Topology Optimization Research Articles

Research on multi-objective topology optimization of unmanned sightseeing vehicle frame based on Analytic Hierarchy Process

To optimize the frame of a sightseeing vehicle, this paper proposes a multi-objective topology optimization method combining Analytic Hierarchy Process (AHP) and topology optimization. Firstly, the edges of the unmanned sightseeing car are statically analyzed. The rectangular steel frame structure of the original frame is replaced with square plates, the basic model of the unmanned sightseeing car frame is established, and a single-objective topology optimization mathematical model of the frame is established to optimize the topology design of the frame. Then, in order to design a frame structure that meets all the working conditions at the same time, a mathematical model of multi-working condition topology optimization is established, and the weights of each working condition are determined by using AHP, and the multi-working condition topology optimization design of the frame is carried out. Finally, a comparison of the comprehensive performance of the frame before and after optimization shows that the proposed method enables the optimized frame to meet the strength requirements under various working conditions, resulting in a weight reduction of 16.5 kg.

A Machine Learning Approach for Mechanical Component Design Based on Topology Optimization Considering the Restrictions of Additive Manufacturing

Additive manufacturing (AM) and topology optimization (TO) emerge as vital processes in modern industries, with broad adoption driven by reduced expenses and the desire for lightweight and complex designs. However, iterative topology optimization can be inefficient and time-consuming for individual products with a large set of parameters. To address this shortcoming, machine learning (ML), primarily neural networks, is considered a viable tool to enhance topology optimization and streamline AM processes. In this work, a machine learning (ML) model that generates a parameterized optimized topology is presented, capable of eliminating the conventional iterative steps of TO, which shortens the development cycle and decreases overall development costs. The ML algorithm used, a conditional generative adversarial network (cGAN) known as Pix2Pix-GAN, is adopted to train using a variety of training data pairs consisting of color-coded images and is applied to an example of cantilever optimization, significantly enhancing model accuracy and operational efficiency. The analysis of training data numbers in relation to the model’s accuracy shows that as data volume increases, the accuracy of the model improves. Various ML models are developed and validated in this study; however, some artefacts are still present in the generated designs. Structures that are free from these artefacts achieve 91% reliability successfully. On the other hand, the images generated with artefacts may still serve as suitable design templates with minimal adjustments. Furthermore, this research also assesses compliance with two manufacturing constraints: the limitations on build space and passive elements (voids). Incorporating manufacturing constraints into model design ensures that the generated designs are not only optimized for performance but also feasible for production. By adhering to these constraints, the models can deliver superior performance in future use while maintaining practicality in real-world applications.

Topology optimization of regenerative cooling structures under high Reynolds number flow with variable thermo-physical properties

In the design of thermal protection system for hypersonic vehicles, the efficient convective heat transfer within regenerative cooling channels plays a critical role in maintaining their thermal performance. This study focuses on the topology optimization (TO) of the cooling channels that operate at high Reynolds number and have variable thermo-physical properties. A novel approach is introduced to enhance the density-based method by incorporating an effective artificial force correction and tabulating the temperature-dependent thermal properties. Several topology-optimized cooling layouts were generated to minimize the maximum temperature within the design domain while considering different power dissipation constraints. This confirms the validity of the proposed lumped correction term in momentum equation accounting both viscous and convective body forces. Regarding the thermal performance of the optimized layouts, the staggered arrangement of cellular ribs in the TO channel was found to induce multiple flow separations and promote turbulent mixing, thereby improving heat transfer efficiency and mitigating the thermal acceleration effect. Conjugate heat transfer calculations revealed that the optimal topology-optimized channel achieved a 24.3% improvement in overall thermal performance while being 15.3% lighter than the straight channel design. Furthermore, the optimal topology optimized layout consistently outperformed the straight channel design by 6.6% to 24.3% in terms of the overall thermal performance across a wide range of heat flux distribution and mass flow rate conditions. This investigation highlights the effectiveness of topology optimization in designing regenerative cooling structures featuring high Reynolds number hydrocarbon thermal fluid flow.

