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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 91 records · Page 5

Application of an unstructured grid flow solver to planes, trains and automobiles

Rampant, an unstructured flow solver developed at Fluent Inc., is used to compute three-dimensional, viscous, turbulent, compressible flow fields within complex solution domains. Rampant is an explicit, finite-volume flow solver capable of computing flow fields using either triangular (2d) or tetrahedral (3d) unstructured grids. Local time stepping, implicit residual smoothing, and multigrid techniques are used to accelerate the convergence of the explicit scheme. The paper describes the Rampant flow solver and presents flow field solutions about a plane, train, and automobile.

Spragle, Gregory S.↗

A robust estimator of mutual information for deep learning interpretability

Abstract We develop the use of mutual information (MI), a well-established metric in information theory, to interpret the inner workings of deep learning (DL) models. To accurately estimate MI from a finite number of samples, we present GMM-MI (pronounced ‘Jimmie’), an algorithm based on Gaussian mixture models that can be applied to both discrete and continuous settings. GMM-MI is computationally efficient, robust to the choice of hyperparameters and provides the uncertainty on the MI estimate due to the finite sample size. We extensively validate GMM-MI on toy data for which the ground truth MI is known, comparing its performance against established MI estimators. We then demonstrate the use of our MI estimator in the context of representation learning, working with synthetic data and physical datasets describing highly non-linear processes. We train DL models to encode high-dimensional data within a meaningful compressed (latent) representation, and use GMM-MI to quantify both the level of disentanglement between the latent variables, and their association with relevant physical quantities, thus unlocking the interpretability of the latent representation. We make GMM-MI publicly available in this GitHub repository.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Hands-on Introduction to Shock Physics (2020 Report, RR2020-IPD-1)

Los Alamos National Laboratory (LANL) researchers have played key roles in the development of high-pressure science and shock physics since the 1950s. Central to the Laboratory’s experimental capability are multiple impact systems and explosive loading capabilities that span impact velocities in excess of 8 km/s. More recently, our efforts have taken us to 3rd and 4th generation light sources where these loading platforms are coupled to X-ray diagnostics that are now providing new insights into matter-at-extremes. As the availability of these new diagnostics and loading techniques increases, there is an increased need within the high pressure community for researchers with the knowledge base and expertise to use them. Few institutions offer any level of theoretical or experimental coursework designed to train students for work in the field of shock physics or dynamic compression science, and those that do cannot meet the current demand of the national laboratories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cardiopulmonary Resuscitation in Lunar and Martian Gravity Fields

Cardiopulmonary resuscitation is required training for all astronauts. No studies thus far have investigated how chest compressions may be affected in lunar and Martian gravities. Therefore a theoretical quantitative study was performed. The maximum downward force an unrestrained person can apply is mg N (g(sub Earth) = 9.78 ms(sup -2), g(sub moon) = 1.63 ms(sup -2), g(sub Mars) = 3.69 ms(sup -2). Tsitlik et a1 (Critical Care Medicine, 1983) described the human sternal elastic force-displacement relationship (compliance) by: F = betaD(sub s) + gammaD(sub s)(sup 2) (beta = 54.9 plus or minus 29.4 Ncm(sup -1) and gamma = 10.8 plus or minus 4.1 Ncm(sup -2)). Maximum forces in the 3 gravitational fields produced by 76 kg (US population mean), 41 kg and 93 kg (masses derived from the limits for astronaut height), produced solutions for compression depth using Tsitlik equations for chests of: mean compliance (beta = 54.9, gamma = 10.8), low compliance (beta = 84.3, gamma = 14.9) and high compliance (beta = 25.5, gamma = 6.7). The mass for minimum adequate adult compression, 3.8 cm (AHA guidelines), was also calculated. 76 kg compresses the mean compliance chest by: Earth, 6.1 cm, Mars, 3.2 cm, Moon, 1.7 cm. In lunar gravity, the high compliance chest is compressed only 3.2 cm by 93 kg, 120 kg being required for 3.8 cm. In Martian gravity, on the mean chest, 93 kg compresses 3.6 cm; 99 kg is required for 3.8 cm. On Mars, the high compliance chest is compressed 4.8 cm with 76 kg, 5.5 cm with 93 kg, with 52 kg required for 3.8 cm.

