Structural Design Optimization Research Articles

Vehicle vibration test platform structure design and control strategy optimization

AbstractFor the needs of vehicle vibration test platform with high precision, large load capacity and fast response, the three‐dimensional model design and analysis of vehicle vibration test platform are carried out; in order to improve the motion performance of the platform, a vibration test plat‐form control strategy combining hybrid heuristic algorithm and PID control is proposed. Based on the designed 3D model parameters, the single‐channel mathematical model of the servo‐electric cylinder is derived and a hybrid heuristic algorithm PID optimization model is established to compare and analyze the control performance of the platform with the Ziegler‐Nichols method PID. The results show that the step system overshoot is 3.80% and the dynamic performance of the system is significantly improved when the hybrid heuristic algorithm PID control is used. The simulation system model of vehicle vibration test platform control is established, and the operation results show that the platform is closer to the input signal in the spatial position change curve when the hybrid heuristic algorithm PID control is used. Its maximum displacement error is 0.09 mm, and the motion accuracy of the system is improved by 61% compared with the Ziegler‐Nichols method PID control.

Multi-scale collaborative prediction of optimal configuration for carbon fiber woven composites based on deep learning neural networks

Since carbon fiber woven composite panels contain complex fiber bundle structures, the aim of this paper is to investigate the factors influencing the macro-equivalent properties and topological flexibility of composite panels resulting from variations in fiber bundle configuration. Firstly, the structural topology optimization design of carbon fiber composite plates was achieved using a multi-scale modeling approach with the variable density method. Nonlinear relationships between carbon fiber bundle configuration parameters and macroscopic equivalent properties, as well as macroscale topological flexibility, were determined using deep learning methods, respectively. The maximum error in the predicted values of the deep learning network model does not exceed 0.5% when compared with the results of the finite element calculations. In addition, utilizing deep learning networks to predict macro-equivalent properties of composites can significantly decrease computational time. The impact of varying the number of filaments in fiber bundles and the spacing of the fiber bundles on the flexibility of the topology was determined using a deep learning network. The optimal topological flexibility, along with its corresponding fiber bundle spacing and number of fiber bundle filaments, are globally searched within the design domain using an adaptive genetic algorithm. The study in this paper can provide a reference for designing fiber bundle configurations of composites for practical applications.

Study on Ring Deformation and Contact Characteristics of Thin-Walled Bearing for RV Reducer

The thin-walled rings of the RV reducer main bearings are prone to structural elastic deformation, which can significantly change the bearing mechanical characteristics. According to the actual assembly state of the RV reducer, the simulation model of the planetary frame–main bearings–pin gear housing is established considering the ring deformation. The model was used to calculate and comparatively analyze the ring deformation and contact characteristics of thin-walled bearings under rigid and flexible conditions, on the basis of which the mechanism of ring deformation was described, and the effects of load conditions, ring thickness and radial clearance on ring deformation, flexible contact characteristics, and ultimate carrying capacity were analyzed. The results show that the distribution of contact loads is the main factor affecting the ring deformation. The ring deformation can optimize the bearing contact characteristics, and the greater the deformation, the more pronounced the optimization effect. However, excessive ring deformation makes the contact ellipse more susceptible to truncation, which, in turn, reduces the ultimate carrying capacity. This study indicates a 38.2% decrease in the carrying capacity of the flexible ring model compared to that of the rigid ring model. In this paper, the effect of ring deformation on bearing mechanical characteristics is deeply discussed. The research results have important guiding significance for the structural optimization design of thin-walled bearings.

Biopolymer Meets Nanoclay: Rational Fabrication of Superb Adsorption Beads from Green Precursors for Efficient Capture of Pb(II) and Dyes.

Renewable, green, and safe natural biopolymer-derived materials are highly desired for the purification of pollutants, but significantly improving their performance without the introduction of additional harmful chemicals remains a huge challenge. Based on the concept of "structure optimization design", environment-friendly composite beads (named SA/PASP/RE) with excellent adsorption performance and recyclability were rationally constructed through a green ionic crosslinking route, using the completely green biopolymer sodium alginate (SA), sodium salt of polyaspartic acid (PASP), and the natural nanoclay rectorite (RE) as starting materials. The nano-layered RE was embedded in the polymer matrix to prevent the polymer chain from becoming over-entangled so that more adsorption sites inside the polymer network were exposed, which effectively improved the mass transfer efficiency of the adsorbent and the removal rate of contaminants. The composite beads embedded with 0.6% RE showed high adsorption capacities of 211.78, 197.13, and 195.69 mg/g for Pb(II) and 643.00, 577.80, and 567.10 mg/g for methylene blue (MB) in Yellow River water, Yangtze River water, and tap water, respectively. And the beads embedded with 43% RE could efficiently adsorb Pb(II) and MB with high capacities of 187.78 mg/g and 586.46 mg/g, respectively. This study provides a new route to design and develop a green, cost-effective, and efficient adsorbent for the decontamination of wastewater.

