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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Experiments with Turbulent Jets at Mach Number 0.9

A systematic investigation of the structure of turbulent jets before their interaction with shock or expansion waves was undertaken during the last year. In particular compressibility and density effects in circular jets issuing in still air were investigated experimentally. Jets with nitrogen, helium, and krypton gases at 0.3, 0.6, and 0.9 Mach numbers were investigated in detail. Particle Image Velocimetry technique was developed, tested, and used to obtain qualitative information of the two-dimensional velocity field on a plane inside the flow field, which was illuminated by a laser sheet. The motion of particles was recorded by a CCD camera, which was appropriately triggered to capture two images within a fraction of a microsecond. Statistical averaging of the data at each location reduced the large amount of acquired data. It was found that the spreading rate of the jets was reduced with increased Mach numbers or increased density ratio. It was also found that decay rates of centerline Mach numbers are higher in gases with reduced density ratio. Mach number fluctuations appear to decrease with increasing Mach number of the flow. It has been proposed that the reason for this behavior is the reduction of vortex stretching activities with increased Mach number.

Agui, Juan↗
DOE OSTI2022

Neural-network learning of SPOD latent dynamics

Here, we aim to reconstruct the latent space dynamics of high dimensional, quasi-stationary systems using model order reduction via the spectral proper orthogonal decomposition (SPOD). The proposed method is based on three fundamental steps: in the first, once that the mean flow field has been subtracted from the realizations (also referred to as snapshots), we compress the data from a high-dimensional representation to a lower dimensional one by constructing the SPOD latent space; in the second, we build the time-dependent coefficients by projecting the snapshots containing the fluctuations onto the SPOD basis and we learn their evolution in time with the aid of recurrent neural networks; in the third, we reconstruct the high-dimensional data from the learnt lower -dimensional representation. The proposed method is demonstrated on two different test cases, namely, a compressible jet flow, and a geophysical problem known as the Madden-Julian Oscillation. An extensive comparison between SPOD and the equivalent POD-based counterpart is provided and differences between the two approaches are highlighted. The numerical results suggest that the proposed model is able to provide low rank predictions of complex statistically stationary data and to provide insights into the evolution of phenomena characterized by specific range of frequencies. The comparison between POD and SPOD surrogate strategies highlights the need for further work on the characterization of the interplay of error between data reduction techniques and neural network forecasts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Laser-driven ramp-compression experiments on the national ignition facility

This report details the analyses and related uncertainties in measuring longitudinal-stress–density paths in indirect laser-driven ramp equation-of-state (EOS) experiments. Experiments were conducted at the National Ignition Facility (NIF) located at the Lawrence Livermore National Laboratory. The NIF can deliver up to 2 MJ of laser energy over 30 ns and provide the necessary laser power and control to ramp compress materials to TPa pressures (1 TPa = 10 × 10 6 atmospheres). These data provide low-temperature solid-state EOS data relevant to the extreme conditions found in the deep interiors of giant planets. In these experiments, multi-stepped samples with thicknesses in the range of 40–120 µm experience an initial shock compression followed by a time-dependent ramp compression to peak pressure. Interface velocity measurements from each thickness combine to place a constraint on the Lagrangian sound speed as a function of particle velocity, which in turn allows for the determination of a continuous stress–density path to high levels of compressibility. In this report, we present a detailed description of the experimental techniques and measurement uncertainties and describe how these uncertainties combine to place a final uncertainty in both stress and density. Here, we address the effects of time-dependent deformation and the sensitivity of ramp EOS techniques to the onset of phase transformations.

