Computational Mesh Research Articles

A framework for in-field and out-of-field patient specific secondary cancer risk estimates from treatment plans using the TOPAS Monte Carlo system

Objective. To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo (MC) framework. Method. Patient planning computed tomography scans were extended superior-inferior using the International Commission on Radiological Protection’s Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS MC system using novel mesh capabilities and the digital imaging and communications in medicine radiotherapy extension interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets. Result. The TOPAS MC framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk. Significance. This work equips the TOPAS MC system with anatomical extension, mesh geometry, and cancer risk model capabilities that make state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users. Furthermore, these capabilities will facilitate further refinement of risk models and sensitivity analysis of patient specific treatment options.

TensoSDF: Roughness-aware Tensorial Representation for Robust Geometry and Material Reconstruction

Reconstructing objects with realistic materials from multi-view images is problematic, since it is highly ill-posed. Although the neural reconstruction approaches have exhibited impressive reconstruction ability, they are designed for objects with specific materials (e.g., diffuse or specular materials). To this end, we propose a novel framework for robust geometry and material reconstruction, where the geometry is expressed with the implicit signed distance field (SDF) encoded by a tensorial representation, namely TensoSDF. At the core of our method is the roughness-aware incorporation of the radiance and reflectance fields, which enables a robust reconstruction of objects with arbitrary reflective materials. Furthermore, the tensorial representation enhances geometry details in the reconstructed surface and reduces the training time. Finally, we estimate the materials using an explicit mesh for efficient intersection computation and an implicit SDF for accurate representation. Consequently, our method can achieve more robust geometry reconstruction, outperform the previous works in terms of relighting quality, and reduce 50% training times and 70% inference time. Codes and datasets are available at https://github.com/Riga2/TensoSDF.

A novel simplified simulation method for the precooler based on the virtual source term: modeling, validation and application

Precooling technology is one of the promising approaches for expanding the flight envelope of conventional turbine engines and enhancing flight performance at high Mach numbers. Within this domain, a crucial challenge is to rapidly and accurately obtain the flow and heat transfer characteristics of the precooler. Currently, full-size simulation of the precooler is impractical, while simplified and fast simulation methods employed in previous research have exhibited certain deficiencies, including excessive simplification and unconvincing validation. In this study, a novel simplified simulation method for the annular precooler based on the virtual source term model was proposed. This method comprehensively considered the axial and radial non-uniformity of airflow caused by the coupling effect between the precooler and the inlet channel in the actual flow field. Subsequently, systematic validations of the reliability and superiority of this method were conducted, along with its application in the overall performance calculation of the precooled engine. The results demonstrate that the simplified method proposed in this paper showcases higher accuracy than the methods employed in previous research. Compared with the real model, the relative errors of the overall parameters are within ± 1 %, and the relative errors of the distortion indices for total temperature and total pressure are 5.1 % and −1.5 %, respectively. Meanwhile, the number of computational mesh cells is reduced by more than 95 %. Moreover, the first application of the simplified method in the overall performance calculation of the precooled engine reveals that the traditional low-dimensional model underestimates both the total pressure loss of the precooler and the fuel consumption for precooling, resulting in larger calculation deviations in the thrust and equivalence ratio, respectively. The values of thrust calculated with the high-dimensional virtual model show an average decrease of 2.01 % compared to those derived from the low-dimensional model. In addition, a higher Mach number results in lower effectiveness, higher air inlet temperature, and reduced resistance of the precooler to heat exchange imbalance caused by flow non-uniformity. These factors lead to an escalating relative deviation of the equivalence ratio between the two models, reaching 26.45 % at Mach 5.

