Structural Design Optimization Research Articles

Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components

Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components

Structural Design and Mechanical Properties Optimization of a Balanced Fiber-Reinforced Rubber Hose

This paper focuses on the optimal design of the structure of a balanced fiber-reinforced rubber hose (RH). A multi-spherical RH is proposed. Based on the grid method, the structure optimization design of single-spherical and multi-spherical RHs is performed. According to the constraints, the optimization results of the structural parameters of the RH are solved. Then, combined with the deformation characteristics of the conical RH, the cone-spherical RH is improved based on the spherical RH. The mechanical equilibrium angle and deformation expressions of the cone-spherical RH are deduced. The mechanical model of the balance performance, stiffness, and burst pressure for the cone-spherical RH is constructed. The structural optimization design of double-spherical and double cone-spherical RHs is performed to further reduce the stiffness of the RH based on the multi-spherical RH. Eventually, the correctness of the theoretical model and its optimization results is verified through experiments. The results of this research can provide reference data for future studies in related fields.

Numerical study of Steady-state dynamic characteristic of non-pneumatic tire with local structural damage

Non-pneumatic tires (NPTs) fundamentally avoid the risk of tire blowout of traditional pneumatic tires, but the overall and key component performance inevitably degrades due to factors such as high temperature, variable load, variable working conditions and impact in its service process. Once this leads to failure, it will significantly impact on vehicle safety. To this end, this paper studied the influence of local structural damage on the dynamic response of NPTs, which lays the foundation for realizing health monitoring of intelligent non-pneumatic tires (INPTs). Firstly, a three-dimensional nonlinear finite element model of NPTs was established, and the failure locations of NPTs were determined by fracture mechanics and maximum strain energy density; Secondly, the influence of structural damage on the static and dynamic performance of NPTs was analyzed; Finally, the sensitivity of the acceleration signal and sensor position of the tire inner liner to the local structural damage was studied. The research results show that structural damage will cause the stress of the spokes and shear layer to increase, and as the number of broken spokes increases, the shear layer will bear a larger load. Compared with the circumferential and lateral acceleration, the radial acceleration has the highest sensitivity to the damage of NPTs. The sensor closest to the damage location is the most sensitive to the damage. The research results provide a reference for the structural optimization design and health monitoring of INPTs.

Effects of structure parameter and material property on thermal performance of on-board hydrogen storage tanks during fast refueling

As a power generation fuel, high-pressure hydrogen gas is widely used in transportation, and significantly contributed to development of hydrogen fuel cell electric vehicles. However, obvious temperature rise generated during fast refueling causes serious safety risk to reliable operation of fuel cell stacks. Therefore, it is necessary to conduct in-depth researches on fast filling process. Based on safety reasons, the SAE J2601/ISO 15869 strictly regulates a maximum temperature limit of 85°C in specifications for refueling hydrogen gas tanks. In this study, a 70MPa, Type Ⅳ on-board hydrogen storage tank is adopted as the research object, and a 2-dimensional axisymmetric numerical model is established to study the temperature rise of storage tanks during fast refueling. The Realizable k-ε turbulence model is employed to simulate high intensity turbulent fluctuation during fast filling. Considering the compressibility of vapor, the state of equation for real hydrogen gas is used by obtaining fluid thermodynamic properties from the National Institute of Standards and Technology database. Three groups of fast filling experiments are selected to validate the developed numerical model. The comparison result shows that the numerical model has good prediction ability on hydrogen fast refueling. The final mass average temperature differences between numerical results and experimental data are 2.6K, 4.3K, and 0.03K, respectively. Based on the developed numerical model, the influences of structure parameters and material properties on the temperature rise of hydrogen storage tanks are investigated. The results indicate that the inlet diameter and wall thickness of the inner and outer layers of the storage tank have weaken impacts on the temperature rise during rapid charging, with maximum temperature differences of 1.8K, 0.74K, and 0.54K, respectively. Due to the influence of heat capacity, the material properties of different layers exhibit a similar variation trend. This work can deepen researchers' understanding of the temperature rise of on-board hydrogen storage tanks during fast filling, and provide technical references for the structural optimal design of tanks and rapid refueling at hydrogen stations.

