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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 307 records · Page 17

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NASA NTRS1995

HINCOF-1: a Code for Hail Ingestion in Engine Inlets

One of the major concerns during hail ingestion into an engine is the resulting amount and space- and time-wise distribution of hail at the engine face for a given geometry of inlet and set of atmospheric and flight conditions. The appearance of hail in the capture streamtube is invariably random in space and time, with respect to size and momentum. During the motion of a hailstone through an inlet, a hailstone undergoes several processes, namely impact with other hailstones and material surfaces of the inlet and spinner, rolling and rebound following impact; heat and mass transfer; phase change; and shattering, the latter three due to friction and impact. Taking all of these factors into account, a numerical code, designated HINCOF-I, has been developed for determining the motion hailstones from the atmosphere, through an inlet, and up to the engine face. The numerical procedure is based on the Monte-Carlo method. The report presents a description of the code, along with several illustrative cases. The code can be utilized to relate the spinner geometry - conical or, more effective, elliptical - to the possible diversion of hail at the engine face into the bypass stream. The code is also useful for assessing the influence of various hail characteristics on the ingestion and distribution of hailstones over the engine face.

Gopalaswamy, N.↗

NASA NTRS2022

The Dynamic Coupling of Streamers and Pseudostreamers to the Heliosphere

The slow solar wind is generally believed to result from the interaction of open and closed coronal magnetic flux at streamers and pseudostreamers. We use three-dimensional magnetohydrodynamic simulations to determine the detailed structure and dynamics of open-closed interactions that are driven by photospheric convective flows. The photospheric magnetic field model includes a global dipole giving rise to a streamer together with a large parasitic polarity region giving rise to a pseudostreamer that separates a satellite coronal hole from the main polar hole. Our numerical domain extends out to 30Rꙩ and includes an isothermal solar wind, so that the coupling between the corona and heliosphere can be calculated rigorously. This system is driven by imposing a large set of quasi-random surface flows that capture the driving of coronal flux in the vicinity of streamer and pseudostreamer boundaries by the supergranular motions. We describe the resulting structures and dynamics. Interchange reconnection dominates the evolution at both streamer and pseudostreamer boundaries, but the details of the resulting structures are clearly different from one another. Additionally, we calculate in situ signatures of the reconnection and determine the dynamic mapping from the inner heliosphere back to the Sun for a test spacecraft orbit. We discuss the implications of our results for interpreting observations from inner heliospheric missions, such as Parker Solar Probe and Solar Orbiter, and for space weather modeling of the slow solar wind.

V. Aslanyan↗

NASA NTRS1989

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

Choudhary, Alok Nidhi↗

NASA NTRS2024

3D Scanning System to Assess Gravity-Dependent Body Shape Changes

The human body shows unique physiological and morphological changes when exposed to different gravity conditions, including muscle atrophy, fluid shift, spinal elongation, and body posture adjustments. Such changes need to be incorporated for human-system integration in the vehicle habitat, garment, and spacesuit designs, as inaccurate body measurements can result in suboptimal crew protection that can potentially decrease injury tolerance. However, the traditional linear measurements, such as stature, segment lengths or circumferences measured using a caliper or tape measure, often show limited consistency and are unable to capture the nonlinear characteristics of the human body. While 3D body scanning can provide significant advantages over linear measurements, the technologies have not been fully developed or customized for in-flight scanning. For ground laboratory use, several different scanner types are commercially available. However, in-flight scanning requires additional technical considerations, such as minimal scan time, simplified calibration, and sufficient capture volume. This work aims to develop a prototype 3-D body scanning system that is customized for in-flight use to scan crewmembers, with the configuration and performance optimized for detecting known gravity-dependent body shape and posture changes. A hardware system will be custom built using a network of commercial off-the-shelf 3D sensors. The sensor parameters and settings will be optimized to detect the targeted body shape changes, specifically using body manikins of which the shape and size are iteratively permuted to simulate the known changes by fluid shift and spinal elongation. The capture volume will be also matched for a range of body sizes from a 1st percentile female to 99th percentile male. Unintentional body motions or floating in microgravity will be also simulated and incorporated. A data acquisition software will be developed for efficient in-flight operations with minimal overhead and easy-to-use user interface. A simplified calibration procedure will be designed for robust scanning against frequent vibration or unexpected sensor position shifts. The system will be tested in the ground laboratory for accuracy and reliability against a reference scanning system. New anthropometry measurements will be also identified to sensitively capture the gravity dependent body shape changes, in addition to the traditional anthropometry measurements. A novel landmark-based technique will be tested for consistent anthropometry measurements across posture variations. If successfully developed and deployed, the new system is expected to provide previously unavailable body shape and size data from different gravitational environments, including 0-g, 1/6-g, and 1-g. Such data can improve suit fit, habitat design, exercise efficacy quantification and sizing of orthostatic intolerance garments.

