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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 127 records · Page 7
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NASA NTRSDate not supplied

Inlet Vortex Generator Design for the X-59 Low Boom Flight Demonstrator

An array of vortex generators was designed for the X-59 Low Boom Flight Demonstrator aircraft inlet. Prior to the a High Speed Inlet Distortion Test, concern regarding potentially high measurements of steady state or dynamic distortion prompted an effort to examine the use of passive flow control to reduce distortion levels. Design of experiments methodology was used to develop two matrices of vortex generators placed inside the inlet serpentine duct and upstream of the inlet on the compression surface, varying on several geometric parameters. Reynolds-Averaged Navier-Stokes simulations were performed using the FUN3D flow solver at Mach 1.45 to analyze the impact of each configuration on total pressure recovery, circumferential distortion, and radial distortion. Results from simulations of the baseline aircraft are compared with data acquired in the NASA Glenn Research Center’s 8- by 6-foot Supersonic Wind Tunnel. A vortex generator configuration with vanes placed upstream of the inlet terminal shock was shown to significantly increase total pressure recovery and decrease circumferential distortion with no penalty to radial distortion levels. Inlet mass flow sweeps at Mach 1.45, 0.6, and 0.3 indicated no detrimental effects from the vanes at off-design conditions.

Vortex generators↗
NASA NTRSDate not supplied

Inlet Vortex Generator Design for the X-59 Low Boom Flight Demonstrator

An array of vortex generators was designed for the X-59 Low Boom Flight Demonstrator aircraft inlet. Prior to the a High Speed Inlet DistortionTest, concern regarding potentially high measurements of steady state or dynamic distortion prompted an effort to examine the use of passive flow control to reduce distortion levels. Design of experiments methodology was used to develop two matrices of vortex generators placed inside the inlet serpentine duct and upstream of the inlet on the compression surface, varying on several geometric parameters. Reynolds- Averaged Navier-Stokes simulations were performed using the FUN3D flow solver at Mach 1.45 to analyze the impact of each configuration on total pressure recovery, circumferential distortion, and radial distortion. Results fromsimulations of the baseline aircraft are compared with data acquired in the NASA Glenn Research Center’s 8- by 6-foot SupersonicWind Tunnel. A vortex generator configuration with vanes placed upstream of the inlet terminal shock was shown to significantly increase total pressure recovery and decrease circumferential distortion with no penalty to radial distortion levels. Inlet mass flow sweeps at Mach 1.45, 0.6, and 0.3 indicated no detrimental effects from the vanes at off-design conditions.

Vortex generators↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-ofthe-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Hesham ElAbd↗
NASA NTRS1989

Spectroscopic analysis of transition state energy levels - Bending-rotational spectrum and lifetime analysis of H3 quasibound states

Converged quantum mechanical calculations of scattering matrices and transition probabilities are reported for the reaction of H with H2 with total angular momentum 0, 1, and 4 as functions of total energy in the range 0.85-1.15 eV on an accurate potential energy surface. The resonance structure is illustrated with Argand diagrams. State-to-state reactive collision delay times and lifetimes are presented. For J = 0, 1, and 4, the lowest-energy H3 resonance is at total energies of 0.983, 0.985, and 1.01 eV, respectively, with lifetimes of about 16-17 fs. For J = 1 and 4 there is a higher-energy resonance at 1.10-1.11 eV. For J = 1 the lifetime is about 4 fs and for J = 4 it is about 1 fs.

Zhao, Meishan↗
NASA NTRS1980

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed.

Park, J. K.↗
NASA NTRS1999

Launch Collision Probability

This report analyzes the probability of a launch vehicle colliding with one of the nearly 10,000 tracked objects orbiting the Earth, given that an object on a near-collision course with the launch vehicle has been identified. Knowledge of the probability of collision throughout the launch window can be used to avoid launching at times when the probability of collision is unacceptably high. The analysis in this report assumes that the positions of the orbiting objects and the launch vehicle can be predicted as a function of time and therefore that any tracked object which comes close to the launch vehicle can be identified. The analysis further assumes that the position uncertainty of the launch vehicle and the approaching space object can be described with position covariance matrices. With these and some additional simplifying assumptions, a closed-form solution is developed using two approaches. The solution shows that the probability of collision is a function of position uncertainties, the size of the two potentially colliding objects, and the nominal separation distance at the point of closest approach. ne impact of the simplifying assumptions on the accuracy of the final result is assessed and the application of the results to the Cassini mission, launched in October 1997, is described. Other factors that affect the probability of collision are also discussed. Finally, the report offers alternative approaches that can be used to evaluate the probability of collision.

