Structural Design Optimization Research Articles

Optimization Mechanism of Nozzle Parameters and Characterization of Nanofibers in Centrifugal Spinning

Nanofibers are an emerging kind of nano-material, widely used in several application domains such as biomedicine, high-efficiency filtration media, precision electronics, and optical devices. Centrifugal spinning, which is a novel nanofiber production technology, has been widely studied. This paper proposes a structural parameter optimization design method of a bent-tube nozzle. The mathematical model of the spinning solution motion in the nozzle is first developed. The optimization function of the structure parameters of the bent-tube nozzle is then obtained by calculation. Afterwards, these parameters are optimized using a neural network algorithm. The obtained results show that, when the bending angle is 15°, the curvature radius is 10 mm, the outlet radius is 0.205 mm, and the head loss of the solution can be minimized. Finally, centrifugal spinning experiments are conducted and the influence of the centrifugal spinning parameters on the nanofibers is analyzed. In addition, the optimized bent-tube nozzle improves the surface morphology of the nanofibers as their diameter distribution becomes more uniform.

Thermal hydraulic optimization on the First Wall of COOL blanket for CFETR

The supercritical carbon dioxide (S-CO2) cOoled Lithium-Lead (COOL) blanket is under development for China Fusion Engineering and Test Reactor (CFETR). The S-CO2 is adopted to cool the structural components, in which the key component First Wall (FW) dominates the total heat power due to the large plasma facing heat flux. In this paper, referring to the response of material temperature, coolant velocity and pressure drop, the thermal hydraulic optimization is firstly performed on the structure design (i.e. cross area and pitch of channel) using the single variable control method, and the optimization principle is that the outlet temperature remains as the same when the optimization variables are changed. Finally, the optimal structure design of FW is obtained, namely cross area of 12 × 12 mm2 and channel pitch of 5 mm. On basis of this, the comparative analyses are carried out using the different cooling system, structural material, i.e. Reduced Activation Ferritic Martensitic (RAFM) steel and Oxide dispersion-strengthened alloy (ODS) ferritic steel, as well as helium as coolant. Furthermore, the satisfied designs are obtained by referring to the constraints of coolant pressure drop and maximum temperature on the structural steel. Then, the thermal hydraulic designs of FW are continuously matching with the Power Conversion System (PCS) to ensure that the heat power removed by the S-CO2 on the primary side can be transferred to the secondary side. Finally, the achievable thermodynamic design are obtained, including the parameters of high operating pressure, turbine inlet temperature, split ratio as well as the thermoelectricity conversion efficiency. The results show that the high pressure of PCS should be larger than 25 MPa when the RAFM steel is used as the structure material, due to the limitation on the outlet temperature of FW. On the contrary, the ODS can raise the outlet temperature, which is beneficial for matching with the PCS, and the thermoelectricity conversion efficiency can reach up to 47.4 % at the high pressure of 25 MPa. The analyses results will provide useful guidance on the system design both for the Primary Heat Transfer System (PHTS) and PCS of CFETR.

Reliability-based design optimization for seismic structures considering randomness associated with ground motions

When addressing the dynamic reliability analysis of structures, it becomes necessary to account for multiple limit state functions or their combinations. In scenarios where structures are subjected to random excitation, this can lead to intricate inter-dependencies among different limit states, and the computational workload can pose a substantial challenge in ensuring sufficient precision. Code-based design primarily ensures safety at the member level, while deterministic optimization fails to accommodate the inherent uncertainties associated with external excitation or the system as a whole. Therefore, in such cases, to address both the uncertainties in excitations and the presence of multiple limit states while mitigating computational challenges, equivalent extreme-value criteria are employed within the framework of the probability density evolution method to calculate the global reliability of the structure subjected to stochastic ground motions generated from the physically motivated stochastic ground motion model. Numerical optimization is subsequently conducted using genetic algorithms, aiming to minimize the cost of the superstructure while adhering to the design performance criteria related to the inter-story drift ratio and considering global reliability. Additionally, multi-objective optimization is carried out using NSGA-II, permitting the generation of multiple solutions, from which one can select the most suitable solution as needed. The numerical results illustrate the effectiveness of this technique in achieving an optimal balance between the cost of the structure and the consideration of global reliability, providing a comprehensive solution for dynamic reliability analysis and design optimization of structures under random excitations.

