Set Of Solvers Research Articles

Computational Investigations in Rectangular Convergent and Divergent Ribbed Channels

Abstract Computational investigations on the rib turbulated flow inside a convergent and divergent rectangular channel with square ribs of different rib heights and different Reynolds numbers (Re=20,000, 40,000 and 60,000). The ribs were arranged in a staggered fashion between the upper and lower surfaces of the test section. Computational investigations are carried out using computational fluid dynamic software ANSYS Fluent 14.0. Suitable solver settings like turbulence models were identified from the literature and the boundary conditions for the simulations on a solution of independent grid. Computations were carried out for both convergent and divergent channels with 0 (smooth duct), 1.5, 3, 6, 9 and 12 mm rib heights, to identify the ribbed channel with optimal performance, assessed using a thermo hydraulic performance parameter. The convergent and divergent rectangular channels show higher Nu values than the standard correlation values.

Recommendations for simulating microparticle deposition at conditions similar to the upper airways with two-equation turbulence models

The development of a CFD model, from initial geometry to experimentally validated results with engineering insight, can be a time-consuming process that often requires several iterations of meshing and solver set-up. Applying a set of guidelines in the early stages can help to streamline the process and improve consistency between different models. The objective of this study was to determine both mesh and CFD solution parameters that enable the accurate simulation of microparticle deposition under flow conditions consistent with the upper respiratory airways including turbulent flow. A 90° bend geometry was used as a characteristic model that occurs throughout the airways and for which high-quality experimental aerosol deposition data is available in the transitional and turbulent flow regimes. Four meshes with varying degrees of near-wall resolution were compared, and key solver settings were applied to determine the parameters that minimize sensitivity to the near-wall (NW) mesh. The Low Reynolds number (LRN) k-ω model was used to resolve the turbulence field, which is a numerically efficient two-equation turbulence model, but has recently been considered overly simplistic. Some recent studies have used more complex turbulence models, such as Large Eddy Simulation (LES), to overcome the perceived weaknesses of two-equation models. Therefore, the secondary objective was to determine whether the more computationally efficient LRN k-ω model was capable of providing deposition results that were comparable to LES. Results show how NW mesh sensitivity is reduced through application of the Green-Gauss Node-based gradient discretization scheme and physically realistic near-wall corrections. Using the newly recommended meshing parameters and solution guidelines gives an excellent match to experimental data. Furthermore, deposition data from the LRN k-ω model compares favorably with LES results for the same characteristic geometry. In summary, this study provides a set of meshing and solution guidelines for simulating aerosol deposition in transitional and turbulent flows found in the upper respiratory airways using the numerically efficient LRN k-ω approach.

Hybrid simulation of a segmental orifice plate

Computational fluid dynamics (CFD) has become a popular tool in the development of flow meters as an alternative to cost-intensive prototyping while preparing for approval tests or particular disturbances in pipe systems. In practical CFD applications, a turbulence model is required to predict the influence of turbulent flow features. Unfortunately, even the most state-of-the-art and commonly used turbulence models – the Reynolds-averaged Navier-Stokes (RANS) models – perform rather poorly in complex and separated flows, while scale-resolving methods such as large eddy simulations (LES) remain unfeasible for most industrial applications and higher Reynolds numbers. To make use of LES accuracy and current computing capacities nonetheless, the utilization of hybrid RANS-LES methods represents an efficient solution today.In this paper, we present a modified stress-blended eddy simulation (SBES) turbulence model capable of making reliable predictions of disturbed pipe flows and the resulting effects on flow meter measurements demonstrated by simulating a segmental orifice plate and its influence on an ultrasonic meter. To illustrate the differences, the SBES results are compared to those of a standard k-ω RANS model. Typical mesh requirements and solver settings are discussed. Also, a spatially dependent blending function for SBES is introduced. Both simulations are compared to a large number of laser Doppler anemometry (LDA) and ultrasonic clamp-on measurements performed on a gravimetrically traceable flow test facility. The comparison with LDA shows the clear superiority of SBES, where RANS fails due to a massive overestimation of the recirculation zone. Near the orifice, SBES even has an advantage over LDA in predicting the ultrasonic meter performance.

