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DOE OSTI2014

Integrated Lift- and Wall-Force Closures in Computational Fluid Dynamics (CMFD)

In this report, we provide the necessary background to put this work in context and for a more detailed background, the reader is referred to CASL 2013 report. Central constraints on the design of LWRs are thermal-structural limits, e.g., maximum fuel pin temperature and maximum allowable working pressure in a pressure vessel. In both of these cases, the knowledge of the spatially and temporally varying two-phase flow is required to make accurate predictions as the distribution of both the phases have an impact on heat extraction as well as neutron moderation. Engineered two-phase flow systems have complex geometry and often high Reynolds numbers which increase the computational cost of an analysis, and generally make direct numerical simulations of the flow field impossible even on the fastest computers today. Consequently, a number of models which seek to reduce this computational cost have been created over the years. One of these called the two-fluid model has become the standard in three dimensional CFD (Computational Fluid Dynamics) codes and is and is also referred to as CMFD (Computational Multiphase Fluid Dynamics). The two-fluid model splits each conserved quantity into two fields, one for each phase that is treated as interspersed continua. Splitting one field into two requires additional interfacial closure relationships. In the two-fluid model, the momentum flux between the phases is governed by a number of these closure relationships. Generally, the net force on the dispersed phase is decomposed into inertial, added mass, buoyancy, drag, lift, and wall forces. In addition, there is a time-dependent Basset force, as well as turbulent dispersion effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

High-fidelity simulation-driven model development for coarse-grained computational fluid dynamics

Nuclear reactor safety analysis requires analysis of a broad range of accident scenarios and determining their consequences. For a nuclear power plant behavior, it is impossible to obtain experimental data at sufficiently large scales to support calibration and validation of various system models. In single-phase flow convective problems, high-resolution methods of Computational Fluid Dynamics (CFD) such as Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide high fidelity results under conditions where physical measurements are unavailable. However, such high-resolution simulations are computationally expensive and not suitable for simulation of long transient scenarios in nuclear reactor accidents. In this work, we investigate the use of a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. Notably, fine-mesh simulations are used to construct physics-informed statistical surrogate of coarse-mesh SGS model. For an initial analysis, we consider a case of turbulent natural convection in a volumetrically heated fluid layer with a thermally insulated lower boundary and isothermal upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a severe nuclear reactor accident, as well as in containment mixing and passive cooling. For this type of flow, the SGS effect is modeled by an added turbulent diffusivity in the energy equation. It is shown that a global correction for the energy equation is sufficient to achieve a significant improvement to the CG-CFD prediction of thermal mixing in the fluid layer. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1992

Computational fluid dynamics analysis of Space Shuttle main engine multiple plume flows at high-altitude flight conditions

Computational fluid dynamics (CFD) analysis is providing verification of Space Shuttle flight performance details and is being applied to Space Shuttle Main Engine Multiple plume interaction flow field definition. Advancements in real-gas CFD methodology that are described have allowed definition of exhaust plume flow details at Mach 3.5 and 107,000 ft. The specific objective includes the estimate of flow properties at oblique shocks between plumes and plume recirculation into the Space Shuttle Orbiter base so that base heating and base pressure can be modeled accurately. The approach utilizes the Rockwell USA Real Gas 3-D Navier-Stokes (USARG3D) Code for the analysis. The code has multi-zonal capability to detail the geometry of the plumes based region and utilizes finite-rate chemistry to compute the plume expansion angle and relevant flow properties at altitude correctly. Through an improved definition of the base recirculation flow properties, heating, and aerodynamic design environments of the Space Shuttle Vehicle can be further updated.

Dougherty, N. S.↗

DOE OSTI2022

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Resolving Anodic Current and Temperature Distributions in a Polymer Electrolyte Membrane Water Electrolysis Cell Using a Pseudo-Two-Phase Computational Fluid Dynamics Model

Expanding upon our prior experimental work, we constructed a three-dimensional model of a polymer electrolyte membrane water electrolyzer using computational fluid dynamics. We applied the assumption of pseudo-two-phase flow, the flow of two phases with equal velocity. Experimental data were used to obtain parameters and to determine the conditions under which this model was valid. Anodic distributions of current density, temperature, liquid saturation, and relative humidity were obtained at various flow rates. The overall current density and temperature difference from inlet to outlet at the anode agreed strongly with experimental measurements under most circumstances. This verification allowed us to further examine the apparent gas coverage calculated from experimental and model temperature data. Results suggested a low liquid saturation and low relative humidity at the anode due to the consumption of liquid water and water vapor. However, we questioned the accuracy of the pseudo-two-phase assumption at low water feed rates. We concluded that the model was applicable to systems with liquid water feed rates greater than 0.6 ml min -1 cm -2 . Therefore, it is a fair screening method that can advise which operating conditions lead to excessive temperatures or drying at the anode, thereby promoting the longevity of the membrane and catalyst.

