Structural Design Optimization Research Articles

Cooperative co-evolution deep echo state network for time series prediction

Abstract The deep echo state network demonstrates strong predictive performance in time series tasks, but inter-layer weight optimization and reservoir structure design are still challenging tasks. To address this, we propose the cooperative co-evolutionary deep echo state network (CCEDESN). Firstly, inspired by the hierarchical structure of the brain, we introduce a modular hierarchical design. Each layer of the reservoir contains multiple sub-reservoirs, with central neurons in each sub-reservoir interacting with those in other sub-reservoirs to enhance information processing. Secondly, an advanced cooperative co-evolutionary algorithm is proposed to simultaneously optimize the layer connection weights and hyperparameters of the deep echo state network. We evaluate the CCEDESN model on the Mackey-Glass system, sunspot data, and Apple stock opening prices. The experimental results show that the CCEDESN model achieves superior prediction accuracy compared to other models.

A Review of Health Monitoring and Model Updating of Vibration Dissipation Systems in Structures

Given that numerous countries are located near active fault zones, this review paper assesses the seismic structural functionality of buildings subjected to dynamic loads. Earthquake-prone countries have implemented structural health monitoring (SHM) systems on base-isolated structures, focusing on modal parameters such as frequencies, mode shapes, and damping ratios related to isolation systems. However, many studies have investigated the dissipating energy capacity of isolation systems, particularly rubber bearings with different damping ratios, and demonstrated that changes in these parameters affect the seismic performance of structures. The main objective of this review is to evaluate the performance of damage detection computational tools and examine the impact of damage on structural functionality. This literature review’s strength lies in its comprehensive coverage of prominent studies on SHM and model updating for structures equipped with dampers. This is crucial for enhancing the safety and resilience of structures, particularly in mitigating dynamic loads like seismic forces. By consolidating key research findings, this review identifies technological advancements, best practices, and gaps in knowledge, enabling future innovation in structural health monitoring and design optimization. Various identification techniques, including modal analysis, model updating, non-destructive testing (NDT), and SHM, have been employed to extract modal parameters. The review highlights the most operational methods, such as Frequency Domain Decomposition (FDD) and Stochastic Subspace Identification (SSI). The review also summarizes damage identification methodologies for base-isolated systems, providing useful insights into the development of robust, trustworthy, and effective techniques for both researchers and engineers. Additionally, the review highlights the evolution of SHM and model updating techniques, distinguishing groundbreaking advancements from established methods. This distinction clarifies the trajectory of innovation while addressing the limitations of traditional techniques. Ultimately, the review promotes innovative solutions that enhance accuracy, reliability, and adaptability in modern engineering practices.

Research on the optimization of drum structure based on virtual prototyping technology

Drums are the core working mechanism of the coal mining machine for coal mining. The structural design level of the drum is crucial for mining efficiency and safety production. Traditional design methods not only have long design cycles and high costs, but also limited design capabilities. This study used computer numerical simulation methods to establish coupled models for drum cutting complex coal seams, which was used to obtain the working performance of drums with different structures. By fitting the comprehensive performance evaluation function of the drum, the optimal structural parameters are obtained through the improved Non-Dominated Sorting Genetic Algorithms (NSGA-II). Taking into account both technical and economic factors, the optimal helix angle is ultimately determined to be 18°, the optimal installation angle is 45°, and the optimal cutting distance is 71 mm. Through experiments, it has been proven that the performance of the optimized drum has significantly improved. Specifically, the average cutting resistance has been reduced by 12.72%, the load fluctuation coefficient has been reduced by 9.81%, the cutting specific energy consumption has been reduced by 2.85%, and the coal loading rate has been increased by 9.59%, providing a reference for the optimization design of the shearer drum structure.