K H Kim↗

NASA NTRS2024

3D Scanning System to Assess Gravity-Dependent Body Shape Changes

K H Kim↗

DOE OSTI2024

Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities

We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a familiar double-well potential, with known stationary distributions, and a Lennard-Jones solid potential (a Galton Board). By sampling Brownian motion trajectories, we are able to compute expectations of observable averages. These multi-basin potential energy problems capture the essence of the challenges with using MLMC, namely, maintaining correspondence of sample paths as time-resolution is varied. Addressing this challenge properly can lead to MLMC significantly outperforming standard Monte Carlo path sampling. We describe the essence of this problem and suggest strategies that circumvent diverging multilevel sample paths for an important class of problems. In the tests we also compare the computational cost of several, “adaptive,” variants of MLMC. Our results demonstrate that MLMC overcomes the collision, time scale limitation of the more familiar Brownian path MC samplers, and our implementation provides tunable error thresholds, making MLMC a promising candidate for application to larger and more complex molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Deployable Element Ultra-High Vacuum Pump

Advancing Ultra High Vacuum (UHV) Pumping Technology: The deployable UHV pump team has designed a theoretical model to boost efficiency in high vacuum environments. Traditional systems face challenges with random molecular motion. The innovative windmill design, using titanium sublimation technology, reduces randomness by deploying a gettering surface that actively captures particles. This marks a notable advancement in UHV pumping technology.

43 PARTICLE ACCELERATORS↗

NASA NTRS1992

Young globular clusters in the Milky Way Galaxy

Ruprecht 106 and Pal 12 are two known globular clusters in the Milky Way that are unequivocally younger than other clusters of similar metallicity. The Galactic coordinates of Ruprecht 106 place it near to the Magellanic Stream in projection, suggesting a tidal capture from the Magellanic Clouds. It is demonstrated that a family of orbits for both clusters can be constructed that are consistent with this capture hypothesis and that these then lead to a prediction of 3 milliarcseconds per year for the proper motions of both Ruprecht 106 and Pal 12.

Lin, D. N. C.↗

NASA NTRS2003

Manipulation of Micro Scale Particles in Optical Traps Using Programmable Spatial Light Modulation

1064 nm light, from an Nd:YAG laser, was polarized and incident upon a programmable parallel aligned liquid crystal spatial light modulator (PAL-SLM), where it was phase modulated according to the program controlling the PAL-SLM. Light reflected from the PAL-SLM was injected into a microscope and focused. At the focus, multiple optical traps were formed in which 9.975 m spheres were captured. The traps and the spheres were moved by changing the program of the PAL-SLM. The motion of ordered groups of micro particles was clearly demonstrated.

Seibel, Robin E.↗

NASA NTRS2005

Reduced-Order Modeling of a Heaving Airfoil

A reduced-order model of a flapping airfoil is developed using Proper Orthogonal Decomposition (POD). The proper basis functions, developed from snapshots of full Navier-Stokes simulations, are used for a Galerkin projection of the governing equations. The resulting coupled, nonlinear ordinary di.erential equations have a low dimension because the first few basis members capture most of the energy of the flow. The reduced-order model is used to simulate heaving motions that are both similar to and different from the motion(s) used to generate the basis functions, and the errors in the model are quantified. Several methods are used to generate mode sets that can be used over a range of heaving parameters, including snapshots from one, two, and multiple Navier-Stokes simulations. As snapshots from additional simulations are added to the decomposition, the mode sets become richer and can simulate a wider range of parameter space, at some computational cost. Whereas the POD method is fully applicable in three dimensions, the simulation technique based on a body-fixed and body-fitted grid suffers large overhead when extended to three dimensions. To reduce the overhead, an embedding technique is discussed which embeds the solid wing into a fixed Cartesian grid. The wing, which can now have multiple pieces and also be flexible, is represented by a distribution of body forces. This distribution is determined to give exactly the flow around a flapping wing.

