Volume Mesh Research Articles

Material extrusion additive manufacturing of dual material composite thermoset silicone components

AbstractAdditive manufacturing (AM) is a disruptive manufacturing process that gives designers freedom to create highly complex shapes through free‐form fabrication. The majority of polymers used in extrusion AM are thermoplastics because they are easy to process in affordable machines. While there are a number of moderate modulus thermoplastics in regular use in AM, thermoplastics are known to weaken with increases in temperature or exposure to solvents and many commodity thermoplastics used in AM are brittle. On the other hand, there are few elastomers, and even fewer elastomer reinforcement schemes, that are accessible using standard AM technologies. In this work, we report a novel dual extrusion process that integrates elastomeric silicone with reinforcing thermoplastic. By developing and demonstrating a dual extrusion 3D printer that can process common thermoplastics with commercially available thermosetting silicones, new types of composite elastomers are reported with good mechanical performance. The 0°/20°/−20° grid pattern thermoplastic reinforced samples achieved 2.5 MPa tensile strength in low extension region (0.5 strain), which improves the initial stiffness of the composite component. Desired mechanical responses of composite structures can be realized by tuning the reinforcement volume ratio and infill percentages, and applying various types of reinforcement mesh patterns and thermoplastics.Highlights A dual extrusion process integrates fus filament fabrication and direct ink writing technologies. Thermoplastic reinforced silicone composite with stiff/soft properties. Tunable volume ratio, infill percentage, mesh pattern, and material option.

Heat flux predictions for hypersonic flows with an overset near body solver on an adaptive block-structured Cartesian off-body grid

The manual volume mesh generation process for body-fitted CFD codes can be a time-intensive process, particularly for complex flight vehicles. The work shown here presents a hybrid body-fitted/Cartesian overset CFD solver capable of automatic volume mesh generation capabilities and accurate surface heating predictions. The solver uses a body-conformal near body solver for capturing boundary layer effects and an off-body Cartesian solver with adaptive mesh refinement for shock and wake tracking within the CHAMPS CFD code. The formulated near body Cartesian solver is the first of its kind to be applied within the context of low and high enthalpy, hypersonic viscous flows. The developed solver is validated on a Mach 9.47 Mars Science Lander and a Mach 6 Orion Crew Exploration Vehicle in a low-enthalpy flow at various non-zero angles of attack followed by a Mach 25.2 AS-202 capsule at a 17.8-degree angle of attack for Earth re-entry. Validation is shown based on grid convergence studies as well as good agreement to available numerical and experimental data in consideration of surface heating and surface pressure predictions.

Evaluating Mesh Geometry and Shade Coefficient for Fog Harvesting Collectors

The most valuable resource for sustaining life on earth is water. In dry and semi-arid areas, the problem of water scarcity can be resolved with the aid of fog collection techniques employing fog collectors. Fog collection is greatly influenced by a variety of factors. Some are design parameters, while others depend on ambient circumstances. Geometry and the mesh’s shade coefficient are important design factors that can be modified and have an impact on the rate at which fog collects in fog collectors. The shape of the mesh holes and the process used to create the mesh serve to identify geometry and measure the shade coefficient. In this paper, a straightforward mathematical technique is proposed to make it easier to calculate the shade coefficient of various mesh shapes used in fog harvesting and to provide an approximation of the mesh volume and cost. Five alternative geometries were used: the rectangular mesh, square mesh, Raschel mesh, triangular mesh, and hexagonal mesh. The current simple method will facilitate the design of the fog mesh collector and can assist in achieving the ideal shade coefficient and most effective mesh geometry for fog harvesting. Rectangular meshes were solely used as an example to evaluate the results. Stainless steel rectangular meshes with various shade coefficients were tested for fog collection, and the amount of water collected by each mesh varied. It was concluded that the optimum shade coefficient ranged 50–60% for fog collection.

Topology optimization of silencer guard for two-wheelers using finite element analysis

The goal of this study is to use finite element analysis to try and determine the best load distribution for a silencer guard. The topology optimization model based on equivalent static load is also included in this study. The present work describes optimizing the existing design of the silencer guard using Finite Element Method (FEM). The CAD model is developed by using Creo Software for creating a volume mesh. The investigation's findings showed that it is possible to reduce the weight of the silencer plate while still maintaining a lightweight and structurally sound design. Through this method, weight decrease is successfully predicted before optimization 1.0052 kg and after optimization 0.96244 kg.