Topology optimisation of fibre-reinforced composites accounting for buckling resistance and manufacturability

A topology optimisation approach that accounts for buckling resistance and manufacturability using fibre-reinforced composites is presented. This approach combines topology optimisation and fibre orientation optimisation to achieve a design with maximum buckling resistance. To ensure the optimal designs can be manufactured using 3D printing, constraints based on the continuity of fibre orientation and fibre path generation are applied. A compressed column, a stubby cantilever and an MBB beam are designed to demonstrate the response of the topology and fibre orientation when accounting for buckling resistance, as well as the compromise due to the inclusion of manufacturing constraints. The results show that the presented approach successfully guarantees manufacturability with a significant increase in buckling resistance.

A one-time training machine learning method for general structural topology optimization

Machine learning (ML) methods have found some applications in structural topology optimization. In the existing methods, however, the ML models need to be retrained when the design domains and supporting conditions have been changed, posing a limitation to their wide applications. In this paper, we propose a one-time training ML (OTML) method for general topology optimization, where the self-attention convolutional long short-term memory (SaConvLSTM) model is introduced to update the design variables. An extension–division approach is used to enrich the training sets. By developing a splicing strategy, the training results of a small design space (i.e., a basic cell of either two- or three-dimensions) can be extended to tackling the optimization problem of a large design domain with arbitrary geometric shapes. Using the OTML method, the ML model needs to be trained for only one time, and the trained model can be used directly to solve various optimization problems with arbitrary shapes of design domains, loads, and boundary conditions. In the SaConvLSTM model, the material volume of the post-processed thresholded designs can be precisely controlled, though the control precision of the gray-scale designs might be slightly sacrificed. The effects of model parameters on the computational cost and the result quality are examined. Four examples are provided to demonstrate the high performance of this structural design method. For large-scale optimization problems, the present method can accelerate the structural form-finding process. This study holds a promise in the high-resolution structural form-finding and transdisciplinary computational morphogenesis.

Topology Optimization of Functionally Graded Structure for Thermal Management of Cooling Plate

The fast charge and discharge of a battery will significantly increase the overall temperature and thermal difference of the battery, which will further affect the working performance and safety of the battery. Therefore, a heat–fluid coupling topology optimization pipeline for developing radiation performance of the cooling plate is presented to ensure the thermal homogeneity of the battery in this paper. First, the Brinkman penalty model is utilized to construct the solid and fluid structures. Then, a local volume constraint is introduced to create the lattice structure to reduce the temperature difference of the cooling plate. Furthermore, a functionally graded lattice structure via a variable influence radius is presented to improve the radiation performance of the cooling plate when the thermal load is uneven. Numerical experiments are carried out to evaluate the performance of the presented methods on the optimization of the cooling plate, which indicates that the designed cooling plate by the proposed method improves the radiation performance when compared against a traditional straight channel and a SIMP-based optimal design.

Topology optimization with continuously varying load magnitude and direction for compliance minimization

Topology optimization with continuously varying load magnitude and direction for compliance minimization

Multi-objective optimization of a triple-eccentric butterfly valve considering structural safety and sealing performance

The structural safety and sealing performance of a triple-eccentric butterfly valve are crucial technical indicators that influence its reliability and service life. In this study, a new multi-objective optimization strategy is proposed to realize a lightweight design of valve trims, reduce the maximum equivalent stress, and reasonably distribute the sealing-specific pressure. A two-stage optimization scheme is designed by combining topology optimization (TO) and response surface methodology optimization (RSM). The topology optimization is employed to allocate the material distribution of the valve trims and provide the parameters for the response surface optimization, while the response surface methodology optimization conducts a further revision and optimization of the structural parameters of the valve trims. The results of the simulation experiments indicate that the maximum equivalent stress of the lightweight designed valve trims is reduced from 290.85 MPa to 99.88 MPa, and the maximum sealing-specific pressure of the sealing surface is reduced from 197.78 MPa to 77.83 MPa. Additionally, a novel approach is presented for assessing the sealing performance using the clearance of the fitting surface. This method can intuitively evaluate the state of metal sealing and guide the design of the fitting tolerance by analyzing the sensitivity of the dimensional deviation to the sealing-specific pressure. The findings demonstrate that the optimized valve exhibits good structural safety and sealing performance.

