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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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NASA Ames Center personnel presented data on stages of code development and corresponding experiments in the application of computational fluid dynamics for aeronautical investigations. Specific subjects included algorithms, grid generation, facilities, instrumentation, and data acquisition. Numerical simulation and flow modelling were described to show the procedure for calibration and validation.
An implicit, finite volume code for solving two dimensional, compressible turbulent flows is described. Second order upwind differencing of the inviscid terms of the equations is used to enhance stability and accuracy. A diagonal form of the implicit algorithm is used to improve efficiency. Several zero and two equation turbulence models are incorporated to study their impact on overall flow modeling accuracy. Applications to external and internal flows are discussed.
The microbe, Zymomonas mobilis, can efficiently convert sugars to 2,3 butanediol (BDO), an important intermediate for downstream chemical products, only in a well-controlled microaerated environment. However, controlling oxygen distribution in industrial-scale bioreactors is challenging, and at-scale BDO production is hard to optimize using traditional engineering methods. This study takes a step towards addressing this problem through a computational model for reacting multiphase flows in large-scale bioreactors. A phenomenological metabolic model was first developed and validated against experiments, and then it was coupled to a multiphase computational fluid dynamics (CFD) solver using a subcycling algorithm for simulating long conversion times (~30 hours). Large-scale (~500 m 3 ) bubble column simulations using this coupled approach demonstrated a 25% improvement in BDO yield with low sparging rates (0.002 m/s) and low height-to-diameter ratio (0.875) compared to a baseline bubble column (35 m height, 5 m diameter) with a superficial gas velocity of 0.06 m/s.
The Plateau-to-River (P2R) Model is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by Central Plateau Cleanup Company (CPCCo) at the Hanford Site in Washington State. Figure 1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the composite analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3 documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application.
A continuum modeling approach by self-consistently coupling plasma dynamics and gas flow will be presented for the analysis of high density plasma reactors. Experimental data shows that gas flow distribution affects the etch rate uniformity even at low pressures (6-20 mTorr) and flow rates (20-70 sccm). This study will investigate the effects of gas flow and gas energy on bulk plasma densities and temperatures using a continuum model. The model solves multidimensional equations of mass balance for neutrals and ions, gas momentum, separate energy equations for electrons and neutrals and Maxwell's equations for power coupling. A test case of N2 plasma in a 300mm TCP etch reactor, for which hybrid model and Langmuir probe data are available, is chosen for this analysis. Our preliminary results show that modeling gas flow and energy improves the predictions of electron density and its spatial variation in the reactor when compared with the experimental data. The aim of this study is to identify the operating conditions for the TCP reactor when a self-consistent modeling of gas flow is important.
A method was developed of obtaining propulsive base flow data in both hot and cold jet environments, at Mach numbers and altitude of relevance to NASA launcher designs. The base flow data was used to perform computational fluid dynamics (CFD) turbulence model assessments of base flow predictive capabilities in order to provide increased confidence in base thermal and pressure load predictions obtained from computational modeling efforts. Predictive CFD analyses were used in the design of the experiments, available propulsive models were used to reduce program costs and increase success, and a wind tunnel facility was used. The data obtained allowed assessment of CFD/turbulence models in a complex flow environment, working within a building-block procedure to validation, where cold, non-reacting test data was first used for validation, followed by more complex reacting base flow validation.
This report documents the research conducted to update computer models for dynamic fluid flow simulation of the E-1 test stand subsystems at te NASA John C. Stennis Space Center.Work also involved significant upgrades to the capabilities of EASY/ROCKETS library through the inclusion of the NIST-12 thermodynamic property database and development of new control system modules.
The Taylor-Couette Flow is a form of viscous flow in which fluid flows between two cylindrical walls with a prescribed rotation. A diagram is shown on the right (Figure 1) where Ω is the rotational velocity, H is the distance between the two cylinders, R is the radius the outer cylinder, r is the radius of the inner cylinder and L is the length of the cylinders. When the rotating inner cylinder reaches a critical velocity, the flow of the liquid becomes unstable and creates vortices in between the layers. In this experiment, the Taylor-Couette cylinders were modeled so that the vortices would be created after reaching a critical velocity. After the initial experiment, the velocity of the inner cylinder was decreased and increased to look at how the results changed.
Intake flow for a dual intake valved diesel engine is modeled using moving valves and realistic geometries. The objectives are to obtain accurate initial conditions for combustion calculations and to provide a tool for studying intake processes. Global simulation parameters are compared with experimental results and show good agreement. The intake process shows a 30 percent difference in mass flows and average swirl in opposite directions across the two intake valves. The effect of the intake process on the flow field at the end of compression is examined. Modeling the intake flow results in swirl and turbulence characteristics that are quite different from those obtained by conventional methods in which compression stroke initial conditions are assumed.
Through-flow analysis practices are presently evaluated by comparing their results with the flow measured on a single-stage compressor rotor that had been tested at the nominal design flow coefficient of 0.85, using both thick and thin inlet endwall boundary layers. Sufficient experimental data was available for both the required aerodynamic input of the calculations and the detailed assessment of the computational results obtained. It is noted that, while through-flow theory reasonably characterizes many aspects of the flow, the features less well predicted suggest the need for a more precise formulation of the equation, and the inclusion of such often neglected effects as the radial component of blade force and/or the fluctuation terms due to the flow's nonaxisymmetry, as found in the phenomenon of blockage.