Electromagnetic Fields Calculation and Optimization of Structural Parameters for Axial and Radial Helical Air-Core Inductors

To improve the current density distribution and electromagnetic performance of air-core inductors, a structural optimization method combining back-propagation(BP) neural network and genetic algorithm(GA) is proposed for the study of axial and radial spiral multi-winding inductors. The Monte Carlo method was used to extract the structural size samples of the inductors, and the training dataset was obtained through the finite element calculation of electromagnetic fields. Based on BP neural networks, nonlinear mapping models between the inductance value, volumetric inductance density, current distribution non-uniformity coefficient, and inductor structural parameters were constructed. A sensitivity analysis of the inductor inductance value affected by the structural parameters was conducted using the Sobol index calculation. Using the current distribution non-uniformity coefficient as the fitness function and the volumetric inductance density as the constraint condition, a genetic algorithm was applied to globally optimize the structural parameters of the inductor. The optimization results were verified through a finite element comparison. The results show that, under the requirement of satisfying the volumetric inductance density, the current distribution non-uniformity coefficient of the Axial Helical Inductor (AHI)-type inductor was reduced by 4.57% compared with the best sample in the sampling, while that of the Radial Helical Inductor (RHI)-type inductor was reduced by 5.33%, demonstrating the practicality of the BP-GA joint algorithm in the structural optimization design of inductors.

Multi-objective Optimization Design of a MDOF Structure with Attached Nonlinear Gas-spring Damper

Multi-objective Optimization Design of a MDOF Structure with Attached Nonlinear Gas-spring Damper

Research on the influence of unsteady cavitation on the dynamics structures of a twisted hydrofoil based on variational mode decomposition method

Cavitation will produce complex dynamic effects on hydrofoil structures. In this paper, the effects of unsteady cavitation conditions on the dynamics of twisted hydrofoil structures are studied by using variational mode decomposition (VMD) and pearson correlation coefficient (PCC), etc. The research results indicate that there is a certain synergy between the flow field pressure pulsation signal and the structural field stress-strain signal in the frequency distribution of the hydrofoil under cavitation conditions. The second-order center frequency of ΔP1 and the first-order center frequency of ΔP7 are close to the second-order center frequency of the stress-strain signal of the hydrofoil (1202.4Hz). Unsteady cavitation can lead to the increase of the high effective force region of the hydrofoil, especially the high effective force region connecting the leading edge and the root, which is the reason for the degradation of the hydrofoil performance. Cavitation increases the natural frequency of the hydrofoil, but has no obvious effect on the natural mode of the hydrofoil. The research results of this study reveal the effect of unsteady cavitation on the dynamics of hydrofoil structure, and provide important theoretical support for the optimization design and performance improvement of hydrofoil structure.

Historical evolution of structural optimization techniques for steel skeletal structures including industrial design applications

This study covers the review of algorithms developed for the optimum design of steel skeletal structures from the first article published in 1960 until to date. The paper initially describes the mathematical formulation of a simple truss structural design problem. The early optimum design algorithms that were based on mathematical programming techniques where the design variables are assumed to be continuous are reviewed. The optimum design of steel framed structures necessitates the selection of steel profiles from the standard list of discrete steel sections and requires the satisfaction of design code provisions. Both mathematical programming and optimality criteria techniques need more capability to produce solution to this type of optimum design problems. Soft computing techniques emerged recently provide solution directly without needing any approximation. These techniques are classified and reviewed and their use in obtaining the optimum solution of actual industrial steel design applications is given.

