Mesh Generation Research Articles

Hybrid Base Complex: Extract and Visualize Structure of Hex-dominant Meshes.

Hex-dominant mesh generation has received significant attention in recent research due to its superior robustness compared to pure hex-mesh generation techniques. In this work, we introduce the first structure for analyzing hex-dominant meshes. This structure builds on the base complex of pure hex-meshes but incorporates the non-hex elements for a more comprehensive and complete representation. We provide its definition and describe its construction steps. Based on this structure, we present an extraction and categorization of sheets using advanced graph matching techniques to handle the non-hex elements. This enables us to develop an enhanced visual analysis of the structure for any hex-dominant meshes.We apply this structure-based visual analysis to compare hex-dominant meshes generated by different methods to study their advantages and disadvantages. This complements the standard quality metric based on the non-hex element percentage for hex-dominant meshes. Moreover, we propose a strategy to extract a cleaned (optimized) valence-based singularity graph wireframe to analyze the structure for both mesh and sheets. Our results demonstrate that the proposed hybrid base complex provides a coarse representation for mesh element, and the proposed valence singularity graph wireframe provides a better internal visualization of hex-dominant meshes.

Unstructured surface mesh generation based on conformal welding

Unstructured surface mesh generation based on conformal welding

Algorithmic analysis and application of structural tessellation in design and optimization

This paper explores the application of structural tessellation in architectural and structural design, where surfaces or spaces are divided into smaller repeating shapes or units to create aesthetic and functional structures. Structural tessellation offers various advantages, including improved stability, increased load-bearing capacity, and enhanced aesthetic appeal. The growing use of digital tools and advanced numerical algorithms has facilitated the creation of complex and intricate tessellations that can be tailored to suit specific project requirements. This research focuses on algorithmic methods for generating tessellations and their utilization in structural engineering and design optimization. Diverse patterns and configurations of tessellation are investigated through mesh generation algorithms, parametric approaches, and pattern gradation and repetitions, with data visualization accomplished using computing scripts and Grasshopper. The tessellation elements are employed to discretize the design domain in structural optimization and create initial patterns. The paper demonstrates the feasibility of proposed frameworks for structural design and application through the examination of various numerical examples. In conclusion, the strategic use of structural tessellation proves to be effective in producing unique and functional structures that seamlessly combine visual appeal with material and resource efficiency.

Isomorphic Mesh Generation from Point Clouds with Multilayer Perceptrons.

A novel neural network called the isomorphic mesh generator (iMG) is proposed to generate isomorphic meshes from point clouds containing noise and missing parts. Isomorphic meshes of arbitrary objects exhibit a unified mesh structure, despite objects belonging to different classes. This unified representation enables various modern deep neural networks (DNNs) to easily handle surface models without requiring additional pre-processing. Additionally, the unified mesh structure of isomorphic meshes enables the application of the same process to all isomorphic meshes, unlike general mesh models, where processes need to be tailored depending on their mesh structures. Therefore, the use of isomorphic meshes can ensure efficient memory usage and reduce calculation time. Apart from the point cloud of the target object used as input for the iMG, point clouds and mesh models need not be prepared in advance as training data because the iMG is a data-free method. Furthermore, the iMG outputs an isomorphic mesh obtained by mapping a reference mesh to a given input point cloud. To stably estimate the mapping function, a step-by-step mapping strategy is introduced. This strategy enables flexible deformation while simultaneously maintaining the structure of the reference mesh. Simulations and experiments conducted using a mobile phone have confirmed that the iMG reliably generates isomorphic meshes of given objects, even when the input point cloud includes noise and missing parts.

LATTICE BOLTZMANN ANALYSIS OF MIXED CONVECTION IN A LID-DRIVEN CAVITY WITH AN INNER HOT ELLIPTICAL BLOCK: EFFECT OF BLOCK INCLINATION

