Mesh Geometry Research Articles

Fine-Grained Multi-View Hand Reconstruction Using Inverse Rendering

Reconstructing high-fidelity hand models with intricate textures plays a crucial role in enhancing human-object interaction and advancing real-world applications. Despite the state-of-the-art methods excelling in texture generation and image rendering, they often face challenges in accurately capturing geometric details. Learning-based approaches usually offer better robustness and faster inference, which tend to produce smoother results and require substantial amounts of training data. To address these issues, we present a novel fine-grained multi-view hand mesh reconstruction method that leverages inverse rendering to restore hand poses and intricate details. Firstly, our approach predicts a parametric hand mesh model through Graph Convolutional Networks (GCN) based method from multi-view images. We further introduce a novel Hand Albedo and Mesh (HAM) optimization module to refine both the hand mesh and textures, which is capable of preserving the mesh topology. In addition, we suggest an effective mesh-based neural rendering scheme to simultaneously generate photo-realistic image and optimize mesh geometry by fusing the pre-trained rendering network with vertex features. We conduct the comprehensive experiments on InterHand2.6M, DeepHandMesh and dataset collected by ourself, whose promising results show that our proposed approach outperforms the state-of-the-art methods on both reconstruction accuracy and rendering quality. Code and dataset are publicly available at https://github.com/agnJason/FMHR.

PaintHuman: Towards High-Fidelity Text-to-3D Human Texturing via Denoised Score Distillation

Recent advances in zero-shot text-to-3D human generation, which employ the human model prior (e.g., SMPL) or Score Distillation Sampling (SDS) with pre-trained text-to-image diffusion models, have been groundbreaking. However, SDS may provide inaccurate gradient directions under the weak diffusion guidance, as it tends to produce over-smoothed results and generate body textures that are inconsistent with the detailed mesh geometry. Therefore, directly leveraging existing strategies for high-fidelity text-to-3D human texturing is challenging. In this work, we propose a model called PaintHuman to addresses the challenges from two perspectives. We first propose a novel score function, Denoised Score Distillation (DSD), which directly modifies the SDS by introducing negative gradient components to iteratively correct the gradient direction and generate high-quality textures. In addition, we use the depth map as a geometric guide to ensure that the texture is semantically aligned to human mesh surfaces. To guarantee the quality of rendered results, we employ geometry-aware networks to predict surface materials and render realistic human textures. Extensive experiments, benchmarked against state-of-the-art (SoTA) methods, validate the efficacy of our approach.Project page: https://painthuman.github.io/.

Free and forced vibration analysis over meshes with tangled (non-convex) elements

Tangled (non-convex) elements, i.e. elements with negative Jacobian determinant, can lead to erroneous results in the standard finite element method (FEM). Constructing tangle-free, well-structured meshes for complex geometries is often impossible. Hence there is a need to explore analysis methods that can directly handle such tangled meshes.In this paper, we propose the isoparametric tangled finite element method (i-TFEM) for free and forced vibration problems over tangled meshes. By employing piece-wise invertible mapping, a variational formulation is derived, leading to a simple modification of the standard FEM stiffness and mass matrices with the incorporation of additional compatibility constraints. Moreover, i-TFEM reduces to standard FEM for non-tangled (regular) meshes. The proposed method is implemented for three types of elements: 4-node quadrilateral, 9-node quadrilateral, and 8-node hexahedral elements. The numerical results demonstrate that i-TFEM is able to consistently handle general tangled (non-convex) elements, enabling convenient meshing for complex geometries.

Finite element modeling of infrasound resonance in an underground tunnel structure

Recent observations of acoustic/infrasound signals emanating from an underground mine in central Utah show a spectral signature consisting of several dominant harmonics whose amplitude decay rate increases with frequency. This spectral character is consistent with a model in which the observed signals are generated from acoustic resonance within the mine tunnels. I present models of these signals computed using a discontinuous-Galerkin finite element formulation. The mesh geometry of these models is based on the known geometry of the mine tunnels obtained using traditional survey methods. Explosion source locations in the mine are known from previous analysis of seismic signals and operator logs and are associated with observations of infrasound resonance at multiple far-field stations. I explore the sensitivity of the modeled signals to changes in the source spectrum, boundary conditions within in the mine and perturbations to tunnel geometry. I discuss the possible application of my results to volcanic monitoring, industrial monitoring of underground structures, and the possible determination of underground tunnel geometries using far-field observations of acoustic resonance.