Equivalent plate formulation of Double–Double laminates for the gradient-based design optimization of composite structures

Equivalent plate formulation of Double–Double laminates for the gradient-based design optimization of composite structures

Analysis of the main factors affecting the polar axis offset characteristics of intact spherical superconducting rotors

Superconducting rotor has great potential for application in the field of precision measurement by virtue of its unique physical properties. The superconducting rotor magnetic levitation device can make high-precision angular velocity sensors. Under the action of external interference torque, the pole-axis deviation from the initial position is the cause of the superconducting rotor pole-axis drift error, in which the spherical surface error and the earth's rotation belong to the main sources of error, and compensating the pole-axis drift speed caused by the spherical surface error of the superconducting rotor is a key step in realizing the high precision of the superconducting rotor magnetic levitation device. Based on this, the research on the influence factors of the spherical surface error of a complete spherical superconducting rotor and the rotation of the earth on the pole-axis offset characteristics of a superconducting rotor is carried out. First, this paper models the magnetic support structure of the superconducting rotor based on the vector magnetic potential equation, analyzes the magnetic field strength distribution on the surface of the superconducting rotor in the ideal state (i.e., suspended in the center of the spherical cavity), and investigates the magnetic support force characteristics. Then the magnetic support interference moment of the superconducting rotor caused by the spherical surface error is analyzed, and a superconducting rotor dynamics model is established based on the superconducting rotor dynamics equations, and the distribution law of the superconducting rotor pole-axis drift error under different rotor structural parameters is given. Finally, the influence of the earth's rotation on the superconducting rotor drift test is investigated. The results provide a reference for the subsequent improvement of rotor drift accuracy, optimization of rotor structure design and improvement of drift test methods.

Optimum Design of truss structures considering nonlinear analysis and dynamic loading using metaheuristic algorithms

Optimum Design of truss structures considering nonlinear analysis and dynamic loading using metaheuristic algorithms

Low flow force spool structure design and multi-objective optimization of servo-proportional valve

Low flow force spool structure design and multi-objective optimization of servo-proportional valve

Design, Synthesis and Biological Activities of Novel meta-Diamide Compounds Containing 1,2,4-Oxadiazole Group

To discover new bisamide compounds with insecticidal and fungicidal activities, 19 novel cyproflanilide derivatives containing 1,2,4-oxadiazole group were designed and synthesized according to the principle of biologically active factor splicing. Preliminary biological assay data indicated that the majority of target compounds demonstrated significant insecticidal activity against Lepidopteran pests. Meanwhile, compounds 5p and 5q showed 97.22 and 100% lethality against Tetranychus cinnabarinus at 400 mg L-1, which were better than cyproflanilide (41.11% at 400 mg L-1). In addition, it is exciting that we have achieved our initial goals as some of the target compounds exhibited both insecticidal and fungicidal activities. For instance, compounds 5b and 5c showed 59.26 and 74.07% fungicidal activities against Cucumber downy mildew at 400 mg L-1, as well as 100% insecticidal activity against Plutella xylostella and armyworm at 100 mg L-1. Compound 5h showed 100% insecticidal activity against armyworm at 10 mg L-1, and also displayed 66.67% fungicidal activity against Cucumber downy mildew at 400 mg L-1. The inhibition rate of compounds 5l and 5s against Cucumber downy mildew reached 88.89 and 96.30% at 400 mg L-1. This work showed the effectively fungicidal application of 1,2,4-oxadiazole group in bisamide compounds and provides insights for optimal structural design.

Study on Performance of Cable Stayed Bridge with Different Geometric Conditions

The construction of cable-stayed bridges has been on the rise in recent years, driven by their aesthetic appeal and unique structural design. This research focuses on the analysis of cable-stayed bridges, The study employed the MIDAS CIVIL software to model and analyse the cable-stayed bridges of two types H-shape and A-D shape, with all the bridges having the same material and section properties. For the seismic analysis time-history analysis has been performed by utilizing data from the 1940 El Centro earthquake, allowing for the investigation of the dynamic behaviour of the bridges. The cable-stayed bridge design is characterized by the transmission of the deck's reaction forces to the pylons, which in turn transfer the load to the foundation. The study reviewed a range of evaluations, including axial forces, displacements, and bending moments, to understand the structural behaviour of the cable-stayed bridges. The results reveal that as the complexity of the cable-stayed bridge design rises, the structural behaviour becomes more complex. The findings of this research contribute to the understanding of the dynamic response of cable-stayed bridges, which is vital for their structural health monitoring and design optimization.