Performance assessment of a ductless personalized ventilation system using a validated CFD model

The aim of this study is twofold: to validate a computational fluid dynamics (CFD) model, and then to use the validated model to evaluate the performance of a ductless personalized ventilation (DPV) system. To validate the numerical model, a series of measurements was conducted in a climate chamber equipped with a thermal manikin. Various turbulence models, settings, and options were tested; simulation results were compared to the measured data to determine the turbulence model and solver settings that achieve the best agreement between the measured and simulated values. Subsequently, the validated CFD model was then used to evaluate the thermal environment and indoor air quality in a room equipped with a DPV system combined with displacement ventilation. Results from the numerical model were then used to quantify thermal sensation and comfort using the UC Berkeley thermal comfort model.

Analysis of Deformation and Equivalent Stress during Biomass Material Compression Molding

Ansys is adopted to analyze mold deformation and stress field distribution rule during the process of compressing biomass under pressure of 20Mpa. By means of unit selection, material property setting, mesh partition, contact pair establishment, load and constraint applying, and solver setting, the stress and strain of overall mold are analyzed. Deformation and equivalent Stress of compression structure, base, mold, and compression bar were analyzed. We can have conclusions: The distribution of stress forced on compressor is not completely uniform, where the stress at base is slightly decreased; the stress and strain of compression bar is the largest, and stress concentration my occur at top of compression bar, which goes against compression bar service life; the overall deformation of main mold is smaller; although there is slight difference between upper and lower part, the overall variation is not obvious, but the stress difference between upper and lower part of main mold is extremely large so that reaches to 10 times; the stress and strain in base decrease in circular shape, but there is still stress concentration in ledge, which goes against service life; contact stress does not distribute uniformly, there is increasing or decreasing trend in adjacent parts, which is very large in some parts. in constructing both.

Transition turbulence model calibration for wind turbine airfoil characterization through the use of a Micro-Genetic Algorithm

The aerodynamic characterization of airfoils is of crucial importance for the design and optimization of wind turbines. The present paper tries to provide an engineering methodology for the improvement of the accuracy and reliability of 2D airfoil computational fluid dynamics models, by coupling the ANSYS Fluent solver and a Micro-Genetic Algorithm. The modeling strategy provided includes meshing optimization, solver settings, comparison between different turbulence models and, mainly, the calibration of the local correlation parameters of the transition turbulence model by Menter, which was found to be the most accurate model for the simulation of transitional flows. Specifically, the Micro-Genetic Algorithm works by generating populations of the missing local correlation parameters. In doing so, it is possible to search for the minimization of the error in lift calculations. For each specific Reynolds number, the calibration was carried out only at the Angle of Attack where the lift drop occurs and the airfoil completely stalls. This new idea allowed for a relatively rapid and good calibration as demonstrated by the experimental–numerical comparisons presented in this paper. Only the experimental stall angle and the relative lift coefficient were, therefore, necessary for obtaining a good calibration. The calibration was made using the widely known S809 profile data. The correlation parameters, obtained as so, were subsequently used for testing on the NACA 0018 airfoil with satisfactory results. Therefore, the calibration obtained using the S809 airfoil data appeared to be reliable and may be used for the simulation of other airfoils. This can be done without the need for further wind tunnel experimental data or recalibrations. The proposed methodology will, therefore, be of essential help in obtaining accurate aerodynamic coefficients data. This will drastically improve the capabilities of the 1D design codes at low Reynolds numbers thanks to the possibility of generating accurate databases of 2D airfoil aerodynamic coefficients. The advantages of the proposed calibration will be helpful in the generation of more accurate 3D wind turbine models as well. The final objective of the paper was thus to obtain a fine and reliable calibration of the transition turbulence model by Menter. This was specifically made for an accurate prediction of the aerodynamic coefficients of any airfoil at low Reynolds numbers and for the improvements of 3D rotor models.