Impact of parametric variation to achieve extreme mechanical metamaterials through topology optimization

Metamaterials are manufactured structures having extreme properties which do not exist in nature. Topology optimization (TO) provides an excellent alternative to the intuition-based homogenization approach used in commercial packages for automating the design of metamaterials. However, multiple topological parameters must be decided to get the tailored effective properties. This research aims to study the optimum parameters to be used in TO for developing incompressible material. To achieve this, we design microstructures to maximize the bulk modulus. A number of parametric studies are performed by varying topological control parameters such as volume fraction, penalization power, filter radius, mesh size and initial design. In addition to this, the combinations of these parameters are also investigated. These studies will be helpful for the design of incompressible metamaterials. The bulk modulus for topologically optimized designs approaches the Hashin–Shtrikman upper bound (HSUB). The results show that appropriate parameter selection can significantly improve the microstructure’s incompressibility. Such materials can have potential applications in designing aerospace and energy-absorbing components.

Modeling and hexahedral meshing of cerebral arterial networks from centerlines.

Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires extracting precise models of arteries from low-resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it encodes both the geometric and topological information and facilitates manual editing. In this work, we propose an automatic method to generate a structured hexahedral mesh suitable for CFD directly from centerlines. We addressed both the modeling and meshing tasks. We proposed a vessel model based on penalized splines to overcome the limitations inherent to the centerline representation, such as noise and sparsity. The bifurcations are reconstructed using a parametric model based on the anatomy that we extended to planar n-furcations. Finally, we developed a method to produce a volume mesh with structured, hexahedral, and flow-oriented cells from the proposed vascular network model. The proposed method offers better robustness to the common defects of centerlines and increases the mesh quality compared to state-of-the-art methods. As it relies on centerlines alone, it can be applied to edit the vascular model effortlessly to study the impact of vascular geometry and topology on hemodynamics. We demonstrate the efficiency of our method by entirely meshing a dataset of 60 cerebral vascular networks. 92% of the vessels and 83% of the bifurcations were meshed without defects needing manual intervention, despite the challenging aspect of the input data. The source code is released publicly.

Automatic Prediction of Metastasis-Free Survival (MFS) Using Prostate-Specific Membrane Antigen (PSMA) PET for Oligometastatic Castration-Sensitive Prostate Cancer (omCSPC)

Recent data have shown the promise of metastasis-directed therapy (MDT) to improve outcomes in omCSPC patients. Response biomarkers are still needed to identify patients at an early time point who will not respond to the treatment. We have shown that PSMA PET-CT SUVmax changes over time may be a useful response biomarker that correlates with MFS, an important endpoint in these omCSPC patients. This study investigated radiomic imaging biomarkers derived from PSMA-PET acquired pre- and post-MDT for MFS prediction, which may provide better features to discriminate response in the future to improve the outcome of these patients. We accrued an international multi-institutional cohort of omCSPC patients treated with stereotactic ablative radiation therapy (SABR) MDT. The cohort includes 32 patients from Institution 1 (USA) and 38 patients from Institution 2 (Europe). Both pre- and 6-month post-treatment PSMA-PET/CT were acquired. Combat was used for data harmonization in the image domain to minimize imaging variations across institutions. We defined the GTV volume as zone 1 and a 3-5 mm expansion ring area outside the GTV as zone 2 for radiomics analysis. 874 radiomics features (214 original and 660 wavelet filtered features) were extracted from both zones using open-source software and used together for MFS prediction. Function Chi2 was used to select the most significant five features. Several machine learning models (Random Forest, Logistic regression, Support Vector Machine, Naïve Bayesian) were implemented to predict MFS. The models were tested using both a leave-one-out strategy and cross-validation across the two institutions. In the leave-one-out biomarker using 70 patients, random forest achieved the best accuracy, with MFS predicted correctly for 56 (80% of 70) patients. The five radiomic features identified based on their ability to predict MFS included Entropy, Skewness, and Compactness from zone 1, Skewness, and Mesh volume from zone 2. In the cross-institution tests, random forest predicted MFS correctly for 24 (75% of 32) patients when being trained using 38 Institution 2 patients and validated against 32 Institution 1 patients. Vice versa, the model predicted MFS correctly for 28 (74% of 38) patients when being trained using Institution 1 patients and validation using Institution 2 patients. The five features identified for prediction included Entropy and Skewness from both zones and Flatness from zone 1. Our study demonstrated the promise of using pre- and post-MDT PSMA-PET-based imaging radiomic biomarkers for MFS prediction for omCSPC patients. Imaging biomarkers predictive of MFS were identified in both GTV and the ring area outside GTV. Over 74% prediction accuracy was achieved in the cross-institution validation test. The model provides a valuable tool for prognosis prediction early following MDT, which opens up a unique opportunity for monitoring or treatment interventions for patients identified with poor prognoses to improve outcomes.