47 OTHER INSTRUMENTATION↗
NASA NTRS2023

Chemical Thermodynamics and the Mathematical Integration of Reaction Kinetics

Key advances in the development of numerical methods for non-reacting compressible flows have been enabled by translating physical requirements into concrete numerical guidelines, such as the satisfaction of entropy inequalities for shock-capturing techniques [Lax, Contributions to Nonlinear Functional Analysis (1971) 603-634]. In the present work, we present nonlinear numerical analysis tools that draw from Chemical Thermodynamics , the branch of Nonequilibrium Thermodynamics that deals with chemical reactions. Through Gibbs formalism, chemical thermodynamics provides a well-known theoretical expression for the chemical equilibrium constant of a reaction in terms of reduced chemical potentials. A less-known, yet extremely valuable result, due to [Krambeck, Arch. Ration. Mech. Anal. , 38 (1970) 317], states that when this expression is implemented, mass-action kinetic models are consistent with the dynamical prescriptions of the 2nd law of thermodynamics. For fixed-temperature ordinary differential equations modeling constant-volume reacting gas mixtures, this leads to a decreasing Helmholtz free energy. If the temperature is allowed to vary in accordance with conservation of energy (1st law), this leads to the statement of increasing entropy. These nonlinear prescriptions can, and should be, used to further develop temporal integration techniques for reaction kinetics. We demonstrate that Krambeck's result holds even when the equilibrium constants are approximated from data. We prove this result by constructing the implicit free energy and the implicit entropy inherent to a given approximation. This is first done for a 5-species, 17-reaction model problem for air. With this structure established, elements of discrete entropy-stability theory [Tadmor, Acta Numer. , 12 (2003) 451] are leveraged to examine the consistency of time-integration schemes with these prescriptions. Using chemical potentials, one can compute the respective contributions of the kinetics model and of the temporal scheme to free energy/entropy variations. We introduce a nonlinear-stable version of the Discontinuous-Galerkin (DG) scheme in time which shows robustness improvements over the standard linearly-stable version. Most notably, the maximum timestep that can be resolved with the nonlinearly-stable variant tends to grow with polynomial order, in contrast to the linearly-stable variant. We generalize our constructions to arbitrary systems of reversible chemical reactions, ultimately showing that the compressible reacting Euler system admits the opposite of the implicitly constructed thermodynamic entropy as a mathematical entropy . This lays important theoretical foundations towards robust scheme development [Harten, J. Comput. Phys. 49 (1983) 151-164].

STMD↗
DOE OSTI2020

Calculation of the detonation state of HN 3 with quantum accuracy

HN 3 is a unique liquid energetic material that exhibits ultrafast detonation chemistry and a transition to metallic states during detonation. We combine the Chebyshev interaction model for efficient simulation (ChIMES) many-body reactive force field and the extended-Lagrangian multiscale shock technique molecular dynamics method to calculate the detonation properties of HN 3 with the accuracy of Kohn–Sham density-functional theory. ChIMES is based on a Chebyshev polynomial expansion and can accurately reproduce density-functional theory molecular dynamics (DFT-MD) simulations for a wide range of unreactive and decomposition conditions of liquid HN 3 . We show that addition of random displacement configurations and the energies of gas-phase equilibrium products in the training set allows ChIMES to efficiently explore the complex potential energy surface. Schemes for selecting force field parameters and the inclusion of stress tensor and energy data in the training set are examined. Structural and dynamical properties and chemistry predictions for the resulting models are benchmarked against DFT-MD. We demonstrate that the inclusion of explicit four-body energy terms is necessary to capture the potential energy surface across a wide range of conditions. Our results generally retain the accuracy of DFT-MD while yielding a high degree of computational efficiency, allowing simulations to approach orders of magnitude larger time and spatial scales. The techniques and recipes for MD model creation we present allow for direct simulation of nanosecond shock compression experiments and calculation of the detonation properties of materials with the accuracy of Kohn–Sham density-functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2010

Extraction of Modal Parameters from Spacecraft Flight Data

The modeled response of spacecraft systems must be validated using flight data as ground tests cannot adequately represent the flight. Tools from the field of operational modal analysis would typically be brought to bear on such structures. However, spacecraft systems have several complicated issues: 1. High amplitudes of loads; 2. Compressive loads on the vehicle in flight; 3. Lack of generous time-synchronized flight data; 4. Changing properties during the flight; and 5. Major vehicle changes due to staging. A particularly vexing parameter to extract is modal damping. Damping estimation has become a more critical issue as new mass-driven vehicle designs seek to use the highest damping value possible. The paper will focus on recent efforts to utilize spacecraft flight data to extract system parameters, with a special interest on modal damping. This work utilizes the analysis of correlation functions derived from a sliding window technique applied to the time record. Four different case studies are reported in the sequence that drove the authors understanding. The insights derived from these four exercises are preliminary conclusions for the general state-of-the-art, but may be of specific utility to similar problems approached with similar tools.

