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At least 145 records · Page 8

MFIX-Exa: A path toward exascale CFD-DEM simulations

MFIX-Exa is a computational fluid dynamics–discrete element model (CFD-DEM) code designed to run efficiently on current and next-generation supercomputing architectures. MFIX-Exa combines the CFD-DEM expertise embodied in the MFIX code—which was developed at NETL and is used widely in academia and industry—with the modern software framework, AMReX, developed at LBNL. The fundamental physics models follow those of the original MFIX, but the combination of new algorithmic approaches and a new software infrastructure will enable MFIX-Exa to leverage future exascale machines to optimize the modeling and design of multiphase chemical reactors.

97 MATHEMATICS AND COMPUTING↗

OC7 phase I: CFD investigation of viscous forces on rectangular members of semisubmersibles

In Phase I of the Offshore Code Comparison Collaboration 7 (OC7) project, we aim to address key questions related to the modeling of viscous hydrodynamic loads on floating platforms. Here, this paper presents results from a collaborative effort within Phase I of the OC7 project. We investigate viscous forces acting on the rectangular members of semisubmersible platforms using high-fidelity computational fluid dynamics (CFD) simulations. The parametric CFD analyses include two-and-a-half-dimensional (2.5D) simulations of pontoon sections of two different semisubmersible platform designs (the VolturnUS-S and the INO WINDMOOR) and full three-dimensional (3D) structure simulations of the VolturnUS-S platform. We extract both the added mass and drag coefficients that are typically used in engineering-level hydrodynamic models from the 2.5D forced oscillation simulations with various Keulegan-Carpenter numbers and compare them to the coefficients from the 3D forced oscillation simulations. We observe consistent variation of the coefficients along the pontoon legs due to 3D platform and free-surface effects. With the breadth of the simulations and component-level detailed analyses, this work establishes a useful database and several empirical formulas for selecting hydrodynamic coefficients when modeling semisubmersible platforms in engineering tools.

13 HYDRO ENERGY↗

A Poisson equation method for prescribing fully developed non-Newtonian inlet conditions for computational fluid dynamics simulations in models of arbitrary cross-section

Prescribing inlet boundary conditions for computational fluid dynamics (CFD) simulations of internal flow in complex geometries such as anatomical vascular models is challenging. In the absence of patient-specific inlet velocity data, a common approach for long blood vessels is to assume that the inlet flow is fully developed. In vessels of irregular cross section, however, prescribing fully developed conditions is complicated due to the lack of a general closed-form analytical solution. In this study, we develop a simple Poisson equation method for prescribing fully developed inlet conditions for the flow of either Newtonian or non-Newtonian fluids in CFD models of arbitrary cross-section. We first derive the generalized Poisson equation for fully developed flow of a non-Newtonian fluid and we then develop and verify a methodology for numerically computing the solution on any planar boundary domain. In addition, we develop a simple extension of the method for prescribing a non-orthogonal inlet velocity that represents fully developed flow from an upstream tube that is connected to the CFD inlet at a non-orthogonal angle. This may be used to investigate a common source of uncertainty in CFD simulations of internal flow that is due to a lack of information concerning the exact streamwise flow direction at the inlets. Comparison to several Newtonian and non-Newtonian benchmark verification solutions shows the method to be extremely accurate. As a practical demonstration case, we use the method to prescribe fully developed conditions on multiple non-circular inlets for the non-Newtonian flow of blood in a patient-specific model of the inferior vena cava (IVC). Finally, we further demonstrate the utility of the method by performing a sensitivity study using the patient-specific IVC model, wherein we investigate the influence of inlet velocity flow direction on the non-Newtonian IVC hemodynamics. Given its simplicity and computational efficiency, the method is shown to be far superior to alternative approaches for prescribing fully developed inlet conditions in such complicated geometries. In conclusion, to facilitate the adoption of our Poisson equation method, we have distributed our OpenFOAM source code and the associated test cases from this study as open-source software.

97 MATHEMATICS AND COMPUTING↗

Reduced Models for Chemical Kinetics derived from Parallel Ensemble Simulations of Stirred Reactors

Detailed chemical kinetic models are essential to improve the predictive capability of computational fluid dynamics (CFD) simulations and to impact the development of next generation combustion technologies. However, such detailed kinetic models are beyond the reach of CFD codes due to the computational cost of transporting additional chemical degrees of freedom. Reduced order models for combustion kinetics exploit the presence of lower dimensional manifolds in the state space and require far fewer number of scalars to be transported as part of CFD simulations. In this paper, we describe the software infrastructure developed to allow large ensembles of stirred reactor configurations with detailed chemical kinetics. The canonical reactor simulations are incorporated in a workflow with sparse grid and data reduction methodologies aimed at development of reduced order models. We present results from analyzing the results of the stirred reactor calculations for syngas mixture using principal component analysis (PCA) and neural network methodologies. The results show that nonlinear autoencoder model can surpass PCA in representing the original dataset with far fewer degrees of freedom.