Performance assessment and optimisation of a concentric two-piston compressor system for hydrogen storage

The ionic compressor has a prospective application potential for the conversion of mechanical energy into internal energy in high-pressure hydrogen as the ionic liquid can separate the metal piston and the hydrogen gas. The sloshing of the liquid inside is inevitable in such a liquid piston compressor, which has an impact on the specific energy consumption of the hydrogen compression. The thermofluid behaviour of this liquid sloshing can be effectively influenced by the baffle structure and piston trajectory. A novel concentric two-piston compressor is proposed in this paper, which has a unique structure that can act as a baffle inside and actively influences the fluid flow by adjusting the piston trajectory. The quantitative influence of key structural design factors on the compressor performance is investigated by mathematical modelling, based on which the optimal structural design was obtained by Taguchi and analysis of variance methods. Results indicate that the diameter ratio of Piston A to Piston B is the dominating factor for both the mass delivered and the specific energy consumption. With the optimal design in the structure, the specific energy consumption is found as 2328.49 kJ/kg, where the mass delivered and power consumption are observed as 21.42 kg/h and 13.86 kW, respectively.

Study on design optimization of GFRP tubular column composite structure based on machine learning method.

Circular reinforced concrete wound glass fiber reinforced polymer (GFRP) columns and reinforced concrete filled GFRP columns are extensively utilized in civil engineering practice. Various factors influence the performance of these two types of GFRP columns, thereby impacting the whole project. Therefore, it is highly significant to establish the prediction models for ultimate displacement and ultimate bearing capacity to optimize the design of the two types of GFRP columns. In this study, based on the experiments conducted under different conditions on the two kinds of GFRP columns, automatic machine learning along with four other commonly used machine learning methods were employed for modeling to analyze how the column parameters (cross section shape, concrete strength, height of GFRP column, wound GFRP wall thickness, inner diameter of wound GFRP column) affect their performance. The differences in performance among these five machine learning methods were analyzed after modeling. Subsequently, we obtained the variation patterns in ultimate displacement and ultimate bearing capacity of the columns influenced by each parameter by testing the data using the optimal model. Based on these findings, the optimal design schemes for the two types of GFRP columns are proposed. The contribution of this paper is three-fold. First, AutoML sheds light on the automatic prediction of ultimate displacement and ultimate bearing capacity of GFRP column. Second, in this paper, two optimal design schemes of GFRP columns are proposed. Third, for AEC industrial practitioners, the whole process is automatic, accurate and less reliant on data expertise and the optimization design scheme proposed in the article is relatively scientific.

Investigations on the Johnson-Cook Constitutive and Damage-Fracture Model Parameters of a Q345C Steel

Due to the rapid development of high-speed trains, the service safety of vehicle body materials and structures has become a focal point in transport and impact engineering. Numerical simulations on the collision resistance of vehicle materials and structures are crucial for the safety assessment and optimal structural design of high-speed trains but have not been fully investigated due to the lack of damage model parameters. This study focuses on the Johnson-Cook (J-C) constitutive and damage-fracture models of a typical vehicle material, Q345C steel. A series of mechanical tests are conducted on the Q345C steel, including the quasi-static and dynamic compression/tension tests, quasi-static tension tests at different temperatures, and fracture tests along different stress paths, using the material test system and the split Hopkinson pressure/tension bar. Then, the parameters of the Johnson-Cook constitutive and damage-fracture models are calibrated based on the experimental results. In terms of the damage parameters related to stress paths, a new method of combining experiments and simulations is proposed to obtain the real, local fracture strains of the Q345C steel samples. This method allows the measurements of equivalent plastic strain and stress triaxiality histories under nonlinear stress paths, which are hardly accessible from individual experiments, and facilitates the accurate calibration of stress-path-related damage parameters. In addition, a high-speed plate penetration test is used to validate the J-C parameters, which can be directly implemented in the commercial finite element software Abaqus. The projectile trajectories from the simulation and experiment agree well with each other, demonstrating the reliability of the model parameters for impact scenarios and the efficiency of the experimental procedures utilized for calibration.

