Structural Design Optimization Research Articles

Parameter and Topology Optimization of Structures in the Frequency Domain under Nevanlinna–Pick Interpolation Constraints

The design optimization of structures can be conducted in either the time domain or the frequency domain. The frequency domain approach is advantageous compared to its time domain counterpart, especially if the degree of freedom is large, the objectives and/or constraints are formulated in the frequency domain, or the structure is subject to random loading. In this paper, an attempt is undertaken to obtain feasible optimal solutions by implementing the Nevanlinna–Pick (NP) interpolation theory across multi-objective structural optimization problems in the frequency domain. The NP equations introduce a trade-off that originates from the interpolation theory for complex variables. According to the NP theory, a complex function cannot have an independent amplitude from its derivative at a certain frequency. Consequently, the frequency response of a physical system cannot be shaped arbitrarily at discrete frequencies. Our objectives within this paper include calculating the weight, natural frequency, fatigue life, frequency domain response, and its derivative. To illustrate our claims, sample parameter and topology optimization problems were formulated and solved, both with and without the NP constraints. It was found that the inclusion of NP constraints induced a considerable improvement in the optimal solutions, while also causing the convergence to the optimal solution to become smoother.

A Formulation of Structural Design Optimization Problems for Quantum Annealing

We present a novel formulation of structural design optimization problems specifically tailored to be solved by qa. Structural design optimization aims to find the best, i.e., material-efficient yet high-performance, configuration of a structure. To this end, computational optimization strategies can be employed, where a recently evolving strategy based on quantum mechanical effects is qa. This approach requires the optimization problem to be present, e.g., as a qubo model. Thus, we develop a novel formulation of the optimization problem. The latter typically involves an analysis model for the component. Here, we use energy minimization principles that govern the behavior of structures under applied loads. This allows us to state the optimization problem as one overall minimization problem. Next, we map this to a qubo problem that can be immediately solved by qa. We validate the proposed approach using a size optimization problem of a compound rod under self-weight loading. To this end, we develop strategies to account for the limitations of currently available hardware. Remarkably, for small-scale problems, our approach showcases functionality on today’s hardware such that this study can lay the groundwork for continued exploration of qa’s impact on engineering design optimization problems.

Machine learning and sequential subdomain optimization for ultrafast inverse design of 4D-printed active composite structures

Shape transformations of active composites (ACs) depend on the spatial distribution and active response of constituent materials. Voxel-level complex material distributions offer a vast possibility for attainable shape changes of 4D-printed ACs, while also posing a significant challenge in efficiently designing material distributions to achieve target shape changes. Here, we present an integrated machine learning (ML) and sequential subdomain optimization (SSO) approach for ultrafast inverse designs of 4D-printed AC structures. By leveraging the inherent sequential dependency, a recurrent neural network ML model and SSO are seamlessly integrated. For multiple target shapes of various complexities, ML-SSO demonstrates superior performance in optimization accuracy and speed, delivering results within second(s). When integrated with computer vision, ML-SSO also enables an ultrafast, streamlined design-fabrication paradigm based on hand-drawn targets. Furthermore, ML-SSO empowered with a splicing strategy is capable of designing diverse lengthwise voxel configurations, thus showing exceptional adaptability to intricate target shapes with different lengths without compromising high speed and accuracy. As a comparison, for the benchmark three-period shape, the finite element and evolutionary algorithm (EA) method was estimated to need 219 days for the inverse design; the ML-EA achieved the design in 54 min; the new ML-SSO with splicing strategy requires only 1.97 s. By further leveraging appropriate symmetries, the highly efficient ML-SSO is employed to design active shape changes of 4D-printed lattice structures. The new ML-SSO approach thus provides a highly efficient tool for the design of various 4D-printed, shape-morphing AC structures.

Comprehensive design optimization of vertical seismic absorbers incorporating sensitivity and robust analysis: A case study of the KDamper

This study presents a comprehensive design optimization approach for building vibration control systems, demonstrated through a case study on the KDamper implemented as a vertical seismic absorber (VSA). The methodology encompasses a series of steps to identify the most suitable VSA design while maximizing the utilization of available resources and considering model and reality imperfections. The outcomes of this investigation include a Pareto front featuring optimal structures and a set of design guidelines specifically tailored for the development of a VSA system. Moreover, optimization analyses conducted on simplified systems have revealed their potential effectiveness even without certain components. Furthermore, a bi-objective robust optimization has demonstrated the system’s resilience to manufacturing uncertainties prevalent in real-world scenarios. Finally, this approach has yielded more consistent system performance than conventional optimization approaches. The proposed methodology holds broad applicability to diverse systems, offering valuable support in achieving widespread utilization and facilitating the design of optimal structures, such as the vibration-absorption system examined in this study.

