from titanium alloy to demonstrate the possibility of production of the proposed design.

EFFICIENT DESIGN OF AIRCRAFT BRACKET USING TOPOLOGY OPTIMIZATION AND ADDITIVE TECHNOLOGIES

The design of an aircraft must always meet opposite criteria. On the one hand, the structure must be strong, rigid, stable and at the same time to have the least weight. The design requirements listed above in modern conditions must be complemented by the requirement of safety increasement of the crew in case of emergency. One of the possible solutions for ensuring safety is creation of structures capable of accumulating impact energy during an emergency landing of an aircraft. Additive technologies have fewer restrictions on the complexity of shape geometry than traditional ones. Modern methods of topological optimization make it possible to determine the direction of power flows in a structure. Based on this data, the optimal design is determined to take into account the requirements of working capacity and minimum weight. The combination of new technologies with topological optimization techniques allows to design parts more efficiently. The article discusses various options of using different approaches of material distribution in a given volume of a part. Topological optimization was performed using the variable density algorithm. This method is used to create a solid and lattice structure of a bracket for wing to fuselage joint of the ATR-42-300 aircraft. A comparison was made between the original bracket, the bracket with a solid structure and lattice structure obtained as a result of topology optimization method. The optimized design options are determined under the requirements of strength and minimum weight in working conditions. The estimation of the energy absorption by the bracket for all three variants of structures under the conditions of an emergency landing was carried out. For the first time, a comparison of the results of topological optimization for a lattice structure and solid structure model of material distribution was performed. The comparison of all options with each other showed that lattice structure is the best design. This type of structure allows to reduce the weight of the original structure by up to 60%. In addition to reducing weight, these structures increase the safety of the crew in case of emergency by increasing energy absorption on impact.

Improved Efficient Projection Density Function Based on Topology Optimization

Topology optimization is a powerful tool having capability of generating new solution to engineering design problems, while these designs enhance manufacturability and reduce manufacturing costs in a computational setting. Mesh-independent convergence and other techniques have been widely used as topology optimization technique, but they produce gray transition regions which is not a favorable condition for any material. In this article, a modified topology optimization formulation using a new function has been proposed. The suggested scheme makes use of the Heaviside Projection Method (HPM) to continuum topology optimization. Such technique is helpful to obtain the minimum length scale influence on void and solid phases. Application of this proposed approach is implemented to obtain the minimum compliance for macrostructures. Numerical remarkable examples illustrate the noteworthy value of the proposed approach.

Designing drones by combining finite element and atomistic simulations: a didactic approach

A didactic multiscale approach for drone modeling is proposed. Specifically, we investigate the drone structure at both macroscopic and microscopic scales, by making use of finite element and atomistic simulations, respectively. The structural analysis is performed with the aim to equip the drone with specific sensors and measuring instruments capable to detect the existence of volcanic ash, SO 2 , CO 2 and other pollutants in the atmosphere after a volcanic eruption. We show that, by modeling the tubular structure of the drone with a sandwich constituted by a a polystyrene core, carbon fiber skins and epoxy matrix, a weight saving of 7 grams for each drone arm can be obtained, in comparison to the standard commercial drones, although a slight worsening of the mechanical performances is observed. In addition, the molecular structure of the polystyrene chains has been investigated by using atomistic Molecular Dynamics simulations, providing further information on the local structure of the polymer chains. Additional improvements of the weight saving could be obtained by means of the the topological optimization techniques on the body of the drone and on the supports for landing.

Network topology optimisation based on dynamic thermal rating and battery storage systems for improved wind penetration and reliability

The nonflexible operations of transmission networks with high load demand and wind power increase the likelihood of power congestions and deteriorate grid reliability. This condition causes higher load curtailments and inhibits the penetrations of wind power, subsequently leading to higher dispatch cost because more expensive generators compensate for the loss of wind integrations. These unfavourable factors contribute to a higher total system operating cost, which should be reduced. This paper applies a network topology optimisation technique to optimise line and busbar switching for relieving network congestions and improving network flexibility. A dynamic thermal rating system is used to enhance overhead line ratings. A battery storage system is utilised to time shift wind power usage and avoid wind spillage. These methods are effective but they have been studied only in isolation. This paper presents an assessment framework that combines all the three methods in a single model to evaluate their synergistic effects on wind integration and network reliability. The proposed framework is generic and can be applied on any networks with changes only to the numerical results. The battery energy and power ratings required to maintain the prevailing security of supply standards in a large scale wind-integrated network are determined probabilistically. Case studies performed on a modified IEEE 24-bus reliability test system show that the proposed combination of methods reduces system dispatch, load curtailment and wind curtailment costs the most when compared to any combinations with fewer methods or using each method in isolation.