Structural Optimization Design of Three Phase Enclosed GIS Disconnector Based on MOGOA and ELM

Due to the compact and complex internal structure of 110 kV three‐phase enclosed GIS disconnector, the voltage distribution between the contact breaks of each phase has an influence on the insulation performance of the GIS disconnector, and its internal insulation design is a difficult point to be solved. To solve this problem, this paper firstly establishes a three‐dimensional model of three‐phase enclosed GIS disconnecting switch and conducts a research on the distribution of electric field under a specific working condition, it is found that the outer corner of the static contact, the inner corner of the static arc contact, the inner corner of the outer end of the moving contact and the inner corner of the moving contact are the internal electric field concentration of the three‐phase enclosed GIS disconnector. Then, in order to further reduce the electric field strength and improve the insulation margin and performance, this paper proposes a method based on the combination of Extreme Learning Machine (ELM) and Multi‐objective Grasshopper Optimization Algorithm (MOGOA) to optimize the structural design of three‐phase enclosed GIS disconnector, and a ELM model is established, which takes the internal fillet radius of stationary arcing contact, the internal fillet radius of moving contact, the internal fillet radius of external end of dynamic and static contact, the radius of the outer corner of the two static side contacts and the opening distance of the grounding contact as the inputs, and takes the maximum electric field strength of the two static side contacts and the moving side contacts as outputs; Finally, the structural parameters are optimized by MOGOA algorithm. Compared to the pre‐optimization period, the electric field strengths of the bus bar static‐side contact, dynamic contact and static side contact of the B‐phase after optimization decreased from 20.2, 9.28 and 17.5 to 11.4, 6.65 and 11.5 kV/mm, respectively. The electric field strengths of the dynamic and static side contacts are significantly reduced, which is beneficial for improving the insulation performance of the three‐phase enclosed GIS disconnector. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Optimal structural design for a certain near-space composite propeller of airship using adaptive region division blending model

Near-space airship is a frontier and hotspot in current military research and development, and the near-space composite propeller is the key technology for its development. In order to obtain higher aerodynamic efficiency at an altitude of 22 km, a certain near-space composite propeller is designed as a long and slender aerodynamic shape with a 10 m diameter, which brings many challenges to the composite structure design. The initial design is obtained by the composite structure variable stiffness design method using based on fixed region division blending model. However, it weighs 23.142 kg, exceeding the required 20 kg. In order to meet the structural design requirements of the propeller, a variable stiffness design method using the adaptive region division blending model is proposed in this paper. Compared with the methods using the fixed region division blending model, this method optimizes region division, stacking thickness and stacking sequence in a single level, considering the coupling effect among them. Through a more refined region division, this method can provide a more optimal design for composite tapered structures. Additionally, to improve the efficiency of optimization subjected to manufacturing constraints, a hierarchical penalty function is proposed to quickly filter out the solutions that do not meet manufacturing constraints. The above methods combined with a Genetic Algorithm (GA) using specific encoding are adopted to optimize the near-space composite propeller. The optimal design of the structure weighs 18.831 kg, with all manufacturing constraints and all structural response constraints being satisfied. Compared with the initial design, the optimal design has a more refined region division, and achieves a weight reduction of 18.6%. This demonstrates that a refined region division can significantly improve the mechanical performance of the composite tapered structure.