Using Multiscale Direct Simulation Approach to Understanding Transports Behavior Inside PEM Water Electrolyzer

In this work, numerical modeling techniques were developed to predict oxygen bubble evolution through complex pore geometries to provide information of gas transport pathways inside saturated porous transport layers (PTL). Each PTL undergoes an image processing technique that uses X-ray CT images to generate accurate 3D microstructures. An example of a generated PTL structure is shown in Figure 1.Historically, meshing of the complex geometry was tedious and non-automated. Due to the random particle size across the geometry, a constant base size for meshing resulted in an inadequate mesh for accurate predictions. The Lattice-Boltzmann method is therefore more commonly used because a lattice is easier than a finite volume mesh to generate. Although sufficiently fine lattices adhered to the topology of the physical structure, simulations required a timestep between 1e-8 and 1e-10 seconds, resulting in long computational time.Meshing techniques have improved and can now be applied to complex geometries. Using the finite volume method accompanied with an adaptive mesh and adaptive time scale, provides an accurate representation of the PTL structure and larger timesteps. A volume of fluid (VoF) method was used to model two phase flow, using liquid water and gaseous oxygen, through different PTL structures. Evolution, growth, size, velocity, and surface interaction of oxygen bubbles through microstructures were studied as also shown in Figure 2. Findings from the work will provide better understanding of oxygen evolution through saturated PTLs Figure 1

VOLMAP: a Large Scale Benchmark for Volume Mappings to Simple Base Domains

AbstractCorrespondences between geometric domains (mappings) are ubiquitous in computer graphics and engineering, both for a variety of downstream applications and as core building blocks for higher level algorithms. In particular, mapping a shape to a convex or star‐shaped domain with simple geometry is a fundamental module in existing pipelines for mesh generation, solid texturing, generation of shape correspondences, advanced manufacturing etc. For the case of surfaces, computing such a mapping with guarantees of injectivity is a solved problem. Conversely, robust algorithms for the generation of injective volume mappings to simple polytopes are yet to be found, making this a fundamental open problem in volume mesh processing. VOLMAP is a large scale benchmark aimed to support ongoing research in volume mapping algorithms. The dataset contains 4.7K tetrahedral meshes, whose boundary vertices are mapped to a variety of simple domains, either convex or star‐shaped. This data constitutes the input for candidate algorithms, which are then required to position interior vertices in the domain to obtain a volume map. Overall, this yields more than 22K alternative test cases. VOLMAP also comprises tools to process this data, analyze the resulting maps, and extend the dataset with new meshes, boundary maps and base domains. This article provides a brief overview of the field, discussing its importance and the lack of effective techniques. We then introduce both the dataset and its major features. An example of comparative analysis between two existing methods is also present.

The asymptotic homogenization evaluation of effective mechanical property of the C/C-ZrC composite by the reconstruction technique

In this framework, we formulate a procedure to reconstruct the structure of general random 3D braid heterogeneous media based on transformation of Gaussian random fields, where the correlation of the underlying Gaussian field is determined explicitly rather than through iterative methods. The reconstructed media can meet the key microstructural information contained in the micrographs and two-point correlation function of the reference media. A robust and efficient algorithm is the operation for accurate determination the effective physical properties from a local heterogeneous material based on the methods of asymptotic homogenization and the finite element. Comparison of the present result to the experimental data from the literature shows a good agreement. The correlation length, Gaussian complexity, representative volume element size and mesh size are investigated and selected to highlight the importance of morphologically realistic microstructures. The effective properties of 3D braid composites are evaluated numerically and the respective effect of the volume fraction and relative material parameters of the reinforcement is assessed numerically. This breakthrough is the possibility to design, predict properties, and even manufacture materials not only with the help of experiments but also with computer science.