Topologically optimal design and failure prediction using conditional generative adversarial networks

AbstractAmong the various structural optimization tools, topology optimization is the widely used technique in obtaining the initial design of structural components. The resulting topologically optimal initial design will be the input for subsequent structural optimizations such as shape, size and layout optimizations. However, iterative solvers used in conventional topology optimization schemes are known to be computationally expensive, thus act as a bottleneck in the manufacturing process. In this paper, a novel deep learning‐based accelerated topology optimization technique with the ability to predict ductile material failure is presented. A Conditional Generative Adversarial Network (cGAN) coupled with a Convolutional Neural Network (CNN) is used to predict the optimal topology of a given structure subject to a set of input variables. Subsequently, the same cGAN is trained to predict the Von‐Mises stress contours on the optimal structure by means of color transformed image‐to‐image translations. The ductile failure criterion is evaluated by comparing the cGAN predicted maximum Von‐Mises stress with the yield strength of the material. The proposed novel numerical method is proven to arrive at the topologically optimal design, accompanying the material failure decision within a negligible amount of time but also maintaining a higher prediction accuracy.

Application of topology optimization technique in sand casting process of a complex product based on FDM 3D printing technology

Design optimization is one of the emerging CAE technologies thanks to the robust and strong structure of the computer and the ability to create complex designs using material additive technology. Recent modern innovations in 3D printing technology have made metal casting new breakthroughs. The demand of many products with complex shapes and geometries becomes very high. This makes the 3D printing more helpful and meaningful to contribute in the field of product design and development. This study presents an integrated framework for the implementation of complex 3D product design from fundamental technologies of CAD/CAE/AM (Computer Aided Design/Computer Aided Engineering/Additive manufacturing). Then, we apply casting technology to create models for products with complex shapes from FDM 3D printing technology. This integrated process is essential in assisting engineers to quickly design and create prototypes, and to fully control errors occurring during prototyping through CAD/CAE simulation to improve production efficiency of businesses and reduce time to bring products to customers. The experiment of sand casting based on the mold core from AM technology confirmed that the integrated approach is effective and applicable in the practice at manufacturing enterprises .

The advances of topology optimization techniques in orthopedic implants: A review.

Metal implants are widely used in the treatment of orthopedic diseases. However, owing to the mismatched elastic modulus of the bone and implants, stress shielding often occurs clinically which can result in failure of the implant or fractures around the implant. Topology optimization (TO) is a technique that can provide more efficient material distribution according to the objective function under the special load and boundary conditions. Several researchers have paid close attention to TO for optimal design of orthopedic implants. Thanks to the development of additive manufacturing (AM), the complex structure of the TO design can be fabricated. This article mainly focuses on the current stage of TO technique with respect to the global layout and hierarchical structure in orthopedic implants. In each aspect, diverse implants in different orthopedic fields related to TO design are discussed. The characteristics of implants, methods of TO, validation methods of the newly designed implants, and limitations of current research have been summarized. The review concludes with future challenges and directions for research. Wang TO design of global layout and local structure of implants in diverse fields of orthopedic.

Efficient EM Topology Optimization Incorporating Advanced Matrix Padé Via Lanczos and Genetic Algorithm for Microwave Design

Electromagnetic (EM) topology optimization aims at finding the optimal shape and topology of the EM structure by adding or eliminating materials, such as metal within the design space. This optimization problem cannot be solved by the widely used surrogate-based optimization because different shapes and topologies cannot be related by changing the values of a given set of geometrical parameters. EM simulations are needed when the shape and topology change. This article proposes an efficient EM topology optimization technique for microwave component design. The finite element method (FEM) is used for EM simulation. We propose a new method to integrate the matrix Padé via Lanczos (MPVL) and the Householder formula. The proposed method combines the advantages of the MPVL and the Householder formula so that the effort of solving the large FEM matrix equation at many frequencies is reduced to the effort of solving only a small matrix problem at a single frequency point, thereby speeding up the topology optimization process. We further propose a new method to reduce the small matrix problem into an even smaller one by exploiting the inheritance pattern of a genetic algorithm (GA). New formulations are derived to exploit the common factors between new children EM structures and the parent EM structures in each generation of GA so that computational expense can be further reduced. The proposed technique incorporating advanced FEM-MPVL and the inheritance pattern of GA can greatly accelerate the topology optimization process. Three microwave examples are used to demonstrate the proposed technique.

