Optimal Design Results Research Articles

Design Method of Worn Rail Grinding Profile for the Curve Section

The grinding profile directly affects the wheel–rail contact relationship, so it is necessary to study the design method of rail grinding profiles for the curve section. Based on the Frechet distance method, the selection method of representative profile for worn rails was established. Based on the non-uniform rational B-spline theory, the description model of the rail profile was constructed. The reduction of rail grinding material removed and improvement of wheel–rail contact geometry were taken as the optimization objectives, and the multi-objective function of the grinding profile of the outer rail in the transition curve and circular curve section was established. The optimized design results show that compared with the measured grinding profile in the field, the rail grinding amount is reduced by 80.1% and 11.3% by using grinding profiles designed for the transition curve section and the circular curve section, respectively, and the distribution of wheel–rail contact points is more uniform. The dynamic indexes under different velocities and different radii are significantly reduced, and the curve passing performance is improved. The area of wheel–rail contact spot changes uniformly with the lateral displacement of the wheelset, and the maximum von Mises stress is improved obviously. The wear index and surface fatigue index decreased significantly. The optimized grinding profile can effectively extend the maintenance cycle and service life of the curved rail.

Size reduction of the square microstrip patch antenna with Koch fractal for 1.575 GHz applications

This paper discusses a square patch microstrip antenna with a resonant frequency of 1.575 GHz. The initial design of the antenna was carried out using a theoretical approach and then applied fractal Koch with 1-iteration and 2-iteration. The design optimization is done using the AWR simulator. Based on the optimal design results, the use of Koch fractals has been able to reduce the antenna size. In the first iteration, the antenna size can be reduced by 28% with a minimum return loss value of -33.36 dB at a frequency of 1.575 GHz. In the second iteration, the antenna size can be reduced by 42.4% from the design without fractals with a minimum return loss of -37.18 dB at a frequency of 1.575 GHz. The gain of each antenna design has almost the same value, namely 5.115 dB.

Optimization Design and Preliminary Results of Synthesis of [Ni(Me<sub>3</sub>en)(acac)]BPh<sub>4</sub> Complex: The Optimization and Preliminary Implementation of Synthesis Process for the Inorganic and Analytical Chemistry Experiment of the 10th National Undergraduate Chemistry Laboratory Tournament

Optimization Design and Preliminary Results of Synthesis of [Ni(Me<sub>3</sub>en)(acac)]BPh<sub>4</sub> Complex: The Optimization and Preliminary Implementation of Synthesis Process for the Inorganic and Analytical Chemistry Experiment of the 10th National Undergraduate Chemistry Laboratory Tournament

Experimental study of printed-circuit heat exchangers with airfoil and straight channels for optimized recuperators in nitrogen Brayton cycle

• The recuperator has been reported as the largest component in nitrogen Brayton cycles. • The compactness and economics can be enhanced by adopting advanced channel shapes. • Experiments of advanced channel shapes, such as airfoil and straight, were performed. • New correlations for the airfoil channel were developed to design the recuperator. • Optimal design results of recuperator were discussed in terms of flow channel shapes. In this study, experiments with straight and airfoil channels of printed-circuit heat exchanger (PCHE) are conducted within a 3 % heat balance difference to investigate thermal-hydraulic performances for nitrogen (N 2 ) Brayton cycle recuperator. The results reveal that the airfoil PCHE has higher heat transfer performance and pressure drop than the straight PCHE. In the case of straight PCHE, the Gnielinski correlation for heat transfer and Blasius correlation for pressure drop show sufficient predictability. For airfoil PCHE, new correlations for Nusselt number and friction factor are developed to predict the experimental data with a maximum error of 2 % for heat transfer and 8 % for pressure drop. Subsequently, the newly developed and other previous correlations for different channel configurations are used to compare the comprehensive performances. The results indicate that airfoil PCHE has the highest comprehensive performance rather than straight, zigzag, and S-shape PCHE channels under the given hydraulic diameter and pumping power conditions. With the validated PCHE 1-D code, the optimal volumes are calculated for target conditions considering the PCHE channel configuration effect. The design result of the airfoil type has the smallest volume compared with other PCHE channel types, which was almost 21 % reduced volume than that of zigzag PCHE.