Numerical investigation on energy absorption characteristics and damage modes of biomimetic thin-walled structures in aircraft

The crashworthiness of aircraft is essential for both airlines and passengers. Creating lightweight protective structures that achieve a balance between weight and impact resistance while also providing excellent cushioning and energy absorption presents a significant challenge for aircraft designers. The desert beetle's exoskeleton demonstrates remarkable strength and toughness, effectively shielding its body from external threats. This study examines the desert beetle's exoskeleton by developing bio-inspired thin-walled models with three distinct bottom structures based on its cross-section. Numerical simulations were used for calculations and model optimization. The research systematically investigates how various design parameters, such as impact angle, number of support plates, and wall thickness, affect energy absorption performance. The findings indicate that increasing the inclination angle notably decreases the energy absorption capacity of the protective structure, while adding more partitions can significantly enhance this capacity. Additionally, changes in wall thickness directly influence the structure's compressive performance. Furthermore, a comparative analysis of the optimized structure's energy absorption characteristics under various conditions is provided. Ultimately, this paper highlights the significance of design optimization for protective structures in micro aerial vehicles and outlines future research directions to better balance performance and practicality.

Structurization of information flows for optimal design of aviation structures using artificial intelligence

The task of structuring information flows that provide the process of designing a transport category aircraft for creating a strategy for optimal design of aviation structures using artificial intelligence is considered. The task of creating strategies for the optimal design of aircraft structures is currently partially solved. This task requires the creation of additional optimization and information technology, which allows transferring individual design tasks from humans to artificial intelligence. Artificial intelligence should relieve people in solving complex problems, reduce the time for designing new aircraft and increase their efficiency.

Topology Optimization of Elastoplastic Structure Based on Shakedown Strength

ABSTRACTThe traditional approach to structural lightweight optimization design, which is based on the elastic limit rule, often results in a structure that exhibits either weight redundancy or strength redundancy to some extent. This study introduces a novel integration of shakedown analysis with structural topology optimization, departing from the conventional elastic limit rule. Shakedown analysis identifies a non‐failure external load region beyond the elastic limit but below the plastic limit, independent of loading history. The proposed method, for the first time, accounts for the influence of self‐equilibrium residual stress at the element level, redefining effective and ineffective elements in topology optimization. Shakedown total stress replaces elastic equivalent stress, offering a comprehensive measure. Utilizing Melan's lower bound theorem, a gradient‐based topology optimization framework for shakedown analysis is developed, ensuring structures stay within the elastic–plastic range, preventing excessive plastic deformation. The approach, employing the moving asymptotes method after adjoint sensitivity analysis of shakedown total stress, is applied to a three‐dimensional L‐shaped bracket. Even with a remarkable 50% reduction in weight, the maximum total shakedown stress of the bracket reveals that it only increases by a modest 17.20% from its initial value. Moreover, compared to traditional topology optimization methods based on either elastic stress or stiffness, the proposed method based on total shakedown stress leads to a higher shakedown limit. Specifically, the configuration designed using the total shakedown stress exhibited increases of 2.01% and 9.82% in the shakedown limit compared to those obtained using stiffness and equivalent elastic stress, respectively. This suggests that the proposed method can effectively balance the trade‐off between shakedown strength and structural stiffness, achieving a 2.01% rise in shakedown strength with only a 2.24% compromise in structural stiffness. These findings highlight the method's effectiveness and potential, emphasizing the benefit of redefining effective and ineffective elements using shakedown stress in topology optimization.

Local Structure Optimization Design of Floating Offshore Wind Turbine Platform Based on Response Surface Analysis

The floating platform is a critical component of the floating offshore wind turbine (FOWT), and its internal structure design plays a key role in ensuring the safe operation of the FOWT. In this study, the local model of the floating platform was firstly parameterized, and a response surface model was obtained by conducting an orthogonal test. The response surface model was then optimized using a gradient descent algorithm. Finally, the internal structure arrangement was validated through a safety calibration. The optimization results indicate that the maximum stress of the optimized model is reduced by 22.12% compared to the original model, while maintaining the same mass, centroid, and other mass-related parameters. The optimization significantly improves the safety of the structure and provides valuable references for the design and construction of a FOWT platform.