Zhang, Pei↗

Performance Evaluation of Low-Cost Condensers Immersed in the Water Tank of a Heat Pump Water Heater

This paper reports the effect of low-cost immersed condensers on the performance of a heat pump water heater (HPWH) that does not require a water-circulating pump. The proposed design is based on the immersion of an L-style condenser coil through an opening in the top of the water tank. The novel design aims to eliminate the need for the water-circulating pumps, thereby substantially improving efficiency and reducing costs and maintenance of the HPWH system. Comprehensive computational fluid dynamics (CFD) simulations and experimental tests were performed, and the results showed that the CFD simulations were close to the experimental data. Further results confirm that the L-style condenser can introduce buoyancy-driven flow and eliminate temperature stratification in the studied HPWH water tank, thereby improving the heat transfer coefficient and coefficient of performance of the HPWH. The testing results further showed that the L-style condenser enabled more than 53% higher coefficient of performance and 400% higher heat transfer coefficient compared with the straight vertical condenser, and achieved much faster water heating. Furthermore, the effects of immersed condensers with different circuits on the HPWH performance were evaluated and compared. All results indicate that the current energy-saving and inexpensive HPWH technology is technically valid, and the benefits of performance improvement and low cost are attractive in future HPWH design.

Gao, Zhiming [ORNL] (ORCID:0000000271397995)↗

A Transported Livengood–Wu Integral Model for Knock Prediction in Computational Fluid Dynamics Simulation

This work describes the development of a transported Livengood–Wu (L–W) integral model for computational fluid dynamics (CFD) simulation to predict autoignition and engine knock tendency. The currently employed L–W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics, and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition (HCCI) combustion for three different fuels, showing good accuracy in prediction of autoignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L–W integral model is coupled with G-equation model to indicate end-gas autoignition and knock tendency in CFD simulations of a direct-injection spark-ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely, Co-Optima alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multivariable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity, and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency—indicated by the fuel energy contained in the autoignited region—of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

33 ADVANCED PROPULSION SYSTEMS↗

DISCRETE ELEMENT MODELING OF BLADE–STRIKE FREQUENCY AND SURVIVAL OF FISH PASSING THROUGH HYDROKINETIC TURBINES

Evaluating the consequences from blade-strike of fish on marine hydrokinetic (MHK) turbine blades is essential for incorporating environmental objectives into the integral optimization of machine performance. For instance, experience with conventional hydroelectric turbines has shown that innovative shaping of the blade and other machine components can lead to improved designs that generate more power without increased impacts to fish and other aquatic life. In this work, we used unsteady computational fluid dynamics (CFD) simulations of turbine flow and discrete element modeling (DEM) of particle motion to estimate the frequency and severity of collisions between a horizontal axis MHK tidal energy device and drifting aquatic organisms or debris. Two metrics are determined with the method: the strike frequency and survival rate estimate. To illustrate the procedure step-by-step, an exemplary case of a simple runner model was run and compared against a probabilistic model widely used for strike frequency evaluation. The results for the exemplary case showed a strong correlation between the two approaches. In the application case of the MHK turbine flow, turbulent flow was modeled using detached eddy simulation (DES) in conjunction with a full moving rotor at full scale. The CFD simulated power and thrust were satisfactorily comparable to experimental results conducted in a water tunnel on a reduced scaled (1:8.7) version of the turbine design. A cloud of DEM particles was injected into the domain to simulate fish or debris that were entrained into the turbine flow. The strike frequency was the ratio of the count of colliding particles to the crossing sample size. The fish length and approaching velocity were test conditions in the simulations of the MHK turbine. Comparisons showed that DEM-based frequencies tend to be greater than previous results from Lagrangian particles and probabilistic models, mostly because the DEM scheme accounts for both the geometric aspects of the passage event ---which the probabilistic method does--- as well as the fluid-particle interactions ---which the Lagrangian particle method does. The DEM-based survival rates were comparable to laboratory results for small fish but not for mid-size fish because of the considerably different turbine diameters. The modeling framework can be used for applications that aim at evaluating the biological performance of MHK turbine units during the design phase and to provide information to regulatory agencies needed for the environmental permitting process.