A new decomposition-based multi-objective symbiotic organism search algorithm for solving truss optimization problems

This study presents a comprehensive study on the potential and efficacy of decomposition-based multi-objective symbiotic organism search (MOSOS/D) algorithm for truss structure optimization. The investigation is carried out on five benchmark truss structures, e.g., 37-bar, 60-bar, 72-bar, 120-bar, and 200-bar truss problems. The optimization performance of MOSOS/D is compared with other established algorithms, such as Multi-Objective Evolutionary Algorithm Based on Decomposition, Non-Dominated Sorting Genetic Algorithm-II, Multi-Objective Equilibrium Optimizer, Multi-Objective Marine Predator Algorithm, Decomposition-Based Multi-Objective Heat Transfer Search, Multi-Objective Passing Vehicle Search, Multi-Objective Evolutionary Algorithm Based on Decomposition Differential Evaluation, Multi-Objective Symbiotic Organisms Search, and Multi-Objective Multi-Verse Optimizer considering several metrics, including Generational Distance, Spacing, Spread, Inverted Generational Distance, Hypervolume and Runtime. The findings demonstrate MOSOS/D’s competitiveness in providing non-dominated solutions with less space between them. It also achieves a good balance between convergence and coverage and, thus, delivers diverse solutions with less computational complexity. However, the efficiency of the MOSOS/D algorithm varies depending on the complexity of the considered truss structure, with some algorithms occasionally outperforming it in one or two aspects for specific benchmarks. This study provides valuable insights to engineers and designers aiming to achieve optimal truss structure design.

Optimum design of slot and magnet structure of permanent magnet synchronous generator with teaching‐learning‐studying‐based optimization

AbstractFrom the point of production to consumption, electrical energy should be utilized effectively and qualitatively. Efficiency at the electricity consumption stage is not sufficient, and the desired criteria must be met at the production stage. The efficient and high‐quality generation of electrical energy is directly related to the performance of the generator used. In order to achieve the desired criteria for a generator design, many issues should be considered together. In order for this study to do, a 14‐pole and 5 kW permanent magnet synchronous generator (PMSG) was designed using the innovative optimizer named the weighted mean of vectors (INFO), the jumping spider optimization algorithm (JSOA), the teaching–learning‐based optimization (TLBO), the pelican optimization algorithm (POA) and the teaching‐learning‐studying‐based optimization (TLSBO) algorithms. The generator performance was optimized within the determined inequality constraints by the offset and embrace value and six parameters of the stator slot structure. The generator designed with the parameters determined by the TLSBO was more successful than the generators designed according to all the other proposed algorithms. The total harmonic distortion (THD) value decreased by 51.983% compared to the initial design at approximately the same efficiency.

The study of N-polar GaN/InAlN MOS-HEMT and T-gate HEMT biosensors

The sensing performance of N-polar GaN/InAlN MOS-HEMT biosensors for neutral biomolecules was investigated and compared with the Ga-polar MOS-HEMT and N-polar T-gate HEMT by numerical simulation. The results indicate that the N-polar GaN/InAlN MOS-HEMT biosensor has higher sensing sensitivity than the Ga-polar MOS-HEMT and N-polar T-gate HEMT biosensors. Furtherly, to improve the sensing performance of N-polar MOS-HEMT, the influence of cavity dimensions, GaN channel layer thickness, and InAlN back barrier layer thickness on device performance was investigated. It is demonstrated that the sensitivity of the biosensor increases as the cavity height decreases and the cavity length increases. Therefore, the sensing performance of the N-polar MOS-HEMT device will be enhanced by thinning the GaN channel layer thickness or increasing the InAlN back barrier thickness, which can be mainly attributed to the variation of the energy band structure and two-dimensional electron gas concentration in the HEMT heterostructure. Finally, the highest sensitivity can be obtained for the N-polar MOS-HEMT with 6 nm-thick GaN channel layer, 30 nm-thick InAlN back barrier layer, and two 0.9 μm-long and 5 nm-high cavities. This work provides structural optimal design guidance for the N-polar HEMT biosensor.

Research on a Wire Rope Breakage Detection Device for High-Speed Operation Based on the Multistage Excitation Principle

Wire rope breakage, as damage easily produced during the service period of wire rope, is an important factor affecting the safe operation of elevators. Especially in the high-speed elevator operation process, the problem of magnetization unsaturation caused by speed effects can easily lead to deformation of the magnetic flux leakage detection signal, thereby affecting the accuracy and reliability of wire breakage quantitative detection. Therefore, this article focuses on the problem that existing wire rope detection methods cannot perform non-destructive testing on high-speed elevator wire ropes and conducts design and experimental research on a high-speed running wire rope breakage detection device based on the principle of multi-stage excitation. The main research content includes simulation research on the multistage excitation, structural design, and simulation optimization of open–close copper sheet magnetizers and the building of a detection device for wire rope breakage detection experimental research. The simulation and experimental results show that the multistage magnetization method can effectively solve the problem of magnetization unsaturation caused by the velocity effect. The multistage excitation device has a good wire breakage recognition effect for speeds less than or equal to 3 m/s. It can detect magnetic leakage signals with a minimum of four broken wires and has good detection accuracy. It is a new and effective wire breakage detection device for high-speed elevator wire rope, providing important technical support for the safe and reliable operation of high-speed elevators.