Multiphase patient-specific simulations to study fibrillation-induced thrombosis in the left atrial appendage

Thrombosis commonly develops in the left atrial appendage of patients with atrial fibrillation. The formation of blood clots in atrial appendage is a complex process, which depends on the shape of the appendage, the velocity of blood flow, the concentrations of red blood cells, platelets, and coagulation, among other factors. In this work, we present a new methodology to identify the key factors contributing to clot formation in the left atrial appendage during atrial fibrillation. The new methodology combines computed tomography imaging, computational fluid dynamics, mesh processing, and multiphase thrombosis modeling. We begin by running simulations to investigate flow patterns inside the left atrial appendages with realistic geometries. Our simulations suggest that at the entrance of the left atrial appendage, the flow forms vortices, which can intrude inside the appendage depending on the phases of the cardiac cycle. Next, we introduce blood coagulation and consider different scenarios corresponding to physiological values of blood flow velocity, geometry of the left atrial appendage, and hematocrit values. Numerical results suggest that the chances of clot formation are higher in the “cactus” geometry than in the “chicken-wing” one, in agreement with the literature. Furthermore, they suggest that slower flow circulation facilitates the development of a clot in the depth of the left atrial appendage. Slower blood movement also favors the procoagulant activity of platelets, while faster flow circulation enhances the procoagulant effect from erythrocytes. Finally, our simulations show that increased hematocrit upregulates the generation of fibrin polymer, regardless of flow velocity.

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

AbstractTopography and the computational mesh grid are fundamental inputs to all two‐dimensional (2D) hydrodynamic models, however their resolutions are often arbitrarily selected based on data availability. With the increasing use of drone technology, the end user can collect topographic data down to centimeter‐scale resolution. With this advancement comes the responsibility of choosing a resolution. In this study, we investigated how the choice of mesh grid and digital elevation model (DEM) resolutions affect 2D hydrodynamic modeling results, specifically water depths, velocities, and inundation extent. We made pairwise comparisons between simulations from a 2D HEC‐RAS model with varying mesh grid resolutions (1 and 2 m) and drone‐based lidar DEM resolutions (0.1, 0.25, 0.5, 1, and 2 m) over a 1.5 km reach of Stroubles Creek in Blacksburg, Virginia. The model was rerun for up to ±4% change in floodplain roughness to determine how the DEM and mesh grid changes relate to an equivalent change in roughness. We found that the modeled differences from resolution change were equivalent to altering floodplain roughness by up to 12% for depths and 44% for velocities. The largest differences in velocity were concentrated at the channel‐floodplain interface, whereas differences in depth occurred laterally throughout the floodplain and were not correlated with lidar ground point density. We also found that the inundation boundary is dependent on the DEM resolution. Our results suggest that modelers should carefully consider what resolution best represents the terrain while also resolving important riparian topographic features.

Experimental and Numerical Determination of the Aerodynamic Characteristics of a Cruise Missile Model

A model of a cruise missile was tested in symmetrical air flow in a low-speed wind tunnel of the Military University of Technology (Warsaw, Poland). A virtual model of the missile was developed, and the geometry of the computational domain was built in the CAD environment of the ANSYS computational software suite. The domain was discretised in the ANSYS Meshing application, creating a hybrid computational mesh. Boundary conditions were determined in the ANSYS Fluent application, and physical (turbulent compressible flow) and numerical models were selected. Calculations were performed for three different turbulence models – Spalart-Almaras, realizable k-ε, and SST k-ω – and the results were compared to find the model providing the best convergence with in-tunnel measurements.

Mérope: A microstructure generator for simulation of heterogeneous materials

Mérope is a software devoted to the geometrical design and the discretization of microstructures of random heterogeneous materials. Mérope aims at building large samples of microstructured materials, called Representative Volume Elements, in order to derive their effective physical behaviors. Various microstructures are supported: spherical, polyhedral or spheropolyhedral inclusions, polycrystals, Gaussian fields and Boolean combinations of these. Discretization takes two forms: either regular Cartesian grids of (composite) voxels for computations with FFT-based solvers, or tetrahedral meshes for computations with Finite Element solvers. A special emphasis on the code has been put on performance, which will be further improved in the future.This article aims at introducing the main features of the software as well as exemplifying its use.