Sarkar, Subhajit↗

Loss tolerant speech decoder for telecommunications

A method and device for extrapolating past signal-history data for insertion into missing data segments in order to conceal digital speech frame errors. The extrapolation method uses past-signal history that is stored in a buffer. The method is implemented with a device that utilizes a finite-impulse response (FIR) multi-layer feed-forward artificial neural network that is trained by back-propagation for one-step extrapolation of speech compression algorithm (SCA) parameters. Once a speech connection has been established, the speech compression algorithm device begins sending encoded speech frames. As the speech frames are received, they are decoded and converted back into speech signal voltages. During the normal decoding process, pre-processing of the required SCA parameters will occur and the results stored in the past-history buffer. If a speech frame is detected to be lost or in error, then extrapolation modules are executed and replacement SCA parameters are generated and sent as the parameters required by the SCA. In this way, the information transfer to the SCA is transparent, and the SCA processing continues as usual. The listener will not normally notice that a speech frame has been lost because of the smooth transition between the last-received, lost, and next-received speech frames.

Prieto, Jr., Jaime L.↗

DNTTD (Distributed Non-Negative Tensor Train Decomposition)

The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.

Bhattarai, Manish↗

Diamond precipitation dynamics from hydrocarbons at icy planet interior conditions

The pressure and temperature conditions at which precipitation of diamond occurs from hydrocarbon mixtures is important for modelling the interior dynamics of icy planets. However, there is substantial disagreement from laboratory experiments, with those using dynamic compression techniques finding much more extreme conditions are required than in static compression. Here we report the time-resolved observation of diamond formation from statically compressed polystyrene, (C 8 H 8 ) n , heated using the 4.5 MHz X-ray pulse trains at the European X-ray Free Electron Laser facility. Diamond formation is observed above 2,500 K from 19 GPa to 27 GPa, conditions representative of Uranus’s and Neptune’s shallow interiors, on 30 μs to 40 μs timescales. This is much slower than may be observed during the ~10 ns duration of typical dynamic compression experiments, revealing reaction kinetics to be the reason for the discrepancy. In conclusion, reduced pressure and temperature conditions for diamond formation has implications for icy planetary interiors, where diamond subduction leads to heating and could drive convection in the conductive ice layer that has a role in their magnetic fields.

79 ASTRONOMY AND ASTROPHYSICS↗

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗

Portable color multimedia training systems based on monochrome laptop computers (CBT-in-a-briefcase), with spinoff implications for video uplink and downlink in spaceflight operations

This report describes efforts to use digital motion video compression technology to develop a highly portable device that would convert 1990-91 era IBM-compatible and/or MacIntosh notebook computers into full-color, motion-video capable multimedia training systems. An architecture was conceived that would permit direct conversion of existing laser-disk-based multimedia courses with little or no reauthoring. The project did not physically demonstrate certain critical video keying techniques, but their implementation should be feasible. This investigation of digital motion video has spawned two significant spaceflight projects at MSFC: one to downlink multiple high-quality video signals from Spacelab, and the other to uplink videoconference-quality video in realtime and high quality video off-line, plus investigate interactive, multimedia-based techniques for enhancing onboard science operations. Other airborne or spaceborne spinoffs are possible.

Scott, D. W.↗

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗

Linear Actuator Has Long Stroke and High Resolution

The term precision linear actuator, direct drive ( PLADD ) refers to a robust linear actuator designed to be capable of repeatedly performing, over a lifetime of the order of 5 to 10 years, positioning maneuvers that include, variously, submicron increments or slews of the order of a centimeter. The PLADD is capable of both long stroke (120 mm) and high resolution (repeatable increments of 20 nm). Unlike precise linear actuators of prior design, the PLADD contains no gears, levers, or hydraulic converters. The PLADD, now at the prototype stage of development, is intended for original use as a coarse-positioning actuator in a spaceborne interferometer. The PLADD could also be adapted to terrestrial applications in which there are requirements for long stroke and high resolution: potential applications include medical imaging and fabrication of semiconductor devices. The PLADD (see figure) includes a commercially available ball-screw actuator driven directly by a commercially available three-phase brushless DC motor. The ball-screw actuator comprises a spring-preloaded ball nut on a ball screw that is restrained against rotation as described below. The motor is coupled directly (that is, without an intervening gear train) to a drive link that, in turn, is coupled to the ball nut. By eliminating the gear train, the direct-drive design eliminates the complexity, backlash, and potential for misalignment associated with a gear train. To prevent inadvertent movement, there is a brake that includes flexured levers compressed against the drive link by preload springs. This is a power-off brake: There are also piezoelectric stacks that can be activated to oppose the springs and push the levers away from the drive link. Hence, power must be applied to the piezoelectric stacks to release the drive link from braking. To help ensure long operational life, all of the mechanical drive components are immersed in an oil bath within hermetically sealed bellows. The outer end of the bellows holds the outer end of the ball screw, thereby preventing rotation of the ball screw. Positioning is controlled by an electronic control system that includes digital and analog subsystems that interact with the motor and brake and with two sensor/encoder units: a Hall-effect-sensor rotation encoder and a linear glass-scale encoder. This system implements a proportional + integral + derivative control algorithm that results in variation of voltage commands to each of the three pairs of windings of the brushless DC motor. In one of two alternative control modes, the voltages are applied to the windings in a trapezoidal commutation scheme on the basis of timing signals obtained from the Hall-effect sensors; this scheme yields relatively coarse positioning - 24 steps per motor revolution. The second control mode involves a sinusoidal commutation scheme in which the output of the linear glass-scale encoder is transposed to rotational increments to yield much finer position feedback - more than 400,000 steps per revolution.