The flow field simulation and suction structure optimal design of the dual-airway pneumatic fallen jujube fruit pickup device​

The flow field simulation and suction structure optimal design of the dual-airway pneumatic fallen jujube fruit pickup device​

Shape optimization of sound barriers using an isogeometric meshless method

The sound barrier is an important means to reduce noise caused by traveling vehicles on roads or railways. Structural design and optimization of the sound barrier can effectively reduce the use of materials and improve the noise reduction effect. In this paper, a new isogeometric singular boundary method is proposed and applied to the shape optimization of sound barriers. The geometric structure is accurately represented by using non-uniform rational B-splines. The acoustic shape sensitivity of the control points was calculated using the direct differentiation method and the adjoint variable method. After that, the method of moving asymptotes is adopted as an optimizer to search for the optimal layout of the design objective. In the numerical procedure, the shoelace formula is introduced to calculate the area of the closed structure, which only uses the discrete node information on the boundary. The proposed approach completely avoids the mesh division in the finite element method as well as the singular integral calculation in the boundary element method. More importantly, it can be seamlessly connected with the computer-aided design system for the subsequent treatment by engineers. Three numerical examples are provided to illustrate the accuracy and effectiveness of the proposed isogeometric method. This work provides a simple and effective way for the structural optimization design of sound barriers.

Study on damage mechanism and damage distribution of the rear plate under impact of debris cloud

The debris cloud generated by the hypervelocity impact (HVI) of orbiting space debris directly threatens the spacecraft. A full understanding of the damage mechanism of rear plate is useful for the optimal design of protective structures. In this study, the hypervelocity yaw impact of a cylindrical aluminum projectile on a double-layer aluminum plate is simulated by the FE-SPH adaptive method, and the damage process of the rear plate under the impact of the debris cloud is analyzed based on the debris cloud structure. The damage process can be divided into the main impact stage of the debris cloud and the structural response of the rear plate. The main impact stage lasts a short time and is the basis of the rear plate damage. In the stage of structure response, the continuous deformation and inertial motion of the rear plate dominate the perforation of the rear plate. We further analyze the damage mechanism and damage distribution characteristics of the rear plate in detail. Moreover, the connection between velocity space and position space of the debris cloud is established, which promotes the general analysis of the damage law of debris cloud. Based on the relationship, the features of typical damage areas are identified by the localized fine analysis. Both the cumulative effect and structural response cause the perforation of rear plate; in the non-perforated area, cratering by the impact of hazardous fragments is the main damage mode of the rear plate.

Multi-objective topology optimization for thermo-elastic systems based on periodic constraints

Thermo-elastic systems have a wide range of applications in various engineering fields. Traditional single-objective topology optimization (TO) design of thermos-elastic structures is difficult to achieve the combined optimum of multiple properties, and the non-periodic TO design of results are complex and difficult to fabricate. This paper introduces a multi-objective TO formulation based on density for designing thermo-elastic structures with periodic constraints, aiming to overcome the aforementioned issues. This paper assesses two competing weighted objective functions, the first function corresponds to structural and thermal compliance, while the second pertains to regional temperature and global stress. To solve the optimization issue, we utilize the p-norm function with a modified coefficient for evaluating the maximum temperature and stress values. Additionally, the adjoint variable method is employed to evaluate the sensitivity of various objectives, while the method of moving asymptotes (MMA) is used to update the design variables. Then the influence of different weight coefficients and subregion numbers regarding thermos-elastic coupled analysis is demonstrated through numerical examples. The results show that the complexity of the subregion features decreases as the number of subregions increases, and that changing both the number of subregions and the weighting coefficients results in changes in the overall structural performance. Finally, the geometric model is reconstructed using the TO results, and the structural performance is validated through the simulation of the reconstructed model. The results indicate that the TO results obtained by the method of this paper have predefined performance.