James, George H.↗
NASA NTRSDate not supplied

Exploring the Accuracy of RANS Simulations for Mars Entry Vehicles

Accurate yet inexpensive predictions of aerodynamic coefficients for Mars entry vehicles have remained a consistent challenge over the past five decades. Below Mach 6, drag on the backshell becomes significant and must be accurately predicted. Steady Reynolds-averaged Navier-Stokes (RANS) models are commonly used, despite their poor predictions of backshell pressure. While scale-resolving simulations have shown promise in the past decade, there is still a need for cheap, accurate RANS predictions for large aerodynamic databases. The Mars Science Laboratory (MSL) is used as a case study to examine predictive accuracy and known shortcomings for RANS predictions of Mars entry vehicles. Several different grid generation techniques are compared, including a comparison between prismatic boundary layer grids and fully unstructured, tetrahedral grids. Comparisons are made to experimental data for Mach 2.5, 3.5, and 4.5. The accuracy of predicted aerodynamic coefficients is examined. Overpredictions in axial force and drag are explained by a closer examination of the surface pressure. These findings document sensitivities and best practices for future RANS database development of Mars entry vehicles.

RANS↗
NASA NTRS1993

Investigation of high-speed free shear flows using improved pressure-strain correlated Reynolds stress turbulence model

A high-speed shear layer is studied using compressibility corrected Reynolds stress turbulence model which employs newly developed model for pressure-strain correlation. MacCormack explicit prediction-corrector method is used for solving the governing equations and the turbulence transport equations. The stiffness arising due to source terms in the turbulence equations is handled by a semi-implicit numerical technique. Results obtained using the new model show a sharper reduction in growth rate with increasing convective Mach number. Some improvements were also noted in the prediction of the normalized streamwise stress and Reynolds shear stress. The computed results are in good agreement with the experimental data.

Tiwari, S. N.↗
NASA NTRS1998

Determination of Yield and Flow Surfaces for Inconel 718 Under Axial-Torsional Loading at Temperatures Up to 649 C

An experimental program to determine flow surfaces has been established and implemented for solution annealed and aged IN718. The procedure involved subjecting tubular specimens to various ratios of axial-torsional stress at temperatures between 23 and 649 C and measuring strain with a biaxial extensometer. Each stress probe corresponds to a different direction in stress space, and unloading occurs when a 30 microstrain (1 micro eplison = 10(exp -6) mm/mm) offset is detected. This technique was used to map out yield loci in axial-torsional stress space. Flow surfaces were determined by post-processing the experimental data to determine the inelastic strain rate components. Surfaces of constant inelastic strain rate (SCISRS) and surfaces of constant inelastic power (SCIPS) were mapped out in the axial-shear stress plane. The von Mises yield criterion appeared to closely fit the initial loci for solutioned IN718 at 23 C. However, the initial loci for solutioned IN718 at 371 and 454 C, and all of the initial loci for aged IN718 were offset in the compression direction. Subsequent loci showed translation, distortion, and for the case of solutioned IN718, a slight cross effect. Aged IN718 showed significantly more hardening behavior than solutioned IN718.

Gil, Christopher M.↗
DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗
DOE OSTI2023

Direct prediction of inelastic neutron scattering spectra from the crystal structure*