25 ENERGY STORAGE↗

DOE OSTI2026

Extreme Wave Computational Fluid Dynamics Modeling with 1-Way Fluid Structure Interaction for a Wave Energy Converter

Contractor will perform a computational fluid dynamics (CFD) analysis of the Participant's CETO wave energy converter (WEC) in an extreme wave environment. The load cases will be based on model test data that will be used for validation.

16 TIDAL AND WAVE POWER↗

NASA NTRS1999

Inlet Development for a Rocket Based Combined Cycle, Single Stage to Orbit Vehicle Using Computational Fluid Dynamics

Design and analysis of the inlet for a rocket based combined cycle engine is discussed. Computational fluid dynamics was used in both the design and subsequent analysis. Reynolds averaged Navier-Stokes simulations were performed using both perfect gas and real gas assumptions. An inlet design that operates over the required Mach number range from 0 to 12 was produced. Performance data for cycle analysis was post processed using a stream thrust averaging technique. A detailed performance database for cycle analysis is presented. The effect ot vehicle forebody compression on air capture is also examined.

DeBonis, J. R.↗

DOE OSTI2013

Computational Fluid Dynamics Analysis of Flexible Duct Junction Box Design

IBACOS explored the relationships between pressure and physical configurations of flexible duct junction boxes by using computational fluid dynamics (CFD) simulations to predict individual box parameters and total system pressure, thereby ensuring improved HVAC performance. Current Air Conditioning Contractors of America (ACCA) guidance (Group 11, Appendix 3, ACCA Manual D, Rutkowski 2009) allows for unconstrained variation in the number of takeoffs, box sizes, and takeoff locations. The only variables currently used in selecting an equivalent length (EL) are velocity of air in the duct and friction rate, given the first takeoff is located at least twice its diameter away from the inlet. This condition does not account for other factors impacting pressure loss across these types of fittings. For each simulation, the IBACOS team converted pressure loss within a box to an EL to compare variation in ACCA Manual D guidance to the simulated variation. IBACOS chose cases to represent flows reasonably correlating to flows typically encountered in the field and analyzed differences in total pressure due to increases in number and location of takeoffs, box dimensions, and velocity of air, and whether an entrance fitting is included. The team also calculated additional balancing losses for all cases due to discrepancies between intended outlet flows and natural flow splits created by the fitting. In certain asymmetrical cases, the balancing losses were significantly higher than symmetrical cases where the natural splits were close to the targets. Thus, IBACOS has shown additional design constraints that can ensure better system performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Computational Fluid Dynamics Analysis of Flexible Duct Junction Box Design

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2001

Textbook Multigrid Efficiency for Computational Fluid Dynamics Simulations

Considerable progress over the past thirty years has been made in the development of large-scale computational fluid dynamics (CFD) solvers for the Euler and Navier-Stokes equations. Computations are used routinely to design the cruise shapes of transport aircraft through complex-geometry simulations involving the solution of 25-100 million equations; in this arena the number of wind-tunnel tests for a new design has been substantially reduced. However, simulations of the entire flight envelope of the vehicle, including maximum lift, buffet onset, flutter, and control effectiveness have not been as successful in eliminating the reliance on wind-tunnel testing. These simulations involve unsteady flows with more separation and stronger shock waves than at cruise. The main reasons limiting further inroads of CFD into the design process are: (1) the reliability of turbulence models; and (2) the time and expense of the numerical simulation. Because of the prohibitive resolution requirements of direct simulations at high Reynolds numbers, transition and turbulence modeling is expected to remain an issue for the near term. The focus of this paper addresses the latter problem by attempting to attain optimal efficiencies in solving the governing equations. Typically current CFD codes based on the use of multigrid acceleration techniques and multistage Runge-Kutta time-stepping schemes are able to converge lift and drag values for cruise configurations within approximately 1000 residual evaluations. An optimally convergent method is defined as having textbook multigrid efficiency (TME), meaning the solutions to the governing system of equations are attained in a computational work which is a small (less than 10) multiple of the operation count in the discretized system of equations (residual equations). In this paper, a distributed relaxation approach to achieving TME for Reynolds-averaged Navier-Stokes (RNAS) equations are discussed along with the foundations that form the basis of this approach. Because the governing equations are a set of coupled nonlinear conservation equations with discontinuities (shocks, slip lines, etc.) and singularities (flow- or grid-induced), the difficulties are many. This paper summarizes recent progress towards the attainment of TME in basic CFD simulations.