Optimization of Structural Design in Steel Buildings Based on the Site-Specific Design Spectra of the Mexico Seismic Regulations

Optimization of Structural Design in Steel Buildings Based on the Site-Specific Design Spectra of the Mexico Seismic Regulations

A numerical study on load effects of low-rise buildings in a wind-blown sand environment

The transportation process of wind-blown sand, represented by sandstorms, occurs frequently in arid and semi-arid regions. The combined action of wind and sand impact load in a wind-sand environment poses a serious threat to the safety of construction, transportation and other engineering structures. However, most of the current structural designs only considers the effect of wind, and there is little detailed research on the surface load distribution of structures caused by sand impact, which leads to uncertainty in the safety assessment of engineering structures in wind-sand areas. In this paper, low-rise buildings which are easily damaged in strong wind-sand environments are taken as the research object. A numerical model of coupling turbulent wind field and particle motion was then established, and the reliability of the numerical simulation results was verified through wind tunnel experiments. Finally, the wind-sand movement around the low-rise building model and the load distribution characteristics on the building surface are simulated under different wind speed and sand concentration conditions. The results show that the edges and corners of engineering structures are subject to more severe particle erosion-abrasion. As the sand concentration increases in the flow field, the wind speed and the wind load acting on the structures weakens. Whereas the sand impact load increases with the increment of wind speed and sand concentration. The increased effect of sand particles on the total load can be considered by amplifying the wind load shape coefficient on the windward side. This study is helpful to understand the mechanism of sand wind-induced damage on low-rise buildings, and provides basic tools and a theoretical basis for the wind and wind-blown sand resistance design and performance optimization of engineering structures.

Meso-structural optimization design of multifarious and complex fabric rubber composite structure

Fabric clothes are widely used to toughen the fabric rubber composite structure due to their strong designability and flexibility. The diversity and complexity of the meso-structural forms of fabric clothes bring great challenges to the efficient design of meso-structures of fabric rubber composite structure. The current studies are difficult to design the fabric rubber composite structure with complex structural forms whatever at macroscale or mesoscale. In this paper, the multiscale optimization design method of fabric rubber composite structure is established. Initially, the anisotropic theoretical models of the textile fabric rubber composite and reticulated fabric rubber composite are proposed based on meso-structural forms of the textile fabric and reticulated fabric. Then, the multiscale optimization framework and optimization process of fabric rubber composite structure, as well as the calculation methods of constraints and optimization objectives are established. Finally, the optimal meso-structures of textile fabric and reticulated fabric obtained by three optimization algorithms are compared. The results show that the difference of optimal meso-structures obtained by the three optimization algorithms is mainly reflected in the reticulated fabric. It is expected that the multiscale optimization design method has important scientific guiding significance for the performance improvement of fabric rubber composite structure.

Non‐uniform voltage distribution characteristics of metallized film capacitors in flexible HVDC projects

AbstractThe problem of non‐uniform voltage distribution in the internal element of metallized film capacitors in flexible HVDC transmission systems exists, the influence of electrical parameters of dielectric and metal copper row are not considered in the existing metallized film capacitor equivalent circuit model. In this paper, the conductance of biaxially oriented polypropylene film (BOPP) for metalized film capacitors is measured at different electric field intensity and dielectric properties at different frequencies. The current density distribution and voltammetric properties of the metalized film capacitor elements under AC and DC superimposed voltages are calculated by the finite element method, and the voltammetric properties of the copper row considering the skin effect are derived. The equivalent circuit model of the metalized film capacitor under the AC‐DC superposition voltage is proposed. The simulation results of the capacitor equivalent circuit model show that the voltage distribution of the internal elements of the capacitor is uniform at low frequency AC voltages (<102 Hz), and the voltage amplitude and phase difference between the elements of the capacitor gradually increases with increasing AC voltage frequency. At an AC voltage frequency of 105 Hz, the difference in magnitude between the two capacitor elements on the same copper row was up to 2.01% and the phase difference was 13.5%, while the difference in magnitude between capacitors at the same horizontal position on different copper rows was up to 56.8% and the phase difference was 10.44%. The results of this paper provide some guidance for the modeling of the internal components of metalized film capacitors, the calculation of voltage distribution and the structural optimization design.