Bi-material microstructural design of biodegradable composites using topology optimization

Biodegradable materials have demonstrated promising potential for the treatment of bone fractures. Therefore, it is crucial to design biodegradable composites considering the degradation effect. Accordingly, to realize a composite material with controlled stiffness at the bone repair stage, this study introduces a novel topological optimization technique for the material layout design in microstructure, considering material degradation. In this approach, two sets of variables are adopted: a density field that defines the material layout, which is also the design variable, and a time field that determines the effect of material degradation on composite material properties. A continuous degradation update formula is proposed by integrating the Heaviside function and the Kreisselmeier–Steinhauser function to guarantee its derivability. The objective of this study was to maximize the material stiffness in some fixed time steps under a specified volume fraction. The sensitivity of the aforementioned objective relative to the design variable was deduced by considering the material degradation over time. The proposed design approach was demonstrated with several design examples, considering different degradable interface boundary conditions. Furthermore, the obtained results were compared with the results obtained without considering material degradation, thereby verifying the effectiveness of the proposed method.

Evolutionary Topology Optimization of Spatial Steel-Concrete Structures

Topology optimization techniques based on finite element analysis have been widely used in many fields, but most of the research and applications are based on single-material structures. Extended from the bi-directional evolutionary structural optimization (BESO) method, a new topology optimization technique for 3D structures made of multiple materials is presented in this paper. According to the sum of each element's principal stresses in the design domain, a material more suitable for this element would be assigned. Numerical examples of a steel- concrete cantilever, two different bridges and four floor systems are provided to demonstrate the effectiveness and practical value of the proposed method for the conceptual design of composite structures made of steel and concrete.

(Invited) Additively Manufactured Graphene Aerogel Supercapacitors

Electrochemical energy storage (EES) and conversion devices (e.g. batteries, supercapacitors, and reactors) are emerging as primary methods for global efforts to shift energy dependence from limited fossil fuels towards sustainable and renewable resources. These electric-based devices, while showing great potential for meeting some key metrics set by conventional technologies, still face significant limitations. For example, an EES device tends to exhibit large energy density (e.g. lithium-ion battery) or power density (e.g. supercapacitor), but not both. This inability of a single device to simultaneously achieve both metrics represents a major obstacle to widespread adoption of EES devices. Improvements in materials, such as the integration of 2D materials (e.g. graphene, dichalcogenides, MXene, etc.) into electrochemical devices has yielded some exciting results towards tackling this issue, but significant improvements are still needed. Our approach to simultaneously achieving high energy and power density is to focus on one of the fundamental processes that occur in these systems: mass (or charge) transport. The efficient transport of ions within EES devices is critical to realizing both large power and energy densities. The pore structure of the electrode is a key factor in determining this transport phenomena, but in many cases, engineering the pore structure in a highly deterministic fashion is not pursued or even possible for many electrode materials. In this work, we explore a number of additive manufacturing methods (e.g. direct ink write, projection microstereolithography, etc.) to engineer the pore structure of device electrodes. We also determine effective electrode geometries using both simple theory and topology optimization techniques. The topology optimization couples the solution of the forward electrochemical problem over the full electrode domain with gradient-based optimization. The output of our code is a three-dimensional CAD representation which optimizes over specific performance metrics and which can be used to print functional electrodes. This work provides a systematic path toward automatic design and fabrication of engineered electrodes with precise control over the fluid and species distribution.This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

REDUCTION IN WEIGHT OF HOUSING OF AXIAL MINE FAN IMPELLER WITH ROTATING BLADES

The study uses topological optimization techniques in design of the housing of an impeller meant for the increased rotational speeds in ANSYS. The objective function of the impeller optimization is the minimum yield, and the optimization parameter is assumed as the change in the interior volume of the structure under certain constraints imposed on the external geometry of the impeller. The optimization of the impeller housing shows that it is possible to reduce the weight of the power belt, and to make one web to be load-bearing and the other web to be thinner, or to switch to the impeller with one web. Moreover, the design can use some elements of a lattice structure.

A cell-centered indirect Arbitrary-Lagrangian-Eulerian discontinuous Galerkin scheme on moving unstructured triangular meshes with topological adaptability