Structure simulation and design optimization of high-performance lithium niobate thin film electro-optic modulator

Structure simulation and design optimization of high-performance lithium niobate thin film electro-optic modulator

Dynamic heat-transfer mechanism and performance analysis of an integrated Trombe wall with radiant cooling for natural cooling energy harvesting and air-conditioning

Natural cooling energy and high-efficient radiant cooling techniques are essential to mitigate energy resources shortage crisis, breakthrough on traditional convective air-conditioning systems in isolation between indoor and outdoor environment with high indoor air quality. In this paper, a polyethylene aerogel (PEA) and phase change material (PCM) integrated novel Trombe wall was proposed, involving natural cooling energy harvesting, cooling energy storage, indoor ventilation and radiant cooling. A two-dimensional unsteady numerical model based on surface-to surface (S2S) radiation model and effective specific heat capacity method was developed in the commercial software Ansys Fluent to evaluate the cooling performance and dynamic heat-transfer mechanism of the novel Trombe wall. Subsequently, climate-responsive operation strategies on ventilation modes were proposed to maximize natural cooling energy utilization and fresh air supply. Parametrical and comparative studies were conducted on optimal structural design and robust operation. Our results showed that, with the novel design and advanced operation strategies, passive cooling capacity of 0.64 kWh/m2·day can be provided, together with fresh air supply of 2705.2 kg/day (1.4 m2 Trombe wall), corresponding to air change rate per hour (ACH) of 1.15. In terms of active cooling system, the integration of PEA and PCM can effectively prevent moisture condensation and shift peak cooling load. Hence, radiant cooling capacity of 0.99 kWh/m2·day and radiant cooling ratio of 47 % can be achieved by the novel Trombe wall, with electricity consumption only at valley period. Moreover, economic saving of 55.0 CNY/day and decarbonization potential of 23.8 kg CO2,e/day can be achieved when the novel Trombe wall is integrated into a typical office building in subtropical climate Guangzhou. This study provides a novel structural design and optimal operation strategies on a Trombe wall, together with guidelines on techno-economic-environmental performance improvement, promoting effective natural cooling energy utilization and energy-flexible/efficient radiant cooling for decarbonization of buildings in cooling-dominant regions.

A level set reliability-based topology optimization (LS-RBTO) method considering sensitivity mapping and multi-source interval uncertainties

With the diversification of engineering structure performance requirements and the continuous development of structural design refinement, structural design methods are facing more and more factors to be considered. It is necessary to develop advanced design technology. In this paper, a sensitivity mapping technique is proposed to improve the effect of topology optimization based on a gradient optimization algorithm. The applicability of this technology is analyzed. In addition, considering the influence of multi-source uncertainties in the whole life cycle of the structure, a reliability-based topology optimization strategy based on the level set method is proposed. The sensitivity of displacement constraint and reliability constraint with pseudo time is derived. Numerical examples and Monte Carlo verification results fully illustrate the applicability, effectiveness, and efficiency of the proposed method. This method has been successfully applied to the topology optimization design of the rocket skid structure.