Haj-Hariri, H.↗

NASA NTRS2022

A Numerical Study of the Liquid Motion in Titan’s Subsurface Ocean

An ocean filled with liquid water lies beneath the icy surface of several Jovian and Saturnian moons. In such an ocean, the currents are driven by various phenomena such as the tidal forcing, the deformation of the ice shell lying at its top, the temperature gradient resulting from the surface and bottom heat fluxes…The flow induced by the first two forcings can be modelled by means of a 2D depth-averaged model, while the third one generates horizontal and vertical density variations whose effects can only be captured by a 3D baroclinic model. We study the tides of Titan’s subsurface ocean and the impact of the ice shell on the liquid motion by means of the Second-generation Louvain-la-Neuve Ice–ocean Model, SLIM (https://www.climate.be/slim). The impact of the ice shell lying at the top of the ocean is modelled by a surface friction term and surface pressure terms. The latter are a function of the difference between the ocean elevation and the vertical displacement of the shell and the time derivative of this difference. Because of Titan’s appreciable obliquity (0.306°), the tidal motion expected (and found) is similar to the Europa tidal scenario described by Tyler (2008): the surface elevation consists of two bulges rotating around Titan and the associated depth-averaged velocity field consists of two gyres, separated by an area of high speed flow, whose centre follows a sinusoidal path centred on the equator. The ice shell damps the surface motion, thus slowing down the flow, without significantly modifying the spatial patterns of these fields. The depth of the ocean and the mechanical characteristics of the ice shell being poorly constrained, a sensitivity analysis is conducted. The depth-averaged flow slows down when the depth is increased and a lag appears in the tidal phase but the tidal range remains similar. The ice shell mechanical characteristics influences both the elevation and depth-averaged velocity fields in terms of magnitude but does not modify the spatial patterns of these fields. The influence of the surface heat flux is studied by means of the 3D baroclinic version of SLIM. The heat flux derived from Titan’s topography by Kvorka et al. (2018) is used as surface boundary condition for the temperature equation while a uniform bottom heat flux is implemented. Its value is computed assuming that the heat budget of the ocean is at equilibrium. These boundary conditions cause density variations, which impact the hydrodynamics of the ocean. While the flow velocity induced by these variations is two orders of magnitude smaller than the tidal flow, its orientation is time-independent, hence impacting the orientation of the velocity field. Although the variations of ocean surface elevation and speed with respect to the shell mechanical properties can be larger than those induced by the surface heat flux, taking into account the latter results in large variations of the velocity field global patterns, which was not observed when modifying the shell mechanical properties. Future studies should therefore focus on modelling the surface and bottom heat fluxes while uncertainties about the mechanical characteristics of the shell can be tolerated.

Titan↗

DOE OSTI2024

Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion

In system prognostics and health management, multivariable degradation models have been widely developed to predict the life of complex systems using degradation data of multiple Performance Characteristics (PCs). Recent studies have detected a Long-Term Memory (LTM) effect among the degradation process of various PCs, implying a strong coupling phenomenon between the future degradation behavior and historical degradation trajectory. Although the LTM has been widely integrated into single-PC-based degradation modeling, it has not been considered in multi-PC-based scenarios. To capture LTM among multiple PCs, this article proposes a novel LTM-integrated Multivariate Degradation Model (MDM) for system life prediction based on multivariate fractional Brownian motion, which simultaneously incorporates the cross-correlation among different PCs. To estimate parameters of the LTM-integrated MDM, a maximum likelihood method is developed. Here, two likelihood-ratio hypothesis tests are developed to test the existence of the overall and individual LTM effect among multiple PCs. Both simulation studies and physical experiments on the performance degradation of solar energy conversion and storage devices are conducted to validate the proposed model. Results reveal that the proposed LTM-integrated MDM significantly outperforms existing MDMs in life prediction, while the lifetime uncertainty is heavily underestimated by those traditional approaches that neglect the LTM.