Cook, Brant T.↗

Missile impact craters (White Sands Missile Range, New Mexico) and applications to lunar research: Contributions to astrogeology

Craters in natural materials at White Sands Missile Range, N. Mex., were produced by the impact of high-velocity to hypervelocity missiles traveling along oblique trajectories with kinetic energies between 2.1 and 81 × 1014 ergs. The oblique impacts produce craters 2 to 10 m across with morphologies and ejecta that are bilaterally symmetrical with respect to the plane of the missile trajectory. Rims are high and the amount of ejecta large in down-trajectory and lateral directions, whereas rims are low to nonexistent and ejecta thin to absent up-trajectory. Symmetry development and modifications of the symmetry are a function of target material, local topography, and angle of impact. Seven mappable units can be recognized in and around the craters. Three of these are ejecta: thick ejecta near the crater, thin to discontinuous ejecta at greater distances, and scattered ejecta at the greatest distances to the limit of throwout. These ejecta units may be absent on the up-trajectory side; if present, they are rarely as thick or continuous as on other sides of the crater. Three units are target materials: undeformed target material exposed in local patches through thin to discontinuous ejecta and everywhere between the fragments of scattered ejecta, tilted and broken target material exposed in upper crater walls, and shattered and fractured target material exposed on the up-trajectory crater wall. The seventh unit is slope material composed of talus and fallback within the crater. Development, character, and exposure of these units varies chiefly with the target material. Ejecta from the craters is chiefly broken but relatively undeformed target material that may range in size from very fine grained debris to large blocks. Where the target is porous, significant amounts of the ejecta are composed of sheared and compressed fragments, some coated with dark layers of mixed projectile pieces, powder, and fused metal mixed with crushed target material. For layered targets, the original stratigraphic sequence is crudely preserved and in inverted order in thick ejecta. Secondary impact craters are produced by the impact of ejected fragments when the surrounding surface materials are sufficiently weak. A wide variety of secondary impact crater relations may result. Secondary craters nearest the primary crater have blocks in them that are larger than or the same size as the crater they produced. Farther from the primary crater, the fragments are generally smaller than the secondary crater and are ejected from it. Excavation of four craters revealed a mixed breccia beneath the crater floor composed of missile pieces, sheared and compressed target material, and crushed debris. Banded, disaggregated target material and nonmixed breccia surrounded the mixed breccia, and these breccias were surrounded by a zone of conjugate fractures. Beneath the ejecta on the lateral and down-trajectory crater flanks, the target materials were tilted upward and broken. Up-trajectory, open fractures and downward displacement occurred in two of the craters. No displacement was observed for the other two. Beneath the down-trajectory rims of craters with distinct layering, overturned synclines were observed. Missile breakup and behavior during cratering are a function of target and missile properties. Missile breakup depends on missile velocity and is most extensive at high velocities, where the missile is fragmented, powdered, and partly fused. Burial of missile or its fragmented, powdered, and fused remains is greatest for porous targets and least for dense cohesive targets. For very porous targets, camouflet structures containing the fragmented missile may form. Least squares fit to the data on craters in dry to moist targets indicate V(a) = 10^(-11.433)E(p)^(1.205) where V(a) is the volume of the apparent crater and E(p) is the kinetic energy of the missile. This equation is consistent with expectations of the equations relating apparent depth and radius to kinetic energy. Extrapolation of displaced masses and kinetic energies for laboratory impacts with sand and rock converge near 10^(15) to 10^(16) ergs, where the extrapolations are near the data on missile impact craters, corrected for impact angle. Displaced masses of craters produced by missile impacts and by chemical explosives with small scaled depths of burial are about the same when the kinetic energies of the missiles (corrected for angle of impact) are equal to the TNT equivalent energy of the explosive. The problem of equivalent scaled depth of burst for an impact crater is complicated and not entirely resolved, however. Both missile impact craters and chemical explosive craters in water-saturated targets are larger than their counterparts in dry to moist materials. Data collected during the study of missile impact craters have helped resolve a number of problems in lunar research: (1) the soillike nature of lunar surface materials was predicted, (2) sizes of craters produced by artificial impacts were correctly predicted, (3) certain features imaged by Surveyor were found to be analogous to features associated with missile impact craters, {4) missile impacts were used in support of the Apollo passive seismic experiment, (5) craters seen in Apollo orbital photographs were found to be similar to some missile impact craters, (6) missile impact craters supplied data on sample collection and crater phenomenology used in training astronauts, and (7) some returned lunar samples are similar to coated, sheared, and compressed fragments ejected from missile impact craters.