Mechanical Response and Anti-Reflective Crack Design in New Asphalt Overlays on Existing Asphalt Overlaying Composite Portland Cement Pavement

A detection and evaluation system containing a two-level index of structural integrity and bearing capacity was constructed based on ground-penetrating radar (GPR) and a falling weight deflector (FWD). This system was constructed to solve problems with the detection, evaluation, and structural and material design of asphalt rehabilitation for the prevention and control of asphalt reflection cracks in asphalt overlaying composite Portland cement pavement. Based on the detected data from the GPR and FWD, the reasonable and recommended thickness range of the stress-absorbing layer was determined by the finite element method, and the optimization design of an anti-reflective crack structure is proposed. Furthermore, a material design and engineering application of the stress-absorbing layer was carried out. The results show that an additional 10 cm layer of repaved asphalt can reduce temperature stress by 64.1%, reduce fatigue stress by 29.3% at the cement slab bottom, and extend the service life by 23.1 years. The reasonable thickness of the stress-absorbing layer ranges from 1.6 cm to 2.0 cm, and the recommended structural combination design is a 4 cm SMA-13 upper layer, a 4 cm AC-16 lower layer, and a 2 cm stress-absorbing layer overlaying existing asphalt overlay. The impact toughness of the designed stress-absorbing layer is 1.05 times and 1.44 times that of the other stress-absorbing layer and the AC-16 asphalt mixture, respectively, which have been successfully used for more than 5 years. The recommended design rehabilitation has good engineering application. The uniformity of the stress-absorbing layer can reach 63%, and an anti-reflective crack effect is expected. The results of this study provide design methodology and experience for composite pavement repaving.

Sustainable and cost-effective optimal design of steel structures by minimizing cutting trim losses

Since the beginning of the structural optimization field, the optimal design was characterized by the least-weight configuration. In this sense, all the researchers agreed on adopting the minimum-weight optimization statement as the most promising approach to achieve an optimized employment of material. However, especially for steel structures, this approach completely fails the primary goal of encouraging standardization of pieces during the production phase. Except for rare cases, increasing diversity among structural elements leads to a dramatic increase in the financial cost as well as the environmental impact of the structure because of the material waste generated during the cutting procedure.In this paper, a real-coded Genetic Algorithm has been adopted and the well-known one-dimensional Bin Packing Problem has been implemented within the structural optimization process. The Objective Function formulation lies in a marked change of the paradigm in which the target function is represented by the amount of steel required by the factory instead of the structural cost (e.g. weight). The proposed approach is tested on different steel structures moving from 2D truss beams to 3D domes. Addressing the optimal stock of existing elements leads to a significant waste reduction of 40% in almost all the investigated case studies.

Low-frequency broadband acoustic metamaterial absorber based on nested resonator and synergistic coupled weak resonances

Utilizing absorbers with sub-wavelength thickness for low-frequency broadband noise control is a challenging problem, and rapid on-demand design of structures based on target noise frequency has received continuous attention. In this work, nested cavities are introduced into the typical neck-embedded Helmholtz resonator (NEHR) to obtain the nested neck-embedded Helmholtz resonator (NNEHR), which exhibits better cavity partitioning volume fraction and covers wider sound absorption band. Both theoretical analysis and simulations demonstrate that NNEHR possesses superior acoustic properties: generating an additional absorption peak, lowering the position of the first absorption peak by 11 %, and increasing the absorption coefficient by 4.7 %. Instantaneous velocity fields and thermal-viscous energy dissipation density illustrate that the efficient sound absorption of NNEHR originates from resonant dissipation in the neck and surrounding areas. Furthermore, by combining the theoretical model with genetic algorithms, three sets of NNEHR metasurfaces are optimized. The optimized structures achieve average absorption coefficients of 0.831, 0.913, and 0.885 in the range of 250–550 Hz, 400–1000 Hz, and 500–2000 Hz, with a thickness of only 50 mm, reflecting sub-wavelength, low-frequency broadband sound absorption characteristics. The excellent absorption stems from synergistic coupled weak resonances and higher-order absorption peaks of constituent units, and the overdamping characteristic ensures the realization of the optimal structure with minimal thickness. The contribution of weak resonant units to the total sound absorption performance can be measured by the surface admittance normalized by the total incident area, and the essence of the coupling effect is the strong interaction between units with adjacent absorbing frequencies. The proposed structure exhibits good sound absorption performance and great adjustability, while the genetic algorithm optimization based on the theoretical model demonstrates high efficiency and robustness, providing a methodology for the design and on-demand optimization of low-frequency broadband structures.