The effect of variations in experimental and computational fidelity on data assimilation approaches

AbstractWe conduct a comprehensive analysis of two data assimilation methods: the first utilizes the discrete adjoint approach with a correction applied to the production term of the turbulence transport equation, preserving the Boussinesq approximation. The second is a state observer method that implements a correction in the momentum equations alongside a turbulence model, both applied to fluid dynamics simulations. We investigate the impact of varying computational mesh resolutions and experimental data resolutions on the performance of these methods within the context of a periodic hill test case. Our findings reveal the distinct strengths and limitations of both methods, which successfully assimilate data to improve the accuracy of a RANS simulation. The performance of the variational model correction method is independent of input data and computational mesh resolutions. The state observer method, on the other hand, is sensitive to the resolution of the input data and CFD mesh.

An aerodynamic digital twin of real-world leading edge erosion: Acquisition, Generation and 3D CFD

Wind turbine blades face extremely challenging environmental conditions over their operating life-time, that can easily exceed 2 decades. Airborne particles (insects, sand, rain, hail, ice, sea spray etc.) strike the blade leading edge (LE) first and erode or attach to it, roughening its surface. Leading edge roughness (LER) can critically alter the aerodynamic performance of blades, as its aerodynamic impact is strongly coupled to its height with respect to the local boundary layer thickness, which is thinnest around the LE. The actual, detailed topographic manifestation of LER on in-service blades—needed to accurately assess its aerodynamic impact—is highly probabilistic, as it depends on the interaction of multiple stochastic parameters, like the environmental conditions, material composition and production process. Yet little high-resolution topographic LER data of this kind is currently available. This paper details how such data is collected from blades of different turbine manufacturers and processed consistently to build digital twins of the measured LER, that can be analysed aerodynamically using 3D CFD or wind tunnels. Here a special focus lies on how to reconstruct the LER topography and build the computational mesh such that the correct aerodynamic response is observed. For this purpose multiresolution signal decomposition is used to process the topographies and a special meshing procedure established.

Mesh-based topology, shape and sizing optimization of ribbed plates

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction industry. A coupled plate-beam finite element model and its computational mesh enable simultaneous topology, shape and sizing optimization of ribbed plate systems. Using analytical sensitivity analysis and gradient-based optimization, we achieve significant weight reductions in the range of 24–57%, in comparison to reference designs with regular ribbing patterns. The results strengthen the argument in favor of ribbed plates as a structural system that can serve the environmental goals of the construction industry. While our focus is on ribbed concrete plates in buildings, the proposed mesh-based design parameterization is applicable in the general case of optimizing stiffened shells—with potential contributions also to automotive and aerospace applications. All computer codes used in this study are freely available through a public repository, https://zenodo.org/records/11489996.

NACA 2412 Drag Reduction Using V-Shaped Riblets

This research focuses on addressing a significant concern in the aviation industry, which is drag. The primary objective of this project is to achieve drag reduction through the implementation of riblets on a wing featuring the NACA 2412 aerofoil, operating at subsonic speeds. Riblets, with the flow direction on wing surfaces, have demonstrated the potential to effectively decrease drag in diverse applications. This investigation includes computational analysis within the ANSYS Workbench framework, employing a polyhedral mesh model. The scope of this research encompasses the analysis of both a conventional wing and a modified wing with riblets. A comparative analysis is conducted to assess variations in drag values between the two configurations. Parameters, including geometry, dimensions, and riblet placement at varying angles of attack, are explored to comprehend their impact on drag reduction. Notably, 15.6% and 23% reductions in drag were identified at a 16-degree angle of attack with midspan and three-riblet models, separately. The computational mesh and method were validated using appropriate techniques.