Out-Plane Buckling of Arches with Variable Cross-Section

The variable cross-section arch is widely used in practical engineering because of its beautiful arc and excellent mechanical properties. However, there is still no systematic and comprehensive study on the out-plane buckling of variable cross-section arches. In view of this, this paper is focused on the elastic analytical research of out-plane buckling of arches with variable cross-sections under a uniformly distributed radial local load. The pre-buckling and out-plane buckling behavior of a variable cross-sectional arch under an external load is quite different from that of an arch with a uniform cross-section. Castigliano’s second theorem is used to establish pre-buckling force method equilibrium equations for variable cross-sectional arches under a uniformly distributed radial local load, and corresponding analytical solutions of normal stress, axial compression, and the bending moments are obtained. Based on the energy method and the Ritz method, analytical solutions of the critical load for the elastic out-plane buckling of arches with variable cross-sections are derived. Comparisons with ANSYS results indicated that the analytical solutions are able to accurately predict the pre-buckling internal forces and critical out-plane buckling load of variable cross-section arches subjected to a uniformly distributed radial local load. It is found that the internal forces and the out-plane buckling load of an arch are significantly affected by the variation of cross-sectional height. As the ratio of the arch’s cross-sectional height increases, the bending moment decreases, and the axial force and critical out-plane buckling load increase. Analytical solutions of pre-buckling internal force and critical out-plane buckling load problems for arches with variable cross-sections have a wider significance since they can provide an effective explicit analytic method for the optimal design of arch structures.

Numerical design optimization of real size complex steel space frame structures using a novel adaptive cuckoo search method

AbstractIn this study, real size complex steel space frame structures are numerically designed to achieve optimal design weight. For this aim, standard cuckoo search algorithm is rectified through a newly proposed adaptive method over two fundamental algorithmic parameters of alien egg probability detection (Pa) and step size control (α) to overcome incompetency of trapping into local optima. Besides, to strengthen exploitation phase of newly proposed algorithm, it is boosted with greedy selection (GS). So, novel algorithm has more promising exploration and exploitation capabilities. An 8‐story, 1024‐member and a 20‐story, 1860‐member real size complex steel space frame structures are selected as design examples. Also, initially to verify the supremacy of novel algorithm, a well‐known welded beam is optimized as a benchmark structural design problem. Afterwards, the steel space frame structures are optimally designed via novel algorithm. Since ready steel section lists are utilized as selection pool for design variables, discrete programming problem is come into existence. The dead, live, snow, and wind design loads acting on frame structures are calculated in direction of ASCE 7‐05 provisions. Furthermore, the structural design constraints are determined from LRFD‐AISC specifications. Eventually, the newly proposed adaptive cuckoo search algorithm boosted with GS presents outstanding algorithmic performance.

Optimization Study of Driver Crash Injuries Considering the Body NVH Performance

Optimal body structure design is a central focus in the field of passive automotive safety. A well-designed body structure enhances the lower threshold for crash safety, serving as a basis for the deployment of other safety systems. Frontal crashes, particularly those with an overlap rate below 25%, are the most frequent types of vehicular accidents and pose elevated risks to occupants due to variable energy absorption and force transmission mechanisms. This study aims to identify an optimized, cost-effective, and lightweight solution that minimizes occupant injuries. Using a micro-vehicle as a case study and accounting for noise, vibration, and harshness (NVH) performance, this paper employs Elman neural networks to predict key variables such as the first-order modes of the body, the body’s mass, and the head injury values for the driver. Guided by these predictions and constrained by the first-order modes and body mass, a genetic algorithm was applied to explore optimal solutions within the solution space defined by the body panel thickness. The optimized design yielded a reduction of approximately 173.43 in the driver’s head injury value while also enhancing the noise, vibration, and harshness performance of the vehicle body. This approach offers a methodological framework for future research into the multidisciplinary optimization of automotive body structures.

Structural Analysis and Design Optimization of Ceramic Products Based on 3D Scene Simplification Algorithm

Structural Analysis and Design Optimization of Ceramic Products Based on 3D Scene Simplification Algorithm

A unified formulation for axial compression of steel tube-confined concrete and concrete-filled steel tube stub columns