Multi-interface engineering design of nitrogen-doped bamboo-based carbon/Fe/Fe3C composite electromagnetic wave absorber based on honeycomb-ant nest-like structure

The integration and development of artificial intelligence (AI) and 5G communication technology have brought tremendous changes to human society. How to create a green electromagnetic environment has attracted people's attention. Rich heterostructure design based on interface engineering is considered an effective means of obtaining efficient electromagnetic wave absorbers. In this work, we have achieved innovative design of nitrogen doped carbon/Fe/Fe3C multi-interface heterostructures. The delignification modification of bamboo enriches the cellular pore channels, effectively regulates the loading of Fe3+and the diffusion binding of pyrrole molecules and promotes the deep construction of multi-layer heterogeneous interfaces. Further in-situ pyrolysis resulted in the formation of abundant honeycomb ant nest like structural pores and nitrogen doped multiphase heterostructure interfaces. Provided the best multi-component loss mechanism and impedance matching for the material, improving the overall dielectric and interface polarization effects of the material. Therefore, the obtained absorbent exhibits satisfactory electromagnetic wave absorption performance at a low load of 20 %, with an effective absorption bandwidth of 6.5 GHz (1.85 mm). This work provides new ideas for the high-value utilization of biomass in nature, optimization and innovative design of multi-level pore structures for microwave absorbers.

The history and the current state of the art related to structures under stress and corrosion

The paper deals with the current state of the art arising in the design of the structures, operating under traditional mechanical loading in the aggressive environment causing their corrosion. The express goal in this case is establishing the corrosion rate dependence on the stress state of the structure and considering its durability. Thus, the use of basic mathematical models that describe the effect of corrosion rate depending on the stress state of the structure is considered. The main objective of this paper is to provide a review of useful approximations that have been suggested to deal with interaction of stress and corrosion fields. The first model that considers such a relationship is the Dolinsky model, which uses a linear dependence of the stress effect on the corrosion rate. Additionally, the Gutman model, in which the dependence of the corrosion rate on stress is expressed by an exponential law, is considered. When constructing mathematical models of structures’ corrosion wear, it is also necessary to take into account the protective coatings operation and determine the incubation period duration, which is the durability of the applied protective coatings. In this regard, the use of one of these models, which takes into account the decrease in the polymer coatings’ protective properties and a combined approach to accounting for corrosion and the anti-corrosion coatings’ protective properties are presented. Determining their reliability is an equally important aspect in the design of structures subject to corrosion. Therefore, the main theories of reliability and their practical application were considered on specific examples. A characteristic feature of the work is the coverage of issues related to the optimal design of structures operating in corrosion conditions. Two classes of problems were studied. First, determining the optimal form of structures under various types of mechanical loading and the use of the above corrosion models is considered. In the second class, the use of promising optimization models related to the solution of multi-criteria problems (using the fuzzy sets theory), as well as models with a pronounced economic bias, which allow making a cost estimate of structures failure-free operation during their lifetime, is considered. This article's novelty consists of preparing a comprehensive review of the interaction of stress and corrosion conditions. Researchers are deemed to greatly benefit from knowing the existing literature along with their strengths and weaknesses.

