Search Results (9)

This study presents the development and validation of a comprehensive numerical optimisation methodology used to improve the energy efficiency of a pump with normal characteristics: volume flow rate, Q nom = 6.3 m³/h, and head, H = 20 mH₂O. The methodology was implemented in ANSYS Workbench using ANSYS CFX and optiSLang. The optimisation process is based on data from 853 RANS (SST) calculations on a sample generated by the LHC method, varying the parameters of the blades and flow path. Response surfaces (RSM) were constructed using anisotropic and classical kriging, which were optimised using an Evolutionary Algorithm (EA). The optimised geometry was verified numerically by URANS SST and experimentally. For physical validation, the wheel was manufactured using SLS technology from PA-12 Industrial powder, a strength assessment FSI was performed, and the geometry was checked by 3D scanning. 3D scanning showed a high manufacturing accuracy (deviations of 0.1–0.3 mm). The result is a geometry that increases efficiency while maintaining head, which has been confirmed by experimental validation. Full article

This study focuses on improving the efficiency of interior permanent magnet synchronous motors (IPMSMs) for electric vehicle (EV) compressors. Seven rotor topologies (B, dB, V, dV, D, U, and UV) were first compared, among which the U-type rotor demonstrated the highest efficiency and the lowest total loss. Subsequently, the influence of the turn number and rotor outer diameter (ROD) on the shift of the high-efficiency region was analyzed, and six key design variables were identified through Pearson correlation-based sensitivity analysis. Using these variables, a multi-objective optimization was performed in Ansys OptiSLang, which improved the integrated part load value (IPLV)-weighted efficiency from 91.05% to 92.29% and shifted the high-efficiency region closer to the main operating point. Experimental validation of the reference model confirmed the reliability of the FEM analysis, and the proposed optimal design is expected to enhance low-speed efficiency and reduce battery energy consumption in EV compressor applications. Full article

To enhance the electromagnetic performance of flat-wire permanent magnet synchronous motors, three different groove structures were designed for the rotor, and a multi-objective optimization algorithm combining a genetic algorithm (GA) with the TOPSIS method was proposed. Firstly, an 8-pole 48-slot flat-wire motor model was established, and the cogging torque was analytically calculated to compare the motor’s performance under different groove schemes. Secondly, global multi-objective optimization of the rotor groove dimensions was performed using a combined simulation approach involving Maxwell, Workbench, and Optislang, and the optimal rotor groove size structure was selected using the TOPSIS method. Finally, a comparative analysis of the motor’s performance under both rated-load and no-load conditions was conducted for the pre- and post-optimization designs, followed by verification of the mechanical strength of the optimized rotor structure. The research results demonstrate that the combined optimization approach utilizing the genetic algorithm and the TOPSIS method significantly enhances the torque characteristics of the motor. The computational results indicate that the average torque is increased to 165.32 N·m, with the torque ripple reduced from 28.37% to 13.32% and the cogging torque decreased from 896.88 mN·m to 187.9 mN·m. Moreover, the total distortion rates of the air-gap magnetic flux density and the no-load back EMF are significantly suppressed, confirming the rationality of the proposed motor design. Full article

This study explores the tensile performance of blind rivet joints in galvanized steel sheets, focusing on their behavior under shear and normal load conditions. Blind rivets are frequently used in structural applications due to their ease of installation and ability to be applied from one side, making them highly effective in industries like aerospace and automotive. Two types of DIN 7337—4.8 × 8 blind rivets—galvanized steel St/St and stainless steel A2/A2—paired with galvanized steel sheets DX51D + Z275, were experimentally tested to assess how their material properties affect their joint strength, deformation patterns, and failure modes. Single-lap shear, double-lap shear, and pure normal load tests were conducted in multiple configurations to evaluate joint performance under varying loading conditions, simulating real-world stresses. Using custom-built equipment, controlled forces were applied perpendicular to the rivet joints to replicate practical loading conditions. The results revealed distinct differences in the load-bearing capacities of the two materials, offering valuable insights for applications where corrosion resistance and structural integrity are critical. Finite element analysis (FEA) was then used to simulate the behavior of the joints, with the results validated against experimental data. To enhance the reliability of numerical simulations in optimizing the design of rivet joints, a methodology was proposed to calibrate non-linear FEA models to experimental results, and a substantial agreement of 92.53% was achieved via optimization in ANSYS OptiSLang. This research contributes to our broader understanding of riveted connections, providing practical recommendations for assessing the performance of such joints in various engineering fields. Full article