Characteristics Analysis and Optimization of the Structural Parameters of PTRB

Bearings, as integral parts and components in machinery and equipment, play a critical role in system performance. In this paper, the theoretical models of basic axial load rating, basic radial load rating, and friction torque for the planetary thread roller bearing (PTRB) were derived. Then, a detailed comparison was made between the performance indexes of a PTRB prototype and common high-quality bearing products to demonstrate the advantages of PTRB in volume, bearing capacity, and use method. Next, the effects of different structural parameters on the performance indexes of PTRB were analyzed. On this basis, a multi-objective optimization design was carried out on PTRB under axial load and radial load separately with basic load rating and friction torque as optimization objects to obtain PTRB with superior comprehensive performance. Designers could, in consideration of their specific needs and optimized design results, select the structural parameters of PTRB. Furthermore, a dedicated performance test system was researched and developed, which verified the good static bearing capacity and impact resistance of the PTRB prototype. Within the range of dynamic load rating, the test data were slightly larger than the simulation data for the friction torque, manifesting a relatively high degree of precision of the theoretical model.

Fault-Tolerant Design Process of Spoke-Type IPM Motor Considering Irreversible Demagnetization of PM in Integrated Electric Brake System

In this article, a novel fault-tolerant design process of the spoke-type interior permanent magnet (IPM) motor is proposed to prevent the increase of cogging torque and torque ripple due to partial demagnetization fault and to minimize the motor size. First, unlike other research papers on the irreversible partial irreversible demagnetization of permanent magnet (PM), in this article, the effect of partial irreversible demagnetization faults on the cogging torque and torque ripple for the fault cases is investigated. Then, a novel fault-tolerant design process is proposed to solve the problem of partial demagnetization faults that increase the cogging torque and torque ripple. In the novel fault-tolerant design process, first, to solve the problem of increasing cogging torque and torque ripple due to the partial demagnetization fault, a process for implementing a uniform irreversible PM demagnetization is proposed. Second, to compensate for the motor torque constant decreased by degraded PM, which is caused by irreversible demagnetization of PM, a torque compensation coefficient is also proposed. The proposed fault-tolerant design process is applied to the motor design for the integrated electric brake (IEB) system that requires high torque density. In the optimal design process, Latin hypercube sampling (LHS), a kriging method, and a genetic algorithm are utilized. To verify the effectiveness of the proposed fault-tolerant design process, it is compared with the conventional optimized design results in which irreversible demagnetization of PM is not allowed at all to prevent the partial demagnetization faults. As a result of comparing the optimal design results, the proposed optimization model utilizing the fault-tolerant design process can significantly reduce the motor volume by 12.9%, compared to the conventional optimization model.

Artificial-Intelligence-Based Design for Circuit Parameters of Power Converters

Parameter design is significant in ensuring a satisfactory holistic performance of power converters. Generally, circuit parameter design for power converters consists of two processes: analysis and deduction process and optimization process. The existing approaches for parameter design consist of two types: traditional approach and computer-aided optimization (CAO) approach. In the traditional approaches, heavy human-dependence is required. Even though the emerging CAO approaches automate the optimization process, they still require manual analysis and deduction process. To mitigate human-dependence for the sake of high accuracy and easy implementation, an artificial-intelligence-based design (AI-D) approach is proposed in this article for the parameter design of power converters. In the proposed AI-D approach, to achieve automation in the analysis and deduction process, simulation tools and batch-normalization neural network (BN-NN) are adopted to build data-driven models for the optimization objectives and design constraints. Besides, to achieve automation in the optimization process, genetic algorithm is used to search for optimal design results. The proposed AI-D approach is validated in the circuit parameter design of the synchronous buck converter in the 48 to 12 V accessory-load power supply system in electric vehicle. The design case of an efficiency-optimal synchronous buck converter with constraints in volume, voltage ripple, and current ripple is provided. In the end of this article, feasibility and accuracy of the proposed AI-D approach have been validated by hardware experiments.

Numerical Simulation and Optimization Control of Precious Metal Jewelry Process Based on VR Virtual Technology

In order to solve the problem that the design direction of precious metal ornaments in virtual reality environment which is complicated and most of them are operated by human, and the speed of obtaining the global optimal design result is not good, this paper proposes the numerical simulation and optimization control of precious metal ornaments process based on VR virtual technology. Through the hierarchical modeling structure design of precious metal jewelry and the coding of jewelry modeling gene, the fitness function is used to evaluate the fitness of individuals and determine the fitness of coding individuals; the evolution of jewelry modeling design scheme is supported by genetic operators. After the artificial participation conditions are met, the design scheme is evaluated manually in the virtual reality environment until a satisfactory scheme is produced. The experimental results show that under the same conditions, the design results of industrial ornaments based on genetic algorithm are 410 times less than those generated by conventional methods. Conclusion. It can accurately converge to the global optimal design result, which indicates that the genetic algorithm converges to the global optimal result faster and better in the industrial jewelry modeling design under the virtual reality environment.