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2004

Characterization of Composite Fan Case Resins

The majority of commercial turbine engines that power today s aircraft use a large fan driven by the engine core to generate thrust which dramatically increases the engine s efficiency. However, if one of these fan blades fails during flight, it becomes high energy shrapnel, potentially impacting the engine or puncturing the aircraft itself and thus risking the lives of passengers. To solve this problem, the fan case must be capable of containing a fan blade should it break off during flight. Currently, all commercial fan cases are made of either just a thick metal barrier or a thinner metal wall surrounded by Kevlar-an ultra strong fiber that elastically catches the blade. My summer 2004 project was to characterize the resins for a composite fan case that will be lighter and more efficient than the current metal. The composite fan case is created by braiding carbon fibers and injecting a polymer resin into the braid. The resin holds the fibers together, so at first using the strongest polymer appears to logically lead to the strongest fan case. Unfortunately, the stronger polymers are too viscous when melted. This makes the manufacturing process more difficult because the polymer does not flow as freely through the braid, and the final product is less dense. With all of this in mind, it is important to remember that the strength of the polymer is still imperative; the case must still contain blades with high impact energy. The research identified which polymer had the right balance of properties, including ease of fabrication, toughness, and ability to transfer the load to the carbon fibers. Resin deformation was studied to better understand the composite response during high speed impact. My role in this research was the testing of polymers using dynamic mechanical analysis and tensile, compression, and torsion testing. Dynamic mechanical analysis examines the response of materials under cyclic loading. Two techniques were used for dynamic mechanical analysis. The ARES Instrument analyzed the material through torsion. The second machine, TA Instruments apparatus, applied a bending force to the specimen. These experiments were used to explore the effects of temperature and strain rate on the stiffness and strength of the resins. The two different types of loading allowed us to verify our results. An axial-torsional load frame, manufactured by MTS Systems, Inc., was used to conduct the tensile, compression, and torsional testing. These tests were used to determine the stress-strain curves for the resins. The elastic and plastic deformation data was provided to another team member for characterization of high fidelity material property predictions. This information was useful in having a better understanding of the polymers so that the fan cases could be as sturdy as possible. Deformation studies are the foundation for the computational modeling that provides the structural design of a composite engine case as well as detailed analysis of the blade impact event.

Dvoracek, Charlene M.↗
NASA NTRS1977

Computational models for the analysis of three-dimensional internal and exhaust plume flowfields

This paper describes computational procedures developed for the analysis of three-dimensional supersonic ducted flows and multinozzle exhaust plume flowfields. The models/codes embodying these procedures cater to a broad spectrum of geometric situations via the use of multiple reference plane grid networks in several coordinate systems. Shock capturing techniques are employed to trace the propagation and interaction of multiple shock surfaces while the plume interface, separating the exhaust and external flows, and the plume external shock are discretely analyzed. The computational grid within the reference planes follows the trace of streamlines to facilitate the incorporation of finite-rate chemistry and viscous computational capabilities. Exhaust gas properties consist of combustion products in chemical equilibrium. The computational accuracy of the models/codes is assessed via comparisons with exact solutions, results of other codes and experimental data. Results are presented for the flows in two-dimensional convergent and divergent ducts, expansive and compressive corner flows, flow in a rectangular nozzle and the plume flowfields for exhausts issuing out of single and multiple rectangular nozzles.

Dash, S. M.↗
NASA NTRS1991

A very high speed lossless compression/decompression chip set

A chip is described that will perform lossless compression and decompression using the Rice Algorithm. The chip set is designed to compress and decompress source data in real time for many applications. The encoder is designed to code at 20 M samples/second at MIL specifications. That corresponds to 280 Mbits/second at maximum quantization or approximately 500 Mbits/second under nominal conditions. The decoder is designed to decode at 10 M samples/second at industrial specifications. A wide range of quantization levels is allowed (4...14 bits) and both nearest neighbor prediction and external prediction are supported. When the pre and post processors are bypassed, the chip set performs high speed entropy coding and decoding. This frees the chip set from being tied to one modeling technique or specific application. Both the encoder and decoder are being fabricated in a 1.0 micron CMOS process that has been tested to survive 1 megarad of total radiation dosage. The CMOS chips are small, only 5 mm on a side, and both are estimated to consume less than 1/4 of a Watt of power while operating at maximum frequency.

Venbrux, Jack↗
NASA NTRS1990

Micro Blowing Simulations Using a Coupled Finite-Volume Lattice-Boltzman n L ES Approach

Three dimensional large-eddy simulations (LES) of single and multiple jet-in-cross-flow (JICF) are conducted using the 19-bit Lattice Boltzmann Equation (LBE) method coupled with a conventional finite-volume (FV) scheme. In this coupled LBE-FV approach, the LBE-LES is employed to simulate the flow inside the jet nozzles while the FV-LES is used to simulate the crossflow. The key application area is the use of this technique is to study the micro blowing technique (MBT) for drag control similar to the recent experiments at NASA/GRC. It is necessary to resolve the flow inside the micro-blowing and suction holes with high resolution without being restricted by the FV time-step restriction. The coupled LBE-FV-LES approach achieves this objectives in a computationally efficient manner. A single jet in crossflow case is used for validation purpose and the results are compared with experimental data and full LBE-LES simulation. Good agreement with data is obtained. Subsequently, MBT over a flat plate with porosity of 25% is simulated using 9 jets in a compressible cross flow at a Mach number of 0.4. It is shown that MBT suppresses the near-wall vortices and reduces the skin friction by up to 50 percent. This is in good agreement with experimental data.

