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In this study, we propose a tetrahedral mesh generation and adaptive refinement method for multi-chamber, multi-facet, multiscale and surface-solid mesh coupling with extremely thin layers, solving the two challenges of mesh generation and refinement in current electromagnetic simulation models.

Utilizing innovative topology transformation techniques, high-precision intersection judgment algorithms and highly reliable boundary recovery algorithms to reduce the number of Steiner locking points. The feasible space for the reposition of Steiner points is determined by using the linear programming. During mesh refinement, an edge-split method based on geometric center and boundary facets node size is devised. Solving the problem of difficult insertion of nodes in narrow geometric spaces, capable of filtering the longest and boundary edges of tetrahedrons, refining the mesh layer by layer through multiple iterations, and achieving collaborative optimization of surface and tetrahedral mesh. Simultaneously, utilizing a surface-facet preserving mesh topology optimization algorithm to improve the fit degree between the mesh and geometry.

Initial mesh generation for electromagnetic models, compared to commercial software, the method proposed in this paper has a higher pass rate and better mesh quality. For the adaptive refinement performance of high-frequency computing, this method can generate an average of 50% fewer meshes compared to commercial software while meeting simulation accuracy.

This paper proposes a complete set of mesh generation and adaptive refinement theories and methods designed for the structural characteristics of electromagnetic simulation models, which meet the needs of real-world industrial applications.

The paper aims to propose a generation approach for unstructured surface mesh to speed up mesh generation.

The paper proposes a lightweight interactive generation approach for unstructured surface mesh and presents several key technologies to support this approach.

The experimental results show that the proposed approach is feasible for unstructured meshes and it can accelerate the mesh generation process.

More geometric defects should be covered, and more convenient and efficient interactive means need to be provided.

The proposed approach and key technologies are implemented in NNW-GridStar.UG, which is the unstructured version of the mesh generation software of National Numerical Windtunnel (NNW).

This paper proposes a lightweight interactive approach for unstructured surface mesh generation, which can speed up mesh generation.

The purpose of this paper is to optimize the key parameters (mesh count, paper type and ink type) in screen printing, which are affecting the printed ink volume. The objective of the optimization was to maximize the color reliability by decreasing the color difference (ΔE value) of the prints while minimizing the ink consumption. Screen printing is still dominating the printing industry to make cost-effective production when high volumes are needed.

The experiment was designed using the Taguchi method, and the samples were prepared with screen-printing by using the standard squeegee angle and pressure. The effect of mesh count, ink type and paper type on ink consumption was evaluated with using analysis of variances and main effects plots of S/N ratio and standard deviation.

The factors ink type, paper type and mesh count were found significant for ink consumption due to their Probability (P) values which were lower than 0.05. It was determined that the mesh count was the most critical variable with the analysis of variance. The analysis showed that the selection of an optimum mesh count was the key to controlling the amount of the deposited ink. Although mesh counts were inversely proportional with the ink consumptions, they did not affect the color differences as expected.

The optimization of process parameters, that are most effective on the print quality, is necessary to minimize the ink usage and lower the costs and environmental impact without exceeding the desired ΔE value limits.

The primary objective of this study is to tackle the enduring challenge of preserving feature integrity during the manipulation of geometric data in computer graphics. Our work aims to introduce and validate a variational sparse diffusion model that enhances the capability to maintain the definition of sharp features within meshes throughout complex processing tasks such as segmentation and repair.

We developed a variational sparse diffusion model that integrates a high-order L₁ regularization framework with Dirichlet boundary constraints, specifically designed to preserve edge definition. This model employs an innovative vertex updating strategy that optimizes the quality of mesh repairs. We leverage the augmented Lagrangian method to address the computational challenges inherent in this approach, enabling effective management of the trade-off between diffusion strength and feature preservation. Our methodology involves a detailed analysis of segmentation and repair processes, focusing on maintaining the acuity of features on triangulated surfaces.