Comparison of CFD-calculations of centrifugal compressor stages by NUMECA Fine Turbo and ANSYS CFX programs

Computational Fluid Dynamics (CFD) methods are widely used for centrifugal compressors design and flow analysis. The calculation results are dependent on the chosen software, turbulence models and solver settings. Two of the most widely applicable programs are NUMECA Fine Turbo and ANSYS CFX.The objects of the study were two different stages. CFD-calculations were made for a single blade channel and for full 360-degree flow paths.Stage 1 with 3D impeller and vaneless diffuser was tested experimentally. Its flow coefficient is 0.08 and loading factor is 0.74. For stage 1 calculations were performed with different grid quality, a different number of cells and different models of turbulence. The best results have demonstrated the Spalart-Allmaras model and mesh with 1.854 million cells.Stage 2 with return channel, vaneless diffuser and 3D impeller with flow coefficient 0.15 and loading factor 0.5 was designed by the known Universal Modeling Method. Its performances were calculated by the well identified Math model. Stage 2 performances by CFD calculations shift to higher flow rate in comparison with design performances. The same result was obtained for stage 1 in comparison with measured performances. Calculated loading factor is higher in both cases for a single blade channel. Loading factor performance calculated for full flow path (“360 degrees”) by ANSYS CFX is in satisfactory agreement with the stage 2 design performance. Maximum efficiency is predicted accurately by the ANSYS CFX “360 degrees” calculation. “Sector” calculation is less accurate. Further research is needed to solve the problem of performances mismatch.

Simulation on the Compression Molding Process of Biomass Material

ANSYS finite element analysis theory was employed to simulate the process of biomass compression molding. The analysis and calculation like element selection, material attribute setting, mesh generation, contact pair establishment, load and constrain applying and solver setting were finished. The results shows that: The biomass produced in this mold contains heterogeneous density where the density in one end is higher than the other end; There is still shear stress at the section of molding fuel, which cannot be removed after molding; moreover, along with the natural expansion of biomass material after compression, crack is likely to appear on the surface of biomass molding fuel. With respect to mold, it is obvious that, the stress of top of compression material to mold is the largest, which is caused by the concentrated stress on mold generated by joint action of friction between raw material and mold, larger extrusion force at top and deformation force of raw material resisting compression. Thus, the abrasion of this mold at this part is the largest.

Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.

Analysis of Mold Overall Deformation and Contact Stress During Biomass Cold Compression Molding

Ansys is adopted to analyze mold deformation and stress field distribution rule during the process of compressing biomass under pressure of 20Mpa. By means of unit selection, material property setting, mesh partition, contact pair establishment, load and constraint applying, and solver setting, the stress and strain of overall mold are analyzed; meanwhile, the size as well as distribution of various contact stresses is explored. The mold deformation is small while the displacement of compression bar and compressed fuel is larger. Since displacement is the manifestation of overall deformation situation, the lower part of fuel will definitely be lower than that of upper part with the compaction of fuel, but the displacement of compression bar is the largest. Overall equivalent pressure diagram indicates that, the pressure on compression bar is the largest, followed by compressor; The pressure at the contact place of compressor and base is larger while other places is smaller so that it decreases in the form of semi circle. The contact stresses are various in different places of contact pair and the difference in some is large. However, fuel compression is a repetitive periodic process, so each contact pair will generate alternating stress, under which fatigue phenomenon may quickly occur in mold.