Flexural Behavior and Failure Modes of Pultruded GFRP Tube Concrete-Filled Composite Beams: A Review of Experimental and Numerical Studies

Pultruded glass fiber-reinforced polymer (GFRP) materials are increasingly recognized in civil engineering for their exceptional properties, including a high strength-to-weight ratio, corrosion resistance, and ease of fabrication, making them ideal for composite structural applications. The use of concrete infill enhances the structural integrity of thin-walled GFRP sections and compensates for the low elastic modulus of hollow profiles. Despite the widespread adoption of concrete-filled pultruded GFRP tubes in composite beams, critical gaps remain in understanding their flexural behavior and failure mechanisms, particularly concerning design optimization and manufacturing strategies to mitigate failure modes. This paper provides a comprehensive review of experimental and numerical studies that investigate the impact of key parameters, such as concrete infill types, reinforcement strategies, bonding levels, and GFRP tube geometries, on the flexural performance and failure behavior of concrete-filled pultruded GFRP tubular members in composite beam applications. The analysis includes full-scale GFRP beam studies, offering a thorough comparison of documented flexural responses, failure modes, and structural performance outcomes. The findings are synthesized to highlight current trends, identify research gaps, and propose strategies to advance the understanding and application of these composite systems. The paper concludes with actionable recommendations for future research, emphasizing the development of innovative material combinations, optimization of structural designs, and refinement of numerical modeling techniques.

The Structural Design and Analysis of the Multi Nozzle Relay Air-Jet Inserting System by Profile Reed Guiding for 3D Weaving Machine

Introduction: Based on the literature, this article designs a parameterized simulation model of a multi-layer jet weft insertion system by profiles reed guidance for a 3D loom on the PTC Creo9.0 platform, including the main supersonic nozzle, supersonic auxiliary nozzle (relay nozzle), and multi-slot profiles reed components. Method: Based on the existing basic theory, experimental results, and empirical data of turbulent jet, the parameters of the multi-layer jet weft insertion system, as well as the structural parameters and the relative positions of the main, auxiliary nozzle and profile reed components, such as the center distance of each layer's main nozzle, auxiliary nozzle spacing, auxiliary nozzle installation angle, spray direction angle, and spray angle, have been determined preliminarily. Result: Further, the basic flow field parameters, such as the supply pressure of the main and auxiliary nozzles and the shape of multi-layer profile reeds, have been determined optimally on the Virtual Prototype Collaborative Simulation Platform (PTC Creo9.0/ANSYS Workbench/Fluent 2024R1), and the rationality of the structural design also been verified; on the premise of ensuring that the airflow velocity of each layer's profiles groove meets the requirements of weft insertion, the design and simulation calculation is repeatedly modified, and the optimal structural design parameters of the multi-layer weft insertion system and nozzle is finally determined. Conclusion: To explore the feasibility of multi-layer jet weft insertion, the design of threedimensional multi-layer jet weft insertion looms has laid a theoretical foundation, laying a good foundation for the emergence and industrial manufacturing of three-dimensional multi-layer jet weft insertion looms, and providing an important reference for the innovative design of threedimensional multi-layer water jet weft insertion looms.

Dynamic characteristics analysis and optimization design of medical grinding machine

In order to improve the stability and reliability of medicinal grinding machine, reduce vibration and noise, and enhance the strength of load-bearing, a scheme for optimizing dynamic response characteristics without increasing mass was proposed based on multi-objective optimization methods. Using the finite element method, the modal analysis was conducted on the entire model of the grinding machine to determine its natural frequencies and vibration modes. The structural optimization design was carried out with the optimization goal of having a sixth-order natural frequency below 30 Hz and a seventh-order natural frequency above 100 Hz. The stress distribution was obtained by conducting the strength analysis on the connecting rod structure. The optimization design of the structure was carried out with the minimum value of the stress peak and the maximum value of the fatigue safety factor as the optimization objectives. The results show that the multi-objective optimization method can make the equipment avoid the resonance zone and reduce the peak stress, which is of great significance for improving the performance of the medical grinding machine.

Modal analysis and optimization design of modular steel structures used in construction

In order to improve the stability and reliability of modular steel structures and reduce design redundancy, a multi-objective optimization study was conducted based on modal analysis. The finite element method was used to obtain the natural frequencies and modes under actual constraint conditions through ANSYS. The first-order natural frequency was used as a constraint condition to rationally configure the dimensions of the modular steel structure, and lightweight design was carried out based on the response surface method. In order to meet the overall structural stiffness requirements, the weight of the structure was minimized as much as possible. The finite element analysis and modal verification of the optimized model were carried out to verify the optimization results that meet the design requirements. The results show that the weight of the model was reduced by 5.36 %, and the increase in the first-order natural frequency was 20.14 %. After analyzing and verifying the modal vibration mode structure, it was found that the optimized modal vibration mode structure could still meet the mechanical performance requirements, providing an important reference for research in the field of building engineering.