Subject-specific finite element head models for skull fracture evaluation-a new tool in forensic pathology.

Post-mortem computed tomography (PMCT) enables the creation of subject-specific 3D head models suitable for quantitative analysis such as finite element analysis (FEA). FEA of proposed traumatic events is an objective and repeatable numerical method for assessing whether an event could cause a skull fracture such as seen at autopsy. FEA of blunt force skull fracture in adults with subject-specific 3D models in forensic pathology remains uninvestigated. This study aimed to assess the feasibility of FEA for skull fracture analysis in routine forensic pathology. Five cases with blunt force skull fracture and sufficient information on the kinematics of the traumatic event to enable numerical reconstruction were chosen. Subject-specific finite element (FE) head models were constructed by mesh morphing based on PMCT 3D models and A Detailed and Personalizable Head Model with Axons for Injury Prediction (ADAPT) FE model. Morphing was successful in maintaining subject-specific 3D geometry and quality of the FE mesh in all cases. In three cases, the simulated fracture patterns were comparable in location and pattern to the fractures seen at autopsy/PMCT. In one case, the simulated fracture was in the parietal bone whereas the fracture seen at autopsy/PMCT was in the occipital bone. In another case, the simulated fracture was a spider-web fracture in the frontal bone, whereas a much smaller fracture was seen at autopsy/PMCT; however, the fracture in the early time steps of the simulation was comparable to autopsy/PMCT. FEA might be feasible in forensic pathology in cases with a single blunt force impact and well-described event circumstances.

Evaluating 3D printed mesh geometries in ceramic LiB electrodes

Additive manufacturing techniques have the potential to promote a paradigmatic change in the electrode fabrication processes for lithium-ion batteries (LiBs) as they may offer alternative component designs to boost their performance or to customise the application. The present research work explores the use of low-cost fused filament fabrication (FFF) 3D printing to fabricate Li4Ti5O12 (LTO) mesh electrodes in the search for enlarged electrochemically active areas. Using different nozzle diameters (ND), we have 3D printed several mesh electrodes that after sintering allow an increase in the surface to volume ratio by up to ≈290% compared to conventional flat cylindrical geometries. As the conventional route to produce 3D printed meshes, i.e. stacking of consecutive layers with a 90° rotation, leads to problems of vertical misalignment that may affect the electrical contact, we have developed a new compact design that maximises the contact between layers. All the 3D printed mesh electrodes with thicknesses of 400 and 800 μm, exhibit electrochemical performance very close to those of thin (70 μm) electrodes, e.g. 175 mAh g−1 at C/2 in the case of ND = 100 μm, which is the theoretical capacity value for LTO. At higher C-rates, 800 μm-thick mesh electrodes with larger ND exhibit a marked drop in the reversible capacity (28 mAh g−1 at 8 C), although the values obtained improve notably those of the equivalent thick solid electrode (almost null at 8 C). The compact design demonstrated superior performance at high C-rates, improving by ≈70% the results of the best conventional mesh electrode at 8 C for 800 μm electrodes. These results highlight the potential of FFF-3D printing to generate novel high aspect ratio geometries and the impact of design and printing parameters on the performance of LiB electrode materials. Exploring alternative efficient geometries may facilitate the integration of thick electrodes in high energy density LiBs.

