Structural Design Optimization Research Articles

Optimization of the annulus space structure for hydrocyclone separation of rubber particles based on NSGA-II and GMDH

Rubber particles produced during industrial rubber manufacturing pose significant health and environmental risks. Due to their small size, these particles are difficult to efficiently separate and recover. Previous studies have shown that increasing the annular gap can reduce the circulation of small particles within the hydrocyclone. However, the optimal design of the annular gap structure has not been thoroughly investigated. This paper focuses on the structural optimization of the annular space, dividing it into three parts: annular width (w), insertion depth (L), and diameter (Dh). Single-factor analysis reveals that an increase in annular width lowers the internal pressure field; an increase in annular insertion depth causes vortex movement downward, reducing the separation zone; and an increase in annular diameter generates vortices within the annular gap. Multi-factor analysis using GMDH and NSGA-II shows that the GMDH model has excellent predictive capability, with R2 values of 94.23 % for separation efficiency and 92.77 % for pressure drop. The optimal structure obtained from NSGA-II is the C-type hydrocyclone (Dh: 7.45, L: 7.2, w: 3.96), with separation efficiency and pressure drop of 85.72 % and 0.1649 MPa, respectively. The optimized hydrocyclone shows improvements of 4.46 % in separation efficiency and 8.89 % in pressure drop compared to the non-optimized performance. This study applies genetic algorithms to the structural optimization of the annular gap, providing theoretical insights into the design of hydrocyclone annular gap structures.

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.

Design optimization method of pipeline parameter based on improved artificial neural network

The rationality of pipeline design is directly related to its energy efficiency, reliability, and safety. Pipeline vibration may lead to negative effects such as mechanical loss and fatigue damage. Therefore, this study utilizes pipeline optimization design to mitigate these effects. Recently, neural networks have been widely used in structure design optimization. In the study, a backpropagation neural network (BP) combined with a variant slime mould algorithm (SMA) is utilized to solve the pipeline structure design optimization problem. Pipeline transport plays a crucial role in the efficient movement of various commodities, including but not limited to gas, oil, water, and other liquid substances. The interaction between liquid and pipeline can cause pipeline vibration and even damage. Therefore, based on the simulation model considering FSI (fluid-structure interaction), machine learning methods such as BP can predict vibration characteristics of fluid-conveying pipelines. However, existing research has shown that BP has insufficient parsing ability in structure mechanics problems, especially in solving the overall characteristics of complex structures (such as maximum structural strain). This study proposes an Arithmetic-based slime mould algorithm (ACSMA) with an adaptive decision strategy and a chaotic mapping strategy. A hybrid algorithm named ACSMA-BP is presented to promote the model's prediction ability. At last, to verify the effectiveness of the proposed pipeline structure design optimization approach, the ACSMA-BP model is utilized to complete a structure design optimization case for a simulated pipeline. The numerical results indicate that compared with AOA, CWOA, ESSAWOA, NGS_WOA, and RSA, the ACSMA has the best optimization ability.

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.

A structural mechanics analysis on a Type IV hydrogen storage tank during refueling and discharging

High-pressure hydrogen gas, as a power generation fuel widely used in transportation, has significantly contributed to the development of hydrogen fuel cell electric vehicles. However, obvious temperature rise and drop during fast refueling and discharging cause serious safety risk to the structural stability of on-board hydrogen storage tank. The American Society of Automotive Engineers SAE J2601 and the international standard ISO 15869 strictly stipulate that the operation temperature range of hydrogen storage tank varies from −40 °C to 85 °C. In this study, a finite element mechanics model was constructed using ACP and Static Mechanical software to better understand the deformation, stress, strain, and failure modes experienced by a Type IV tank during charging and discharging. Detailed parameters such as ply angle, ply thickness, mesh generation, and boundary conditions, were extensively elucidated. The results indicate that the high temperature and pressure generated during fast fueling of the storage tanks are less likely to cause yield failure of the inner, outer layers and plug, but the stress concentration caused by low temperature and high pressure may lead to the fracture rupture of internal polyethylene materials. Aluminum alloy plug, serving as sealing devices for the tank, are most susceptible to yielding failure under coupled conditions. The mechanical load reaching the yield stress of the plug is approximately 85 MPa with the nominal working temperature of 85 °C. Additionally, the maximum stress on the outer layer can be reduced by adjusting the circumferential layer direction from 90° to 70° or by optimizing the orientation of the maximum stress layer increasing it by 110°. The present study can offer new insights into the dynamic loading behavior of the Type IV tanks during fast charging and discharging, and may provide technical references for optimization design of the tank structures.

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.

Structural design optimization of cast glass artwork via a digital design solution

Structural design optimization of cast glass artwork via a digital design solution

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.