This study is a computational analysis of hydrodynamic and thermal behavior of combined natural and forced convection with a moving wall in a square enclosure containing an elliptical block. This inner block is exposed to a hot temperature. The enclosure is full of air which is cooled on its side walls by a low temperature. The remaining surfaces are thermally insulated, and the upper surface is sliding at a steady speed <i>u</i><sub>0</sub>. In particular, the impact of various factors related to geometry, such as the emplacement and the elliptical block inclination are analyzed for the range of the dimensionless parameter Richardson number (0.01 ≤ Ri ≤ 100) by using lattice Boltzmann method (LBM) with single relaxation time model (SRT). LBM offers the advantage of handling irregular geometries and curved boundaries without requiring complex mesh generation, simplifying computations, and reducing computational costs in comparison to the traditional methods. The findings are in the forms of streamlines, temperature contours, the mean Nusselt number, and the fluid mean temperature inside the enclosure. The results show that for the prevailing natural convection and for the centrally placed elliptical block, the dynamic and thermal fields are almost indicated by symmetry with regard to the mid-vertical of the enclosure. Moreover, the inclination of the elliptical block prevents the enhancement of the heat transfer for all positions of the block; except when the block is located close to the upper surface, the inclination improves the rate of heat transfer especially for Ri ≤ 1.

System multi-scale analysis of temperature control for spaceborne electronic devices

<sec>To improve the simulation resolution and accuracy in thermal analysis of spaceborne electronic devices and the temperature control performance of passive thermal control devices, a system multi-scale model is established, thereby obtaining the temperature field and heat flux of electronic devices inside the satellite on different scales as illustrated in the below figure. The temperature fluctuation mechanism inside the satellite is analyzed on different physical scales. The thermal analysis resolution of spaceborne electronic equipment is improved, and a method to reduce the power fluctuation of spaceborne equipment is proposed based on the results of system multi-scale thermal analysis.</sec><sec>The results indicate that the accuracy deviation between the multi-scale model of the system and the actual model is less than 9%. However, the system multi-scale model saves 99.67% of the mesh generation time, which greatly improves the computation efficiency. The system multi-scale model can capture the thermal information about device-level chip microstructures at a lower computational cost. The system-level model can evaluate the temperature control and insulation performance of passive thermal control materials on a macroscale. The temperature fluctuation amplitude of the platform compartment is 7.95 K, while the temperature fluctuation amplitude of the load compartment decreases to 2.43 K after the temperature of the composite phase change insulation material has been controlled, which is 69.43% lower than that of the platform compartment. Compared with traditional vacuum insulation panels, the composite phase change materials are very superior in controlling the temperature of the chamber and suppressing temperature fluctuations. The temperature fluctuation signal after being insulated by the composite phase change insulation materials shows a characteristic of shifting to the high-frequency domain. After selecting the cabins that require key insulation and temperature control through multiple regression analysis, a simplified model at device level is employed to obtain temperature fields under different thermal control device layouts as a training dataset. A neural network genetic algorithm is used to predict the optimal installation position of passive thermal control device on the device scale and a thermal control layout scheme is obtained, which reduces the maximum temperature fluctuation of the device by 2.74 K. If the temperature uniformity coefficient is taken as the optimization goal, the temperature of each device on PCB board can be reduced to 14.39% of the average temperature of all devices through optimizations.</sec>

A metrics-based polycube construction method for hexahedral mesh generation

A metrics-based polycube construction method for hexahedral mesh generation

Digital solutions for monitoring and control of solar power in off-grid farms

The primary challenge for agricultural operations is their remoteness from centralized power supply systems. This necessitates the construction of an appropriate infrastructure to connect them to the general grid. One potential solution to this problem is the use of solar energy. The infrastructure required to create such a system is relatively inexpensive and allows for the creation of an autonomous system that provides all the necessary needs of the consumer. The control of such a system necessitates the development of specialized software. The paper presents the development of the hardware and software structure, as well as fragments of the prototype of the graphical user interface and a description of the main functionalities.

Multiscale simulation of highly heterogeneous subsurface flow with physically adaptive 3D unstructured grids

The multiscale finite volume framework is extended with physical-based grid adaptation (MSFV-GA) for three-dimensional fully unstructured grids. The MSFV method produces large errors for highly heterogeneous and anisotropic problems on standard coarse grids generated based on geometrical features. Adding constraints based on the fine-scale physical properties to construct coarse grids can increase the accuracy and robustness of the MSFV solutions. A novel and automated coarse grid generation strategy adaptable to the reservoir heterogeneity for 3D unstructured grids is presented. Adaptive coarse grids are generated based on local variations of fine scale permeability field. The proposed procedure is very flexible respect to the local physical and geometrical limitations in coarse blocks. Multiscale coarse grid adaptation notably improves the basis functions calculations. The performance of the MSFV-GA in handling challenging problems involving high media contrasts or impermeable shale layers is assessed. The results are very promising and show that the MSFV-GA can accurately approximate complex physics problems. The presented 3D unstructured procedure can notably improve the applicability of the multiscale finite volume method and provide a promising framework for the next generation of reservoir flow simulators.