TokaMaker: An open-source time-dependent Grad-Shafranov tool for the design and modeling of axisymmetric fusion devices

In this paper, we present a new static and time-dependent MagnetoHydroDynamic (MHD) equilibrium code, TokaMaker, for axisymmetric configurations of magnetized plasmas, based on the well-known Grad-Shafranov equation. This code utilizes finite element methods on an unstructured triangular grid to enable capturing accurate machine geometry and simple mesh generation from engineering-like descriptions of present and future devices. The new code is designed for ease of use without sacrificing capability and speed through a combination of Python, Fortran, and C/C++ components. A detailed description of the numerical methods of the code, including a novel formulation of the boundary conditions for free-boundary equilibria, and validation of the implementation of those methods using both analytic test cases and cross-code validation is shown. Results show expected convergence across tested polynomial degree for analytic and cross-code test cases.

Enabling particle transport on CAD-based geometries for radiation simulations with penRed

Geometry construction is a fundamental aspect of any radiation transport simulation, regardless of the Monte Carlo code being used. Typically, this process is tedious, time-consuming, and error-prone. The conventional approach involves defining geometries using mathematical objects or surfaces. However, this method comes with several limitations, especially when dealing with complex models, particularly those with organic shapes. Furthermore, since each code employs its own format and methodology for defining geometries, sharing and reproducing simulations among researchers becomes a challenging task. Consequently, many codes have implemented support for simulating over geometries constructed via Computer-Aided Design (CAD) tools. Unfortunately, this feature is lacking in penRed and other PENELOPE physics-based codes. Therefore, the objective of this work is to implement such support within the penRed framework. New version program summaryProgram Title: Parallel Engine for Radiation Energy Deposition (penRed)CPC Library link to program files:https://doi.org/10.17632/rkw6tvtngy.2Developer's repository link:https://github.com/PenRed/PenRedCode Ocean capsule:https://codeocean.com/capsule/1041417/treeLicensing provisions: GNU Affero General Public License v3Programming language: C++ standard 2011.Journal reference of previous version: V. Giménez-Alventosa, V. Giménez Gómez, S. Oliver, PenRed: An extensible and parallel Monte-Carlo framework for radiation transport based on PENELOPE, Computer Physics Communications 267 (2021) 108065. doi:https://doi.org/10.1016/j.cpc.2021.108065.Does the new version supersede the previous version?: YesReasons for the new version: Implements the capability to simulate on CAD constructed geometries, among many other features and fixes.Summary of revisions: All changes applied through the code versions are summarized in the file CHANGELOG.md in the repository package.Nature of problem: While Monte Carlo codes have proven valuable in simulating complex radiation scenarios, they rely heavily on accurate geometrical representations. In the same way as many other Monte Carlo codes, penRed employs simple geometric quadric surfaces like planes, spheres and cylinders to define geometries. However, since these geometric models offer a certain level of flexibility, these representations have limitations when it comes to simulating highly intricate and irregular shapes. Anatomic structures, for example, require detailed representations of organs, tissues and bones, which are difficult to achieve using basic geometric objects. Similarly, complex devices or intricate mechanical systems may have designs that cannot be accurately represented within the constraints of such geometric models. Moreover, when the complexity of the model increases, geometry construction process becomes more difficult, tedious, time-consuming and error-prone [2]. Also, as each Monte Carlo geometry library uses its own format and construction method, reproducing the same geometry among different codes is a challenging task.Solution method: To face the problems stated above, the objective of this work is to implement the capability to simulate using irregular and adaptable meshed geometries in the penRed framework. This kind of meshes can be constructed using Computer-Aided Design (CAD) tools, the use of which is very widespread and streamline the design process. This feature has been implemented in a new geometry module named “MESH_BODY” specific for this kind of geometries. This one is freely available and usable within the official penRed package1. It can be used since penRed version 1.9.3b and above.