Bollenbacher, Gary↗
NASA NTRS2023

The J and K Dependencies of the Line Coupling and Line Mixing Effects: Theoretical Studies of the Relaxation Matrices of N 2 -Broadened Ch 3 D

Line coupling and line mixing effects in parallel and perpendicular bands of CH 3 D perturbed by N 2 have been studied. The work focuses on exhibiting the j and k dependencies of these two processes. The calculations were based on a previously reported anisotropic intermolecular potential including both the long-range multipole, induction, and dispersion forces and a short-range atom-atom model. It is shown that components with L 1 = 3 of the atom-atom model are dominant contributions to the diffusion operator. As a consequence, in comparison with other molecular systems such as the CH 3 Cl-N 2 and CH 3 I-N 2 , theoretically predicted line coupling and line mixing effects exhibit completely new j and k dependencies. In general, the theoretically calculated halfwidths and intra-doublets’ off-diagonal elements of the relaxation matrix are in reasonable agreement with measurements.

Methane-d↗
NASA NTRS2015

Theoretical Studies of Spectroscopic Line Mixing in Remote Sensing Applications

The phenomenon of collisional transfer of intensity due to line mixing has an increasing importance for atmospheric monitoring. From a theoretical point of view, all relevant information about the collisional processes is contained in the relaxation matrix where the diagonal elements give half-widths and shifts, and the off-diagonal elements correspond to line interferences. For simple systems such as those consisting of diatom-atom or diatom-diatom, accurate fully quantum calculations based on interaction potentials are feasible. However, fully quantum calculations become unrealistic for more complex systems. On the other hand, the semi-classical Robert-Bonamy (RB) formalism, which has been widely used to calculate half-widths and shifts for decades, fails in calculating the off-diagonal matrix elements. As a result, in order to simulate atmospheric spectra where the effects from line mixing are important, semi-empirical fitting or scaling laws such as the ECS (Energy-Corrected Sudden) and IOS (Infinite-Order Sudden) models are commonly used. Recently, while scrutinizing the development of the RB formalism, we have found that these authors applied the isolated line approximation in their evaluating matrix elements of the Liouville scattering operator given in exponential form. Since the criterion of this assumption is so stringent, it is not valid for many systems of interest in atmospheric applications. Furthermore, it is this assumption that blocks the possibility to calculate the whole relaxation matrix at all. By eliminating this unjustified application, and accurately evaluating matrix elements of the exponential operators, we have developed a more capable formalism. With this new formalism, we are now able not only to reduce uncertainties for calculated half-widths and shifts, but also to remove a once insurmountable obstacle to calculate the whole relaxation matrix. This implies that we can address the line mixing with the semi-classical theory based on interaction potentials between molecular absorber and molecular perturber. We have applied this formalism to address the line mixing for Raman and infrared spectra of molecules such as N2, C2H2, CO2, NH3, and H2O. By carrying out rigorous calculations, our calculated relaxation matrices are in good agreement with both experimental data and results derived from the ECS model.

Formalism↗
NASA NTRS2021

Carbon- and Ceramic-Matrix Composite Nozzle Extensions for Liquid Rocket Engines

Carbon-carbon (C-C) composite and ceramic matrix composite (CMC) nozzle extensions are being considered and developed for use with a variety of cryogenic liquid rocket engine systems. Some of the potential applications include in-space, lunar lander, and launch vehicle upper stage propulsion systems. Composite material systems of interest include C-C and carbon/silicon-carbide (C-SiC) composites, as well as modified versions of such composites (coatings, mixed matrices, oxidation inhibitors, etc.). Nozzle extension materials and fabrication methods under development by industry support both National Aeronautics and Space Administration (NASA) and Department of Defense (DOD) requirements, as well as those of the broader Commercial Space industry. Marshall Space Flight Center (MSFC) efforts are aimed at both (a) assisting industry with the development of composite nozzle extensions for cryogenic liquid rocket engines, and (b) developing and demonstrating capabilities for characterizing, testing, and qualifying such nozzle extensions. Results of recent MSFC nozzle-extension characterization efforts and engine firing demonstrations will be presented.

carbon-carbon↗
NASA NTRS1981

Transportation systems evaluation methodology development and applications, phase 3

Transportation systems or proposed changes in current systems are evaluated. Four principal evaluation criteria are incorporated in the process, operating performance characteristics as viewed by potential users, decisions based on the perceived impacts of the system, estimating what is required to reduce the system to practice; and predicting the ability of the concept to attract financial support. A series of matrix multiplications in which the various matrices represent evaluations in a logical sequence of the various discrete steps in a management decision process is used. One or more alternatives are compared with the current situation, and the result provides a numerical rating which determines the desirability of each alternative relative to the norm and to each other. The steps in the decision process are isolated so that contributions of each to the final result are readily analyzed. The ability to protect against bias on the part of the evaluators, and the fact that system parameters which are basically qualitative in nature can be easily included are advantageous.