Tests described in report conducted to validate two-dimensional shear-flow analytical model for determination of acoustic impedance of acoustic liner in grazing-incidence, grazing-flow environment by use of infinite-waveguide method. Tests successful for both upstream and downstream propagations. Work has potential for utility in testing of engine ducts in commercial aircraft.
Load unbalance in electric distribution systems is unavoidable. Unbalanced load currents will lead to negative sequence (NS) voltages that may damage electric equipment. Unbalanced power flow analysis is a common tool to detect and mitigate NS voltage issues and requires accurate models of grid components. While traditional source models are available, grid-forming (GFM) inverter models are not well developed. GFM inverters implement various control strategies, which affect their power flow models. Here, in this paper, a novel GFM inverter model considering control effects is proposed. We show that for some control methods, unbalanced system loading will lead to unbalanced terminal voltages of the GFM inverters, which are modeled through an equivalent negative sequence impedance. The proposed models are initially validated using a simple test circuit. Then, they are applied in the power flow analysis on the IEEE 13-bus and 34-bus systems to demonstrate the accuracy improvement over the state-of-the-art. Using time-domain simulations as benchmarks, we show that the proposed models reduce the calculation error of negative sequence voltages by at least 25% in unbalanced distribution systems.
A series of numerical experiments is conducted for rotating annulus flow using Miller et al.'s (1992) Geophysical Flow Simulation (GFS) model; a mixture of 25-percent upwind-differencing and 75-percent center-differencing is employed to approximate the temperature advective terms. Attention is given to the wavenumber selection time and wavenumber regimes, the sensitivity in the wavenumber transition regions, and hysteresis and irregular wavenumber selections.
This paper presents a numerical approach to calculating turbulent flows employing advanced turbulence models. The main features include a line-by-line Gauss-Seidel algorithm using Roe's approximate Riemann solver, TVD numerical schemes, implicit boundary conditions and a decoupled turbulence-model solver. Based on the problems tested so far, the method has consistently demonstrated its ability in offering accuracy, boundedness and a fast rate of convergence to steady-state solution.
CFD (Computational Fluid Dynamic) simulation of aerosol-laden natural convective flow and particle deposition in a spent fuel storage canister with 37 assemblies is currently computationally prohibitive. PWR (Pressurized Water Reactor) assemblies have up to 289 pins or tubes with several spacer grids to align the pins. Spacer grids with mixing vanes induce swirling during operation to increase heat transfer. Each spacer grid contains hundreds of small structures such as retaining clips, channel walls, and openings. The largest canisters store 37 PWR assemblies thus, there are numerous pins, tubes, and spacer grids for which the flow region between and around these structures needs to be determined along with the movement and deposition of aerosol particles. Because of the complicated geometry, modeling the intricate flow even for just one assembly is currently impractical. Nonetheless, we are developing techniques for a practical model to assess the natural aerosol particle deposition process in a canister in the event that a release occurs from one or more fuel pins. In the previous work it was demonstrated that CFD can model the flow through a PWR spacer grid with mixing vanes, including particle deposition, in a reasonable amount of time on a personal computer. In this work, the analysis is extended to include the bypass region between an assembly and the canister basket walls. It is shown that the flow velocity in the bypass region is about three times that of the interstitial region between the pins. The lengths before and after the spacer grid are also extended to determine when the flow becomes fully developed. In addition, the approach of computationally “stitching together” segments of an assembly is demonstrated with the plan to ultimately model a full assembly. The fraction of particles that are deposited in a segment with a spacer grid is determined as a function of particle size and flow velocity.
Liquid metal plasma facing components are considered an attractive design choice for fusion devices including pilot plants. Virtual prototyping of such devices includes modeling of free-surface flow of the electrically conductive liquid, which requires computational fluid dynamics (CFD) and magnetohydrodynamics (MHD) simulations. Numerical tools capable of simulating flows and heat transfer in the free-surface MHD flow were developed at PPPL based on the customized ANSYS CFX. Here, MHD is introduced using a magnetic vector potential approach. Free-surface flow capabilities are available in the code and were tested. Special stabilization procedures were derived and applied to improve convergence of the momentum equations with the source terms due to the Lorentz force and surface tension. Important characteristics of the fusion-relevant liquid metal flow is free surface smoothness and stability. Heat flux from the plasma impacts the liquid surface at a very acute angle, so any change of the free surface from axisymmetry can dramatically increase the local heat flux density and thus create excessive evaporation of liquid lithium into the plasma, which is detrimental to operations. Stability analysis of the liquid metal film flow was performed to determine applicable flow regimes. Thin film flow along horizontal wall is considered. Effects of gravity, magnetic field, and surface tension are included in the analysis.
It has been proposed that the flow of mechanical energy through a structural/acoustic system may be modeled in a manner similar to that of flow of thermal energy/in a heat conduction problem. If this hypothesis is true, it would result in relatively efficient numerical models of structure-borne energy in large built-up structures. Fewer parameters are required to approximate the energy solution than are required to model the characteristic wave behavior of structural vibration by using traditional displacement formulations. The energy flow hypothesis is tested in this investigation for both longitudinal vibration in rods and transverse flexural vibrations of beams. The rod is shown to behave approximately according to the thermal energy flow analogy. However, the beam solutions behave significantly differently than predicted by the thermal analogy unless locally-space-averaged energy and power are considered. Several techniques for coupling dissimilar rods and beams are also discussed. Illustrations of the solution accuracy of the methods are included.
In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model’s input parameters. Here we develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model’s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier–Stokes) flow simulator, using shock-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow.