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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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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Executive summary, aerothermal modeling program, phase 1

Submodels used in the combustor analytical models that were successfully used in designing advanced technology combustors were assessed. Specific recommendations for further improvement of model accuracy for combustor design purposes were made. Based upon an exhaustive literature survey, a number of test cases were selected to assess accuracy of submodels of turbulence, turbulence/chemistry interaction, spray combustion, and dilution jet mixing processes within a confined cross-stream. These test cases included simple flows and complex flows with and without swirl. Nonrecirculating and recirculating, and nonreactive and reactive flows were investigated. It was concluded that the current models give qualitative trends for the recirculating secondary flows (as encountered in a gas turbine combustor primary zone), but the predictions are good for the dilution zone.

Srinivasan, R.↗
NASA NTRS1992

Comparison of turbulence models for powered-lift flow fields

The development of a practical turbulence model for the complex flows with strong streamline curvature associated with powered-lift aircraft was investigated. The approach was to modify existing models that were compatible with the widely used kappa-epsilon model already available in an existing 3D Navier-Stokes code. The state-of-the-art of current turbulence models was examined. Several models that provide curvature corrections to the kappa-epsilon model were numerically investigated. An algebraic Reynolds stress model, which provides additional physics, was also examined. Test cases including an impinging jet, an impinging jet in a crossflow, and two adjacent impinging jets with the resultant upwash fountain were calculated. The first two test cases could be modeled reasonsbly well with some of the models. The upwash fountain could not be modeled with sufficient accuracy, which is consistent with the findings of other investigators.

Roberts, Donald W.↗
DOE OSTI2018

Flow Measurements of Methane-Fueled Rotating Detonation Combustion

Time-resolved particle image velocimetry (PIV) is applied to the flow field at the immediate exit of a rotating detonation combustor (RDC) operating on methane fuel and oxygen-enriched air. The detailed experimental results, which allow for the quantification of the periodic flow field, are believed to be the first such measurements acquired for a RDC. A thorough understanding of the velocity flow field exiting the combustor is important to develop future rotating detonation engine (RDE) design, as well as to successfully implement the flow conditioning devices to power generating turbine hardware located downstream. In this study, multiple PIV tests were conducted and a test case with over 16,000 consecutive image pairs acquired at a PIV framing rate of 30 kHz is analyzed in detail, and is supplemented with another test case to verify the repeatability of the measurements. Results are discretized into a two-dimensional flow field to reveal the significant insights to characterize the cyclical velocity fluctuations. While the flow field is primarily axial, a significant circumferential velocity component is also present. Key attributes of the velocity flow field are observed to be repeated from cycle-to-cycle. The codependency of the fluctuations in axial and circumferential velocity components are investigated, as is the relationship between velocity magnitude and flow orientation. At discrete measurement locations, the Fourier analysis of PIV data is used to reconstruct the cyclical variation of velocity components with respect to the phase angle.

03 NATURAL GAS↗
DOE OSTI2014

Examining System-Wide Impacts of Solar PV Control Systems with a Power Hardware-in-the-Loop Platform

High penetration levels of distributed solar PV power generation can lead to adverse power quality impacts such as excessive voltage rise, voltage flicker, and reactive power values that result in unacceptable voltage levels. Advanced inverter control schemes have been proposed that have the potential to mitigate many power quality concerns. However, closed-loop control may lead to unintended behavior in deployed systems as complex interactions can occur between numerous operating devices. In order to enable the study of the performance of advanced control schemes in a detailed distribution system environment, a Hardware-in-the-Loop (HIL) platform has been developed. In the HIL system, GridLAB-D, a distribution system simulation tool, runs in real-time mode at the Pacific Northwest National Laboratory (PNNL) and supplies power system parameters at a point of common coupling to hardware located at the National Renewable Energy Laboratory (NREL). Hardware inverters interact with grid and PV simulators emulating an operational distribution system and power output from the inverters is measured and sent to PNNL to update the real-time distribution system simulation. The platform is described and initial test cases are presented. The platform is used to study the system-wide impacts and the interactions of controls applied to inverters that are integrated into a simulation of the IEEE 8500-node test feeder, with inverters in either constant power factor control or active volt/VAR control. We demonstrate that this HIL platform is well-suited to the study of advanced inverter controls and their impacts on the power quality of a distribution feeder. Additionally, the results from HIL are used to validate GridLAB-D simulations of advanced inverter controls.