Numerical study on the melting performance of PCM by fractal fins in three-tube heat storage system

In order to solve the problems of low heat storage efficiency and uneven melting in the PCM area of the traditional heat accumulator, this paper takes the three-tube phase change heat accumulator with eight longitudinal fins as the basic structure to ensure that the volume of the fins in the heat accumulator is unchanged. The longitudinal fins are fractal in the shape of ' Y ', and the influence of the length and branch angle of the Y-shaped fins on the heat storage performance of the three-tube phase change heat accumulator is simulated by FLUENT software. The results show that the addition of fractal fins to the triple-tube phase change heat accumulator increases the heat transfer area and facilitates the development of natural convection compared with the addition of ordinary longitudinal straight fins, which effectively shortens the time required for the complete melting of PCM. After comprehensive analysis, the root and branch of Y-shaped fins account for 25% and 75% of the total length respectively, and the branch angle is 60°, which is the best Y-shaped fin structure. The complete melting rate of PCM is obviously improved. Compared with the ordinary straight fin heat accumulator, the heat storage rate is increased by 16.1%, and the overall heat storage performance is improved. By optimizing the design, it is found that the eccentricity has a significant effect on the melting process of the PCM. When the eccentricity is 11.5%, the overall heat storage time is the least. Compared with the original structure without eccentricity, the heat storage speed is increased, and the heat storage time is saved by about 14%. It provides a basis for the structural optimization design of phase change heat system.

Research on Optimization Design of Front and Side Structures under the 24th Edition of C-NACP Automotive Collision Standard

Structural crashworthiness plays a core role in vehicle safety design, mainly focusing on the maximum impact force that the body structure can withstand in collision accidents, and striving to maximize collision energy absorption to ensure that passengers have sufficient living space. The design of structural crashworthiness needs to consider the deformation mechanism and energy absorption characteristics of vehicles under different collision modes, and improve crashworthiness through material selection, structural optimization, and other means. In addition, the structural crashworthiness is closely connected to the passenger restraint system, which together constitute the key to the passive safety performance of the vehicle. In vehicle safety design, the improvement of structural crashworthiness can significantly enhance the vehicle's ability to protect passengers in collision accidents and reduce the risk of injury. Therefore, in-depth research on structural crashworthiness and the development of efficient crashworthiness structures are important directions for improving vehicle safety performance.

A generalized model for a triboelectric nanogenerator energy harvesting system

A triboelectric nanogenerator (TENG) energy harvesting system involves at least three components: the mechanical source that inputs mechanical energy to drive TENGs, the TENG device itself as an energy converter, and an external electrical circuit that output the energy from TENGs. Multiple theoretical models have been developed for structural optimization design and maximum power output, yet there has been less emphasis on dynamic modelling of the entire energy harvesting system. This work presents attempts to establish such system-level models that encompass both mechanical and electrical systems. Special consideration is paid to the dynamic contact problem in this generalized model, since dynamic response of impacts can significantly affect the electric outputs. To address contact constraint problems, the penalty function method is utilized to handle non-smoothness and discontinuity. Subsequently, this research specifies how to improve the maximum energy conversion efficiency, and suggest optimal executive strategies for maximizing the energy output through a thorough parametric study. The anticipated outcome is that the generalized model will not only guide optimization design and predict the dynamic characteristics of the energy harvesting system but also assess the potential feasibility of mechanical energy harvesting technology across diverse application domains.

Axial compression behavior of concrete-filled prefabricated aligned steel fiber UHPC tubes

This study presents an innovative composite column system featuring exceptional ductility and versatility, suitable for replacing traditional concrete columns or UHPC composite columns. The composite column, comprised of concrete-filled aligned steel fiber ultra-high performance concrete (UHPC) tubes (ASFUTs), offers superior mechanical properties. Apart from its function as a formwork, the ASFUT provides exceptional rigidity and lateral confinement capabilities, enabling it to withstand substantial axial forces directly. Initially, steel fibers were aligned using an electromagnetic field. Computed Tomography (CT) imaging elucidated an average inclination angle of 16.36° between the fibers and the circumference of ASFUT sections. Compared to conventional UHPC, aligned steel fiber UHPC demonstrates an average 9.1 % increase in compressive strength and an average 129.67 % increase in maximum equivalent tensile. This enhancement can be attributed to the improved fiber bridging effect resulting from the orientation of fibers. Then, the mechanical properties of the concrete-filled ASFUT columns were evaluated by axial compression testing of eight specimens with different fiber contents, shapes, and orientations. The findings indicate that the ASFUTs outperform conventional concrete-filled UHPC tubes, exhibiting notable enhancements across various performance metrics. Specifically, at a fiber volume fraction of 1 %, the concrete-filled ASFUT exhibits a compressive strength, elastic modulus, ductility, and energy dissipation capacity that are 1.12 times, 1.03 times, 1.25 times, and 1.54 times respectively, in comparison to conventional concrete-filled UHPC tubes. Finally, an advanced predictive model for estimating the axial bearing capacity of ASFUT concrete columns was proposed, offering valuable insights for structural design optimization and widespread implementation.