Our findings indicate that the proposed variational sparse diffusion model significantly outperforms traditional smooth diffusion methods in preserving sharp features during mesh processing. The model ensures the delineation of clear boundaries in mesh segmentation and achieves high-fidelity restoration of deteriorated meshes in repair tasks. The innovative vertex updating strategy within the model contributes to enhanced mesh quality post-repair. Empirical evaluations demonstrate that our approach maintains the integrity of original, sharp features more effectively, especially in complex geometries with intricate detail.

The originality of this research lies in the novel application of a high-order L₁ regularization framework to the field of mesh processing, a method not conventionally applied in this context. The value of our work is in providing a robust solution to the problem of feature degradation during the mesh manipulation process. Our model’s unique vertex updating strategy and the use of the augmented Lagrangian method for optimization are distinctive contributions that enhance the state-of-the-art in geometry processing. The empirical success of our model in preserving features during mesh segmentation and repair presents an advancement in computer graphics, offering practical benefits to both academic research and industry applications.

Beginners and even experienced ones have difficulties in completing the structural fire analysis due to numerical difficulties such as convergence errors and singularity and have to spend a lot of time making many repetitive changes on the model. The aim of this article is to highlight the advantages of explicit solver which can eliminate the mentioned difficulties in finite element analysis containing highly nonlinear contacts, clearance between modeled parts at the beginning and large deflections because of high temperature. This article provides important information, especially for researchers and engineers who are new to structural fire analysis.

The finite element method is utilized to achieve mentioned purposes. First, a comparative study is conducted between implicit and explicit solvers by using Abaqus. Then, a validation process is carried out to illustrate the explicit process by using sequentially coupled heat transfer and structural analysis.

Explicit analysis offers an easier solution than implicit analysis for modeling multi-bolted connections under high temperatures. An optimum mesh density for bolted connections is presented to reflect the realistic structural behavior. Presented explicit process with the offered mesh density is used in the validation of an experimental study on multi-bolted splice connection under ISO 834 standard fire curve. A good agreement is achieved.

What makes the study valuable is that the points to be considered in the structural fire analysis are examined and it is a guide that future researchers can benefit from. This is especially true for modeling and analysis of multi-bolted connections in finite element software under high temperatures. The article can help to shorten and even eliminate the iterative debugging phases, which is a problematic and very time-consuming process for many researchers.

Currently, massive multiple-input multiple-output (m-MIMO) antennas are typically designed using complex trial-and-error methods. The purpose of this study is to determine an effective optimization method to achieve more efficient antenna design processes.

This paper presents the design stages of a m-MIMO antenna array compatible with 5G smartphones operating in long term evolution (LTE) bands 42, 43 and 46, based on a specific algorithm. Each antenna element in the designed 10-port m-MIMO antenna array is intended to perfectly cover the three specified LTE bands. The optimization methods used for this purpose include the Nelder–Mead simplex algorithm, covariance matrix adaptation evolution strategy, particle swarm optimization and trust region framework (TRF).

Among the primary optimization algorithms, the TRF algorithm met the defined objectives most effectively. The achieved antenna efficiency values exceeded 60.81% in the low band and 68.39% in the high band, along with perfect coverage of the desired bands, demonstrating the success of the design with the TRF algorithm. In addition, the potential electromagnetic field exposure caused by the designed m-MIMO antenna array is elaborated upon in detail using computational human models through specific absorption rate analysis.

The comparison of four different algorithms (two local and two global) for use in the design of a 10-element m-MIMO antenna array with a complex structural configuration and the success of the design implemented with the selected algorithm distinguish this study from others.

This study aims to obtain the minimum torque ripple at the maximum average torque for Flux-switching permanent magnet (FSPM) machines.

This paper is about torque performance optimization of the FSPM machines. To achieve that, finite element analysis and genetic algorithm (GA) are used. Five different designs are simulated, optimized and compared on their air gap flux density, back electromotive force, cogging torque, average torque, torque density and torque ripple.

After the thousands of iterations, its proved that all proposed shaping techniques have potential for reducing torque ripple and cogging torque, with slightly reduced average torque. The best design is the joint stator and rotor shaping, Design V, which results in the lowest torque ripple and cogging torque. The techniques should be applicable to FSPMs with other stator slot/rotor pole number combinations.