An Overview of Carbon Dioxide Photo/Electrocatalyzed by Titanium Dioxide Catalyst

AbstractThis study provides a comprehensive review of recent advancements in photocatalytic and electrocatalytic carbon dioxide reduction using titanium dioxide catalysts. The basic concepts of light absorption, electron transport, and reduction processes are introduced in this paper, which also delves into the specifics of photocatalytic and electrocatalytic reduction of carbon dioxide. The paper highlights the key applications and benefits of titanium dioxide, including its strong stability, outstanding light absorption capacity, and good electron transport performance, in the photocatalytic and electrocatalytic reduction of carbon dioxide. Furthermore, it examines the impact of various surface modification techniques on catalytic performance, as well as the effects of various titanium dioxide catalyst forms on catalytic activity and selectivity in carbon dioxide reduction. The in‐depth analysis exhibit promising catalytic properties and hold significant potential for future advancements. However, some obstacles still need to be overcome, such as increasing catalytic activity and selectivity while minimizing energy dissipation. In order to improve catalytic performance and efficiency, future research should prioritize the optimization of structural design and surface modification techniques for catalysts. Additionally, the paper provides a scientific foundation for accomplishing sustainable carbon conversion, it also calls for additional experimental and theoretical research into the mechanism of action for titanium dioxide catalyst.

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.

Topology optimization of smart structures to enhance the performances of vibration control and energy harvesting

Abstract With the growing interest in smart materials, the utilization of shunted piezoceramics for dynamic vibration control has gained significant attention due to their unique characteristics, such as the ability to absorb strain energy from vibrating systems and convert it into electrical energy. Designing and analyzing the behavior of structures in hybrid mitigation/harvesting conditions, considering both reliability and performance, pose challenges. This paper aims to achieve optimal design parameters for the structure by employing a multiobjective optimization approach that strikes a compromise between maximizing harvested power and minimizing structural damage. To evaluate the effectiveness of the design, topology optimization was conducted in three different cases to compare the results. By systematically exploring the design space, these cases provide insights into the influence of various parameters on the structural performance. In addition, to enhance computational efficiency, the structure was represented as a metamodel using neural networks. This approach enables rapid evaluation and prediction of the structure’s behavior, facilitating the optimization process. By integrating multiobjective optimization, topology optimization, and metamodeling techniques, this study aims to provide valuable insights into the optimal design of structures that simultaneously incorporate shunt circuitry for vibration control and energy harvesting, leading to improved performance and reliability.

Energy generation from friction-induced vibration of a piezoelectric beam

The primary challenge in harnessing vibration energy with piezoelectric materials is the discrepancy in frequency between the energy source and the energy generator, which lowers the efficiency of energy harvesting. To address the challenge, a piezoelectric beam under friction-induced vibration (FIV) is designed, modeled, and studied for the first time to realize the pronounced FIV contributing to energy generation by adapting the vibrations of the continuum structure to align close to its resonant frequencies. The Stribeck friction model is applied to characterize the variation of friction based on the relative sliding velocity vr between contacting objects. The analytical solution is derived to solve the dynamic responses, and transient charging simulation validated by the experiment is utilized to assess energy output. Furthermore, parameter studies are conducted based on the validated model with regard to the material properties of the beam and piezoelectric material, electrode connections of piezoelectric patches, and friction model parameters to investigate their influences on energy output. Considering the same dimensional properties, materials with low Young's modulus E and density ρ are desired for the host structure to facilitate large dynamic strain in piezoelectric materials. With an exponential decay factor C = 8, representing optimal material contact interface, pronounced higher FIV mode can be induced leading to higher output power. A root mean square charging power PeRMS of 42.4 mW and a peak instant charging power Pe − peak of 263 mW can be achieved. In the current study, the model is implemented on a beam coupled with one piezoelectric patch, which has potential applicability to non-uniform beams with various layouts of piezoelectric patches. The presented model enables efficient optimization of continuum structural design for higher piezoelectric energy generation under friction.

An improved adaptive Kriging method for the possibility-based design optimization and its application to aeroengine turbine disk

Possibility-based design optimization (PBDO) can provide theoretical basis for the structural optimal design of fuzzy uncertainty model in engineering, so as to obtain the optimal design variables. The genetic algorithm (GA) based on adaptive Kriging method for PBDO requires high precision in the whole design space, while the region far from the limit state surface (LSS) of the constraint function has little effect on PBDO, thus greatly affects the computational efficiency. In order to improve the efficiency of PBDO, an improved adaptive Kriging method combined with active possibility constraint (I-AK-AC) is proposed in this paper. In I-AK-AC, the enhanced expected improvement learning function is first put forward to promote the convergence efficiency of Kriging model by reducing the accuracy of the region far from the LSS of the constraint function. Whereafter, the active possibility constraint is identified, and only the boundaries of active possibility constraint need to be approximated precisely by Kriging model. By these ways, the convergence speed of Kriging model is further ameliorated without affecting the computational accuracy, and the efficiency of PBDO is significantly improved. Three test examples and an engineering application of aeroengine turbine disk illustrate the validity and accuracy of the proposed I-AK-AC.

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.

Systematic analysis of Structural optimization design of post-disaster emergency rescue robot

Systematic analysis of Structural optimization design of post-disaster emergency rescue robot