Menon, S.↗
DOE OSTI2024

A mesoscale 3D model of irradiated concrete informed via a 2.5 U-Net semantic segmentation

The concrete biological shield in light-water reactors is exposed to neutron and gamma irradiation, which deteriorates the concrete’s mechanical properties in the long term. To assess the irradiation-induced damage, predictive mechanical models are developed and used in parallel with the characterization of irradiated concrete samples. Realistic 3D simulation domains can drastically improve a model’s prediction. In this work, we utilized x-ray computed tomography (XCT) data of a concrete specimen to reconstruct its 3D microstructure. The XCT data shows low contrast between the concrete’s aggregates and cement paste, resulting in poor image segmentation when using traditional unsupervised techniques. To address this issue, we developed and trained a 2.5D U-Net model on only 24 pre-labeled XCT layers to segment 651 layers of the XCT data. The overall F1-score of the model is approximately 96%. Then, we created a 3D finite element (FE) mesh based on the stack of segmented images. The FE model contains radiation-induced expansion, damage, and creep. The constitutive equations are adapted to each phase (aggregates and cement paste). Here, we simulated the effects of neutron irradiation in the concrete specimen as well as the specimen’s mechanical response to uniaxial compression. Finally, model validation was performed using experimental data on similar concrete specimens in the literature.

2.5D U-Net↗
NASA NTRS1995

Vibrational Energy Coupling in Expanding N2/O2/NO Admixtures

Recent direct measurements of N2 and O2 vibrational populations in expansions of synthetic air show a closer coupling of the vibrational energies than indicated by adapting earlier experimental results from shock compressions to the nozzle expansion problem. An important difference between the shock wave and nozzle flow problems is the presence of NO in significant amounts throughout the relaxation in the case of a nozzle flow. This may account for the stronger coupling since NO is well suited to promote vibrational energy exchange. The results of a series of experiments and analysis examining vibrational energy coupling in expansions of admixtures approximating air are reported. N2 and O2 vibrational populations are determined by a single-pulse spontaneous Raman scattering technique. NO vibrational populations are determined by broadband absorption by the NO(y) system. The resulting data permit the role of NO in promoting vibrational energy coupling to be better understood, and are used to evaluate models of vibrational energy exchange for application to expanding flows.

Gilmore, John O.↗
NASA NTRS2003

Measurement of the Specific Heat Using a Gravity Cancellation Approach

The specific heat at constant volume C(sob V) of a simple fluid diverges near its liquid-vapor critical point. However, gravity-induced density stratification due to the divergence of isothermal susceptibility hinders the direct comparison of the experimental data with the predictions of renormalization group theory. In the past, a microgravity environment has been considered essential to eliminate the density stratification. We propose to perform specific heat measurements of He-3 on the ground using a method to cancel the density stratification. A He-3 fluid layer will be heated from below, using the thermal expansion of the fluid to cancel the hydrostatic compression. A 6% density stratification at a reduced temperature of 10(exp -5) can be cancelled to better than 0.1% with a steady 1.7 micro K temperature difference across a 0.05 cm thick fluid layer. A conventional AC calorimetry technique will be used to determine the heat capacity. The minimized bulk density stratification with a relaxation time 6500 sec at a reduced temperature of 10(exp -5) will stay unchanged during 1 Hz AC heating. The smear of the specific heat divergence due to the temperature difference across the cell is about 0.1% at a reduced temperature of 10(exp -6). The combination of using High Resolution Thermometry with a 0.5 n K temperature resolution in the AC technique and the cancellation of the density stratification will enable C(sub V) to be measured down to a reduced temperature of 10(exp -6) with less than a 1% systematic error.

Zhong, Fang↗