In this paper, rotor pole shaping by notching, chamfering and generic shaping, stator tooth shaping and joint shaping techniques are investigated for 12 s/10p FSPM machines. Rotor and stator flanks are optimized separately and jointly, by using finite element analysis and GA for optimization to achieve maximum average torque and minimum torque ripple. Five different design is implemented and compared, respectively.

This paper aims to investigate the moisture diffusion behavior in a system-in-package module systematically by moisture-thermalmechanical-coupled finite element modeling with different structure parameters under increasingly harsh environment.

A finite element model for a system-in-package module was built with moisture-thermal-mechanical-coupled effects to study the subsequences of hygrothermal conditions.

It was found in this paper that the moisture diffusion path was mainly dominated by hygrothermal conditions, though structure parameters can affect the moisture distribution. At lower temperatures (30°C~85°C), the direction of moisture diffusion was from the periphery to the center of the module, which was commonly found in simulations and literatures. However, at relatively higher temperatures (125°C~220°C), the diffusion was from printed circuit board (PCB) to EMC due to the concentration gradient from PCB to EMC across the EMC/PCB interface. It was also found that there exists a critical thickness for EMC and PCB during the moisture diffusion. When the thickness of EMC or PCB increased to a certain value, the diffusion of moisture reached a stable state, and the concentration on the die surface in the packaging module hardly changed. A quantified correlation between the moisture diffusion coefficient and the critical thickness was then proposed for structure parameter optimization in the design of system-in-package module.

The different moisture diffusion behaviors at low and high temperatures have seldom been reported before. This work can facilitate the understanding of moisture diffusion within a package and offer some methods about minimizing its effect by design optimization.

This study aims to investigate the possible defects and their root causes in a soft-termination multilayered ceramic capacitor (MLCC) when subjected to a thermal reflow process.

Specimens of the capacitor assembly were subjected to JEDEC level 1 preconditioning (85 °C/85%RH/168 h) with 5× reflow at 270°C peak temperature. Then, they were inspected using a 2 µm scanning electron microscope to investigate the evidence of defects. The reliability test was also numerically simulated and analyzed using the extended finite element method implemented in ABAQUS.

Excellent agreements were observed between the SEM inspections and the simulation results. The findings showed evidence of discontinuities along the Cu and the Cu-epoxy layers and interfacial delamination crack at the Cu/Cu-epoxy interface. The possible root causes are thermal mismatch between the Cu and Cu-epoxy layers, moisture contamination and weak Cu/Cu-epoxy interface. The maximum crack length observed in the experimentally reflowed capacitor was measured as 75 µm, a 2.59% difference compared to the numerical prediction of 77.2 µm.

This work's contribution is expected to reduce the additional manufacturing cost and lead time in investigating reliability issues in MLCCs.

Despite the significant number of works on the reliability assessment of surface mount capacitors, work on crack growth in soft-termination MLCC is limited. Also, the combined experimental and numerical investigation of reflow-induced reliability issues in soft-termination MLCC is limited. These cited gaps are the novelties of this study.

The purpose of this study is to apply the topology and parameter optimization (TPO) to interior permanent magnet (IPM) motors to obtain the optimized shape with higher torque, lower ripple and sufficient mechanical strength.

The constraints regarding the maximum stress, connectivity and mesh quality were considered to achieve not only high electrical performance but also high mechanical strength. To enhance the accuracy of the finite element analysis of the elastic analysis, this paper used body-fitted mesh adaptation technique to avoid the stress concentration.

The proposed method in this study resulted in feasible shapes with sufficiently high strength compared to previous studies. It is also shown that TPO yielded IPM motors with higher torque compared to topology optimization (TO) with fixed parameters.

Different from the existing studies on topology optimization of IPM motors, the mechanical strength is even considered by evaluating the stress values. Therefore, in the practical phase, geometries can be designed that are less likely to be damaged due to deformation, even in the high-speed rotation range.

This paper performed TO and parameter optimization (PO) simultaneously, considering not only the electrical performance but also the mechanical strength. Furthermore, the mechanical strength was evaluated more precisely by devising the elastic analysis conditions and mesh generation.