INVESTIGATION OF THE EFFECT OF MESH SIZE AND FRACTION VOLUME ON BENDING STRENGTH CHARACTERISTICS OF GEOPOLYMER COMPOSITE

Composite material is a material consisting of two or more type materials that have different properties, by combining macroscopically, and good interfacial bonds from one material to another. Currently, polymer composite materials are widely applied in the land, sea, and air transportation industries, moreover polymer composites with fire resistance properties have been developed with the addition of geopolymer that has the advantage of producing high performance. This study aims to determine the effect of mesh size and volume fraction of lightweight brick powder on flexural strength. The benefits of this research directly increase the economic value of lightweight brick waste and produce a tough advanced material at a low cost. The composite filling material used lightweight brick waste and sieved using a sieve with a level of 50, 100, 150, and 200 at a volume fraction of 45%, and a volume fraction of 0%, 15%, 30%, 45%, and 60% at a mesh 200. While the composite matrix used the thermoset polymer Ripoxy R-804. Based the result, addition of lightweight brick powder with variations in particle size of the lightweight brick powder and volume fraction showed a decrease in flexural strength resistance compared to those without lightweight brick powder.

Introducing radiomics model to predict active plaque in multiple sclerosis patients using magnetic resonance images

Multiple Sclerosis (MS) is the most common non-traumatic disabling disease in young people. The prediction active plaque has the potential to offer new biomarkers for assessing the activity of MS disease. Consequently it supports patient management in the clinical setting and trials. This study aims to investigate the predictive capability of radiomics features for identifying active plaques in these patients using T2 FLAIR (Fluid Attenuated Inversion Recovery) images. For this purpose, a dataset images from 82 patients with 122 lesions was analyzed. Feature selection was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) method. Six different classifier algorithms, namely K-Nearest Neighbors (KNN), Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF), were employed for modeling. The models were evaluated using 5-fold cross-validation, and performance metrics including sensitivity, specificity, accuracy, area under the curve (AUC), and mean squared error were computed. A total of 107 radiomics features were extracted for each lesion, and 11 robust features were identified through the feature selection process. These features consisted of four shape features (elongation, flatness, major axis length, mesh volume), one first-order feature (energy), one Gray Level Co-occurrence Matrix feature (correlation), two Gray Level Run Length Matrix features (gray level non-uniformity, gray level non-uniformity normalized), and three Gray Level Size Zone Matrix features (low gray level zone emphasis, size zone non-uniformity, small area low gray level emphasis). The NB classifier demonstrated the best performance with an AUC, sensitivity, and specificity of 0.85, 0.82, and 0.66, respectively. The findings indicate the potential of radiomics features in predicting active MS plaques in T2 FLAIR images.

Numerical modelling of hook and claw-type vacuum pump performance based on cut cell Cartesian method

Vacuum pump is widely used in aviation, chemical, semiconductor and other fields because of its superior performance. In order to study the internal flow characteristics and pump performance, 1-D Chamber Model method and the CFD modelling method based on static grid are commonly used, such methods ignore many important three-dimensional transient flow details. However, in numerical modelling of three-dimensional transient flow field for hook and claw-type vacuum pump with cusps in the rotor profile, the generation of flow field grid is always a challenge. The body-fitted mesh method is difficult to generate effective dynamic grid for such kind of fluid domain, which usually leads to the divergence of calculation. In order to solve these problems, the cut cell Cartesian method is proposed to simulate the three-dimensional transient flow field in hook and claw-type vacuum pump. Firstly, the mathematical basis of the cut cell Cartesian method was introduced in detail, in which the immersed boundary method (IBM) was combined with the generation process of adaptive Cartesian volume mesh. Aiming at modelling the hook and claw-type vacuum pump, firstly, the profile design method of hook and claw-type vacuum pump was derived, and the geometric model of the calculation domain was established. The transient flow field characteristics of the vacuum pump with different inter-lobe clearance sizes were analyzed, and the velocity, pressure, vortices and temperature characteristics inside the vacuum pump were obtained. The influence of clearance variation on the performance of the vacuum pump was discussed. The feasibility and accuracy of the method were verified by a study case of a two-stroke reciprocating piston pump. The research provides a good reference for dynamic grid generation and precise numerical simulation of hook and claw-type vacuum pump.