Kuhlthau, A. R.↗
NASA NTRS1983

A mathematical model for efficient estimation of aircraft motions

In the usual formulation of the aircraft state-estimation problem, motions along a flight trajectory are represented by a plant consisting of nonlinear state and measurement models. Problem solution using this formulation requires that both state- and measurement-dependent Jacobian matrices be evaluated along any trajectory. In this paper it is shown that a set of state variables can be chosen to realize a linear state model of very simple form, such that all nonlinearities appear in the measurement model. The potential advantage of the new formulation is computational: the Jacobian matrix corresponding to a linear state model is constant, a feature that should outweigh the fact that the measurement model is more complicated than in the conventinal formulation. To compare the modeling methods, aircraft motions from typical flight-test and accident data were estimated, using each formulation with the same off-line (smoothing) algorithm. The results of these experiments, reported in the paper, demonstrate clearly the computational superiority of the linear state-variable formulation. The procedure advocated here may be extended to other nonlinear estimation problems, including on-line (filtering) applications.

Bach, R. E., Jr.↗
NASA NTRS1990

An improved Newton iteration for the generalized inverse of a matrix, with applications

The purpose here is to clarify and illustrate the potential for the use of variants of Newton's method of solving problems of practical interest on highly personal computers. The authors show how to accelerate the method substantially and how to modify it successfully to cope with ill-conditioned matrices. The authors conclude that Newton's method can be of value for some interesting computations, especially in parallel and other computing environments in which matrix products are especially easy to work with.

Pan, Victor↗
NASA NTRS2000

Highly Parallel Computing Architectures by using Arrays of Quantum-dot Cellular Automata (QCA): Opportunities, Challenges, and Recent Results

There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA-based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.

Fijany, Amir↗
NASA NTRS1976

Zero-G processing of magnets experiment MA-070

Solidification of magnetic materials in the low gravity orbital environment was studied. The magnetic compounds under study, manganese bismuth and copper cobalt cerium ((Cu, Co)5Ce), both have the potential for the development of high coercive strength. Preliminary results indicate that static fluid configurations, in the absence of the gravitational body force, differ substantially from the documented terrestrial behavior. Chemical homogeneity is substantially enhanced on a macroscopic and microscopic level. Single crystal matrices have been grown in the coordinated growth regions of the flight samples. Primary crystals one order of magnitude greater than those grown terrestrially have been noted and are limited in size by the ampoule dimensions.

Larson, D. J., Jr.↗
NASA NTRS1985

Some iterative schemes for transonic potential flows

The minimal residual (MR) method for the numerical solution of transonic potential flows is closely related to the conjugate gradient method, which has found widespread use in the solution of large sparse, symmetric, and positive-definite linear equations. The primary advantage of the MR method is its applicability to both symmetric and nonsymmetric matrices.

Wong, Y. S.↗
NASA NTRS1991

Simulated space environmental effects on some experimental high performance polymers

Organic polymeric materials are currently being considered for long term use (more than 10 years) in structural (adhesives and composite matrices) and functional (films and coatings) applications on spacecraft. Although organic polymers have been utilized successfully in short term missions, the long term durability of these materials in space is of concern. As part of a NASA effort on high performance polymers for potential space applications, various experimental polymeric materials recently synthesized at NASA Langley Research Center were evaluated under simulated space environmental conditions. Experimental resins from blends of acetylene terminated materials, poly(arylene ether)s and low color polyimides were exposed to high energy electron and ultraviolet radiation in an attempt to simulate space environmental effects. Thin films, neat resin moldings and carbon fiber reinforced composites were exposed and the effect on certain polymer properties were determined. This paper reviews recent research involving the effects of various radiation exposures on the physical, optical and mechanical properties of several experimental polymer systems.

Connell, John W.↗
NASA NTRS2000

Molecular Spectroscopy in Astrophysics: The Case of Polycyclic Aromatic Hydrocarbons

The role of molecular spectroscopy in astrophysics and astrochemistry is discussed in the context of the study of large, complex, carbon-bearing molecules, namely, Polycyclic Aromatic Hydrocarbons or PAHs. These molecular species are now thought to be widespread in the interstellar medium in their neutral and ionized forms. Identifying the carriers responsible for unidentified interstellar spectral bands will allow to derive important information on cosmic elemental abundances as well as information on the physical conditions (density, temperature) reigning in specific interstellar environments. These, in turn, are key elements for a correct understanding of the energetic mechanisms that govern the origin and the evolution of the interstellar medium. A multidisciplinary approach - combining astronomical observations with laboratory simulations and theoretical modeling - is required to address these complex issues. Laboratory spectra of several PAHs, isolated at low temperature in inert gas matrices or seeded in a supersonic jet expansion, are discussed here and compared to the astronomical spectra of reddened, early type, stars. The electronic spectroscopy of PAHs in the ultraviolet, visible, and near-infrared domains is reviewed and an assessment of the potential contribution of PAHs to the interstellar extinction in the ultraviolet and in the visible is discussed.

Salama, Farid↗