The application of ICPA optimization algorithm in multi-objective optimization structural design of prefabricated buildings

With the prefabricated buildings developing, traditional architectural design methods can no longer meet the requirements of efficient, green, and sustainable development. In view of this, based on the analysis of the framework structure of the cyclical parthenogenesis algorithm, the study introduced chaotic optimization algorithm for improvement. And the improved new algorithm was applied to multi-objective problems in the optimization design of prefabricated building structures. Finally, a novel structural design optimization model was proposed. These experiments confirmed that the improved algorithm had the least 160 iterations and 17 optimal solutions, which was an increase of 15 compared to traditional aphid algorithms. Two function solutions of this new structural design optimization model were both between –0:5 and 0.5, with relatively smaller values. In addition, this model could effectively optimize and transform physical buildings, increasing their structural stability by 2.43%, increasing their structural quality coefficient by 4.49%, reducing vibration cycles by 0.06%, and reducing inter story displacement angles by 0.04%. In summary, the improved cyclical parthenogenesis algorithm has good performance in solving multi-objective problems in prefabricated structures, and can quickly and accurately find the global optimal solution. This study aims to provide guidance for the prefabricated building structure design.

Evaluation of Mixing Process in Batch Mixer Using CFD-DEM Simulation and Automatic Post-Processing Method

A batch mixer is an important piece of equipment for polymer filling modification, and the kinematics of agglomerate breakup and distribution are necessary for the structure design and mixing process optimization of the rotor, particularly in light of the cohesive forces that exist within the agglomerate. In this paper, computational fluid dynamics (CFD) was coupled with discrete element method (DEM) to simulate the mixing process, including breakup and distribution, which was further quantitatively evaluated by the post-processing involving numerical method. To study the mixing process of an agglomerate composed of massive spherical particles (individual particle ratio was r), the coordinates of the particles were exported from the CFD-DEM simulation results. Then, the coordinate data were automatically processed with an automate custom-built post-processing program to obtain the average radius of gyration (Rgy) and the particle distribution density (ε). The kinematics analyzation of breakup and distribution was represented by curve of Rgy/r versus mixing time (t) and curve of ε versus t, respectively. The value of Rgy/r and ε decreased over time until they reached an equilibrium and vibrated around a certain value. In particular, a notable decline in the value of Rgy/r was observed following an increase prior to critical time. The increase in Rgy/r stated that the agglomerate or aggregates undergo stretching deformation. Additionally, mixing processes of rotors with different pressurization coefficients (S) and rotation speeds could be facilitated and intensified by large S and high rotation speed. Finally, a “breakup-line” was developed by considering the influence of cohesive force and rotation speed on the agglomerate breakup process. The agglomerate could be broken if the combination of rotation speed and bonding strength was above the “breakup line”, otherwise the agglomerate was not broken. Furthermore, rotors with larger slopes exhibited stronger breakup ability.

Collaborative Hollow Porous Structure Design and N Doping to Achieve a Win–Win Situation of “Stable” and “Fast” Lithium Battery

ABSTRACTPolymer‐derived SiOC materials are widely regarded as a new generation of anodes owing to their high specific capacity, low discharge platform, tunable chemical/structural composition, and good structural stability. However, tailoring the structure of SiOC to improve its electrochemical performance while simultaneously achieving elemental doping remains a challenge. Besides, the lithium storage mechanism and the structural evolution process of SiOC are still not fully understood due to its complex structure. In this study, a hollow porous SiOCN (Hp‐SiOCN) featuring abundant oxygen defects is successfully prepared, achieving both the creation of a hollow porous structure and nitrogen element doping in one step, finally enhancing the structural stability and improving the lithium storage kinetics of Hp‐SiOCN. In addition, the formation of a fully reversible structural unit, SiO3C─N, through the chemical interaction between N and Si/C, showcases a strong lithium adsorption capacity. Taking advantage of these combined benefits, the as‐prepared Hp‐SiOCN electrode delivers a reversible specific capacity of 412 mAh g−1 (93% capacity retention) after 500 cycles at 1.0 A g−1 and exhibited only 4% electrode expansion. This work offers valuable mechanistic insights into the synergistic optimization of elemental doping and structural design in SiOC, paving the way for advanced developments in battery technology.