Brandt, Achi↗

NASA NTRS2005

Airborne Shaped Sonic Boom Demonstration Pressure Measurements with Computational Fluid Dynamics Comparisons

The Shaped Sonic Boom Demonstration project showed for the first time that by careful design of aircraft contour the resultant sonic boom can maintain a tailored shape, propagating through a real atmosphere down to ground level. In order to assess the propagation characteristics of the shaped sonic boom and to validate computational fluid dynamics codes, airborne measurements were taken of the pressure signatures in the near field by probing with an instrumented F-15B aircraft, and in the far field by overflying an instrumented L-23 sailplane. This paper describes each aircraft and their instrumentation systems, the airdata calibration, analysis of the near- and far-field airborne data, and shows the good to excellent agreement between computational fluid dynamics solutions and flight data. The flights of the Shaped Sonic Boom Demonstration aircraft occurred in two phases. Instrumentation problems were encountered during the first phase, and corrections and improvements were made to the instrumentation system for the second phase, which are documented in the paper. Piloting technique and observations are also given. These airborne measurements of the Shaped Sonic Boom Demonstration aircraft are a unique and important database that will be used to validate design tools for a new generation of quiet supersonic aircraft.

Haering, Edward A., Jr.↗

NASA NTRS1991

Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics

A new and efficient method is presented for aerodynamic design optimization, which is based on a computational fluid dynamics (CFD)-sensitivity analysis algorithm. The method is applied to design a scramjet-afterbody configuration for an optimized axial thrust. The Euler equations are solved for the inviscid analysis of the flow, which in turn provides the objective function and the constraints. The CFD analysis is then coupled with the optimization procedure that uses a constrained minimization method. The sensitivity coefficients, i.e. gradients of the objective function and the constraints, needed for the optimization are obtained using a quasi-analytical method rather than the traditional brute force method of finite difference approximations. During the one-dimensional search of the optimization procedure, an approximate flow analysis (predicted flow) based on a first-order Taylor series expansion is used to reduce the computational cost. Finally, the sensitivity of the optimum objective function to various design parameters, which are kept constant during the optimization, is computed to predict new optimum solutions. The flow analysis of the demonstrative example are compared with the experimental data. It is shown that the method is more efficient than the traditional methods.

Baysal, Oktay↗

NASA NTRS2001

Flight, Wind-Tunnel, and Computational Fluid Dynamics Comparison for Cranked Arrow Wing (F-16XL-1) at Subsonic and Transonic Speeds

Geometrical, flight, computational fluid dynamics (CFD), and wind-tunnel studies for the F-16XL-1 airplane are summarized over a wide range of test conditions. Details are as follows: (1) For geometry, the upper surface of the airplane and the numerical surface description compare reasonably well. (2) For flight, CFD, and wind-tunnel surface pressures, the comparisons are generally good at low angles of attack at both subsonic and transonic speeds, however, local differences are present. In addition, the shock location at transonic speeds from wind-tunnel pressure contours is near the aileron hinge line and generally is in correlative agreement with flight results. (3) For boundary layers, flight profiles were predicted reasonably well for attached flow and underneath the primary vortex but not for the secondary vortex. Flight data indicate the presence of an interaction of the secondary vortex system and the boundary layer and the boundary-layer measurements show the secondary vortex located more outboard than predicted. (4) Predicted and measured skin friction distributions showed qualitative agreement for a two vortex system. (5) Web-based data-extraction and computational-graphical tools have proven useful in expediting the preceding comparisons. (6) Data fusion has produced insightful results for a variety of visualization-based data sets.

John E Lamar↗

DOE OSTI2021

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↗

NASA NTRS1980

A compendium of computational fluid dynamics at the Langley Research Center

Through numerous summary examples, the scope and general nature of the computational fluid dynamics (CFD) effort at Langley is identified. These summaries will help inform researchers in CFD and line management at Langley of the overall effort. In addition to the inhouse efforts, out of house CFD work supported by Langley through industrial contracts and university grants are included. Researchers were encouraged to include summaries of work in preliminary and tentative states of development as well as current research approaching definitive results.