In this paper, we present a novel cell-centered indirect Arbitrary-Lagrangian-Eulerian (ALE) discontinuous Galerkin (DG) scheme on moving unstructured triangular meshes with mesh topological adaptability, aiming to deal with the strong distortions and large deformation flow problems. The scheme combines the explicit time marching Lagrangian DG methodology with the adaptive mesh topology optimization technique. The scheme consists of the following three steps. Firstly, we utilize the Runge-Kutta DG method to solve the compressible Euler equation in Lagrangian framework, and employ a nodal solver to obtain the nodal velocity and numerical fluxes across element boundaries. The physical variable and nodal position are updated in this step. Secondly, the adaptive mesh topology optimization technique, which includes the mesh refinement, edge collapse operation and mesh regularization, is implemented to eliminate the highly distorted elements and improve the mesh quality. Thirdly, the conservative remapping algorithm is employed, which can maintain the conservative interpolation of the Lagrangian solution onto the remeshed grid. The present indirect ALE DG scheme can ensure the high quality of the mesh by optimizing the topology connectivity, so that the present scheme can successfully simulate complex vortical flow problems for a sufficient simulation time. Due to the inherent Lagrangian nature, the present scheme can naturally track the multi-material flow interface, rather than using algorithms with interface reconstruction or diffuse interfaces. The scheme is validated with several benchmark flow problems. It is demonstrated that the present indirect ALE DG scheme with topological adaptability can accurately simulate flow problems with large fluid deformations and distortions. It can achieve remarkable improvements compared with the conventional Lagrangian DG method with fixed topological connectivity.

Milling Tool Optimization by Topology Optimization Technique

In milling operations, the weight of the milling tool greatly affects the motion speed of the mandrel, especially when a complex tool path must be performed. Thus, it is essential to realize more lightweight tools, without a significant decrease in the mechanical and production performance. Traditionally, due to the limitation of the conventional manufacturing processes, the design of a new milling tool cannot be too much complex and thus cannot fully satisfy the mentioned goals. Nowadays, thanks to the topology optimization technique and the additive manufacturing (AM) technologies, such as the selective laser melting (SLM), it is possible to realize more complex part geometries to obtain more lightweight and high-performance tools. In this paper, a new design of a milling tool with a weight reduced by 30% is presented; SLM process has been selected to realize the milling tool. In order to minimize the use of support structures, required by the SLM process to correctly realize the desired part, the new geometry has been little modified. A more lightweight milling tool has been produced and every support structure has been successfully removed from the component.

Topology and FEA modeling and optimization of a patient-specific zygoma implant

Additive manufacturing has proven to be a very beneficial production technology in the medical and healthcare industries. While existing for over four decades, recent work has seen great improvements in the quality of products; particularly in medical devices such as implants. Improved customization reduced operating time and increased cost-effectiveness associated with Metal AM for these products offers a new value proposition. This paper investigates and evaluates modelling methods for the zygoma bone (human jawbone) and explores the most suitable material and optimum design for this critical biomedical implant. This paper proposes an innovative and efficient pre-process methodology that includes modelling, design validation, topological optimization, and numerical analysis. The method includes the generation of the model using reverse engineering of CT scan data and a topology optimization technique which makes the implant lightweight without causing excessive stress concentration. Static structural Finite Element Analysis was conducted to test three different biocompatible materials (Ti6Al4V, stainless steel 316L and CoCr alloys) which are commonly available for metal additive manufacturing. The stresses and conditions in the analysis were that of the human mastication process and all the implant design were tested with the three material types. The Taguchi method was used to determine the optimum design which was found to result in the highest mass reduction of 25% with Ti6Al4V as the implant material.

적층제조설계기법을 이용한 위성용 경량화 전개장치 구조물 개발

Additive manufacturing technology in metals allows for the design and fabrication of integrated satellite structures that reduce part counts and improve performance. This paper, proposes the application of the design for additive manufacturing (DfAM) process in the space environment. The small lightweight deployment mechanism structure was investigated for the strength and stiffness performance. The weight reduction was maximized through shape optimization by applying a topology optimization technique. In addition, a validation of the deployment mechanism structure design was confirmed under strength and vibration conditions through structural analysis. The mechanical properties of Ti64 Grade23 were compared and evaluated by the test of specimens and products manufactured using the power bed fusion (PBF) method.

Design of graded lattice structures in turbine blades using topology optimization

ABSTRACT Designing and manufacturing lattice structures with Topology Optimization (TO) and Additive Manufacturing (AM) techniques is a novel method to create light-weight components with promising potential and high design flexibility. This paper proposes a new design of lightweight-graded lattice structures to replace the internal solid volume of the turbine blade to increase its endurance of high thermal stresses effects. The microstructure design of unit cells in a 3D framework is conducted by using the lattice structure topology optimization (LSTO) technique. The role of the LSTO is to find an optimal density distribution of lattice structures in the design space under specific stress constraints and fill the inner solid part of the blade with graded lattice structures. The derived implicit surfaces modelling is used from a triply periodic minimal surfaces (TPMS) to optimize the mechanical performances of lattice structures. Numerical results show the validity of the proposed method. The effectiveness and robustness of the constructed models are analysed by using finite element analysis. The simulation results show that the graded lattice structures in the improved designs have better efficiency in terms of lightweight (33.41–40.32%), stress (25.52–48.55%) and deformation (7.35–19.58%) compared to the initial design.