The random feature method for solving interface problems

Interface problems have long been a major focus of scientific computing, leading to the development of various numerical methods. Traditional mesh-based methods often employ time-consuming body-fitted meshes with standard discretization schemes or unfitted meshes with tailored schemes to achieve controllable accuracy and convergence rate. Along another line, mesh-free methods bypass mesh generation but lack robustness in terms of convergence and accuracy due to the low regularity of solutions. In this study, we propose a novel method for solving interface problems within the framework of the random feature method (RFM). This approach utilizes random feature functions in conjunction with a partition of unity as approximation functions, and solves a linear least-squares system to obtain the approximate solution. In the context of interface problems, two innovative and crucial components are incorporated into the RFM. Firstly, we utilize two sets of random feature functions on each side of the interface, allowing for the inclusion of low regularity or even discontinuous behaviors in the solution. Secondly, the construction of the loss function is based on the assessment of the partial differential equation, initial/boundary conditions, and the interface condition on collocation points. This approach ensures that these conditions are equally satisfied. Consequently, the challenges arising from geometric complexity primarily manifest in the generation of collocation points, a task amenable to standard methods. Importantly, the proposed method retains its meshfree characteristics and robustness when addressing problems featuring intricate geometries. We validate our method through a series of linear interface problems with increasingly complex geometries, including two-dimensional elliptic and three-dimensional Stokes interface problems, a three-dimensional elasticity interface problem, a moving interface problem with topological change, a dynamic interface problem with large deformation, and a linear fluid–solid interaction problem with complex geometry. Our findings show that despite the solution often being only continuous or even discontinuous, our method not only eliminates the need for mesh generation but also maintains high accuracy, akin to the spectral collocation method for smooth solutions. Remarkably, for the same accuracy requirement, our method requires two to three orders of magnitude fewer degrees of freedom than traditional methods, demonstrating its significant potential for solving interface problems with complex geometries and predetermined intricate evolution.

3D magnetic flux density measurement with reduced sampling and high accuracy using visual localization and adaptive mesh generation

3D magnetic flux density measurement with reduced sampling and high accuracy using visual localization and adaptive mesh generation

An improved method combined modified drag model and modified erosion model based on LES for solid-liquid multiphase flow and erosion with application in a 90° elbow

In various industrial processes, solid-liquid multiphase flows involving continuous carrier and discrete particle phases have erosion challenges. In this work, a modified drag model that considers the influence of turbulence intensity and a modified erosion model that considers the effect of low-angle impact are developed. An improved method combined modified drag model and modified erosion model based on LES is proposed for numerical simulation of solid-liquid multiphase flow and erosion. The commercial software ICEM for grid generation and ANSYS FLUENT for LES are used in the present work. In validation test of velocity distribution of solid-liquid multiphase flow in a vertical pipe, the mean relative error of the liquid phase pulsation velocity is 10.01 % for modified drag model, whereas the mean relative error is 16.11 % for original drag model. In validation test of the maximum erosion depth from a submerged impact test at a tilt angle of 45°, the relative error is 0.23 % for modified erosion model, while the relative error is 13.39 % for original erosion model. Then, the improved method is employed to compute the characteristics of solid-liquid flow and erosion in a 90° elbow. Particles have a significant influence on liquid flow in the shear layer area where the inner arch separation zone interacts with the main flow, and this influence is most pronounced at the position of r* = 0.3 at yd = 0.4D. At this position, particles result in 15.27 % reduction in liquid velocity and 8.75 % increase in turbulence intensity. The mean relative error of the elbow erosion rate by using the improved method is 16.95 %, whereas it is 31.34 % of the reference work. The erosion is affected by impact velocity, angle, and particle number, and the most significant parameter is the particle number in the severe erosion area.