Experimental and numerical study of corrugated steel-plain concrete composite structures under contact explosions

This paper investigates the dynamic response and blast resistance of corrugated steel-plain concrete (CSPC) composite structures subjected to contact blast. A series of explosive tests were conducted to investigate the acceleration, deformation, and damage patterns of CSPC plates under varying blast loads and arrangements of shear connectors, and these findings were compared with reinforced concrete (RC) plates. The results suggested that CSPC plates exhibited superior ductility and blast resistance, and effectively mitigated concrete collapse. The CSPC slab primarily underwent elastic deformation when the TNT charge was small, with the rebound deformation of the concrete and steel plates acting as a significant mode of energy dissipation. As for larger TNT charges, the maximum deformation of the plate progressively increased, especially when exceeding 0.3 kg, the deformation rebound ratio decreased significantly, and the plastic deformation increased. For further increased explosive loads, the concrete and steel plates exhibited a pronounced strain rate effect with a slowed growth rate of deformation. By examining different configurations of shear connectors, it was discovered that the adhesive strength between concrete and steel plates was closely related to the energy dissipation mode, and the elastic recovery capability and deformation resistance of the CSPC structure significantly deteriorated when the shear connectors were shorter, sparser or thinner. A numerical model based on LS-DYNA was designed to further analyze the blast resistance characteristics of CSPC plates. An engineering collapse coefficient Kz was established to predict the failure level of the CSPC plates. This paper provides useful insights for the optimal design and damage assessment of CSPC composite structures.

SABO algorithm for optimum design of truss structures with multiple frequency constraints

In this study, a very recently developed intelligent algorithm called the self-adaptive bonomo optimizer (SABO) algorithm is implemented for the size and shape optimizations of the truss structures with the multiple frequency constraints. The bonomo optimizer (BO) algorithm is a recently developed metaheuristic optimization algorithm that imitates the social behavior and reproductive schemes of the bonobos and this algorithm is successfully applied to solve some challenging and highly nonlinear optimization problems. On the other hand, the BO algorithm suffers from the poor exploration and prematurely converges to the non-optimal solutions, especially when dealing with the multi-dimensional optimization problems. In order to overcome these shortcomings, an improved version of this algorithm, the so-called self-adaptive bonomo optimizer (SABO) algorithm, is utilized to optimize the truss structures subjected to the design constraints. The objective of this study is to minimize the weight of the truss structures with the multiple frequency constraints. Five well-known benchmark problems are considered to verify the robustness and reliability of the SABO algorithm. The design results obtained by the SABO algorithm are compared with those previously reported in the literature.

Optimization of parameters for a fringe projection measurement system by use of an improved differential evolution method.

Fringe projection 3D measurement is widely used for object surface reconstruction. While improving measurement accuracy is a crucial task. Measurement accuracy is profoundly affected by various optical structural parameters. However, the current practice of system construction lacks theoretical guidelines and often relies on the experience of the operator, inevitably leading to unpredictable error. This paper investigates a theoretical optimization model and proposes an automatic optimization method for qualitatively determining the multiple optimal optical structural parameters in fringe projection measurement system. The aim is to enhance measurement accuracy conducting a rational comprehensive optimal structural parameters design prior to the system construction. Firstly, the mathematical model of the measurement system is established based on the principle of optical triangulation, and the phase sensitivity criterion is defined as the optimization norm. Within the full measurement range, the optimization merit function is formulated by combing three positions: the center position, the left and right boundary of the CCD. The imaging effectiveness criteria and sensor geometric dimensions are taken into account as the constraint boundaries. Subsequently, a combined improved differential evolution and Levy flight optimization algorithm is applied to search for the optimal parameters. The optimal structural parameters of the system were designed based on the optimization process. Experimental results validated the improvement in measurement accuracy achieved by the optimized structural parameters.

Topological optimization design for support structure under multiple loading conditions

In view of the lightweight and high stiffness requirements of a certain type of spacecraft support, combined with the special performance and environment of the support, topology optimization technology is introduced into the optimal design of the support structure in the space field. The topology optimization and design of the support are carried out with the stiffness as the objective function and the quality as the constraint condition, and the design of "space hugging configuration" is proposed, and the simulation verification and experimental verification are carried out. Firstly, different load conditions of the support were analyzed and studied. Secondly, the initial model was established based on the relative position relationship between the support and the mounting surface of the loaded equipment. Finally, a design method of the support structure was established based on the combination of topology optimization under multi-load conditions and size optimization considering the influence of strength. The stiffness and strength of the optimized structure were checked under multiple load conditions, and the fundamental frequency was 2.05 times of the index requirement. The maximum response stress is lower than the yield limit of the material used, which meets the strength requirement. Finally, the vibration test is carried out to verify the support. After the test is completed, the position accuracy of the support interface meets the requirements of the index. The obtained bracket has high structural stability, meets the high performance requirements of the load equipment, verifies the feasibility of the topology optimization method, and provides an effective method for the design of lightweight high-stiffness structures.