Computational and Experimental Research on the Influence of Supplied Gas Fuel Mixture on High-Temperature Fuel Cell Performance Characteristics

Currently, the process of creating industrial installations is associated with digital technologies and must involve the stage of developing digital models. It is also necessary to combine installations with different properties, functions, and operational principles into a single system. Some tasks require the use of predictive modeling and the creation of “digital twins”. The main processes during the fuel cell modeling involve electrochemical transformations as well as the movement of heat and mass flows, including monitoring and control processes. Numerical methods are utilized in addressing various challenges related to fuel cells, such as electrochemical modeling, collector design, performance evaluation, electrode microstructure impact, thermal stress analysis, and the innovation of structural components and materials. A digital model of the membrane-electrode unit for a solid oxide fuel cell (SOFC) is presented in the article, incorporating factors like fluid dynamics, mass transfer, and electrochemical and thermal effects within the cell structure. The mathematical model encompasses equations for momentum, mass, mode, heat and charge transfer, and electrochemical and reforming reactions. Experimental data validates the model, with a computational mesh of 55 million cells ensuring numerical stability and simulation capability. Detailed insights on chemical flow distribution, temperature, current density, and more are unveiled. Through a numerical model, the influence of various fuel types on SOFC efficiency was explored, highlighting the promising performance of petrochemical production waste as a high-efficiency, low-reagent consumption fuel with a superior fuel utilization factor. The recommended voltage range is 0.6–0.7 V, with operating temperatures of 900–1300 K to reduce temperature stresses on the cell when using synthesis gas from petrochemical waste. The molar ratio of supplied air to fuel is 6.74 when operating on synthesis gas. With these parameters, the utilization rate of methane is 0.36, carbon monoxide CO is 0.4, and hydrogen is 0.43, respectively. The molar ratio of water to synthesis gas is 2.0. These results provide an opportunity to achieve electrical efficiency of the fuel cell of 49.8% and a thermal power of 54.6 W when using synthesis gas as fuel. It was demonstrated that a high-temperature fuel cell can provide consumers with heat and electricity using fuel from waste from petrochemical production.

Digital Flow in a Pool Induced by a Vertical Jet

Turbulent water jets remain a critical study area, particularly the relation of the water flow with air entrainment and its role in energy dissipation at different hydraulic structures. Plunge pools, formed by the impact of jets on water cushions, play a pivotal role in energy dissipation. Understanding the complex flow dynamics within these pools is essential for designing efficient hydraulic structures. In this research, we present a comprehensive investigation of different numerical simulations, defining two-phase (air-water) in different ways, and them compare with experimental measurements. The primary objective is to analyze the pressure distribution at the bottom of a plunge pool induced by a vertical jet and understand the importance of accurately defining air-water flow in the dynamics of the jet into the pool. Our study bridges the gap between empirical data and computational modeling, shedding light on the intricate behavior of such flows with different method-based solvers: VOF, sub-grid, and multi-phase Euler. Various computational domains, mesh configurations, and analyses spanning different time periods, frequencies, and scales were considered.

Image-based finite element modeling of air flow and thermal transport in Al-fiber-sintered porous materials

In this study, the pressure drop and heat transfer in a heat-transfer tube filled with a sintered porous medium comprising Al fibers were investigated using computational fluid dynamics (CFD) simulations. We reconstructed the sintered fibrous porous structure and generated a computational mesh using X-ray computed tomography data, and the simulated pressure drop and heat transfer agreed well with those reported by Enoki et al. [2021]. The differences in both the form coefficient and the permeability between two different samples can be explained from the differences in both the specific solid surface area and the porosity. Further, the CFD simulations indicated that thermal conduction of the Al solid phase enhanced the heat exchange between the air and Al fibers. To examine the effect of solid-phase thermal conduction, we generated a model of a heat-transfer tube having an ideal wire mesh structure, in which we introduced the interfacial thermal conductivity between Al fibers and the inner tube wall as additional factors. We also performed CFD simulations with four different shell-region thicknesses and found that even a very narrow gap of 5 to 10 μm heavily affected the heat-exchange performance because of the low thermal conductivity of the shell region.