A coupled smoothed particle hydrodynamics-finite volume approach for shock capturing in one-dimension

A novel approach coupling the finite volume method code Pyro2 and the smoothed particle hydrodynamics code PySPH is introduced and applied to one-dimensional shock problems. The finite volume mesh models the bulk of the system, while regions with discontinuous fluid values are identified and populated with PySPH particles to model the fluid around shocks. The approaches are coupled with boundary cells and ghost particles, with linear interpolation used to extract fluid properties at each timestep in the respective boundary regions. Results from three shock problems using Pyro2, PySPH, and a hybrid approach are presented. The hybrid approach preserves accuracy and computational efficiency in strong shock problems. Additionally, the coupling approach provides a potential avenue for including SPH functionality in FVM simulations, including modeling complex geometries and fluid-structure interaction. The preliminary investigation of the hybrid approach in one dimension highlights the potential efficiency gains of applying coupled FVM-SPH methods to larger blast simulations in two and three dimensions.

A Fast Method for Evaluating Volume Potentials in the Galerkin Boundary Element Method

Three algorithms are proposed to evaluate volume potentials that arise in boundary element methods for elliptic PDEs. The approach is to apply a modified fast multipole method for a boundary concentrated volume mesh. If is the meshwidth of the boundary, then the volume is discretized using nearly degrees of freedom, and the algorithm computes potentials in nearly complexity. Here nearly means that logarithmic terms of may appear. Thus the complexity of volume potential calculations is of the same asymptotic order as boundary potentials. For sources and potentials with sufficient regularity the parameters of the algorithm can be designed such that the error of the approximated potential converges at any specified rate . The accuracy and effectiveness of the proposed algorithms are demonstrated for potentials of the Poisson equation in three dimensions.

Multi-physics simulation of 3D in-flight ice-shedding

In-flight ice accretion may possibly jeopardize the safety of fixed- and rotary-wing aircraft. Icing can possibly occur if supercooled water droplets in clouds impinge on the aircraft surfaces and freeze upon impact. It may result in instrument failures and degradation of the aerodynamic performances. A major problem related to ice accretion is the possibility of ice shedding from the main body and impacting other parts of the aircraft or being ingested by the engines. In fixed-wing aircraft, shedding is caused by the action of the aerodynamic forces or the activation of an Ice Protection System. In the present work, a multi-physics framework is presented to simulate ice accretion and shedding from wings and engine nacelles. The aerodynamics is computed using the open-source toolkit SU2 (Economon et al., 2015)[1] . Cloud droplet trajectories are computed using the arbitrary-precision Lagrangian in-house solver PoliDrop. Then, the in-house ice accretion toolkit PoliMIce (Gori et al., 2015) is used to determine the ice layer. An algebraic level-set approach with iterative volume mesh refinement has been developed to extract the ice shape from the iced wing geometry. A FEM structural analysis is performed on the accreted ice shape by means of the open-source code MoFEM (Kaczmarczyk et al., 2014, 2020) [2]. Internal stresses within the ice geometry due to aerodynamic forces are computed. Three-dimensional ice accretion simulations are performed to check the validity of the present approach.

멀티 블록 격자 재분할이 자동차 공기역학에 미치는 영향

The impact of multi-block mesh refinement on automobile aerodynamics was investigated using three refinement methods: (1) overall mesh refinement, (2) ground mesh refinement, and (3) prism layer control. The open source CFD code, OpenFOAM V10, was utilized and simulations were conducted on the full-scale Notchback DrivAer model. For each method, the effects of mesh refinement were analyzed by refining different regions. In the overall mesh refinement study, successive multi-block grid refinement regions were established - the grid size becomes finer as the block is closer to the car surface. The lift coefficient was affected by grid refinement in regions near the automobile body. The ground mesh refinement study was conducted by controlling two grid sizes related to the ground region: volume mesh and surface mesh. The prediction of drag coefficient was fairly robust with ground region refinement, and the lift coefficient was more accurate with a smaller ground region grid. However, an excessively small surface grid reduced the accuracy of both drag and lift coefficients. In the prism layer study, the accuracy of the drag coefficient was independent of the prism layer setup, while the layer thickness and expansion ratio had a significant impact on the lift coefficient.