Structural Design and Performance Optimization of Green Concrete Based on Recycled Pumice and Modified Rubber Powder

Structural Design and Performance Optimization of Green Concrete Based on Recycled Pumice and Modified Rubber Powder

Deformation and failure of asymmetric sandwich structures under low-velocity impact

This work aims to analyze the dynamic response of asymmetry sandwich structure to low-velocity impact and study the influence of different panel thickness on sandwich structure impact performance. The failure mechanism is analyzed by combining experiment, theoretical analysis and simulation. The finite element model (FE model) was constructed in the software ABAQUS, and established a theoretical model to predicting the damage mode. Moreover, the optimal design of the asymmetric sandwich structure is studied by analyzed the EA and SEA of the structure. Pendulum impact test was carried out, the FE model was verified by experiment, and the theoretical model was verified by experiment and simulation. The results show that the front panel mainly affects the energy absorption capacity, and the back panel mainly affects the failure load. When both the front panel and the back panel are less than 1 mm, the structure shows panel fracture failure mode. When the front panel is less than 1 mm while the back panel is greater than 1 mm, intention failure mode occurs. When the front panel is greater than 1 mm, all failure modes of the structure are core shear failure. After research, when the thickness of the front panel is 2 mm and the thickness of the back panel is 3 mm, the EA and SEA are higher, and the structure is more economical.

Flexible composite structure with customizable in-plane Poisson’s ratio under large deformation

Regulating the inherent Poisson's ratio of soft elastic materials under large deformation is important for their application in emerging fields, such as morphing structures and stretchable electronics. In this study, we selected a composite in which an auxetic honeycomb was embedded in a soft material to regulate the in-plane Poisson's ratio. Based on a cantilever beam model, a theoretical model was established to guide the design optimization of composite structures. The macroscopic constitutive relation and in-plane Poisson's ratio of the composite structures with different configurations were predicted by the theoretical model, which were consistent with the finite element analysis results. In the 30% strain range, the slope of the Poisson's ratio–strain curve decreases with an increase in the length of the inclined bar, and the in-plane Poisson's ratio increases with an increase in the angle between the transverse bar and the inclined bar. In addition, we propose an optimization design method with the in-plane Poisson's ratio as the objective function and then optimize and fabricate a skin structure with an in-plane Poisson's ratio of approximately zero for the morphing wings. The achievements of this study provide theoretical guidance for regulating the in-plane Poisson's ratio of thin flexible layers.

Structure optimization design and performance analysis of liquid cooling plate for power battery

The structural design of liquid cooling plates represents a significant area of research within battery thermal management systems. In this study, we aimed to analyze the cooling performance of topological structures based on theoretical calculation and simple structures based on design experience to achieve the best comprehensive performance and analyze their operating environment characteristics. The COMSOL Multiphysics software and topology optimization method were used to calculate the topology structure. To assess performance, the numerical computation method was employed to simulate and calculate the optimized structure, comparing its temperature, velocity, and pressure related parameters and changes. Moreover, the study analyzed the impact of inlet flow velocity, ambient temperature, and coolant temperature on heat dissipation performance. The results revealed a reduction of 0.31 % in the highest temperature and a 21.20 % decrease in pressure drop for the topology-based results compared to the post-processing results. However, the cooling performance advantage offered by the topology structure was not significant, the enhancement in cooling performance did not offset the increase in production cost. Furthermore, we found that variations in service conditions influence the heat dissipation performance of liquid cooling plates, requiring comprehensive consideration when selecting condition parameters.