Conductive paths generation using topology optimization for worst-case thermal design in space systems

Designing thermal systems for space platforms is a challenging task due to the wide variability in thermal conditions during the orbit and the strict constraints imposed by other subsystems. Several strategies have been developed to address these challenges while minimizing the thermal control subsystem’s signature, encompassing different algorithms optimize components positions in the platform. When relocation is not possible, thermal couplings between components can be modified to enhance heat transfer and achieve more uniform temperature distribution. To design optimal thermal paths in 2D space structures, in this paper a topology optimization framework based on the Heaviside Projection Method is introduced, using the Lumped Parameter Method (LPM) and taking the radiation heat transfer into account. The algorithm’s performance is tested on a Printed Circuit Board (PCB) by designing an optimal copper layer to meet specific thermal requirements under both extreme hot and cold conditions. Results show a significant improvement in thermal compliance for all components with the addition of this high-conductivity layer. Additionally, a reduction method is introduced to transfer the material distribution from the optimization to a coarser mesh of any size, which is useful to facilitate its implementation in existing software, where a large number of degrees of freedom can be a limitation.

Data-driven multi-fidelity topology design of fin structures for latent heat thermal energy storage

This work develops a data-driven multi-fidelity topology design (MFTD) method for designing fins in a latent heat thermal energy storage tube. The high-fidelity simulation resolves the actual solid-liquid phase change process using the enthalpy method, while the low-fidelity topology optimization (TO) simply considers the natural convection with Darcy flow. The above MFTD method is integrated into the framework of evolutional algorithm, and the variational autoencoder is introduced to generate new offspring. Fins for accelerating the melting and solidification processes at different Grashof number (Gr) are designed. It is found that when the fin volume fraction is low, the melt designs exhibit strong heterogeneity due to the strong convection, while the solidification designs are almost isotropic. Along with the increase of the fin volume fraction, the fins are first getting longer, then having more branches or sub-branches and finally becoming thicker. The superiority of the present data-driven MFTD method to the gradient-based direct TO method for solving optimization problems with strong multimodality has been demonstrated in this work. Results find that compared with the designs from direct TO, the MFTD melt design can further reduce the melting time by at least 27 % and 20 % at Gr = 3.3 × 103 and Gr = 3.3 × 104 respectively, and the MFTD solidification design can further shorten the solidification time by at least 9 %.

Link Topology and Multi-Objective Mission Flow Optimization for Remote Sensing Satellites With Inter-Layer Links and Satellite-Ground Links

Link Topology and Multi-Objective Mission Flow Optimization for Remote Sensing Satellites With Inter-Layer Links and Satellite-Ground Links

Stress-based topological shape optimization for thick shells using the level set method and trimmed non-conforming multi-patch isogeometric analysis

Stress-based topological shape optimization for thick shells using the level set method and trimmed non-conforming multi-patch isogeometric analysis

A review of structural diversity design and optimization for lattice metamaterials

Metamaterials are a type of groundbreaking engineered materials with unique properties not found in natural substances. Lattice metamaterials, which have a periodic lattice cell structure, possess exceptional attributes such as a negative Poisson’s ratio, high stiffness-to-weight ratios, and outstanding energy dissipation capabilities. This review provides a comprehensive examination of lattice metamaterials. It covers their various structures and fabrication methods. The review emphasizes the crucial role of homogenization methods and multi-scale modeling in assessing metamaterial properties. It also highlights the advancement of topology optimization through advanced computational techniques, such as finite element analysis simulations and machine learning algorithms.

Heat sink design and topology optimization of a DC/AC converter for a general aviation hybrid-electric aircraft

This work aims to explore the potential of topology optimization in the design of forced air-cooled heat sinks for inverters equipping hybrid-electric aeronautical propulsion systems. Compared to the automotive applications that are driving the electrification of the transportation sector, the design of heat sinks in aircraft requires minimizing not only the thermal resistance and pumping power of the fans, but also the weight and volume. The challenge is further made more difficult by ambient air temperature and density that vary with the aircraft’s altitude. Considering the inverter of a real aircraft equipped with a hybrid electric propulsion system, the authors first designed conventional heat sinks with finned configurations by applying semi-empirical formulations and then a free-form heat sink by exploiting topology optimization. Conventional heat sinks serve as a reference for carrying out the evaluation with heat sinks based on topology optimization. The latter prove to be characterized by superior performance as the thermal resistance is up to 7 % lower, the pumping power of the fan is reduced by 34 % at the same inlet velocity and the weight saving is around 45 %. Finally, the heat sinks were verified at the system level by having their models integrated into a completed aircraft model.