14 SOLAR ENERGY↗
DOE OSTI2012

Subgrid-Scale Mixing in Climate Models: A Novel Look at Diffusion, Accuracy, Stability and Climate Sensitivity

This project focuses on evaluating the role of subgrid-scale dissipation in the dynamical core of atmospheric models. All dynamical cores of atmospheric general circulation models (GCMs) employ some form of subgrid-scale dissipation, either explicitly specified or inherent in the chosen numerical schemes. The dissipation processes are needed to keep the simulation stable or to satisfy important physical properties, and the hope is that they capture and mimic in some poorly understood way the true processes at the unresolved subgrid scale. There is no physical basis that such dissipation can accomplish this. We originally posed a set of numerical test cases chosen or designed to isolate the role of the filters and fixers on both the dynamical variables (pressure, temperature, velocity, vorticity) and trace constituents. From these test case results, we synthesize the information to determine the impact of the subgrid-scale assumptions on weather and climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Automated procedure for developing hybrid computer simulations of turbofan engines. Part 1: General description

A systematic, computer-aided, self-documenting methodology for developing hybrid computer simulations of turbofan engines is presented. The methodology that is pesented makes use of a host program that can run on a large digital computer and a machine-dependent target (hybrid) program. The host program performs all the calculations and data manipulations that are needed to transform user-supplied engine design information to a form suitable for the hybrid computer. The host program also trims the self-contained engine model to match specified design-point information. Part I contains a general discussion of the methodology, describes a test case, and presents comparisons between hybrid simulation and specified engine performance data. Part II, a companion document, contains documentation, in the form of computer printouts, for the test case.

Szuch, J. R.↗
NASA NTRS1982

Study of tethered satellite active attitude control

Existing software was adapted for the study of tethered subsatellite rotational dynamics, an analytic solution for a stable configuration of a tethered subsatellite was developed, the analytic and numerical integrator (computer) solutions for this "test case' was compared in a two mass tether model program (DUMBEL), the existing multiple mass tether model (SKYHOOK) was modified to include subsatellite rotational dynamics, the analytic "test case,' was verified, and the use of the SKYHOOK rotational dynamics capability with a computer run showing the effect of a single off axis thruster on the behavior of the subsatellite was demonstrated. Subroutines for specific attitude control systems are developed and applied to the study of the behavior of the tethered subsatellite under realistic on orbit conditions. The effect of all tether "inputs,' including pendular oscillations, air drag, and electrodynamic interactions, on the dynamic behavior of the tether are included.

Colombo, G.↗
NASA NTRS1996

Application of an Upwind High Resolution Finite-Differencing Scheme and Multigrid Method in Steady-State Incompressible Flow Simulations

The analysis and design of a submarine propulsor requires the ability to predict the characteristics of both laminar and turbulent flows to a higher degree of accuracy. This report presents results of certain benchmark computations based on an upwind, high-resolution, finite-differencing Navier-Stokes solver. The purpose of the computations is to evaluate the ability, the accuracy and the performance of the solver in the simulation of detailed features of viscous flows. Features of interest include flow separation and reattachment, surface pressure and skin friction distributions. Those features are particularly relevant to the propulsor analysis. Test cases with a wide range of Reynolds numbers are selected; therefore, the effects of the convective and the diffusive terms of the solver can be evaluated separately. Test cases include flows over bluff bodies, such as circular cylinders and spheres, at various low Reynolds numbers, flows over a flat plate with and without turbulence effects, and turbulent flows over axisymmetric bodies with and without propulsor effects. Finally, to enhance the iterative solution procedure, a full approximation scheme V-cycle multigrid method is implemented. Preliminary results indicate that the method significantly reduces the computational effort.

