Search Results (26)

This article uses the sailfish outline as an airfoil profile to create a dual vertical-axis water turbine model for capturing wave and tidal current energy. A parametric water turbine model is built with the shape function perturbation and characteristic parameter description methods. Optimized by the multi-island genetic algorithm on the Isight platform, a CNC sample of the optimized model is made. Its torque and pressure are measured in a wind tunnel and compared with CFD numerical analysis results. The results show small differences between the numerical and experimental results. Both indicate that the relevant performance parameters of the turbine improved after optimization. During constant flow velocity measurement, the optimized axial-flow turbine has a pressure increase of 55% and a torque increase of 40%, while for the centrifugal turbine, the pressure increases by 60% and the torque by 12.5%. During constant rotational speed measurement, the axial-flow turbine’s pressure increases by 16.7%, with an unobvious torque increase. The Q-criterion diagram shows more vortices after optimization. This proves the method can quickly and effectively optimize the dual vertical-axis water turbine. Full article

This study investigates an aerodynamic optimization framework inspired by marine biological morphology, utilizing the sailfish profile as a basis for airfoil configuration. Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. Parametric studies revealed that pivotal factors including installation angle significantly influenced the fluid dynamic performance metrics of lift generation and pressure drag. Response surface methodology was employed to establish predictive models for these critical performance indicators, effectively reducing computational resource consumption and experimental validation costs. The refined bio-inspired configuration demonstrated multi-objective performance improvements compared to the baseline configuration, validating the computational framework’s effectiveness for hydrodynamic profile optimization studies. Furthermore, a coaxial dual-rotor vertical axis turbine configuration was developed, integrating centrifugal and axial-flow energy conversion mechanisms through a shared drivetrain system. The centrifugal rotor component harnessed tidal current kinetic energy while the axial-flow rotor module captured wave-induced potential energy. Transient numerical simulations employing dynamic mesh techniques and user-defined functions within the Fluent environment were conducted to analyze rotor interactions. Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. Parametric optimization revealed maximum energy extraction efficiency for the centrifugal rotor occurs at λ = 1.25 tip-speed ratio under Re = 1.3 × 10⁵ flow conditions, while the axial-flow counterpart attained optimal performance at λ = 1.5 with Re = 5.5 × 10⁴. This synergistic configuration demonstrated complementary operational characteristics under marine energy conversion scenarios. Full article

Aortic dissection (AD) is a highly lethal cardiovascular emergency, and clinical studies have found that a high percentage of AD patients are hypertensive. In previous studies, the AD model was simplified, such as by treating the vessel wall as a single-layer rigid material, ignoring the complex biomechanical factors of the vascular lumen. This study elucidates key biomechanical mechanisms by which hypertension promotes primary AD progression using multiscale modeling. First, based on experimental data from longitudinal and circumferential uniaxial tensile testing of porcine aortic walls (5–7-month-old specimens), a constitutive model of the aortic wall was developed using the Holzapfel–Gasser–Ogden (HGO) framework. The material parameters were calibrated via inverse optimization in ABAQUS-ISIGHT, achieving close alignment with mechanical properties of the human aorta. Using this validated model to define the hyperelastic properties of the aortic wall, a multiphysics coupling platform was constructed in COMSOL Multiphysics 6.2, integrating computational fluid dynamics (CFD) and fluid–structure interaction (FSI) algorithms. This framework systematically quantified the effects of blood pressure (bp) fluctuations on compressive stresses, von Mises stresses, and deformation of the intimal flap within the AD lesion region. With constant blood rheology, elevated blood pressure enhances wall stresses (compressive and von Mises), and intima-media sheet deformation, this can trigger initial rupture tears, false lumen dilation, and branch arterial flow obstruction, ultimately deteriorating end-organ perfusion. Full article

Clothing management is a major challenge for blind and visually impaired individuals to perform independently. This research developed and validated the iSight, a mechatronic smart wardrobe prototype, integrating computer vision and artificial intelligence to identify clothing types, colours, and alterations. Tested with 15 participants, iSight achieved high user satisfaction, with 60% rating it as very accurate in clothing identification, 80% in colour detection, and 86.7% in near-field communication tag recognition. Statistical analyses confirmed its positive impact on confidence, independence, and well-being. Despite the fact that improvements in menu complexity and fabric information were suggested, iSight proves to be a robust, user-friendly assistive tool with the potential to enhance the daily living of blind and visually impaired individuals. Full article