blade strike↗

Verification and Validation of COMSOL for Heat Transfer in Thin Rectangular Channels Using NACA Test Results

Currently efforts are underway at Oak Ridge National Lab (ORNL) to convert the High Flux Isotope Reactor (HFIR) from high enriched uranium to low enriched uranium fuel. In order to provide confidence to the thermal hydraulics calculations, computational fluid dynamics (CFD) simulations – simulated using COMOSOL – have been employed to calculate the pressure drop and heat transfer in the coolant. While CFD simulations provide well resolved results, turbulence models include a large amount of assumptions and must be validated for use in any safety-based analysis. In HFIR, long thin involute fuel plates are separated by coolant channels of equal size. The coolant channels are best described as thin rectangular channels. Unfortunately, there are few studies verifying and validating CFD for use in thin rectangular channels. This study seeks to bridge that gap by verifying, validating, and comparing various CFD models used in thin channels. To verify and validate CFD for use in thin channels, a series of simple analytic test cases are employed, and MMS is used to further verify the COMSOL tool and mesh geometry. For the validation, a series of tests conducted at NASA were simulated in COMSOL. The results of this study are three-fold. First, it verifies the ability of COMSOL to model heat transfer in thin channels. Second, it addresses the various aspects of CFD modeling that are of greatest concern for heat transfer simulations in the geometry. Third, and finally, it discusses the ability of various CFD models used in COMSOL to accurately predict heat transfer in narrow rectangular channels.

Howard, Trevor↗

Pressure Drop in Seven-Pin Wire-Wrapped Rod Bundle for the Sodium Cartridge Loop in Versatile Test Reactor

This work studies the hydrodynamics of the seven pin wire-wrapped rod bundle in the sodium cartridge loop for the Versatile Test Reactor (VTR) through scaled water experiments and computational fluid dynamics (CFD) simulations. Here, the scaling analysis is first performed to demonstrate the hydrodynamic similarity between water and sodium flows at the same Reynolds number Re. A separate-effects test facility is designed and constructed based on the scaling analysis. Detailed experimental data on the pressure drop covering a wide range of Re values (1165 to 27 689) are obtained, which are used to evaluate existing correlations for friction factor and to benchmark CFD simulations. The experimentally determined friction factors f Exp agree well with the Upgraded Cheng and Todreas Detailed Correlation and Pacio-Chen-Todreas Detailed Model within ±7% but are significantly underpredicted by Rehme's correlation by 25%. Various CFD near-wall treatment methods are tested using ANSYS Fluent and evaluated by experimental data. It is found that when the recommended wall y + values are met, most of the near-wall treatment methods can give accurate friction factor predictions. The resolved near-wall method (y + ~ 1) with the Shear Stress Transport k - ω turbulence model and the scalable wall functions (y + > 12) with the realizable k - ε turbulence model can predict f Exp within ±5% The standard wall functions (y + > 30) and nonequilibrium wall functions (y + > 30) with the realizable k - ε model can predict f Exp within ±10%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Optimization of Workload Distribution of Data Centers Based on a Self-Learning In Situ Adaptive Tabulation Model

Data center cooling typically involves non-uniform airflow and temperature distributions, which are affected by the IT workload distribution. It is helpful to simulate the airflow and temperature to optimize the workload distribution. Traditional computational fluid dynamics (CFD) simulation is usually time-consuming while conventional reduced order models (ROMs), though computationally fast, may generate inaccurate results even after being fully trained. In Situ Adaptive Tabulation (ISAT), contracting to conventional ROM, can make prediction with error lower than a user-specified tolerance. To demonstrate using of ISAT for optimal workload distribution in data center, this paper presents a preliminary study of an ISAT-based genetic algorithm optimization platform. The ISAT is trained offline by using the results from CFD simulations using a hypothetical simple data center. The optimal workload distribution determined by the platform leads to approximately 6.8% of energy savings when compared to the benchmark with a uniform workload distribution. We note that the time cost for the entire optimization process, including the training of ISAT is about 4 hours, which is acceptable in the design phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗

Modifications of Carbonate Fracture Hydrodynamic Properties by CO 2 -Acidified Brine Flow