(Invited) Simulations of Ultra-Scaled Electronic Devices with a Novel Flexible Nano-TCAD Nano-Electronic Simulation Software (NESS) Environment

Simulation of conventional and emerging electronic devices using Technology Computer Aided Design (TCAD) tools has been an essential part of the semiconductor industry as well as academic research. Computational efficiency and accuracy of the numerical modeling are the key criteria on which quality and utility of a TCAD tool is ascertained. Further, the ability of the tool to incorporate different modeling paradigms and to be applicable to a wide range of device architectures and operating conditions is essential.In this talk, I will provide an overview of the new device simulator NESS (Nano-Electronic Software Simulator) developed at Device Modelling Group at University of Glasgow. NESS is a fast, modular software with its own structure and mesh generators, and contains different modules for classical, semi-classical, and quantum transport solvers, mobility calculation, kinetic Monte-Carlo etc. NESS can simulate numerous device architectures such as nanowire and bulk transistors, tunnelling field effect transistors (TFET) and resonant tunnelling diodes. Moreover, NESS accounts for various sources of statistical variability in nano-size electronic devices and it can perform statistical simulations for thousands microscopically different devices.

Numerical method used for the simulation of fluid–solid transitions based on the VOF and SAM models and prediction of snow distributions on large-span roofs

During a snowfall, the surfaces of the snow beds on roofs change dynamically with time and wind conditions. The generation of body-fitted computational fluid dynamics grids for simulating dynamic snow surfaces using the moving-grid method remains challenging. Therefore, a numerical method was developed to simulate the fluid–solid transition based on the volume of the fluid model and solidification and melting models. The snowfall process was divided into n stable steps, and a stable state calculation method was adopted to calculate the air and snow phases. The dynamic snow boundary was simulated at each stage by converting the fluid or solid characteristics of the domain in which the grids resided. Based on the results of the (n−1)th stage, the fluid domain grids buried by the snow were filled with liquid and frozen into the solid domain. Instead, the fluid in the frozen grids, where snow was about to be eroded, was evacuated and converted into fluid-domain grids. Thus, a complex and changeable snow boundary could be adapted without re-meshing. A modified wall friction velocity equation was derived to correct the wall friction velocity at the snow boundary owing to the serrated boundary of the solidified grids, thereby improving calculation accuracy. The numerical simulation results were verified via field observations of snow distribution on the stepped flat and gable roof models. The snow variation on a full-scale, three-span, suspended cable roof under snow-fall conditions was predicted using the proposed method.

Research on Optimization of Valley-Filling Charging for Vehicle Network System Based on Multi-Objective Optimization

Many electric vehicles connected to the grid will lead to problems such as poor stability of power grid generation. The key to solving these problems is to propose an efficient, stable, and economical valley-filling charging scheme for electric vehicles and grid users in the vehicle network system. Firstly, the convex optimization theory is used to make the grid achieve the optimization effect of valley filling. On this basis, the electricity price scheme with a time-varying coefficient as the variable is proposed to meet the single objective optimization of EV charging cost optimization, and its degree of influence on the grid valley-filling effect is analyzed. Secondly, based on the competitive relationship between EV charging cost and battery life, the P2D model is simplified and analyzed, and the attenuation law of battery capacity is quantitatively described. The multi-objective optimization problem is established to express in a Pareto matrix. Finally, the compatibility between the multi-objective optimization and grid valley charging is analyzed. The simulation results show that: (1) The convexity electricity price scheme can satisfy the requirements of various retention rates to achieve the valley-filling effect; (2) The filling effect is satisfied with the electricity price scheme that minimizes the charging cost, and the key factors affecting the filling effect are analyzed; (3) The multi-objective optimization scheme with charging cost and battery life is compatible with the valley-filling effect.

Research of PM-ADC scheme for optimized computational CFD analysis in fast reactor cores

Several challenges exist in the analysis of the sodium-cooled fast reactor (SFR) core using computational fluid dynamics (CFD)codes. These include the intricate task of geometric modeling and mesh partitioning and the substantial computational resources required by CFD calculations. These challenges have been shown to create significant impediments to the practical analysis of the SFR core. This paper proposes a CFD scheme called the Parameterized Modeling and Automated Distributed Computing Approach (PM-ADC) to address the challenges. This approach includes a fuel assembly model tailored for the fast reactor core and incorporates parameterized geometric modeling coupled with a system to automate the distribution of parallel computing. The PM-ADC scheme is divided into two critical components: rapid preprocessing design and the generation of geometric models and meshes for core assemblies, enabled by Parameterized Modeling (PM). In contrast, the Automatic Distributed Computing (ADC) component is responsible for the enhancement of computing efficiency and resource utilization. This is achieved by the automatic allocation and distribution of CFD computing resources within a partitioned domain, resulting in the completion of CFD analyses for all fuel assemblies at full height in a significantly reduced timeframe. The performance of the PM-ADC scheme is analyzed on CFD calculations on representative areas of 81 fuel assemblies within the core of the Chinese Experimental Fast Reactor (CEFR). The results show that the PM-ADC scheme can accurately and efficiently simulate the flow and heat transfer characteristics of the CEFR fuel assembly, demonstrating its potential for high-fidelity analysis of large engineering systems. The study's findings also provide new insights and tools for the ongoing development and analysis of SFRs, contributing to the evolution of nuclear reactor design and safety.