42 ENGINEERING↗

NASA NTRS2005

Safety Ellipse Motion with Coarse Sun Angle Optimization

The Hubble Space Telescope Robotic Servicing and De-orbit Mission (HRSDM) was t o be performed by the unmanned Hubble Robotic Vehicle (HRV) consisting of a Deorbit Module (DM), responsible for the ultimate disposal of Hubble Space Telescope (HST) at the end of science operations, and an Ejection Module (EM), responsible for robotically servicing the HST to extend its useful operational lifetime. HRSDM consisted of eight distinct phases, including: launch, pursuit, proximity operations, capture, servicing, EM jettison and disposal, science operations, and deorbit. The scope of this paper is limited to the Proximity Operations phase of HRSDM. It introduces a relative motion strategy useful for Autonomous Rendezvous and Docking (AR&D) or Formation Flying missions where safe circumnavigation trajectories, or close proximity operations (tens or hundreds of meters) are required for extended periods of time. Parameters and algorithms used to model the relative motion of HRV with respect to HST during the Proximity Operations phase of the HRSDM are described. Specifically, the Safety Ellipse (SE) concept, convenient parameters for describing SE motion, and a concept for initializing SE motion around a target vehicle to coarsely optimize sun and relative navigation sensor angles are presented. The effects of solar incidence angle variations on sun angle optimization, and the effects of orbital perturbations and navigation uncertainty on long term SE motion are discussed.

Naasz, Bo↗

DOE OSTI2024

Performance evaluation of the USGS velocity model for the San Francisco Bay Area

In this study, we evaluated the performance of the United States Geological Survey velocity model developed for the San Francisco Bay Area (SFBA), version 21.1. The evaluation was performed through high-resolution three-dimensional physics-based ground motion simulations of seven small-magnitude earthquakes (ranging from magnitude 3.8 to 4.4) that occurred on the eastern side of the San Francisco Bay. The simulations were performed in the frequency range from 0 to 5 Hz with a minimum shear-wave velocity of 250 m/s, which allowed the capture of wave propagation effects of the near-surface soft materials that characterize local basins. Based on the direct comparison of Fourier amplitude spectra between recorded and simulated ground motions for more than 250 stations, we found that the velocity model generally performs well in the frequency range of 0.2–5 Hz. The median value of the Fourier amplitude residuals was found to be near zero for all seven earthquakes. The slight over-prediction of 0.2 log-natural units at frequencies above 3 Hz in our simulations was attributed to the potentially inaccurate representation of the source radiation pattern by a double-couple point source model, and simple representation of shallow small-scale underground structural complexity in the velocity model. Maps of spectral amplitude differences between the simulated and recorded data were used to identify areas responsible for systematic ground motion over-predictions or under-predictions. For example, while some sub-domains over soft sediments show over-prediction patterns, the block east of the Hayward fault is prone to exhibit patterns of under-prediction. These maps can be used to guide future refinements of the SFBA velocity model. Since our simulation methodology allows for the decoupling of the source and wave propagation effects, the ground motion data generated by our simulations can also be used to quantify the epistemic uncertainty due to the velocity model, in empirically based ground motion estimates for the SFBA.