Although the mechanized harvesting rate of maize in China has exceeded 90%, there are still shortcomings in the mechanized harvesting of silage maize. Some areas still rely on manual harvesting, which is not only inefficient but also requires more labor. Therefore, it is extremely important to realize the mechanized harvesting of silo maize. The aim of this paper is to improve the harvesting efficiency of silo maize, ensure the quality of the silage and reduce the loss of nutrients. Aiming at the problems of wide cutting width, difficult access, low operating efficiency, and uneven straw feeding in the process of corn silage harvesting in terraced fields in hilly and mountainous areas. This study creatively designed a single-disk corn silage harvester. The optimal Latin hypercube method and MATLAB R2021 software are used to analyze the influence of various factors on the evaluation index. The ternary quadratic regression prediction model was constructed by using Isight 5.6 software, and the accuracy of the model was verified by variance analysis and field experiments. In addition, the main program was optimized by writing the program of the SMPSO algorithm. The optimal combination of working parameters was determined: the working speed was 1.00 m/s, the cutter rotation speed was 1085.89 rpm, and the drum rotation speed was 30 m/s. At that time, the machine productivity was 38 t·h⁻¹, the average standard grass length rate was 82.15%, and the stubble qualification rate was 91.95%. After two field trials, the results showed that all indicators met the national standards and industry standards, which confirmed the efficiency and practicality of this design. Full article

This paper explores the application of multidisciplinary design optimization to the blades in horizontal-axis wind turbines. The aerodynamics and structural performance of blades are considered in the optimization framework. In the aerodynamic discipline, class function/shape function transformation-based parameterized modeling is used to express the airfoil. The Wilson method is employed to obtain the aerodynamic shape of the blade. Computational fluid dynamics numerical simulation is performed to analyze the aerodynamics of the blade. In the structural discipline, the materials and ply lay-up design are studied. Finite element method-based modal analysis and static structural analysis are conducted to verify the structural design of the blade. A collaborative optimization framework is set up on the Isight platform, employing a genetic algorithm to find the optimal solution for the blade’s aerodynamics and structural properties. In the optimization framework, the design variables refer to the length of the blade chord, twist angle, and lay-up thickness. Additionally, Kriging surrogate models are constructed to reduce the numerical simulation time required during optimization. An optimal Latin hypercube sampling method-based experimental design is employed to determine the samples used in the surrogate models. The optimized blade exhibits improved performance in both the aerodynamic and the structural disciplines. Full article

The horizontal axis tidal turbine, as a crucial device for capturing tidal energy, has gained significant attention because it has better energy efficiency performance. Enhancing the performance of foils, a vital part of tidal turbine blades, can significantly improve tidal turbine performance. Among numerous methods to enhance the foil performance, the Gurney flap has gained significant attention due to its avoidance of complex structural design. Currently, there is limited research on optimizing the design of Gurney flaps while considering the dynamic performance of foils. In this study, the S809 foil with a blade cross-section was selected as the research subject, a multi-objective optimization design platform was created by integrating a multi-objective optimization algorithm with Computational Fluid Dy-namics (CFD) numerical simulation techniques. The objective of this platform is to enhance the dynamic performance of the hydrofoil by optimizing the geometric structure of the Gurney flap. The improvement of dynamic lift and the size of the dynamic stall hysteresis loop are used as objective variables in this study to evaluate the hydrofoil’s dynamic performance. The optimal Latin hypercube design method is used in the optimization process to choose sample locations, and the Kriging approximation model is used to determine the relationship between the design variables and the objective variables. Meanwhile, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is used to create a multi-objective optimization platform for solving the optimization problem, and the optimized results are validated using CFD. Comparative validation results show that quantifying the dynamic performance during hydrofoil pitching oscillation and using the optimal Latin hypercube design method and Kriging approximation model for optimizing the Gurney flap structure is rational and accurate. This study explores the mechanism of the Gurney flap through in-depth CFD numerical simulations and finds that the Gurney flap affects the flow characteristics at the hydrofoil’s trailing edge, thereby influencing the performance. It increases the pressure difference between the pressure and suction surfaces, thus enhancing the hydrofoil’s lift. Finally, this article provides three recommended parameters to improve the dynamic performance of the hydrofoil. This research can serve as a reference for the application of Gurney flaps in tidal turbine blade design. Full article