Sound transmission loss and bending properties of sandwich structures based on triply periodic minimal surfaces

Four types of triply periodic minimal surfaces sandwich structures (TPMS-SS), namely, G-SS, D-SS, D1-SS, and IWP-SS, have been proposed. The bending properties were evaluated by experiments and numerical simulations, and their sound insulation performance was investigated using theoretical, numerical and experimental methods. Firstly, the bending performance of four TPMS-SS was compared. Then, the acoustic vibration control equation of TPMS-SS was established and the theoretical solution for the sound transmission loss (STL) was derived based on Reissner's theory combined with the fluid-solid coupling condition. Next, experimental study was conducted on the STL performance of TPMS-SS using the impedance tube method, and the numerical model was verified using theoretical and experimental results. Finally, parametric studies were carried out to investigate the effects of parameters such as relative density (RD), panel thickness (hf), and sound incidence elevation angle (φ), as well as the type of structure, on the STL performance. The results show that TPMS-SSs can achieve >30 dB of STL in the frequency range of 1 Hz to 10 kHz. The STL value increases with relative density (RD), panel thickness (hf), and sound incident elevation angle (φ), while the location of the dips in the STL curves is affected by relative density and panel thickness. G-SS has the best bending performance, while D1-SS has the best acoustic performance. The results could be used for the optimization design of lightweight sandwich structures.

Quantitative calculation of rock strain concentration and corresponding damage evolution analysis

Understanding the critical strain and damage evolution process of sandstone can help engineers more accurately predict the failure modes and critical states of sandstone in actual engineering structures. Therefore, this article quantitatively analyzes the strain field data obtained through digital image correlation (DIC), and for the first time establishes a strain concentration calculation model (SCCM) to analyze the critical strain, compaction, and damage evolution process of sandstone under uniaxial compression conditions. The experimental results show that both elastic and plastic strain zones exist on the specimen surface. The proportion curve of strain concentration calculated by SCCM indicates that the strain field ε1 generally undergoes two stages: the elastic strain fluctuation stage and the plastic strain development stage. In contrast, the strain field ε2 exhibits roughly three stages: a rapid change phase, a slow change phase, and a stability phase. Microscopic strain analysis reveals an overlap between the compaction and damage processes of the specimen, and the critical strain value εmd for micro-damage in the specimen is significantly smaller than values obtained by traditional discrimination methods. Specifically, when the defect width of the specimen is 15 mm and 40 mm, the mean εmd vaules are approximately 0.006016 and 0.00539, respectively. In contrast, the mean critical strain values determined by traditional discrimination methods are 0.0180 and 0.0178, respectively. The above research results provide a new method for analyzing the strain field data of geotechnical materials, serving the optimization of engineering structure design.

Boosting polysulfides conversion kinetics through heterostructure optimization and electrons redistribution for robust lithium-sulfur batteries

Lithium-sulfur batteries (LSBs) are gaining significant attention as a promising candidate to satisfy the demand for high energy density. However, their application is still hindered by the notorious shuttle effect of intermediate polysulfides and the sluggish redox kinetics. Herein, we provide an electrocatalyst composed of two-dimensional (2D) bimetallic sulfides with layered cross-linking structure evenly distributed on 2D MXene nanosheets substrates (Bi2S3/MoS2@MX). Composition optimization and rational structural design effectively mitigate the self-stacking defect and expand the exposure of active sites. The electrons redistribution at heterogeneous interfaces generates a built-in electric field, thereby promoting electron transfer efficiency. Experiments and theoretical calculations results confirmed that the synergistic effect of heterostructures can effectively strengthen the adsorption and conversion of polysulfides, thereby significantly mitigating the shuttle effect. The utilization of sulfur is improved, and the corrosion degree of lithium metal anode is reduced. Consequently, the LSBs assembled with Bi2S3/MoS2@MX modified separator manifest an impressive initial specific capacity of 1306 mAh g−1 at 0.2C. Remarkably, the battery exhibits good long-term cycling stability with only 0.069 % capacity degradation per cycle at 2C after 500 cycles. This work demonstrates that synergistic cooperation of diverse catalytic materials represents an effective strategy for enhancing the potential for industrial application of LSBs.