Mathematical optimization is a widespread method in order to improve, for instance, the efficiency of energy systems. A simulation approach based on partial differential equations can typically not be formulated as an optimization problem, thus requiring interfacing to an external optimization environment. This is, among others, also true for the programming language Modelica. Because of high computation time, such coupled approaches are often limited to small-scale optimization problems. Since simulation models tend to get more complex, simulation time and, in turn, associated optimization time rise significantly. To enable proper sampling of the search space, individual optimization runs need to be solved in acceptable times. This paper addresses the search for a proper optimization approach and tool to couple with Modelica/Dymola. The optimization is carried out on an exemplary power plant model from the ClaRa-Library using an evolutionary algorithm (SPEA2-based) with Ansys optiSlang. To verify and evaluate the results, a comparison with the standard Dymola optimization library is performed. Both parallelization and indirect optimization with surrogate models achieved a significant runtime reduction by a factor of up to 5.4. The use of meta models is particularly advantageous for repetitive optimization runs of the same optimization problem but may lead to deviations due to the calculated approximations. Full article

As was shown in the previous part of the study, windshields are an important part of the passive safety means of modern low-floor trams with an extraordinary effect on pedestrian safety in a pedestrian–tram collisions. Therefore, maximum attention must be paid to the definition of tram windshield characteristics. This article describes a windshield crash test, from which data are obtained to verify the feasibility of the applied computational approaches. A developed analytical model is utilised for a simple description of the energy balance during collision with an illustrative definition of the important parameters of laminated glass as well as their clear physical interpretations. The finite element analysis (FEA) performed in Ansys software using two versions of material definition, namely a simpler (*MAT_ELASTIC with nonlocal failure criterion) and a more complex (*MAT_GLASS with brittle stress-state-dependent failure) material model, which are presented as suitable for obtaining a detailed description of the shattering process of laminated glass, which can also be used effectively in windshield engineering. Full article

The reliability of numerical simulations of the structural response of nonhomogeneous materials to high velocity loadings is highly dependent on the used material model and parameters. For nonhomogeneous materials, such as fibres, reinforced concrete is widely used for the Winfrith model, but the question of appropriate material parameters for Ultra-High Performance Fibre Reinforcement Concrete (UHPFRC) under high velocity loadings is still open. The article deals with possible method of inverse identification of material parameters of a UHPFRC slab under blast loading for a Winfrith material model. Possible application is in the field of numerical simulation of protective or critical infrastructure response to blast loading. Experimental measurement of the time–deflection curve through laser scanning using the triangulation method gave us input data for an inverse identification phase conducted in Optislang software. Obtained material parameters from a given range are optimized for blast loading and their Pearson’s correlation coefficient provides us information about their significance for simulation. Full article

In this study, a metamodel of an optimal arrangement of wind turbines was developed to maximize the energy produced by minimizing the energy loss due to wakes in a limited space when designing a wind farm. Metamodeling or surrogate modeling techniques are often used to replace expensive simulations or physical experiments of engineering problems. Given a training set, you can construct a set of metamodels. This metamodel provided insight into the correlation between wind farm geometry and the corresponding turbine layout (maximizing energy production), thereby optimizing the area of the wind farm required to maximize wind turbine capacity. In addition, a design support Microsoft Excel program was developed to quickly and easily calculate the annual energy production forecast considering the wake effect, as well as to confirm the prediction suitability, the annual energy production (AEP) analysis result of the wind farm, and the calculation result from existing commercial software were compared and verified. Full article

Noise vibration and harshness (NVH) development often takes place in the later development phases. Shifting the optimization to the early digital development phase enables more parameters to participate in the optimization and leads to a more holistic development process. Digital NVH development often modifies system and component frequency response functions (FRFs) using finite element (FE) simulation. Currently, the often manual process of creating new FE models for modified designs makes a systematic evaluation of many designs difficult and time-consuming. In this paper, we take on these difficulties and use both a Direct Morphing approach and a Box Morphing approach to automatically adopt the first existing FE models to modified designs. We use the generated simulation results to fit metamodels describing the correlation between geometrical parameters and characteristic FRF values. These metamodels provide an easy and fast to use tool for designers to consider NVH demands. In a simulation example, we demonstrate the capabilities by modifying the kinematic hard points of a vehicle suspension and using them to modify the noise transfer sensitivity. We show that the metamodels can lead the digital design process to intuitively and specifically reduce characteristic component FRF values by changing the location of the component hard points. Full article