Acidic reactive flow in fractures is relevant in subsurface activities such as CO{sub 2} geological storage and hydraulic fracturing. Understanding reaction-induced changes in fracture hydrodynamic properties is essential for predicting subsurface flows such as leakage, injectability, and fluid production. In this study, x-ray computed tomography scans of a fractured carbonate caprock were used to create three dimensional reconstructions of the fracture before and after reaction with CO{sub 2}-acidified brine (Ellis et al., 2011, Greenhouse Gases: Sci. Technol., 1:248-260). As expected, mechanical apertures were found to increase substantially, doubling and even tripling in some places. However, the surface geometry evolved in complex ways including ‘comb-tooth’ structures created from preferential dissolution of calcite in transverse sedimentary bands, and the creation of degraded zones, i.e. porous calcite-depleted areas on reacted fracture surfaces. These geometric alterations resulted in increased fracture roughness, as measured by surface Z{sub 2} parameters and fractal dimensions D{sub f}. Computational fluid dynamics (CFD) simulations were conducted to quantify the changes in hydraulic aperture, fracture transmissivity and permeability. The results show that the effective hydraulic apertures are smaller than the mechanical apertures, and the changes in hydraulic apertures are nonlinear. Overestimation of flow rate by a factor of two or more would be introduced if fracture hydrodynamic properties were based on mechanical apertures, or if hydraulic aperture is assumed to change proportionally with mechanical aperture. The differences can be attributed, in part, to the increase in roughness after reaction, and is likely affected by contiguous transverse sedimentary features. Hydraulic apertures estimated by the 1D statistical model and 2D local cubic law (LCL) model are consistently larger than those calculated from the CFD simulations. In addition, a novel ternary segmentation method was devised to handle the degraded zones, allowing for a bounding analysis of the effects on hydraulic properties. We found that the degraded zones account for less than 15% of the fracture volume, but cover 70% to 80% of the fracture surface. When the degraded zones are treated as part of the fracture, the fracture transmissivities are two to four times larger because the fracture surfaces after reaction are not as rough as they would be if one considers the degraded zone as part of the rock. Therefore, while degraded zones created during geochemical reactions may not significantly increase mechanical aperture, this type of feature cannot be ignored and should be treated with prudence when predicting fracture hydrodynamic properties.

roughness↗

A PIC Bootstrapping Strategy for Exascale CFD-DEM Simulation

The exascale computing era comes with the release of MFIX-Exa, a new code for studying gas-particle fluidization using CFD-DEM and PIC models on massively parallel, heterogeneous high-performance computing architectures. However, as compute resources continue to grow in scale and complexity, so too does the impetus to use them efficiently. Here, we propose a novel bootstrapping method to minimize neglected simulation time and cast the approach more broadly among a growing field of multi-fidelity methods.

Porcu, Roberto↗

Numerical Investigation of Desulfurization Kinetics in Gas-Stirred Ladles by a Quick Modeling Analysis Approach

A quick modeling analysis approach for predicting the slag-steel reaction and desulfurization kinetics in argon gas-stirred ladles has been developed in this study. The model consists of two uncoupled components: (i) a computational fluid dynamics (CFD) model for predicting the fluid flow and the characteristics of slag-steel interface, and (ii) a multicomponent reaction kinetics model for calculating the desulfurization evolution. The steel-slag interfacial area and mass transfer coefficients predicted by the CFD simulation are used as the processing data for the reaction model. Since the desulfurization predictions are uncoupled from the CFD simulation, the computational time of this uncoupled predictive approach is decreased by at least 100 times for each case study when compared with the CFD-reaction kinetics fully coupled model. The uncoupled modeling approach was validated by comparing the evolution of steel and slag compositions with the experimentally measured data during ladle metallurgical furnace (LMF) processing at Nucor Steel Tuscaloosa, Inc. Then, the validated approach was applied to investigate the effects of the initial steel and slag compositions, as well as different types of additions during the refining process on the desulfurization efficiency. The results revealed that the sulfur distribution ratio and the desulfurization reaction can be promoted by making Al and CaO additions during the refining process. It was also shown that by increasing the initial Al content in liquid steel, both Al oxidation and desulfurization rates rapidly increase. In addition, it was found that the variation of the initial Si content in steel has no significant influence on the desulfurization rate. Lastly, if the initial CaO content in slag is increased or the initial Al{sub 2}O{sub 3} content is decreased in the fluid-slag compositional range, the desulfurization rate can be improved significantly during the LMF process.