NekMesh: An open-source high-order mesh generation framework

High-order spectral element simulations are now becoming increasingly popular within the computational modelling community, as they offer the potential to deliver increased accuracy at reduced cost compared to traditional low-order codes. However, to support accurate, high-fidelity simulations in complex industrial applications, there is a need to generate curvilinear meshes which robustly and accurately conform to geometrical features. This is, at present, a key challenge within the mesh generation community, with only a few open-source tools able to generate curvilinear meshes for complex geometries. We present NekMesh: an open-source mesh generation package which is designed to enable the generation of valid, high-quality curvilinear meshes of complex, three-dimensional geometries for performing high-order simulations. We outline the software architecture adopted in NekMesh, which uses a pipeline of processing modules to provide a flexible, CAD-independent high-order mesh processing tool, capable of both generating meshes for a wide range of use cases, as well as post-processing linear meshes from a range of input formats for use with high-order simulations. A number of examples in various application areas are presented, with a particular emphasis on challenging aeronautical and fluid dynamics test cases. Program summaryProgram title: NekMesh (version 5.4.0)CPC Library link to program files:https://doi.org/10.17632/d82hjm4v6r.1Licensing provisions: MITProgramming language: C++External routines/libraries: Boost, TinyXML, OpenCASCADE, Triangle, TetGen, HDF5Nature of problem: NekMesh is a high-order mesh generation framework with the goal of providing a robust framework to automate the process of generating valid meshes for complex three-dimensional CAD geometries.Solution method: Energy minimisation, solid body models and other techniques based around high-order finite element methods.Additional comments including restrictions and unusual features: The supplied cases require a system with 16384 MB of RAM for the automotive example and 32768 MB of RAM for the variational optimisation example.

Investigation the thermal performance of Nano-Enhanced Phase Change Material (NEPCM) in an enclosure

Phase change materials (PCMs) play a vital role in thermal energy storage applications, as they provide efficient and dependable heat storage and release capabilities. This study provides a comprehensive evaluation of the thermal performance of Nano-Enhanced Phase Change Material (NEPCM) in an enclosure, with a focus on the effect of temperature variation and the role of nanoparticles. Variable temperature regimes significantly influence the physical and thermal properties of the NEPCM, as revealed by numerical simulations. The enthalpy-porosity approach for the phase change process and the solution of the Navier-Stokes equations for fluid flow serve as the primary foundations for the numerical model that will be covered in this study. With only a single phase of user input, ANSYS facilitates the creation of three-dimensional models and solid geometry meshes. Notably, an increase in the temperature of the heat-supplying wall resulted in substantial changes to the NEPCM, which we have thoroughly investigated and quantified. It has been demonstrated that the incorporation of various nanoparticles (Al2O3, CuO, and ZnO) into paraffin enhances the heating process, thereby enhancing the thermal conductivity, heat transfer coefficient, and surface tension of the NEPCM. The three nanoparticles decrease the mass fraction of paraffin in the range of 0.00 to 0.960 at the same concentration and testing temperature. In addition, increasing nanoparticle concentration under higher temperature regimes resulted in a faster and more uniform nanoparticle synthesis, significantly enhancing the NEPCM's thermal performance. Particularly, as the temperature increased, the NEPCM near the wall melted more rapidly. The study reveals the crucial role that temperature plays in modulating the behavior and performance of NEPCM, thereby providing valuable insights for thermal management systems. These results demonstrate the significance of temperature control for maximizing the potential of NEPCM in a variety of applications. As the temperature rises, one side becomes covered in the blue color (solid), while in the standard case, the melting curve shows a little red region (melting) at the other side that starts to increase when the nanomaterial's are added.

Optimization of the Second Target Station cold source moderators using an automated workflow