Simulated annealing algorithm for the optimal design of diffractive structures under fluctuation models

In this paper, to improve the optimization capability of the simulated annealing algorithm (SA) in the optimal design of diffractive structures, the random fluctuation problem in the algorithm is investigated, and a new fluctuation calculation model is proposed. The optimal design of phase-type diffraction gratings and beam-shaping devices verified the fast accuracy of the proposed model. The simulation experimental results show that the model’s introduction is particularly significant in substantially reducing computation time (a threefold increase in computation speed) and improving the algorithm’s optimization finding capability. Finally, the setting of the model parameters is discussed analytically to make the proposed model more applicable and robust. The study results provide guidance and assistance for higher speed and effectiveness in the optimal design using simulated annealing algorithms. It can be applied to any complex and large-scale optimization calculation problem.

Optimization design of support structure based on 3D printing technology

Parts are often warped and deformed when they are molded using selective laser melting (SLM) technology. Thus, it is necessary to study the addition support modes of parts molded using SLM. Consequently, we designed dendritic, E-stage and conical supports, having different structural parameters and different partitions using Magics, and then, we analyzed their performances using the finite element software Abaqus. The structural parameters of the supports were optimized and finally tested using SLM molding technology. The maximum stress concentration was found for dendritic supports, followed by E-stage supports, and then conical supports. The stress concentration and deformation level of Scheme 2 were less than those of Scheme 1. The stress intensity and deformation levels for two partitions were less than those for three partitions. For parts molded by SLM, the deformation was maximum for conical supports, followed by dendritic supports, and then E-stage supports. When gradient supports of similar volumes were added, additional partitions did not effectively improve the molding quality. When supports of similar volumes were added, adding gradient supports did not effectively improve the molding quality. The results provide a basis for the application of SLM in molding high-precision parts.

Large‐scale elasto‐plastic topology optimization

AbstractThis work presents large‐scale elasto‐plastic topology optimization for design of structures with maximized energy absorption and tailored mechanical response. The implementation uses parallel computations to address multi million element three‐dimensional problems. Design updates are generated using the gradient‐based method of moving asymptotes and the material is modeled using small strain, nonlinear isotropic hardening wherein the coaxiality between the plastic strain rate and stress is exploited. This formulation renders an efficient state solve and we demonstrate that the adjoint sensitivity scheme resembles that of the state update. Furthermore, the KKT condition is enforced directly into the path dependent adjoint sensitivity analysis which eliminates the need of monitoring the elasto‐plastic switches when calculating the gradients and provides a straight forward framework for elasto‐plastic topology optimization. Numerical examples show that structures discretized using several millions degrees of freedom and loaded in multiple load steps can be designed within a reasonable time frame.

Structural Optimization of a Giant Magnetostrictive Actuator Based on BP-NSGA-II Algorithm

This study introduces an integrated structural optimization design method based on a BP neural network and NSGA-II multi-objective genetic algorithm. Initially, a two-dimensional axisymmetric finite element model of the Giant Magnetostrictive Actuator (GMA) was established, and the coupling simulation of the electromagnetic field, structural field, and temperature field was conducted to obtain the GMA’s performance parameters. Subsequently, the structural parameters of the GMA magnetic circuit, including the magnetic conducting ring, magnetic conducting sidewall, magnetic conducting body, and coil, were used as inputs, and the axial magnetic induction intensity, uniformity of axial magnetic induction intensity, and coil loss on the Giant Magnetostrictive Material (GMM) rod were used as outputs to establish a back propagation (BP) neural network model. This model delineated the nonlinear relationship between structural parameters and performance parameters. Then, the BP-NSGA-II algorithm was applied to perform multi-objective optimization on the actuator’s structural parameters, resulting in a set of Pareto optimal non-dominated solutions, from which a set of optimal solutions was obtained using the entropy weight method. Finally, simulation analysis of this optimal solution was conducted, indicating that under a 5 A power supply excitation, the maximum axial magnetic induction intensity on the optimized GMM rod increased from 0.87 T to 1.12 T; the uniformity of axial magnetic induction intensity improved from 93.1% to 96.5%; and the coil loss decreased from 7.79 × 104 W/m3 to 4.97 × 104 W/m3. Based on the optimization results, a prototype actuator was produced, and the test results of the prototype’s output characteristics proved the feasibility of this optimization design method.