NAVIER STOKES EQUATIONS↗
DOE OSTI2026

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

High-order methods for wind turbine simulations and moving to next-generation platforms

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents an effort to increase the fidelity of Nalu-Wind at a fixed resolution through the implementation of a tensor-product based, matrix-free high order scheme. High order finite element methods have increased local work per datum communicated and have the potential to provide significantly more accurate solutions at a fixed number of degrees of freedom. Previous to this milestone, Nalu-Wind had an arbitrary order Control Volume Finite Element Method discretization as a solver option, but it required too much memory and was too slow to be of practical use. The work in this milestone addresses these issues by first implementing an implicit, high order solver that only partially assembles the global system. This reduces the memory footprint of the high-order scheme by orders of magnitude for higher polynomial orders. Second, a faster, tensor-product based method for evaluating the action of the left-hand side was implemented. This reduces the amount of computational work required by the scheme and dramatically enhanced the time-to-solution on example problems. Finally, this milestone is an evaluation of the value of high order methods in the wind application space. With the enhancements to memory and computational cost, accuracy vs. time-to-solution was evaluated for several resolutions on an under-resolved Taylor Green vortex test case. Results show that the high order scheme is cost-competitive with the production low-order schemes in Nalu-Wind, being moderately more expensive than the production edge-based vertex centered finite volume scheme. The evaluation of accuracy on the test case shows a potential benefit to high order at the highest resolution while not deteriorating accuracy on the lowest tested resolution. More work is needed to show value in the wind application, but positive strides have been made.

17 WIND ENERGY↗
DOE OSTI2023

Detection of False Data Injection Attacks in Battery Stacks Using Input Noise-Aware Nonlinear State Estimation and Cumulative Sum Algorithms

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

25 ENERGY STORAGE↗
DOE OSTI2022

Benchmarking Autonomous Scattering Experiments Illustrated on TAS

With the advancement of artificial intelligence and machine learning methods, autonomous approaches are recognized to have great potential for performing more efficient scattering experiments. In our view, it is crucial for such approaches to provide thorough evidence about respective performance improvements in order to increase acceptance within a scientific community. Therefore, we propose a benchmarking procedure designed as a cost-benefit analysis that is applicable to any scattering method sequentially collecting data during an experiment. For a given approach, the performance assessment is based on how much benefit, given a certain cost budget, it is able to acquire in predefined test cases. Different approaches thus get a chance for comparison and can make their advantages explicit and visible. Key components of the procedure, i.e., cost measures, benefit measures, and test cases, are made precise for the setting of three-axes spectrometry (TAS) as an illustration. Finally, we discuss neglected aspects and possible extensions for the TAS setting and comment on the procedure’s applicability to other scattering methods. A Python implementation of the procedure to simplify its utilization by interested researchers from the field is also provided.

36 MATERIALS SCIENCE↗
DOE OSTI2023

SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0

Abstract. Water flowing under ice sheets and glaciers can have a strong influence on ice dynamics, particularly through pressure changes, suggesting that a comprehensive ice sheet model should include the effect of basal hydrology. Modeling subglacial hydrology remains a challenge, however, mainly due to the range of spatial and temporal scales involved – from subglacial channels to vast subglacial lakes. Additionally, networks of subglacial drainage channels dynamically evolve over time. To address some of these challenges, we have developed an adaptive mesh refinement (AMR) model based on the Chombo software framework. We extend the model proposed by Sommers et al. (2018) with a small but significant change to accommodate the transition from unresolved to resolved flow features. We handle the strong nonlinearities present in the equations by resorting to an efficient nonlinear full approximation scheme multigrid (FAS-MG) algorithm. We outline the details of the algorithm and present convergence analysis results demonstrating its good performance. Additionally, we present results validating our approach, using test cases from the Subglacial Hydrology Model Intercomparison Project (SHMIP) (de Fleurian et al., 2018). We finish by presenting a more complex, 100 km-by-100 km synthetic test case with peaks and valleys that we use to investigate the effective pressure distribution as the number of AMR levels increases. These preliminary results suggest that a minimum spatial resolution is needed to properly capture channel features, but additional work is required to precisely quantify this and its impact on accurately modeling the coupled ice sheet–hydrology system. The efficiency of our approach, relying on localized refinement, is also demonstrated. Future work will include coupling the SUbglacial Hydrology MOdel (SUHMO) with the BISICLES AMR ice sheet model (Cornford et al., 2013), both built on the same numerical framework.