The Second Target Station (STS) at the US Department of Energy’s Oak Ridge National Laboratory is designed to become the world’s highest peak-brightness spallation source of cold neutrons. Successful completion of the STS, which is currently in the preliminary design phase, will provide transformative new capabilities to examine novel materials for future technologies. At STS, neutrons will be generated by spallation reactions in a solid tungsten target. They will be moderated and thermalized in two cold (20 K) para-hydrogen moderators. Careful optimization of these moderators is essential to the project’s success. To find optimal moderator designs, an advanced optimization workflow integrates high-fidelity neutronics calculations using the Monte Carlo N-Particle (MCNP) transport code MCNP6.2 with state-of-the-art optimization algorithms in the Dakota optimization toolkit. For each design iteration, a parametrized solid CAD geometry is generated in Creo and automatically converted into an unstructured mesh geometry by Attila 4MC for the neutronics calculation with MCNP. Iterations repeat until optimal designs are found. This paper presents the results of a sensitivity and optimization study for the cylindrical and tube moderators. Both moderators can be optimized for maximum peak brightness, maximum time-integrated brightness, or any combination between these extremes. Maximum peak brightness is achieved by using smaller optimal dimensions of the moderators, whereas maximum time-integrated brightness is achieved by using larger dimensions. A Pareto front details the designs that optimally balance both brightness metrics. The Pareto front can be found in only 40–110 iterations with 4–5 design parameters when using the efficient global and Pareto-set optimization algorithms in Dakota. Additionally, important engineering constraints can be taken into account, such as the coupling between the cylindrical moderator radius and aluminum vessel wall thicknesses required to ensure structural integrity of the vessels. This interaction has a significant impact on the resulting optimal designs. Our new, highly efficient, fully automated optimization workflow will be used to optimize additional STS components in the future and can be adopted for design and optimization studies at other experimental neutron and accelerator facilities.

Machine learning optimization of compact finite volume methods on unstructured grids

Fourier analysis based optimization techniques have been developed for numerical schemes on structured grids and result in significant performance improvements. However, there lacks an effective optimization technique for numerical schemes on general unstructured grids, due to the mesh geometry complexity that makes Fourier transformation infeasible. To address this issue, an optimization framework based on machine learning is developed in this paper for numerical schemes on unstructured grids. The optimization of a compact high-order variational reconstruction on triangular grids is performed to illustrate the framework. An artificial neural network (ANN) is used to predict the optimal values of the derivative weights on cell interfaces that are the free parameters of the variational reconstruction, given the local geometry as input. The ANN is trained by minimizing the solution errors of a linear advection equation on a set of generated compact stencils, with a set of sampled sine waves as initial conditions. The developed optimization framework is applicable to general numerical schemes on unstructured grids as the training does not require explicit computation of dispersion or dissipation. Numerical results for inviscid flow problems show that the optimized variational finite volume scheme is remarkably more accurate and efficient than its non-optimized counterpart, demonstrating the effectiveness of the machine learning optimization.

Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning.

Automated volumetric meshing of patient-specific heart geometry can help expedite various biomechanics studies, such as post-intervention stress estimation. Prior meshing techniques often neglect important modeling characteristics for successful downstream analyses, especially for thin structures like the valve leaflets. In this work, we present DeepCarve (Deep Cardiac Volumetric Mesh): a novel deformation-based deep learning method that automatically generates patient-specific volumetric meshes with high spatial accuracy and element quality. The main novelty in our method is the use of minimally sufficient surface mesh labels for precise spatial accuracy and the simultaneous optimization of isotropic and anisotropic deformation energies for volumetric mesh quality. Mesh generation takes only 0.13 seconds/scan during inference, and each mesh can be directly used for finite element analyses without any manual post-processing. Calcification meshes can also be subsequently incorporated for increased simulation accuracy. Numerous stent deployment simulations validate the viability of our approach for large-batch analyses. Our code is available at https://github.com/danpak94/Deep-Cardiac-Volumetric-Mesh.

The fast neutron fluence and the activation monitor activity calculations using fine multigroup and continuous nuclear data