The study on the impact of AAA wall motion on the hemodynamics based on 4D CT image data.

Purpose: To analyze the effect of the physiological deformation of the vessel wall on the hemodynamics in the abdominal aortic aneurysm (AAA), this paper compared the hemodynamics in AAA based on the moving boundary (MB) simulation and the rigid wall (RW) simulation. Method: Patient-specific models were reconstructed to generate mesh based on four-dimensional computed tomography angiography (4D CT) data. The dynamic mesh technique was used to achieve deformation of the vessel wall, surface mesh and volume mesh of the fluid domain were successively remeshed at each time step. Besides, another rigid wall simulation was performed. Hemodynamics obtained from these two simulations were compared. Results: Flow field and wall shear stress (WSS) distribution are similar. When using the moving boundary method (MBM), mean time-averaged wall shear stress (TAWSS) is lower, mean oscillatory shear index (OSI) and mean relative residence time (RRT) are higher. When using the 10th and 20th percentile values for TAWSS and 80th and 90th percentile values for RRT, the ratios of areas with low TAWSS, high OSI and high RRT to the entire vessel wall are higher than those assuming the vessel as rigid. In addition, one overlapping region of low TAWSS, high OSI and high RRT by using the MBM is consistent with the location of thrombus obtained from the follow-up imaging data. Conclusion: The hemodynamics results by using the MBM reflect a higher blood retention effect. This paper presents a potential tool to assess the risk of intraluminal thrombus (ILT) formation based on the MBM.

Topological Optimisation Structure Design for Personalisation of Hydrogel Controlled Drug Delivery System.

Personalised controlled drug delivery systems (CDDSs) can adjust drug concentration levels according to patient needs, which has enormous research prospects in precision medicine. In this study, the topological optimisation method was utilised in the structural design of a hydrogel CDDS to achieve a parameter-based adjustment of the drug average concentration in the hydrogel. A polyacrylamide/sodium alginate dual-network hydrogel was selected as a drug carrier, and tetracycline hydrochloride was used as a model drug. The topological optimisation model of the hydrogel CDDS was developed. The effects of the mesh size, target concentration, and volume factor on the optimised results were investigated. Hydrogel flow channel structures were obtained, which satisfied the different target concentrations. To verify the rationality of the optimisation model, in vitro drug release experiments were carried out. The results show that the hydrogel CDDS can control drug release within 7 days, and the drug release tends to follow zero-order release behaviour. The adjustable average concentration of tetracycline hydrochloride in hydrogel CDDS is recommended in the range of 20.79 to 31.04 mol/m3. This novel method provides a reference for personalised structure design of CDDS in the context of precision medicine.

A Rational Approach to Meshing Cerebral Venous Geometries for High-Fidelity Computational Fluid Dynamics.

Computational fluid dynamics (CFD) of cerebral venous flows has become popular owing to the possibility of using local hemodynamics and hemoacoustics to help diagnose and plan treatments for venous diseases of the brain. Lumen geometries in low-pressure cerebral veins are different from those in cerebral arteries, often exhibiting fenestrations and flattened or triangular cross section, in addition to constrictions and expansions. These can challenge conventional size-based volume meshing strategies, and the ability to resolve nonlaminar flows. Here we present a novel strategy leveraging estimation of length scales that could be present if flow were to become transitional or turbulent. Starting from the lumen geometry and flow rate boundary conditions, centerlines are used to determine local hydraulic diameters and cross-sectional mean velocities, from which flow length scales are approximated using conventional definitions of local Kolmogorov and Taylor microscales. By inspection of these scales, a user specifies minimum and maximum mesh edge lengths, which are then distributed along the model in proportion to the approximated local Taylor length scales. We demonstrate in three representative cases that this strategy avoids some of the pitfalls of conventional size-based strategies. An exemplary CFD mesh-refinement study shows convergence of high-frequency flow instabilities even starting from relatively coarse edge lengths near the lower bounds of the approximated Taylor length scales. Rational consideration of the length scales in a possibly nonlaminar flow may thus provide a useful and replicable baseline for denovo meshing of complicated or unfamiliar venous lumen geometries.