Flight Endurance Increasing Technology of New Energy UAV Based on a Strut-Braced Wing

This paper explores the feasibility of using the strut-braced wing (SBW) configuration to improve the flight endurance of the new energy unmanned aerial vehicle (UAV). A conceptual scheme of a new energy UAV with SBW configuration was designed, and the influence of the SBW on the aerodynamic and structural performance was analyzed. The results show that the SBW can improve the structural performance of the wing and increase the solar laying area of the wing, but the aerodynamic performance did not improve significantly. From the perspective of UAV energy consumption in level flight, the subtraction between electric output power and solar input power is selected as the evaluation index of the increasing effect of the flight endurance. A multidisciplinary design optimization (MDO) model was established considering the coupling of aerodynamics, structure, energy, and weight. Surrogate model technology and multiobjective genetic algorithm are used to optimize the SBW configuration. Compared with the conventional configuration, the optimal design result of the SBW configuration can reduce the level-flight output power and increase the solar input power, thus effectively increasing the flight endurance of the UAV.

The Optimal Blading Design and CFD Analysis of Axial Flow Fan

This study proposes a method to optimize the blade angle and chord length distributions of axial flow fan rotor blade, and applied it to the design of the actual industrial axial flow fan. The present design model of the axial flow fan rotor blade is to construct and stack the section profiles using single circular arc and airfoil thickness distribution with the camber and stagger angles as design variables along the blade span height from hub to tip, and the chord length distribution is designed in a parabolic fashion from hub to tip. The performance and efficiency of the fan rotor blades are predicted by applying a through-flow analysis method to the 3D fan blade geometry obtained from the design variables of the camber angle, stagger angle, and chord length of the blade sections. These fan design and through-flow analysis methods are used as the simulation engine for optimization problem. Through applying the optimization algorithm, an optimal axial flow fan rotor is obtained with maximum efficiency and computational fluid dynamics analysis is performed to verify the result of the present optimal design. From the computational fluid dynamics calculation results, it can be seen that the present optimal design model has an efficiency improvement of about 2% compared to the initial design, and maintains relatively high efficiency even under partial load conditions.

Optimum Design of UAV Wing Skin Structure with a High Aspect Ratio Using Variable Laminate Stiffness

This paper quickly calculated the design variables to satisfy the strength and stability conditions, the dominant design verification conditions of the composite wing structure, through a genetic algorithm. It developed a variable stiffness stacking optimization process applicable to aircraft wing structure design. We proposed a laminate parameter-based optimization strategy that considers the stiffness characteristics of the two-dimensional elements used as design variables. Compared with the optimization results obtained using continuous stiffness optimization as an optimization process function of laminate sequences with genetic algorithms, we obtained a reasonable stiffness distribution while complying with critical guidelines related to individual composite layup designs. The results of the stiffness optimization design were implemented as a finite element model, and the results were verified through NASTRAN. We demonstrated the functionality of the stiffness optimization process by obtaining results satisfying the set response conditions, i.e., strength and stability, in many design areas of the wing.

Optimal Design of Failure Mode Control for Semi-rigid Steel Frame Based on Elitist Retained Genetic Algorithm

The post-earthquake reports show that failure mode control design is of great significance to improve the seismic performance of structures. To realize the optimal design of failure mode in semi-rigid steel frame, a failure mode optimisation design method based on an elite retained genetic algorithm was developed in this study. Firstly, a database of 96 extended end-plate connections was established using the ABAQUS finite element software to obtain the initial rotational stiffness and yield moment under failure criteria. Secondly, with section size as the optimisation variable, failure mode as the constraint condition, and total steel consumption as the objective function, elite gene transfer was realized through gene sequence replication, hybridisation and mutation. With a 10-story, 3-span, semi-rigid steel frame as an example is proposed to demonstrate the application of the proposed semi-rigid design method, and pushover and time history analyses were conducted on the optimized results to verify the accuracy of the proposed method. The analysis results showed that the stable and reliable optimal design results were obtained through 1317 generation genetic iterative calculations, and the energy consumption ratio of the semi-rigid connection (including the beam ends) was 95.82% and that of the column was 4.18%; in addition, 76% of the beam ends had plastic hinges to dissipate energy in the pushover analysis. This finding indicates that the optimized frame can achieve the global failure mode during earthquakes, and the design method can effectively improve the seismic performance of the frame.

Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing

At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1–2.3% smaller than that obtained by isotropic optimization.

Temperature Dependence of Optimal Shape and DC Current Transport Characteristics of 3 T Whole Body REBCO MRI Magnet

This paper reports the optimum design results of REBCO high-temperature superconducting magnets for 3 T-whole-body magnetic resonance imaging (MRI). The REBCO magnet consists of a main coil, compensation coil, and shield coil, and optimum design is carried out using an immunogenetic algorithm. A magnetic field uniformity of 20 ppm was observed in the uniform sphere inside the coil, and a 5-gauss region of 2.67 m in radial length and 4.50 m in axial length was realized. The local magnetic field vector distribution of the designed coil was also calculated for the designed magnet using electromagnetic field analysis, and the local voltage was obtained using the magnetic field/temperature dependence of the electric field vs. current density properties evaluated with the REBCO short sample. Then, the voltage vs. current characteristics of the magnet were evaluated by adding it over the entire coil length. Defining the current load factor (operating current/critical current) of the designed magnet using the above analysis results makes it possible to clarify the relationship between the operating current, optimized magnet shape, and required wire length for the operating temperature. In particular, we found that the required HTS tape length and transport current have a simple linear relationship in the operating temperature range below approximately 50 K.

Multi-criteria decision making for adaptive façade optimal design in varied climates: Energy, daylight, occupants’ comfort, and outdoor view analysis

Adaptive façades can enhance interior environmental quality and reduce building energy expenditure. To this end, counterbalancing numerous objectives must be considered during the early stage. However, there remain challenges in this high-performance access, leading to difficulties in obtaining the final design solution. Therefore, this study aims to establish a robust design decision-making process for adaptive façade systems in actual commercial building scales. Firstly, the parametric simulation was implemented in varied climates, simultaneously integrating daylight, energy, and occupants' view analysis. Five comprehensive objectives of maximising daylighting and view quality whilst minimising energy use, thermal discomfort, and visual discomfort were assessed, in which the most challenging criterion, outdoor view, was built precisely upon three all-inclusive facets: view context, view access, and view clarity. Then, the robust multi-criteria decision-making framework was applied to determine the unique optimal design for each selected region with preferences sensitivity analysis. Simulation results revealed that climatic conditions, materials, and configurations significantly impact adaptive façade performance. Meanwhile, optimal design results showed that building energy can save as much as 17% compared to the average design values. Although daylighting and outdoor view criteria meet current building standards, it suggested proper architectural layouts to accomplish the most occupants’ comfort. • The parametric simulation was integrated for adaptive façades in varied climates. • Maximising daylight and view whilst minimising energy use and occupants' discomfort. • The proposed outdoor view factor comprised view context, access, and clarity. • Multi-criteria decision making was investigated by preferences sensitivity analysis. • The optimal designs found complied with current building performance standards.

Design and Optimization of a Magnetron DC–DC Isolated Power Supply With High Efficiency

High-efficiency high voltage dc power supply is the core equipment for magnetron in the microwave industry. This article presents an input-parallel output-serial modular high isolated resonant converter for the magnetron. However, the high stray capacitance of the high isolation transformer brings some challenges, such as high turn-<small>off</small> current, longer dead time, increasing gain, and transformer optimization. A simplified model including the stray capacitances is built to deal with these problems, and the minimum turn-<small>off</small> current is derived after the detailed time-domain analysis. The appropriate deadtime and the maximum magnetic inductance needed for the proposed converter are obtained with the minimum turn-<small>off</small> current. Then, a 15 kW, 60 kV isolation multiple-windings output transformer is designed and optimized for the converter. The insulation design, core shape, losses, and parasitic parameters are calculated thoroughly. The Pareto optimization process optimizes the switching frequency and the transformer&#x0027;s turns to obtain higher efficiency and a more stable gain. The finite element method and time-domain simulation verified the optimized design results. Finally, a 0.8&#x002F;2.5 kV, 15 kW all-SiC dc&#x2013;dc converter module is developed to validate the proposed design. The results indicate that the module efficiency is as high as 98.6&#x0025;.

Multiobjective optimization of 3-DOF magnetic bearing considering eddy current effects and saturation

The multiobjective optimization method of three-degrees-of-freedom hybrid magnetic bearings (3-DOF HMBs) is crucial compared to time-consuming finite element calculation due to their three dimensional magnetic field. Solid rotors are the first choice for high-speed applications because the yield strength of laminated rotors is lower. However, solid materials may induce eddy current effects and saturation problems. In addition, a 3-DOF HMB has solid and laminated materials and permanent magnet materials, and the material price presents a risk for the structure. In view of the above mentioned problems, a dynamic magnetic circuit model of the 3-DOF HMB with eddy current and saturation effects is initial given. Subsequently, a multiobjective optimization design method for maximum axial and radial bearing capacity and the lowest cost is proposed. Finally, the optimized parameters are given, and a prototype is manufactured. The range of all optimal solutions considering saturation is less than that without saturation, and the maximum reduction is 99%. The experimental results demonstrate the effectiveness of the optimized design results.

Concurrent topology and fiber orientation optimization of CFRP structures in space-borne optical remote sensor

Lightweight design is one of the most important concepts in the design of space-borne optical remote sensors. Carbon fiber reinforced polymer (CFRP), as one material with high ratio of modulus to density, is widely employed to realize the lightweight design. To maximize the stiffness and strength of CFRP with prescribed mass, fiber orientation and topology optimization are accomplished and optimum design result is acquired in this paper. First, the optimization algorithm of fiber orientation is put forward to find the optimal fiber direction and verified by theoretical analysis and simulations, illustrating that [90°/+ 45°/− 45°/0°] fiber orientation and symmetrical laminas are indispensable. Furthermore, the topology optimization algorithm including the density interpolation method and sensitivity analysis method is brought about to find the optimal material distribution. The algorithm is validated to be convergent and can provide a conceptual model which offers a reference for the critical design. Finally, acquired in the mechanical test is the performance of the optical remote sensor whose first three characteristic frequencies are respectively 66.95 Hz, 70.37 Hz, and 98.84 Hz. The mechanical amplification factor is 5.29, which meet the performance requirement of the stiffness and strength for the optical remote sensor.

High-Throughput Screening of Optimal Process Parameters for PVD TiN Coatings With Best Properties Through a Combination of 3-D Quantitative Phase-Field Simulation and Hierarchical Multi-Objective Optimization Strategy

Physical vapor deposition (PVD) is one of the most important techniques for coating fabrication. With the traditional trial-and-error approach, it is labor-intensive and challenging to determine the optimal process parameters for PVD coatings with best properties. A combination of three-dimensional (3-D) quantitative phase–field simulation and a hierarchical multi-objective optimization strategy was, therefore, developed to perform high-throughput screening of the optimal process parameters for PVD coatings and successfully applied to technically important TiN coatings. Large amounts of 3-D phase-field simulations of TiN coating growth during the PVD process were first carried out to acquire the parametric relation among the model parameters, microstructures, and various coating properties. Experimental data were then used to validate the numerical simulation results and reveal the correlation between model parameters and process parameters. After that, a hierarchical multi-objective method was proposed for the design of multiple coating properties based on the quantitative phase–field simulations and key experimental data. Marginal utility was subsequently examined based on the identification of the Pareto fronts in terms of various combinations of objectives. The windows for the best TiN coating properties were, therefore, filtered with respect to the model/process parameters in a hierarchical manner. Finally, the consistent optimal design result was found against the experimental results.

Design and optimization of wall-climbing robot impeller by genetic algorithm based on computational fluid dynamics and kriging model

In recent years, wall-climbing robots have begun to replace manual work at heights to reduce economic losses and casualties caused by working at heights. This paper designs a negative pressure adsorption type wall-climbing robot and analyzes the internal fluid movement state of its negative pressure device and the force analysis of the robot when it is adsorbed and balanced. Furthermore, through the experimental prototype, the influence of wall material, robot pose, negative pressure cavity shape and sealing method on the adsorption performance of the wall-climbing robot is explored. The computational fluid dynamics simulation (CFD) simulation method and experimental results are used to verify each other, which proves the correctness of the simulation results. Based on the Kriging surrogate model, the functional relationship between the impeller blade outlet angle, the impeller inlet diameter, the number of blades as the design variables, the negative pressure as the dependent variable was established, and the genetic algorithm (GA) was used to optimize it. Compared with the original design, the optimized design results of impeller parameters have increased the negative pressure value from 3534.75 to 4491.19 Pa, an increase of 27.06%.