The fast neutron fluence and the activation monitor activities are routinely calculated with TORT deterministic code and BUGLE-B7 nuclear data library with 47 broad energy groups. The objective of the paper is to analyse options to improve reactor dosimetry transport calculations. There are two paths to improve reactor dosimetry calculations. Increasing geometry, angular and energy mesh size is applicable for TORT code while using newer nuclear data libraries is relevant for both deterministic and Monte Carlo codes. Two new calculation options (improved TORT and Monte Carlo MCNP6) were compared with the standard TORT calculation for VVER-440 Dukovany Unit 3 Cycle 31. The fast neutron fluence with 0.5 MeV threshold as well as activity of Fe. Ni, Ti, Cu. Mn and Nb monitors were evaluated. Standard TORT calculations were improved from S16P3 to S30P3 with three times finer axial mesh size. 120° core symmetry r-ϑ mesh size with 0.5° step and fine multigroup libraries VUAMIN-B7 with 199 neutron energy groups and ENDF/B-VH.1 with 200 neutron energy groups. Both ENDFB and IRDFF activation cross sections were used. The drawback of expanded mesh size is raised calculation runtime since TORT deterministic code is not parallelized and one calculation can require multiple weeks of CPU time. An alternative option of using MCNP6 Monte Carlo code with continuous ENDF/B-VH.1 nuclear data with detailed 3-D geometry and pin-wise effective neutron source prepared by MOBY-DICK diffusion code reactor analysis wras explored. It was found that using finer mesh size affects reactor dosimetry’ tallies less than the choice of nuclear data library. BUGLE-B7 and VTTAMIN-B7 produce results typically within 1% difference. ENDF/B-VH.1 calculations with 200 neutron energy’ groups with TORT code are even in better agreement with MCNP6 calculations with continuous nuclear data libraries. The largest differences of around 2% were observed between VTTAMIN-B7 library based onENDFB-VH.O nuclear data and ENDF/B-VH.1 library. Nuclear data library’ has larger impact on the results with up to 7 % difference between all 0.5 MeV fast neutron fluence calculations. The largest intact of nuclear data was observed for Mn(n.2n) monitor.

Mathematical and computer modeling of transmission with non-traditional engagement for mining equipment drive

In modern gear mechanics, transmission mechanisms play a crucial role in converting the rotational motion of a driving shaft into the rotational motion of another shaft with varying angular speeds and torque. To achieve optimal designs for the next generation of transmission mechanisms, it is essential to develop mathematical models of their dynamic behavior, conduct computer simulations of the meshing geometry of key components, and visualize the operation of the mechanism. Despite the widespread use of involute gearing in mechanical transmissions, there is ongoing research into new types of gearing that offer advantages over traditional systems. The main challenges facing the industry include increasing the gear ratio in a single stage, enhancing load capacity, and improving efficiency compared to standard gear transmissions. This paper presents the results of mathematical and computer modeling, along with a comparative analysis of the eccentric-cycloid (EC) engagement with the involute gear transmission. Through analytical calculations, the energy-force parameters of the EC gearbox were determined, equivalent stresses and static deflections of transmission shafts were obtained. The paper includes the results of static analysis of elements of the new EC transmission, as well as an algorithm for computer modeling of contact stresses occurring in the engagement. Conclusively, by comparing contact stresses in traditional involute gear transmission, calculated using various analytical methods, with those in EC engagement determined through computer simulation, the advantages of the new transmission type and its potential application in mining equipment transmission mechanisms are highlighted.

2D/3D GPU-accelerated deterministic neutronics solver based on planar method of characteristics and hybrid finite element method

The newly developed 2D/3D method operating over the unstructured mesh geometry is introduced. Implemented in the NuDEAL code, the method alternates the planar method of characterization (MOC) and the diffusion-based hybrid finite element (HFEM), with planar MOC solving the 2D decoupled fine mesh and HFEM providing 3D coarse mesh flux distributions based on the MOC solution. The consistency between the planar MOC and the diffusion HFEM is made with the devised consistency factors operating on volumetric and surface flux distributions. Furthermore, the consistent HFEM is fully accelerated using GPUs, which results in a 50-speedup in the red-black sweep compared to the runtime of the single CPU core. As a result, the accelerated HFEM takes less than 30 seconds to solve the multigroup benchmark problem, which is 20 times faster with a single gaming GPU than with a single CPU core.