58 GEOSCIENCES↗

DOE OSTI2025

Simulation and generalized Langevin equation study of lipid subdiffusion in biomembrane phases

In biomembranes lipid mobility exhibits deviations from the classical diffusive behavior of Brownian particles, i.e. ‘anomalous’ diffusion. The question arises as to how this anomalous diffusive behavior varies in gel, ripple, and fluid biomembrane phases. Here, in this study, we perform all-atom molecular dynamics (MD) simulations of dimyristoylphosphatidylcholine (DMPC) bilayers in the three different phases and analyze the results using the framework of the Generalized Langevin Equation (GLE). This analysis emphasizes sub-diffusive behavior on the relatively short, picosecond-nanosecond timescales, capturing local molecular constraints and transient caging effects during the crossover of atomic dynamics from vibrational to incipient anharmonic motion. The ripple and gel phases are found to exhibit strong transient caging and prolonged memory effects resulting in distinct sub-diffusive behavior. The role of hydrogen bonding in lipid confinement is also examined, demonstrating its influence on phase-dependent molecular ordering and on short-time diffusional constraints. These findings demonstrate the GLE framework’s utility in characterizing molecular transport and lipid dynamics, with implications for longer timescale membrane dynamics.

Malik, Sheeba [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2026

Quantum effects on the dynamics and properties of soft materials

The quantum effects of nuclear and electronic motion play an important role in the structure, dynamics, and function of soft materials, yet they are difficult to capture with conventional classical simulations or static electronic–structure methods. In this work several complementary approaches for treating quantum effects in polymeric and soft–matter systems are demonstrated, with a focus being on the hydrogen-bonded networks, ion and charge transport, and photoactive chromophores. The proton transfer, tunneling, and isotope effects are captured within the reduced-dimensionality models by implementing grid-based nuclear quantum dynamics in terms of the discrete variable and Fourier bases. The nuclear quantum dynamics is extended to larger systems by employing the quantum trajectories and quantum–thermal bath schemes combined with on-the-fly electronic structure, enabling the description of high-dimensional polymeric environments at feasible cost. The dynamics in the electronic degrees of freedom, simulating the optical response in large chromophores such as chlorophylls, is performed using the real-time time-dependent density functional theory implemented in the real-space multigrid (RMG) code. These approaches are demonstrated on case studies of the proton and hydroxide transport in hydrated polymer membranes, charge transfer in conjugated polymers, and the optical spectra of chlorophyll chromophores relevant to polymerized chlorophyll materials and chlorophyll–polymer hybrids. The reviewed methods and applications highlight practical routes of including quantum effects in simulations of soft functional materials.

Garashchuk, Sophya [Univ. of South Carolina, Colum↗

NASA NTRS2013

Overview of the Aeroelastic Prediction Workshop

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. This workshop's technical focus was prediction of unsteady pressure distributions resulting from forced motion, benchmarking the results first using unforced system data. The most challenging aspects of the physics were identified as capturing oscillatory shock behavior, dynamic shock-induced separated flow and tunnel wall boundary layer influences. The majority of the participants used unsteady Reynolds-averaged Navier Stokes codes. These codes were exercised at transonic Mach numbers for three configurations and comparisons were made with existing experimental data. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include wall effects and wall modeling, non-standardized convergence criteria, inclusion of static aeroelastic deflection, methodology for oscillatory solutions, post-processing methods. Contributing issues pertaining principally to the experimental data sets include the position of the model relative to the tunnel wall, splitter plate size, wind tunnel expansion slot configuration, spacing and location of pressure instrumentation, and data processing methods.

Heeg, Jennifer↗

DOE OSTI2026

Learning earthquake ground motions via conditional generative modeling

Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake locations, while physics-based methods are computationally intensive and require accurate representations of Earth structures and earthquake sources. We propose an artificial intelligence (AI) spectrogram generator, Conditional Generative Modeling for Ground Motion (CGM-GM). CGM-GM leverages earthquake magnitudes and geographic coordinates of earthquakes and sensors as inputs, when postprocessed with phase information, capturing spatially continuous Fourier amplitude spectra (FAS) as well as properties such as P and S arrivals, and waveform durations, without explicit physics constraints. This is achieved through a probabilistic autoencoder that extracts latent distributions in the time-frequency domain and variational sequential models for prior and posterior distributions. We evaluate the performance of CGM-GM using small-magnitude earthquake records from the San Francisco Bay Area, a region with high seismic risks. Here, we report that CGM-GM demonstrates potential for complementing physics-based simulations and non-ergodic empirical ground motion models, as well as shows promise in seismology and beyond.

geophysics↗