In order to reduce energy consumption, improve driving mileage, and make vehicles adopt driver styles, research on automatic optimization of control strategy based on driver style is conducted in this paper. According to the structure of the powertrain, the vehicle control strategy is designed and a driver-style recognition model based on fuzzy recognition is added to the rule-based control strategy to improve the driver adaptation of the vehicle. In order to further improve the energy-saving effect of the strategy, the control strategy based on driver style is automatically optimized by the Isight optimization platform to make the strategy reach optimum. The test results show that the strategy based on driver style is able to adapt to different styles of drivers and the economy of the vehicle is improved by 2.06% compared with pre-optimization, which validates the effectiveness of the strategy. Full article

The linkage mechanism of a cotton bundle fiber strength tester will have an unstable clamping force when clamping fiber bundle samples with uneven thickness, resulting in slippage or damage to the fibers increasing the pectin residue, leading to inaccurate test results and increased maintenance costs. To address this problem, according to the structural principle of the connecting rod-clamping mechanism, through the geometric relationship between the connecting rods to establish a parametric model of the mechanism and the use of the principle of virtual work on the mechanism to solve the force, the proposed new Dynamic Alternative Static Approximate Analysis Method (DASAAM) was based on Adams 2020. The Isight integrated Adams automatic optimization design framework was built. The variance of the change curve of the end force of the mechanism when clamping samples of different thicknesses was used as the evaluation function and the assembly conditions were used as the constraints. The dimensional parameters and angles of the mechanism were optimized using the multi-island genetic algorithm. The simulation results showed that when the thickness of the clamped sample varied in the range of 0–4 mm, the clamping force of the mechanism varied in the range of 8920–8630 N. Finally, the variance of the clamping force measured by the clamping force measurement component was 0.0367. The above results show that the DASAAM provided a new method for solving the static problem of mechanism morphological and position change, and the optimized linkage mechanism had better clamping force stability, which made the strength detection of cotton fiber more accurate, thus improving the quality of textile products. Full article

Self-oscillating cavitation jet technology has become a research hotspot of scholars in various fields. However, existing research lacks a summary of the rules of the influence of various factors on the cavitation performance, such that efficient and stable extensive engineering applications are impossible to achieve. This paper aims at optimizing the design of the self-oscillating cavitation jet nozzle (SOCJN) as the objective; this is carried out by the experimental design, optimal Latin hypercube method, and response surface method in (design of experiment) DOE methods on the basis of the ISIGHT optimization method. In addition, taking the vapor volume fraction and cavitation number as a research objective, the obtained optimal structural parameters of the nozzles are applied under the condition of clear water to establish the function mapping relationship between the external geometric characteristics and the vapor volume fraction and cavitation number; then, this is compared with the experiment. The results indicate that the second-order response surface approximate model is suitable for the SOCJN and there is an error smaller than 8% between the approximate model results and the calculated results of the nozzle response. When the diameter of the upper nozzle is D₁ = 4.7 mm, the ratio of the upper nozzle’s diameter to the lower’s diameter (D₁/D₂) is 2.6 and the ratio of the chamber length to the chamber diameter (L/D) is 0.63; pulse jets from the SOCJN have the best pitting effect on the sample at the monitoring point when the convergence angle of collision wall α is 120°. When the structural parameters of the nozzle are optimal structural parameters, the cavitation performance is the best at the initial pressure of 4.8 MPa. This research provides a reference for the optimized design of the SOCJN for industrial applications. Full article

The process parameters in the low-pressure casting of large-size aluminum alloy wheels are systematically optimized in this work using numerical casting simulation, response surface methodology (RSM), and genetic algorithm (NSGA-II). A nonlinear input–output relationship was established based on the Box–Behnken experimental design (BBD) for the crucial casting parameters (pouring temperature, mold temperature, holding pressure, holding time), and response indicators (defect volume fraction, spokes large plane mean secondary dendrite spacing (SDAS)), and a mathematical model was developed by regression analysis. The Isight 2017 Design Gateway and NSGA-II algorithm were used to increase the population and look for the best overall solution for the casting parameters. The significance and predictive power of the model were assessed using ANOVA. Casting numerical simulation was used to confirm the best option. To accomplish systematic optimization in its low-pressure casting process, the mold cooling process parameters were adjusted following the local solidification rate. The results showed that the mathematical model was reliable. The optimal solutions were a pouring temperature of 703 °C, mold temperature of 409 °C, holding pressure of 1086 mb, and holding time of 249 s. The mold cooling process was further optimized, and the sequence solidification of the optimal solution was realized under the optimized cooling process. Finally, the wheel hub was manufactured on a trial basis. The X-ray detection, mechanical property analysis, and metallographic observation showed that the wheel hub had no X-ray defects and its mechanical properties were well strengthened. The effectiveness of the system optimization process scheme was verified. Full article