Numerical Simulation of Helical Coil Tube in Tube Heat Exchangers with Grooved Internal Tube

Abstract: The goal of this work is to analyse the heat transfer effects of providing inner tube with formed groove in helical coil tube in tube HE. In order to investigate further heat transmission improvements, the groove depth was increased to find the comparative study of Nusselt number in different cases analysed in this work. This was performed by use of Ansys CFD Fluent Software package by configuring and employing a compact 3-D model of a real and complex system to solve for the case studies in this research. The context for the topic is discussed, as well as explanation of process breakthroughs in CFD analysis. In order to improve the computational fluid dynamics simulations, information on proper mesh selection and geometry was generated with respect to theoretical concerns and finite CFD practises of element size, nodes, and shape appropriateness. The hot fluid flows through the annulus region and the cold fluid flows through the inner tube in the examined model with counterflow setup. After simulating fluid flow and performing a heat transfer study for a helical coil tube in tube HE with structural configuration as mentioned, post processing techniques is applied to produce the results as furnished by means of graphical representation. Moreover, upon discussion on the impact of variation of Nusselt number and friction factor were established, the analysed results create recommendations with the purpose of better understanding the impact of helical coil grooved tube heat transfer capacity in tube heat exchangers and future research. As a result, grooved inner tube treatment can significantly improve heat exchanger total heat transfer capacity, and the findings of this research can provide assistance theoretically for the development and design of helically coiled tubes in HEs.

From text to tech: Shaping the future of physics-based simulations with AI-driven generative models

This micro-article introduces a method for integrating Large Language Models with geometry/mesh generation software and multiphysics solvers, aimed at streamlining physics-based simulations. Users provide simulation descriptions in natural language, which the language model processes for geometry/mesh generation and physical model definition. Initial results demonstrate the feasibility of this approach, suggesting a future where non-experts can conduct advanced multiphysics simulations by simply describing their needs in natural language, while the code autonomously handles complex tasks like geometry building, meshing, and setting boundary conditions.

Accurate characterization of complex Bloch modes in optical chain waveguides using real-valued computations

This research presents a highly accurate and easy-to-implement method to characterize the complex Bloch modes propagating along optical chain waveguides with three-dimensional (3D) layered geometries and dispersive negative-epsilon material compositions. The technique combines commercial EM solver results with analytical post-processing to avoid iterative complex root estimation on the complex plane. The proposed methodology is based on the real-valued computations that yield the complex Bloch wavevector with superior accuracy even when both radiation and material losses are present. In addition, we introduce a single unit-cell technique to provide the possibility of dense meshing of 3D geometries when available computational resources are limited. To verify our results, two different plasmonic and dielectric case studies are discussed. The obtained results agree well with numerical and experimental results from the literature. Due to its generality, robustness, and high accuracy, the method is beneficial for studying a large variety of waveguide-based nanophotonic components.

Micromechanical modeling for analyzing non-linear behavior of flexible pavements under truck loading

This research paper presents a precise three-dimensional (3D) pavement model designed to accurately account for the detrimental effects of the asphalt layer while representing various layers within a pavement structure. The primary objectives of this study include the development of an accurate 3D pavement model, the integration of asphalt concrete's viscoelastic properties into the analysis, and the improvement of pavement distress prediction accuracy. To achieve these goals, a comprehensive approach was undertaken, involving a stress relaxation test to assess the viscoelastic properties of asphalt concrete. The study incorporates Prony series coefficients into the analysis, employing Finite Element Modeling Software Abaqus for an accurate representation of asphalt concrete behavior. The realistic geometry of asphalt concrete is captured using the Simpleware application, enhancing precision compared to Abaqus mesh geometry. Additionally, a user-defined material subroutine (UMAT) based on the Kelvin viscoelastic model is integrated into the finite element analysis within Abaqus. This approach significantly enhances predictions of vertical displacements and horizontal strains associated with common pavement distresses, surpassing conventional linear pavement modeling methods. Moreover, it offers improved accuracy in representing the actual geometry of asphalt concrete and enhances the prediction of wearing course performance, especially in high-temperature regions. By customizing the UMAT subroutine to simulate flexible pavement behavior, this research contributes to the advancement of pavement analysis and design.