H. J. Moore↗

Neutron (and other Particle) Transport at LANL: An Overview [Presentation]

For decades, Los Alamos National Laboratory has been at the forefront of neutron transport methods research and code development. One such code is PARTISN, the LANL parallel time-dependent discrete ordinate neutron transport code. In this presentation, we describe the various research efforts currently underway by the PARTISN and other code teams. Some examples of current research are a block automated mesh refinement scheme, the application of tensor trains to the discretized neutron transport equation, and GPU code porting. The block automated mesh refinement scheme uses cross section information to refine and coarsen the solution mesh to improve time to solution and reduce memory. The tensor train approach expresses discretized transport operators as tensor products of vectors and matrices to compress the size of linear systems being solved by transport codes. Rather than relying on matrix-free methods such as the transport sweep, we have access to an operator that can be inverted, reshaped, or manipulated algebraically. Finally, we describe how PARTISN is used, what problems we are looking to solve, and what the future holds for neutron transport at LANL. In addition to this, we briefly describe the various research efforts in other particle transport teams using both deterministic and Monte Carlo methods. In the presentation, we list possible opportunities for collaboration between the laboratory and faculty and students.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Vector Quantization With Emergent Codebook Structure

Proposed scheme under development for transmission of vector-quantized digital video images, vector quantizer codebook updated to adapt quantizer to changing signal statistics. Intended to be realized with electronic neural network. Codebook, which consists of patterns constituting video images, will undergo training during operation and scheme will develop codebooks ordered during training. System enables coding more compact, more immune to noise, and supports variable rate compression.

Ahalt, Stanley C.↗

Assimilation of Reconstructed Radiances from IASI Principal Component Scores into the GEOS-ADAS

Hyperspectral Infrared sounders such as IASI, AIRS, and CrIS have long been an integral part of radiance assimilation in numerical weather prediction (NWP), providing vertical profiles of water vapor and temperature information. Principal Component Scores (PCS) are a lossy form of compression that retains most information, such as temperature and moisture, by using a large training set of atmospheric profiles. However, PCS may not well represent profiles which are rare events, such as volcanic eruptions, and drops some sources of random noise. There has been an increased interest in the use of PCS as EUMETSAT plans to distribute future geostationary sounder radiances from MTG-IRS via PCS only. NWP centers use two approaches to deal with PCS: direct assimilation of the PCS by modifying the radiative transfer model to produce PCS and the associated Jacobians, or a simpler approach of decompressing the PCS and reconstructing the radiances back into channel space to allow assimilating radiances without modifications to the data assimilation system. EUMETSAT has developed a PCS product for IASI that has been operational since 2011. We utilize this product opting for the simpler approach, decompressing IASI PCS into channel space, and assimilating those radiances using the GEOS-ADAS. We then compare this with a control using the standard IASI radiance product. Resulting differences in global forecast statistics, differences in Forecast Sensitivity to Observation Impact, along with implications for implementation and quality control are discussed.

Bryan M. Karpowicz↗

Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer

We present regression and compression algorithms for lattice QCD data utilizing the efficient binary optimization ability of quantum annealers. In the regression algorithm, we encode the correlation between the input and output variables into a sparse coding machine learning algorithm. The trained correlation pattern is used to predict lattice QCD observables of unseen lattice configurations from other observables measured on the lattice. In the compression algorithm, we define a mapping from lattice QCD data of floating-point numbers to the binary coefficients that closely reconstruct the input data from a set of basis vectors. Since the reconstruction is not exact, the mapping defines a lossy compression, but, a reasonably small number of binary coefficients are able to reconstruct the input vector of lattice QCD data with the reconstruction error much smaller than the statistical fluctuation. In both applications, we use D-Wave quantum annealers to solve the NP-hard binary optimization problems of the machine learning algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