36 MATERIALS SCIENCE↗

Validation of Computational Fluid Dynamics Simulations for Biological Performance Assessment in Hydropower units (Final Report)

The biological performance assessment (BioPA) toolset developed by Pacific Northwest National Laboratory (PNNL) estimates the relative biological performance of fish passage at a hydroelectric power turbine unit. The tool is based on the use of computational fluid dynamics (CFD) and fish biological response relationships. The recent release, BioPA-v3, is based on directly computed trajectory and collision of material Lagrangian particles using CFD simulation codes rather than the prior version that relies on Tecplot to compute streamtrace trajectories. Before modifying the toolset, a series of validation tests were performed at the various steps of modification in the toolset. Validation is a critical step of any numerical investigation that reflects the accuracy and reliability of the predicted results. It raises the confidence level of the user to use the modified version of the BioPA toolset. Several test cases were simulated and compared, where available, to observed data. The trajectory and collision of the small spherical and cylindrical particles in a water flume were compared to in-house experiments. The CFD predicted collision rate and flow field compared well with experimental observation for vane array and large cylinder as target bodies. Next, the CFD-predicted flow field and hydraulic performance of a laboratory-scale model of a Francis turbine was also successfully validated. Note that the trajectory of the particles is significantly affected by the flow field in such extreme conditions. In addition to the particle trajectories and flow field, the collision detection method employed in the CFD simulations was also successfully validated. The CFD predicted impact velocity, collision time, velocity, and trajectory of a sphere excellently matched with analytical value for a bouncing ball in the elastic collision. A similar approach was also tested and successfully validated for a collision of sphere with a 45° inclined plane. After successfully validating different cases, the BioPA toolset was modified to use direct output of the CFD prediction and the new version can be used in evaluating biological performance at hydroelectric turbines.

13 HYDRO ENERGY↗

Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations

New powertrain solutions are needed to address societal challenges stemming in part from a transportation sector which relies heavily on combustion of conventional hydrocarbon fuels like gasoline. One way to advance new solutions is through predictive simulations. Predictive simulations can potentially limit the extent of experimental validations, reduce time spent in engineering design cycles, unlock new strategies for high efficiency combustion with power density, and minimize tailpipe emissions. However, the simulation tools currently available are either too computationally expensive, inadequate in their accuracy, or a combination of the two. A DOE-funded consortium of national laboratories called the Partnership to Advance Combustion Engines (PACE) seeks to address this gap by rapidly delivering new knowledge and tools which enable market-competitive powertrain solutions for light-duty vehicles. Approaches to modeling combustion in powertrain systems typically incorporate computational fluid dynamics (CFD) simulations with chemical kinetic models. These CFD simulations generally use surrogate fuels featuring a limited number of existing components in a reduced kinetic model to limit computational costs. Such surrogate fuels often sacrifice matching several or more combustion and physical properties of the target gasoline fuel. Validation of surrogate fuels is also often only pursued for a small subset of standard metrics such as research or motor octane number (RON, MON). The purpose of this project is to develop an optimal E10 gasoline surrogate fuel suitable for tasks across PACE to facilitate rapid common analysis and progression toward consortium goals. This project received contributions from tasks led by eight PACE principal investigators. The project funding here reflects all tasks under Pitz, whose tasks also contributed to additional PACE projects. Based on the optimal gasoline surrogate fuel composition, a reduced chemical kinetic model will be shared with PACE researchers, industry, and the broader combustion community.

33 ADVANCED PROPULSION SYSTEMS↗

Comparison of Full-Field and Integrated CFD Convergence Based on Richardson Extrapolation

This work investigated the usefulness of Richardson extrapolation--based discretization error estimates across all points in a solution field to produce a spatial convergence field for a computational fluid dynamics (CFD) simulation. The presented work used previously developed methods for Richardson extrapolation to compute the convergence orders of a CFD simulation at all points of the base (coarsest) mesh solution. Three test cases of increasing complexity were considered: Poiseuille flow, incompressible flow around a sharp corner, and transonic flow over an RAE 2822 airfoil. These test cases highlighted the potential of the proposed method to identify error sources and their relation to the model system-response-quantity convergence orders. However, these test cases also revealed the immaturity of the proposed method stemming from the unreliability of computing observed convergence orders at single points. Nonetheless, the test cases highlighted that the observed convergence orders allow for a more accurate diagnosis of constructive and destructive error transport than mesh pair error estimates. In the long run, the proposed method can be a tool for developing efficient and advanced error management strategies like adaptive mesh refinement.

Weinmeister, Justin↗