A new sensitivity-based robust optimisation of structures under bounded type uncertainty

This paper deals with robust design optimisation (RDO) of structures when uncertainty information about system parameters is limited. For such parameters, neither the statistical moments, nor the probability distribution is available. Rather, based on practical considerations, only bounds of variations of such parameters under uncertainty can be set, which is in-turn used to model them as uncertain-but-bounded (UBB) type. In recent years, convex programming (CP) approaches are used to solve RDO problem with UBB parameters. However, these approaches generally do not consider sensitivity information while formulating an RDO problem. However, it is well accepted that sensitivity is the key focus of an RDO as by definition a robust design should be least sensitive to uncertainty effects. Thus, a new sensitivity-importance-based RDO formulation is proposed in this paper, where a new sensitivity index is defined and minimised along with the usual cost function subjected to a dispersion-related constraint. Then, the proposed RDO is solved through usual CP framework. The improvement by the proposed approach is demonstrated taking four application examples. The results indicate that the proposed approach yields more robust solutions compared to the conventional approaches.

A methodology for stress-strain behavior characterization and mixture optimization of recycled aggregate concrete based on machine learning

The characterization of stress-strain behaviors of recycled aggregate concrete (RAC) excluding physical properties of recycled aggregates (RAs) may result in an inaccurate prediction of mechanical responses in practical applications. In this study, a data-driven model using a refined long short-term memory (LSTM) network is established based on the Bayesian optimization algorithm, with the motivation to accurately predict the uniaxial compressive stress-strain behaviors of RAC, including the stress-strain relation, elastic modulus, peak stress, and the peak strain. Training and testing of the proposed model require the integration of the mixture content and the fundamental physical properties of RAs with the stress-strain relation of ordinary concrete featured by prominent sequential attributes. Upon a dataset containing 100 experimental samples from independent studies, covering a wide range of RA substitution rates, the superior prediction capability of the proposed LSTM network is demonstrated in comparison with the analytical results of three empirical mechanics-driven models. Finally, the trained LSTM network is further employed to optimize the mixture for RAC using the Bayesian optimization technique innovatively, to achieve a balance between the mechanical performance and requirement to the quality of RAs. This study constitutes a beneficial addition to the understanding of the RAs-dependent stress-strain behaviors of RAC from the perspective of the data paradigm and provides a practical tool for the optimal design of RAC materials and structures.

Reconfiguration of stability and control strategy for some unmanned deformable vehicles

An unmanned deformable vehicle can switch between wheeled driving and legged walking through reconfiguration. The system is prone to tipping instability when reconstructing from a vehicle state in wheeled motion to a humanoid state in legged motion. To improve reconfiguration stability, a center-of-mass position-adjusting mechanism was designed based on structure optimization design for the unmanned deformable vehicle. The zero moment point was adjusted by controlling a center-of-mass position-adjusting mechanism, thereby further improving the reconfiguration stability of the system. In this study, the structure of the unmanned deformable vehicle was designed and a reconfiguration kinematic model was established based on spinor theory. A reconfiguration dynamic model was established based on Newton-Euler equation, and the zero moment point was used as the stability criterion for the reconfiguration motion. To improve the reconfiguration stability of the system, simulated annealing algorithm was used to optimize the main parameters of the system under both basic and severe working condition reconfiguration processes. To further improve the reconfiguration stability, a variable universe-fuzzy control strategy was designed to control the stability of the reconfiguration process of the whole vehicle. The results showed that the reconfiguration stability could be significantly improved under various working conditions by using the stability control after the system was optimally designed.

Carbon Nanofibers-Based Anodes for Potassium-Ion Battery.

In recent years, with the global warming getting worse and increasing demand for energy, countries around the world are trying to develop new energy storage technologies to solve this problem. Currently, potassium-ion batteries (PIBs) have attracted tremendous attention from researchers as low-cost and high-performance energy storage devices. However, due to the huge ionic radius of K+, PIBs face significant volume expansion during cycling, which can easily lead to the collapse of electrode structures. In addition, the poor diffusion kinetics of K+ seriously affect the electrochemical performance of the battery. Carbon nanofibers (CNFs)-based materials (including CNFs, metal/CNFs composites, chalcogenide/CNFs composites, and other CNFs-based materials) are widely used as PIBs electrode anode materials due to their three-dimensional conductive network, heteroatom doping and excellent mechanical properties. This review discusses in detail the research progress of CNFs-based materials in PIBs, including material preparation, structural design, and performance optimization. On this basis, this article explores the key issues faced by CNFs-based materials and future development directions, and proposes improvement suggestions for providing new ideas for the development of CNFs-based materials.