Numerical prediction of ventilated planing flat plates for the design of Air Cavity Ships

In recent years, a great world issue is the respect for the environment. Each researcher, in his competence field, proposes new technologies and new approaches in order to reduce the environmental impact of a product or of an industrial process. In the naval field, the main way in order to reduce the environmental impact of the ship during the navigation is the reduction of the drag resistance and so the reduction of requested power. There are many ways in order to obtain a reduction of drag. This paper investigates, with a preliminary numerical study by means of Computational Fluid Dynamics (CFD), the Air Cavity Ships technology (ACS). A first part of the paper concerns the study of the rising bubble phenomenon inside a water column, in order to choice the better solver settings and understand if the CFD is suitable for this kind of problem. In this phase the main parameters analyzed are: the air critical mass, the rising velocity, the shape and the air circulation inside the bubble. In the second part of the work, a flat plate model with artificial air injection is conducted in order to understand the possible advantages of this application. The principal impacts of this technology are presented in terms of drag coefficient and lift coefficient respect to trim and velocity coefficient. The CFD method could be a suitable and fast method, in the preliminary phase, for the design of the ACS.

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1.

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM -KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry. Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM-KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM-KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in "cloud" SOA at the surface in the eastern United States for June 2013.

Cerebral aneurysm blood flow simulations are sensitive to basic solver settings

Computational modeling of peri-aneurysmal hemodynamics is typically carried out with commercial software without knowledge of the sensitivity of the model to variation in input values. For three aneurysm models, we carried out a formal sensitivity analysis and optimization strategy focused on variation in timestep duration and model residual error values and their impact on hemodynamic outputs. We examined the solution sensitivity to timestep sizes of 10−3s, 10−4s, and 10−5s while using model residual error values of 10−4, 10−5, and 10−6 using ANSYS Fluent to observe compounding errors and to optimize solver settings for computational efficiency while preserving solution accuracy. Simulations were compared qualitatively and quantitatively against the most rigorous combination of timestep and residual parameters, 10−5s and 10−6, respectively. A case using 10−4s timesteps, with 10−5 residual errors proved to be a converged solution for all three models with mean velocity and WSS difference RMS errors less than <1% compared with baseline, and was computationally efficient with a simulation time of 62h per cardiac cycle compared to 392h for baseline for the model with the most complex flow simulation. The worst case of our analysis, using 10−3s timesteps and 10−4 residual errors, was still able to predict the dominant vortex in the aneurysm, but its velocity and WSS RMS errors reached 20%. Even with an appealing simulation time of 11h per cycle for the model with the most complex flow, the worst case analysis solution exhibited compounding errors from large timesteps and residual errors. To resolve time-dependent flow characteristics, CFD simulations of cerebral aneurysms require sufficiently small timestep size and residual error. Simulations with both insufficient timestep and residual resolution are vulnerable to compounding errors.

Contest Among Contest Organizers

We study multiple parallel contests where contest organizers elicit solutions to innovation-related problems from a set of solvers. Each solver may participate in multiple contests and exert effort to improve her solution for each contest she enters, but the quality of her solution at each contest also depends on an output uncertainty. We first analyze whether an organizer's profit can be improved by discouraging solvers from participating in multiple contests. We show, interestingly, that organizers benefit from solvers' participation in multiple contests when the solver's output uncertainty in these contests is sufficiently large. A managerial insight from this result is that when all organizers elicit innovative solutions rather than low-novelty solutions, organizers may benefit from solvers' participation in multiple contests. We also show that organizers' average profit increases with solvers' participation in multiple contests even when some contests seek low-novelty solutions as long as other contests seek cutting-edge innovation. We further show that an organizer's profit is unimodal in the number of contests, and the optimal number of contests increases with the solver's output uncertainty. This finding may explain why many organizations run multiple contests in practice, and it prescribes running a larger number of contests when the majority of these organizations seek innovative solutions rather than low-novelty solutions.

Verification of ANSYS Fluent and OpenFOAM CFD platforms for prediction of impact flow

The main goal of the article is a verification of the heat transfer coefficient numerically predicted by two CDF platforms – ANSYS-Fluent and OpenFOAM on the problem of impact flows oncoming from 2D nozzle. Various mesh parameters and solver settings were tested under several boundary conditions and compared to known experimental results. The best solver setting, suitable for further optimization of more complex geometry is evaluated.