Space–time computations of exactly time-periodic flows past hydrofoils

The computation of periodic flows is typically conducted over multiple periods. First, a number of periods is used to develop periodic characteristics, and afterwards statistics are collected from averages over multiple periods. As a consequence, it is uncertain whether the numerical results are exactly time-periodic, and additionally, the time domain might be needlessly long. In this article, we circumvent these concerns by using a time-periodic function space. Consequently, the boundary conditions and solutions are exactly periodic. We employ the isogeometric analysis framework to achieve higher-order smoothness in both space and time. The discretization is performed using residual-based variational multiscale modeling and weak boundary conditions are adopted to enhance the accuracy near the moving boundaries of the computational domain. We enforce the time-periodic boundary condition within the isogeometric discretization spaces, which converts the two-dimensional time-dependent problem into a three-dimensional boundary value problem. Furthermore, we determine the boundary velocities of moving hydrofoils directly from the computational mesh and use a conservation methodology for force extraction. Application of the computational setup to heaving and pitching hydrofoils displays very accurate and exactly periodic results for lift and drag.

Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations

Accurately computing the flow in the nasal cavity with computational fluid dynamics (CFD) simulations requires highly resolved computational meshes based on anatomically realistic geometries. Such geometries can only be obtained from computer tomography (CT) data with high spatial resolution, i.e., featuring a ≤1mm slice thickness. In practice, CT images are, however, recorded at a lower resolution to not expose patients to high radiation and to reduce the overall costs. To overcome this problem and to provide patients with a detailed physics-based diagnosis, e.g., for surgery planning, the potential of super-resolution networks (SRNs) to increase the CT resolution is analyzed. Therefore, an SRN is developed and trained on CT data. Its predictive performance is improved by an automated hyperparameter optimization technique. The training time is further reduced without predictive accuracy degradation by oversampling images with challenging regions. The performance of the SRN is assessed by an analysis of the reconstructed 3D surfaces of the human upper airway and by comparing results of CFD simulations. That is, surfaces and simulation results based on SRN-generated CT data at 1mm resolution are compared to those obtained from unmodified CT data-sets at low (3mm) and high (1mm) resolution, as well as from CT data interpolated to a 1mm resolution from coarse data. The findings reveal the SRN-based approach to have the lowest deviations in the surfaces and CFD results when compared to those based on the original high-resolution data. The pressure loss between the inflow (nostrils) and outflow (pharynx) regions averaged for three test patients differs by only 1.3%, compared to 8.7% and 8.8% in the coarse and interpolated cases. It is concluded that the SRN-based method is a promising tool to enhance underresolved CT data to yield reliable numerical results of respiratory flows.

Application of material point method in modeling soil-geosynthetics interactions-a literature survey

The material point method (MPM) has garnered significant attention in recent years owing to its advantages in solving soil–water-structure interaction problems involving large deformations in geotechnical engineering. The MPM combines the benefits of point-based and mesh-based approaches (finite element method) with both Eulerian computational mesh and continuum descriptions of materials. The successful integration of MPM in simulated landslides, internal erosion, and excavation has been frequently reported. However, solving the soil–geosynthetic interaction problem with the MPM has not been explored, although such problems often entail large deformations. The goal of this study is to collate studies on the simulation of geosynthetics and their interactions with soil using MPM. This paper first discusses the basics of MPM and the formation of thin membrane materials using MPM. It also includes limited applications of MPM in simulating soil–geosynthetic interactions. The applications demonstrate that the MPM is particularly effective in resolving large deformation problems associated with geosynthetics, including problems of landfill settlement, reinforced-slope stability, and geocontainer dropping.