Steel-confined concrete (STCC) columns and concrete-filled steel tube (CFST) columns have different load boundary conditions. In STCC columns, the steel tube transmits minimal axial load. Existing design practices employ different formulas to predict the axial load-bearing capacity of STCCs and CFSTs based on these varying load boundary conditions. However, there has always been a practical and challenging demand for researchers and engineers to develop a unified design formula that accommodates composite columns with different sections and load boundary conditions. This demand aligns with the contemporary design concept of continuous structural design optimization. This paper proposes an analytical solution for the elastic deformation of circular STCCs under axial compression, considering the specific load boundary conditions in circular STCC columns. This solution is then extended to encompass polygonal sections, resulting in a unified formula for determining the strength of STCC columns. Additionally, the influence of load boundary conditions on the confined effect of the core concrete is quantified by reformulating and simplifying the proposed formula. These adjustments are informed by the formulation for the axial load capacity of CFST columns proposed by Yu Min et al. Finally, a simple and convenient unified formulation for calculating the axial compressive strength of both STCC columns and CFST columns is proposed for practical engineering applications.

Research on Contact Anchoring Theory and Contact Optimization of Underwater Pipeline Recovery Tools

Technology for recycling abandoned undersea pipelines is crucial for lowering the cost of installing new submarine pipelines, polluting the ocean less, and improving recycling efficiency. A popular area of study is how to lessen the harm that underwater pipeline recycling instruments do to the inner wall of the pipeline during recycling. In order to recover pipelines, this study examines the anchoring theory and damage process of submerged pipeline recovery equipment. The effect of the contact body’s diameter and radius of the rounded corner on the depth of the pressed-in pipeline and the slip distance is examined using the contact body structure optimization design approach of the underwater pipeline recovery tool, which is based on a multi-objective genetic algorithm. Dynamic simulations of the insertion mechanism as a whole are performed using the Adams simulation program to make sure that the optimized contact body can exert enough contact force on the pipeline’s inner wall. According to the optimization results, the ideal design parameters are D = 57 mm and R = 11.5 mm. While still satisfying the criteria, the improved contact body has higher stability.

Optimisation design of a large space cable-pole tensioned parabolic cylindrical antenna mechanism

The cable-strut structure optimisation of a large space cable-strut tensioned parabolic cylindrical antenna is studied. Firstly, the deployment mechanism is designed, and the degree of freedom and kinematics analysis of the mechanism are conducted. Secondly, a complete tension cable configuration with 58 tension cables in 24 categories is established on the basis of the structural characteristics and constraints. A configuration optimisation design method based on the influence coefficient of comprehensive stiffness is proposed. A less tensioned cable optimisation configuration with better static and dynamic stiffness performance is established on the basis of the fully tensioned cable configuration and using the proposed method, and the stiffness characteristics of the configuration are verified through the analysis of an example. Lastly, a mathematical surrogate model between the designed angle and length parameters of the reflector rod system and the fundamental frequency of the antenna is established using the response surface method, and the optimal solution of the reflector rod system is obtained by a genetic algorithm. The effectiveness of the optimisation is verified by finite element modelling and simulation analysis. This study provides a basis and reference for the structural dynamic modelling, characteristic analysis and optimal design of a large space cable-strut tensioned parabolic cylindrical antenna.

Topological Design Optimization Approach for Winding Oil Flow Paths in Oil-Natural Air-Natural Transformers Based on a Fluidic-Thermal Coupled Model

Power transformers are a critical component in transmission and distribution systems. To limit the temperature rise to extend the life-cycle while operating with enough reliability and controllability of a transformer, the design of the cooling system has attracted extensive research attention. In this paper, a topology optimization (TO) methodology is presented for designing the coolant flow paths in a prototype oil-natural air-natural (ONAN) power transformer to maximize the winding heat dissipation capacity without any compromise on the flow resistance. First, the thermal and fluid flow characteristics in both the winding and the radiator of the prototype transformer are numerically investigated through a fluidic-thermal coupled field approach. The preliminary cooling effectiveness of the oil circulation system is initialized. Second, a material-density-based TO scheme is employed to realize the optimal design of the oil baffle structures. In the TO optimization, artificial Darcy frictional forces are applied to the solidified cells to block their internal flows in the fluidic calculations, while the thermal conduction coefficients in those cells are enhanced to separate the baffles from the flowing oil in thermal analyses. Finally, the fluidic and thermal coupled fields of the prototype transformer winding region with structurally optimized oil baffles are numerically investigated to validate the TO effectiveness.