Numerical and correlation analysis of conjugate heat transfer over the discrete braided composites plate

Braided composites, which have excellent mechanical and thermophysical performance, have been considered promising materials widely used in aerospace, renewable energy, and other fields. However, the conjugate heat transfer mechanism between working fluids and braided structures is still unclear. Due to the complicated structure and computational limitation, with a neglection of the structural discrete feature and velocity distortion, current pertinent research primarily relies on the equivalent method of homogenization. In this research, a detailed numerical investigation of conjugate heat transfer over a three-dimensional four-directional (3D4d) braided composite plate with anisotropic and discrete features is presented. The full-size geometric structure of the 3D4d braided plate is first established utilizing the representative volume element (RVE). For such periodic structures, a continuous Eulerian grid generation technique is developed. A local coordinate system approach for the heat conduction spindle based on discretization is subsequently proposed to address the anisotropy of heterogeneous materials. The accuracy of the proposed discrete model processing approaches is verified by comparison with homogenization techniques widely used and experimental data in the literature. It is discovered that the discrete structure with an interfacial thermal dispersion, has a unique physical field distribution in comparison to the homogenization cases. Moreover, a semi-theoretical heat transfer criterion for 3D4d composite is established based on the thermal correction of dispersed interface.

Radial Basis Functions Approximation Method for Time-Fractional FitzHugh–Nagumo Equation

In this paper, a numerical approach employing radial basis functions has been applied to solve time-fractional FitzHugh–Nagumo equation. Spatial approximation is achieved by combining radial basis functions with the collocation method, while temporal discretization is accomplished using a finite difference scheme. To evaluate the effectiveness of this method, we first conduct an eigenvalue stability analysis and then validate the results with numerical examples, varying the shape parameter c of the radial basis functions. Notably, this method offers the advantage of being mesh-free, which reduces computational overhead and eliminates the need for complex mesh generation processes. To assess the method’s performance, we subject it to examples. The simulated results demonstrate a high level of agreement with exact solutions and previous research. The accuracy and efficiency of this method are evaluated using discrete error norms, including L2, L∞, and Lrms.

Drag Reduction Analysis of Optimal Three-dimensional Bumps on the M6 Wing

Based on Isight optimization software and evolutionary strategy algorithm, this paper builds a bump optimization design platform by integrating the three-dimensional bump shape generator program, grid generation software Gridgen and flow field simulation software Fluent. This platform is successfully validated on the RAE2822 supercritical infinite straight wing, which reduces the drag coefficient by 11 counts and increases the lift-drag ratio by 11.48 percent. Through this platform, the drag reduction characteristics of optimal three-dimensional bumps on the M6 wing are numerical studied. The results show that the three-dimensional bumps can weaken shock waves and have spanwise characteristics, the stronger the shock waves, the more obvious the drag reduction effect of the three-dimensional bumps, and the wing with optimal three-dimensional bumps can improve flow field characteristics and prevent flow separations.

Numerical simulation of flow and heat transfer in a pipe with nail-shaped hurdles

We investigate fluid flow and heat transfer in a channel obstructed by nail-shaped hurdles under forced convection using the Finite Difference Method. Due to the absence of an analytical solution, numerical techniques are employed. The channel is geometrically transformed into a rectangular configuration using curvilinear coordinates. Elliptic grid generation is used to discretize the domain. The Navier–Stokes equations are reformulated through the vorticity stream function formulation, and the Finite Difference Method incorporates a coordinate transformation approach. Effects of Reynolds numbers between (20≤Re≤600), Prandtl numbers (0.71,17.1), and nail spans (0.1≤h≤0.7) on velocity, temperature profiles is studied. Local and Average Nusselt numbers on Nail-shaped hurdle are also calculated. The observed maximum Nusselt numbers are 13.49,27.83, and 11.86 at Ra=600,Pr=7.1, and h=0.1, respectively Results show that higher Reynolds and Prandtl numbers increase Nusselt numbers, enhancing heat transfer. Narrower nail spans improve heat transfer efficiency.