Local correlations for predicting the transition process in separated flows tuned with a large experimental database

This work provides new correlations based on local variables for characterizing the transition process developing in the case of separated flows. The goal is to improve the capability of correlation-based transition models through the use of local variables. This may indeed simplify the implementation of the correlations into modern numerical codes, especially dealing with parallel computation and unstructured meshes. A large experimental database considering about 90 different flow conditions has been used to tune the present correlations. The database accounts for the variation of the flow Reynolds number, the free-stream turbulence intensity and the adverse pressure gradient affecting the boundary layer developing over a flat plate. The parameter variation induces the formation of both short and long laminar separation bubbles. The vorticity Reynolds number, based on the second invariant of the vorticity tensor, has been used as the main local variable for the activation of the transition process. Since it is proportional to the momentum thickness Reynolds number at the separation position, the vorticity Reynolds number (local) can be used in place of its counterpart based on the momentum thickness (integral), which is the variable usually adopted for activation of transition. Then, correlations providing a critical threshold for the vorticity Reynolds number promoting transition are tuned, for both short and long bubbles. These may be used into transition models to directly provide the location where the turbulence production needs to be activated. The proposed correlations have been validated using a second database not adopted for tuning and finally tested with data concerning a separated flow case in a low-pressure turbine cascade.

Integrated Three-Dimensional Airloads and Stresses on Lift-Offset Coaxial Rotors at Extreme Speeds

This paper investigates the three-dimensional (3-D) dynamic stresses on a modern four-bladed hingeless coaxial rotor—inspired by the gross dimensions of the Sikorsky S-97 Raider at extreme flight speeds. The stresses are obtained using integrated 3-D (I3D) aeromechanical analysis—defined as the coupling of 3-D finite element-based structural dynamics with 3-D Reynolds-averaged Navier–Stokes–based fluid dynamics. The coupling was carried out with the University of Maryland/U.S. Army structural dynamic solver X3D and the U.S. Army CREATETM–AV Helios suite of fluid dynamic solvers. The new structural analysis is both enabled and driven by advanced high-performance computing, parallel and scalable solvers, high-order 3-D brick finite elements unified with multibody dynamics, integrated aeromechanics, and a special 3D-to-1D fluid–structure interface that refines the power of the delta-coupling procedure while retaining the advantages of existing computational fluid dynamics mesh motion schemes. The analysis is carried out at 220 knots (μ=0.5)—the cruise speed of the S-97 Raider without reduced tip speed—in order to study the stresses in extreme conditions. At such high speeds, the blade lift is dominated by the complex tip vortex roll-up, and the pitching moments and drag are dominated by the unsteady transonic shocks at the tip. Interesting 3-D dynamic stress patterns are revealed all across the blade that have remained invisible until now since they could neither be predicted nor measured in flight. The key conclusion is that such high-fidelity analysis is now indeed possible and, in fact, necessary to get deeper insights into the dynamics of coaxial rotors at extreme speeds.

Optimizations of the Accelerated Axial Polynomial Method of Characteristics of the APOLLO3® Deterministic Neutron Transport Code

For some years now, the TDT (two- and three-dimensional transport) solver of the APOLLO3® deterministic neutron transport code has been able to perform lattice calculations on three-dimensional extruded and unstructured geometries. A polynomial expansion of the angular flux has been implemented to better describe the flux gradient axially to reduce the number of computational meshes required to reach a given accuracy. Then the polynomial approximation was extended to macroscopic cross sections to perform evolution calculations. Besides these transport schemes, synthetic acceleration has also been implemented, relying on double PN approximations of the angular flux on the boundaries of the spatial regions. The solver has already introduced several techniques to reduce the transport and memory footprint; for example, for the storage of the surfaces crossed by a trajectory or the classification of chords. In this paper, new optimizations are presented. One deals with how monomials of the polynomial basis are integrated along trajectories. Another one concerns the computation of the source term of the transmission equation in the case of polynomial cross sections. The last optimization exploits the fact that, along horizontal trajectories, the flux and the cross sections are constant to speed up the sweep algorithm. Calculations on 5 × 5 and 7 × 7 pressurized water reactor assemblies were performed to assess the gains of these recently developed strategies. The results show good improvements both in computing time and in memory footprint reductions.