58 GEOSCIENCES↗
NASA NTRS1990

Relative efficiency and accuracy of two Navier-Stokes codes for simulating attached transonic flow over wings

In the present study, two codes which solve the three-dimensional Thin-Layer Navier-Stokes (TLNS) equations are used to compute the steady-state flow for two test cases representing typical finite wings at transonic conditions. Several grids of C-O topology and varying point densities are used. After a description of each code and test case, standards for determining code efficiency and accuracy are defined and applied to determine the relative performance of the two codes in predicting turbulent transonic wing flows. Comparisons of computed surface pressure distributions with experimental data are made.

Bonhaus, Daryl L.↗
NASA NTRS2018

Development of a Knowledge-Based Optimization Method for Aerodynamic Design

A new aerodynamic design method, CODISC, has been developed that combines an existing knowledgebased design method, CDISC, with a simple optimization module known as SOUP. The primary goal of this new design system is to improve the performance gains obtained using CDISC without adding significant computational time. An additional benefit of this approach is a reduction in the need for a priori knowledge of good initial input variable values as well as for subsequent manual revisions of those values as the design progresses. A series of 2D and 3D test cases are used to illustrate the development of the process and some of the options available at transonic and supersonic speeds for both laminar and turbulent flow. The test cases start from good baseline configurations and, in all cases, were able to improve the performance. Several new guidelines for good initial values for the design variables, as well new design rules within CDISC itself, were developed from these cases.

Campbell, Richard L.↗
NASA NTRS2020

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗
DOE OSTI2018

High Performance Computing Tools to Advance Materials Joining Technology

In this project, an in-house HPC finite element code was developed with novel computational schemes that provided fast and high-fidelity simulation capability for welding processes and allied manufacturing processes such as metal additive manufacturing processes. Benchmark comparison confirmed that, for the testing cases studied, the newly developed in-house code resulted in increases in computational speed in the ranges of 100x to 1000x depending on the size and complexity of the testing cases, when compared to today’s commercial welding process simulation tools. As demonstrated by the selected examples in this report, the breakthrough increases in computational simulation speeds achieved by the in-house HPC code means that high fidelity simulations of certain complex welding problems that would require months even years of computational time with today’s commercial code could be solved in two to three days. Similar order of magnitudes of reduction in computational times for metal additive manufacturing process were also achieved.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Variability in the Propagation Phase of CFD-Based Noise Prediction: Summary of Results From Category 8 of the BANC-III Workshop

The usage of Computational Fluid Dynamics (CFD) in noise prediction typically has been a two part process: accurately predicting the flow conditions in the near-field and then propagating the noise from the near-field to the observer. Due to the increase in computing power and the cost benefit when weighed against wind tunnel testing, the usage of CFD to estimate the local flow field of complex geometrical structures has become more routine. Recently, the Benchmark problems in Airframe Noise Computation (BANC) workshops have provided a community focus on accurately simulating the local flow field near the body with various CFD approaches. However, to date, little effort has been given into assessing the impact of the propagation phase of noise prediction. This paper includes results from the BANC-III workshop which explores variability in the propagation phase of CFD-based noise prediction. This includes two test cases: an analytical solution of a quadrupole source near a sphere and a computational solution around a nose landing gear. Agreement between three codes was very good for the analytic test case, but CFD-based noise predictions indicate that the propagation phase can introduce 3dB or more of variability in noise predictions.

Lopes, Leonard↗