Inspired by the bionic Bouligand structure, helicoidal carbon fiber-reinforced polymer composite (CFRPC) laminates have been proven to own outstanding out-of-plane mechanical properties. This work aims to further explore the excellent bending characteristics of helicoidal CFRPC laminated plates and find out the optimal helicoidal layup patterns. The optimization design of laminated plates stacked with single-form and combination-form helicoidal layup sequences are carried out by using the finite element method (FEM) and adaptive simulated annealing (ASA) optimization algorithm on the Isight platform. Then, the nonlinear bending responses of optimal helicoidal CFRPC laminated plates are investigated via the FEM for the first time. The helicoidal CFRPC laminated plates under three different types of boundary conditions subjected to transverse uniformly distributed load are considered. The numerical results reveal that the combination-form helicoidal layup sequences can decrease the dimensionless bending deflection of laminated plates by more than 5% compared with the quasi-isotropic plate and enhance the out-of-plane bending characteristics of CFRPC laminated plates effectively. The boundary conditions can significantly influence the nonlinear bending responses of helicoidal CFRPC laminated plates. Full article

In turbine tenon joint structures, fretting fatigue is common and can have detrimental effects on the components. To increase the fretting fatigue life, the design of tenon joint structures must be optimized. A parametric model of the three-tooth mortise and tenon joint structure is developed in this research. Sensitivity analysis yields the primary characteristic parameters, which are then employed as design variables. The objective function is the life of fretting fatigue. An aero-engine turbine three-tooth mortise and tenon joint structure was optimized against fretting fatigue using a Multi-Island Genetic Algorithm (MIGA), which was then experimentally verified. The optimization was based on the multidisciplinary optimization platform ISIGHT to write batch files integrating ANSYS and MATLAB. According to the findings, the three-tooth mortise and tenon joint structure’s fretting fatigue life can be increased by 51.3% by applying the MIGA. The contact pressure was reduced by 0.54% and the maximum slip amplitude has been reduced by 13%. The approach of optimization’s efficacy was confirmed. Full article

Optimizing hydraulic machinery is a critical research area within the field of fluid mechanics, aiming to enhance product design efficiency and improve performance while reducing development time. The application of intelligent algorithms and combinatorial optimization strategies has become increasingly prevalent in this domain, providing a comprehensive understanding of optimization-related theoretical developments. Recently, the emergence of ISIGHT software as a new technology for software integration platforms has opened new avenues for optimization in hydraulic machinery. By leveraging intelligent algorithms and combinatorial optimization strategies, ISIGHT software provides a comprehensive framework for optimizing hydraulic machinery. This paper serves as an introduction to ISIGHT software, highlighting its advantages in addressing optimization problems. It presents a detailed examination of the process and technology involved in hydraulic machinery optimization based on ISIGHT software, along with its practical application. Furthermore, the paper summarizes the future development trends of ISIGHT software, offering engineers a theoretical foundation and reference for optimizing hydraulic machinery performance. Overall, this paper provides a valuable contribution to the field of hydraulic machinery optimization, showcasing the potential of ISIGHT software. Full article

The aluminium alloy front subframe of an automobile was developed through multi-operating condition topology optimization and multi-objective optimization methods. By considering the influences of loads on the strength, static stiffness, and modal of the aluminium alloy front subframe under typical operating conditions, the performance parameters of the aluminium alloy front subframe after topology optimization were obtained. After topology optimization was performed, the parametric model of the aluminium alloy front subframe was established. Based on the Isight optimization platform, sample points were generated with the optimal Latin hypercube test method, and the response surface approximate model was constructed. The minimum mass and maximum first-order frequency were taken as the objectives, the stress under typical working conditions did not exceed the set target value, and the maximum displacement of the installation point was taken as the constraint condition. The multi-objective particle swarm optimization algorithm was used to optimize the aluminium alloy front subframe. The error of the free modal and finite element free modal analysis of the aluminium alloy front subframe samples was less than 15%. The optimized aluminium alloy front subframe was 2.4 kg lighter than the original subframe under the premise of satisfying various performance indices, and the lightweight rate was up to 12%. Full article