Revisiting restricted path consistency

Restricted path consistency (RPC) is a strong local consistency for binary constraints that was proposed 20 years ago and was identified as a promising alternative to arc consistency (AC) in an early experimental study of local consistencies for binary constraints. However, in contrast to other strong local consistencies such as singleton arc consistency (SAC) and max restricted path consistency (maxRPC), it has been neglected since then. In this paper we revisit RPC. First we propose RPC3, a new RPC algorithm that is very easy to implement and can be efficiently applied throughout search. Then we perform a wide experimental study of RPC3 and a light version that achieves an approximation of RPC, comparing them to state-of-the-art AC and maxRPC algorithms. Experimental results obtained under various solver settings, regarding the branching scheme, the variable ordering heuristic, and restarts, clearly show that light RPC is by far more efficient than both AC and maxRPC when applied throughout search. We also examine the experimental behaviour of an algorithm for a simple extension of RCP called 2-RPC, showing that it is competitive with RPC3, and better than both AC and maxRPC. Overall, our results strongly suggest that it is time to reconsider the established perception that MAC is the best general purpose method for solving binary CSPs.

Time-domain Raman analytical forward solvers.

A set of time-domain analytical forward solvers for Raman signals detected from homogeneous diffusive media is presented. The time-domain solvers have been developed for two geometries: the parallelepiped and the finite cylinder. The potential presence of a background fluorescence emission, contaminating the Raman signal, has also been taken into account. All the solvers have been obtained as solutions of the time dependent diffusion equation. The validation of the solvers has been performed by means of comparisons with the results of "gold standard" Monte Carlo simulations. These forward solvers provide an accurate tool to explore the information content encoded in the time-resolved Raman measurements.

Comparative study of gyrokinetic, hybrid-kinetic and fully kinetic wave physics for space plasmas

A set of numerical solvers for the linear dispersion relations of the gyrokinetic (GK), the hybrid-kinetic (HK), and the fully kinetic (FK) model is employed to study the physics of the KAW and the fast magnetosonic mode in these models. In particular, we focus on parameters that are relevant for solar wind oriented applications (using a homogeneous, isotropic background), which are characterized by wave propagation angles averaging close to 90°. It is found that the GK model, while lacking high-frequency solutions and cyclotron effects, faithfully reproduces the FK wave physics close to, and sometimes significantly beyond, the boundaries of its range of validity. The HK model, on the other hand, is much more complete in terms of high-frequency waves, but owing to its simple electron model it is found to severely underpredict wave damping rates even on ion spatial scales across a large range of parameters, despite containing full kinetic ion physics.

Parallel Simulations of Inductive Components with Elmer Finite-Element Software in Cluster Environments

ABSTRACTImprovements in the models of simulating lossy inductive components in the quasi-static approximation in Elmer finite-element software is presented (Elmer, n.d.). Models include laminate stack models for core materials; massive, stranded, and foil winding models for inductors; and coupling to external circuits. The strong scaling parallel performances of the models with different mesh and solver settings are measured in a cluster environment. All models scale well up to at least 96 processes.

Parallel finite element modelling of multi-physical processes in thermochemical energy storage devices

Thermal energy storage technologies are of current interest in order to improve the integration of renewable energy sources as well as energy efficiency. Numerical simulations of thermochemical heat storage are especially challenging and time consuming due to the complexity of the mathematical description of the strongly coupled and highly nonlinear processes characteristics for such systems. These difficulties are exacerbated once practically relevant complex or large geometries are considered as they can occur around heat exchangers or due to internal heterogeneities of the reactive bed. To allow a computationally efficient simulation of such applications, an existing finite element implementation of a thermochemical heat storage model was parallelised using PETSc routines. Input/output, global assembly and the linear solver all work in a distributed fashion. The approach is implemented into the open source framework OpenGeoSys. The performance of the present parallelisation approach is tested by simulating the discharge of a heat store based on calcium oxide and water as a benchmark problem. The algorithm is tested on 2D as well as 3D meshes. The computational time required for the simulation could be reduced significantly. For example, a 3D model running almost 7days on a single core could be solved in less than 1h on 120 cores using the developed framework. The results strongly depend on linear solver and preconditioner settings.