Source record↗

NASA NTRS2010

Computational Fluid Dynamics (CFD) Simulation of Hypersonic Turbine-Based Combined-Cycle (TBCC) Inlet Mode Transition

Methods of computational fluid dynamics were applied to simulate the aerodynamics within the turbine flowpath of a turbine-based combined-cycle propulsion system during inlet mode transition at Mach 4. Inlet mode transition involved the rotation of a splitter cowl to close the turbine flowpath to allow the full operation of a parallel dual-mode ramjet/scramjet flowpath. Steady-state simulations were performed at splitter cowl positions of 0deg, -2deg, -4deg, and -5.7deg, at which the turbine flowpath was closed half way. The simulations satisfied one objective of providing a greater understanding of the flow during inlet mode transition. Comparisons of the simulation results with wind-tunnel test data addressed another objective of assessing the applicability of the simulation methods for simulating inlet mode transition. The simulations showed that inlet mode transition could occur in a stable manner and that accurate modeling of the interactions among the shock waves, boundary layers, and porous bleed regions was critical for evaluating the inlet static and total pressures, bleed flow rates, and bleed plenum pressures. The simulations compared well with some of the wind-tunnel data, but uncertainties in both the windtunnel data and simulations prevented a formal evaluation of the accuracy of the simulation methods.

Slater, John W.↗

NASA NTRS1993

Towards a generalized computational fluid dynamics technique for all Mach numbers

Currently there exists no single unified approach for efficiently and accurately solving computational fluid dynamics (CFD) problems across the Mach number regime, from truly low speed incompressible flows to hypersonic speeds. There are several CFD codes that have evolved into sophisticated prediction tools with a wide variety of features including multiblock capabilities, generalized chemistry and thermodynamics models among other features. However, as these codes evolve, the demand placed on the end user also increases simply because of the myriad of features that are incorporated into these codes. In order for a user to be able to solve a wide range of problems, several codes may be needed requiring the user to be familiar with the intricacies of each code and their rather complicated input files. Moreover, the cost of training users and maintaining several codes becomes prohibitive. The objective of the current work is to extend the compressible, characteristic-based, thermochemical nonequilibrium Navier-Stokes code GASP to very low speed flows and simultaneously improve convergence at all speeds. Before this work began, the practical speed range of GASP was Mach numbers on the order of 0.1 and higher. In addition, a number of new techniques have been developed for more accurate physical and numerical modeling. The primary focus has been on the development of optimal preconditioning techniques for the Euler and the Navier-Stokes equations with general finite-rate chemistry models and both equilibrium and nonequilibrium thermodynamics models. We began with the work of Van Leer, Lee, and Roe for inviscid, one-dimensional perfect gases and extended their approach to include three-dimensional reacting flows. The basic steps required to accomplish this task were a transformation to stream-aligned coordinates, the formulation of the preconditioning matrix, incorporation into both explicit and implicit temporal integration schemes, and modification of the numerical flux formulae. In addition, we improved the convergence rate of the implicit time integration schemes in GASP through the use of inner iteration strategies and the use of the GMRES (General Minimized Resisual) which belongs to the class of algorithms referred to as Krylov subspace iteration. Finally, we significantly improved the practical utility of GASP through the addition of mesh sequencing, a technique in which computations begin on a coarse grid and get interpolated onto successively finer grids. The fluid dynamic problems of interest to the propulsion community involve complex flow physics spanning different velocity regimes and possibly involving chemical reactions. This class of problems results in widely disparate time scales causing numerical stiffness. Even in the absence of chemical reactions, eigenvalue stiffness manifests itself at transonic and very low speed flows which can be quantified by the large condition number of the system and evidenced by slow convergence rates. This results in the need for thorough numerical analysis and subsequent implementation of sophisticated numerical techniques for these difficult yet practical problems. As a result of this work, we have been able to extend the range of applicability of compressible codes to very low speed inviscid flows (M = .001) and reacting flows.

Walters, R. W.↗

DOE OSTI2021

Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization

In recent years, the use of machine learning-based surrogate models for computational fluid dynamics (CFD) simulations has emerged as a promising technique for reducing the computational cost associated with engine design optimization. However, such methods still suffer from drawbacks. One main disadvantage is that the default machine learning (ML) hyperparameters are often severely suboptimal for a given problem. This has often been addressed by manually trying out different hyperparameter settings, but this solution is ineffective in case of a high-dimensional hyperparameter space. Besides this problem, the amount of data needed for training is also not known a priori. In response to these issues that need to be addressed, the present work describes and validates an automated active learning approach, AutoML-GA, for surrogate-based optimization of internal combustion engines. In this approach, a Bayesian optimization technique is used to find the best machine learning hyperparameters based on an initial dataset obtained from a small number of CFD simulations. Subsequently, a genetic algorithm is employed to locate the design optimum on the ML surrogate surface. In the vicinity of the design optimum, the solution is refined by repeatedly running CFD simulations at the projected optima and adding the newly obtained data to the training dataset. It is demonstrated that AutoML-GA leads to a better optimum with a lower number of CFD simulations, compared to the use of default hyperparameters. The proposed framework offers the advantage of being a more hands-off approach that can be readily utilized by researchers and engineers in industry who do not have extensive machine learning expertise.

Owoyele, Opeoluwa↗