Topology Optimization of Planar Microphone Array Based on NSGA-II

Topology Optimization of Planar Microphone Array Based on NSGA-II

Evaluation of complaint damper for assessing its effectiveness and efficiency through the utilization of topology optimization

Evaluation of complaint damper for assessing its effectiveness and efficiency through the utilization of topology optimization

Level-set topology optimization with PDE generated conformal meshes

This paper presents a level-set topology optimization approach that uses conformal meshes for the analysis of the displacement field. The structure’s boundary is represented by the iso-contour of a level-set field discretized on a fixed background design mesh. The conformal mesh is updated for each design iteration via a PDE based mesh morphing process that identifies the set of facets in the background mesh that are homeomorphic to the boundary and relaxes the homeomorphic mesh to conform to the structure’s boundary and ensure high element quality. The conformal mesh allows for a more accurate computation of the response versus density and some level-set based methods which interpolate material properties using the volume fraction. Numerical examples illustrate the proposed approach by optimizing linear-elastic two- and three-dimensional structures, wherein insight into the performance of the mesh morphing process is provided. The examples also highlight the scalability of the approach.

Topology Optimization of the Transmitter Ferrite and Receiver Coil for Minimizing the Weight of the Wireless-Charging Portable Devices

Topology Optimization of the Transmitter Ferrite and Receiver Coil for Minimizing the Weight of the Wireless-Charging Portable Devices

Enhanced Hybrid Congestion Mitigation Strategy for ‘6LoWPAN-RPL based patient-centric IoHT’

The Internet of Healthcare Things (IoHT) is rapidly evolving, providing new opportunities to enhance healthcare delivery. However, the resource limitation of connected medical sensing devices leads to congestion, resulting in reduced network performance, delayed data transmission, and loss of critical medical information, which can have significant consequences in healthcare. To address this issue, this paper proposes an Enhanced Hybrid Congestion Mitigation Strategy (EHCMS) for IPv6 over low-power wireless personal area networks (6LoWPAN) and routing protocol for low-Power and lossy networks (RPL) based patient-centric IoHT (PC-IoHT). The EHCMS combines several techniques, including traffic management, network topology optimization, and load balancing, to enhance network performance and reduce congestion. The proposed framework is a hybrid strategy that utilizes resource- and traffic-control mechanisms to alleviate congestion in the 6LoWPAN-RPL-based patient-centric IoHT network. For the resource-control-based approach, a congestion-aware composite objective function is designed using a few congestion-specific routing metrics and formulated as a multi-attribute decision-making problem solved using Grey relational analysis (GRA). In addition, a non-linear multi-criteria optimization problem-based transmission rate adaptation mechanism is contrived as a traffic-control scheme for congestion mitigation. The effectiveness of the proposed EHCMS is evaluated using simulations on the Cooja simulator in the Contiki-3.0 OS and compared with existing congestion-alleviating strategies. The results demonstrate that the proposed framework can significantly reduce congestion in the IoHT network, perform better than existing works, and improve the quality of service. This research paper contributes to the field of IoHT by proposing an effective congestion mitigation strategy that enhances the reliability and performance of the PC-IoHT network, ultimately improving the quality of healthcare delivery.

Topology optimization of coronary artery stent considering structural and hemodynamic parameters

In the present study, the impact of geometric variables and structural features of stents on hemodynamic parameters is investigated. Intravascular stent implantation is a treatment method whose success largely depends on the geometric structure of the stent and its effect on hemodynamic parameters. Medical devices called stents are inserted into arteries to restore blood flow when an artery is blocked. In this research, an optimal stent was designed and its effect compared to the common commercial stent used for coronary arteries was investigated and compared. It has been found that the geometry of the stent has an effective impact on the wall shear stress in the stented artery. Therefore, in this article, the importance of stent structures in the treatment of the coronary artery disease is discussed. For this purpose, first, an optimal stent is created with the topology optimization technique to find the best structure in the stent design. Finally, the optimized stent is numerically verified with ANSYS software and compared with existing commercial stents, and then the prototype is fabricated using additive manufacturing techniques. Commercial software ABAQUS, SolidWorks, and ANSYS are used in this research. The results showed that in optimizing a square plate, a sample with a minimum residual volume limit equal to 10 and 7 % can be selected as the optimal state. The results indicate that the new design can improve the distribution of wall shear stresses to reduce the adverse hemodynamic changes. Therefore, the proposed stent geometric structure can help improve the treatment. Finally, the optimized stent along with a commercial stent was made with the 3D printing method.