Modified genetic algorithm for optimal design of truss structures

In this paper, topology and shape optimization of truss or frame structures is discussed. The optimization starts from a structure, into which a finite number of nodesare set; all the nodes are connected together by trusses in all possible variants. Unfit variants of the truss system are rejected. Two alternative ways of the optimization are compared: topology optimization starting from initial structure with a larger number of nodes, and topology optimization starting from initial structure with smaller number of nodes but with additional shape optimization of the obtained topology. The topology optimization is solved with original modified genetic algorithm, giving better results in comparison with classical genetic algorithm. Instead of further development of constraint system, the additional step is introduced into algorithm – purification of genotype, which allows complementary improvement of particular population individuals, and together for the optimization process retains more possibilities than stiffening of constraints. The shape optimization is solved by classical genetic algorithm. Both strategies effectively improve the solution, however the common topology/shape optimization requires less computer resources. All numerical examples are obtained with original software developed by the authors.

Reliability analysis and optimization design of magnetic fluid dynamic seal shell structure under thermal/mechanical load

In order to study the reliability of Magnetic fluid dynamic seal shell structure under thermal/mechanical load, the improving cooling structure, calculating fuzzy fatigue reliability, and collaborative optimization design of fatigue reliability and lightweight are studied in this paper. The temperature model of the shell structure under four temperature conditions is established to analyze the influence of the thermal deformation caused by excessive local temperature. The cooling structure is improved, and the maximum temperature under the maximum temperature condition is reduced by 40.154 °C. For the sake of calculating the reliability of the new shell structure, a strength analysis model under thermal/mechanical load is built, and the fuzzy fatigue reliability function is obtained based on Latin hypercube sampling and the second-order response surface method. Four kinds of reliability are acquired by coding the functional functions and four kinds of membership functions with MATLAB, but all of them are lower than 90 % of the industrial requirements. To improve the reliability of the new shell structure and carry out the anti-fatigue lightweight design at the same time, an approximate model was constructed based on the interval analysis method and second-order response surface method for analysis. The accuracy of the approximate model was verified by re-sampling and finite element analysis. Based on the non-dominated sorting genetic algorithm, the optimal solution is determined. The optimization results show that the stress target value is reduced by 19.3 %, the weight target value is reduced by 3 %, and the fuzzy fatigue reliability reaches 94.65 %, 94.58 %, 93.89 %, and 96.31 % respectively. A new cooling structure of the Magnetic fluid dynamic seal is obtained and the maximum temperature is reduced. Moreover, the reliability of the new shell structure under thermal/mechanical load coupling is improved.

Calculation on maximum output power of wave energy-PTO system

The energy conversion efficiency of wave energy device is one of the key problems in the large-scale utilization of wave energy. The study of the maximum output POWER of PTO (Power-Take-Off) system provides a theoretical reference for the efficient utilization of energy. In this paper, genetic algorithm and adaptive differential evolution algorithm based on neighborhood search are used to optimize the two-objective multi-order differential equations for the maximum output power of PTO system, and the global optimal solution is obtained. Compared with the traversal algorithm, the algorithm involved in this paper is efficient and the optimal output power obtained can provide a scientific basis for the structural optimization design and material selection of the wave energy device.

Numerical simulation of the effect of jet small orifice structure on cavitation characteristic and jet impact flow field

The jet impingement-negative pressure deamination reactor (JI-NPDR) is a continuous, non-clogging, and efficient deamination equipment characterized by its simple structure. Research has demonstrated that the fluid passing through the jet orifices in the jet impact section of the reactor leads to partial cavitation. This situation directly impacts the flow characteristics before jet impact and the gas-liquid separation behavior in the negative pressure separation section. Therefore, this work proposes to utilize the CFD numerical simulation method to analyze the fluid cavitation evolution rules under the aspect ratio l/d structure of different jet orifices and to investigate the influence of orifice structure on the jet impact flow field. The results indicate that an increase in the liquid flow rate and the small orifice aspect ratio l/d promotes the conversion of pressure energy to kinetic energy, leading to an increase in cavitation intensity in the jet orifice. Furthermore, the evolution behavior of the jet impact flow field can be effectively controlled based on the l/d structural parameter of the small orifice aspect ratio. The research results can provide fundamental data support for the structural optimization design and engineering application of the JI-NPDR.

Topology Optimization Design and Mechanical Properties of 3D-Printed Solid-Lattice Hybrid Structures with Variable-Density or Iso-Density

Topology Optimization Design and Mechanical Properties of 3D-Printed Solid-Lattice Hybrid Structures with Variable-Density or Iso-Density