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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 343 records · Page 19

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗

Scenario Development Process at the Vertical Motion Simulator

There has been a significant effort within the simulation community to standardize many aspects of flight simulation. More recently, an effort has begun to develop a formal scenario definition language for aviation. A working group within the AIAA Modeling and Simulation Technical Committee has been created to develop a standard aviation scenario definition language, though much of the initial effort has been tailored to training simulators. Research and development (R&D) simulators, like the Vertical Motion Simulator (VMS), and training simulators have different missions and thus have different scenario requirements. The purpose of this paper is to highlight some of the unique tasks and scenario elements used at the VMS so they may be captured by scenario standardization efforts. The VMS most often performs handling qualities studies and transfer of training studies. Three representative handling qualities simulation studies and two transfer of training simulation studies are described in this paper. Unique scenario elements discussed in this paper included special out-the-window (OTW) targets and environmental conditions, motion system parameters, active inceptor parameters, and configurable vehicle math model parameters.

Vertical Motion Simulator↗

Spacecraft Solar Sails Containing Electrodynamic Tethers

A report discusses a proposal to use large, lightweight solar sails embedded with electrodynamic tethers (essentially, networks of wires) to (1) propel robotic spacecraft to distant planets, then (2) exploit the planetary magnetic fields to capture the spacecraft into orbits around the planets. The purpose of the proposal is, of course, to make it possible to undertake long interplanetary missions without incurring the large cost and weight penalties of conventional rocket-type propulsion systems. Through transfer of momentum from reflected solar photons, a sail would generate thrust outward from the Sun. Upon arrival in the vicinity of a planet, the electrodynamic tethers would be put to use: Motion of the spacecraft across the planetary magnetic field would induce electric currents in the tether wires, giving rise to an electromagnetic drag force that would be exploited to brake the spacecraft for capture into orbit. The sail with embedded tethers would be made to spin to provide stability during capture. Depending upon the requirements of a particular application, it could be necessary to extend the tether to a diameter greater than that of the sail.

Johnson, Les↗

Simulation of the turbulent Rayleigh-Benard problem using a spectral/finite difference technique

The three-dimensional, incompressible Navier-Stokes and energy equations with the Bousinesq assumption have been directly simulated at a Rayleigh number of 3.8 x 10 to the 5th power and a Prandtl number of 0.76. In the vertical direction, wall boundaries were used and in the horizontal, periodic boundary conditions were used. A spectral/finite difference numerical method was used to simulate the flow. The flow at these conditions is turbulent and a sufficiently fine mesh was used to capture all relevant flow scales. The results of the simulation are compared to experimental data to justify the conclusion that the small scale motion is adequately resolved.

Eidson, T. M.↗

Substrate-Mediated Evaporation and Stochastic Evolution of Supported Au Nanoparticles

Here, we use in situ transmission electron microscopy with automated tracking to study supported gold nanoparticles (NPs) during high-temperature vacuum annealing. The average mass loss per NP is governed by a flat, nearly size-independent substrate-mediated evaporation profile. On top of this mean shrinkage, individual NPs show significant fluctuations in apparent growth or shrinkage, and NP volume follows a random-walk-like trajectory. To rationalize both the ensemble-mean behavior and the particle-resolved variability, we develop a self-consistent theory that couples substrate-mediated evaporation to collective 2D Ostwald-type mass exchange through a shared adatom field, described in terms of a renormalized screening length and background concentration. In the experimentally relevant regime, the theory predicts an approximately size-independent mean shrinkage rate and clarifies how net mass loss suppresses classical coarsening. Superimposed on this deterministic drift, we quantify stochastic volume trajectories and capture their fluctuation spectrum with a minimal Langevin description consistent with intermittent adatom attachment and detachment events. In addition, we characterize the lateral diffusive motion of NPs, which is responsible for their coalescence. Altogether, our results highlight that stochasticity is intrinsic at the nanoscale and that predicting the evolution of supported NPs at early and intermediate times requires a unified framework combining substrate-mediated evaporation, collective mass exchange, and stochastic fluctuations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Simulation of decelerating landing approaches on an externally blown flap STOL transport airplane

A fixed-base simulator program was conducted to define the problems and methods for solution associated with performing decelerating landing approaches on a representative STOL transport having a high wing and equipped with an external-flow jet flap in combination with four high-bypass-ratio fan-jet engines. Real-time digital simulation techniques were used. The computer was programed with equations of motion for six degrees of freedom and the aerodynamic inputs were based on measured wind-tunnel data. The pilot's task was to capture the localizer and the glide slope and to maintain them as closely as possible while decelerating from an initial airspeed of 140 knots to a final airspeed of 75 knots, while under IFR conditions.

Grantham, W. D.↗

Microgravity-Driven Optic Nerve/Sheath Biomechanics Simulations

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a concern for long-duration space flight. Current thinking suggests that the ocular changes observed in VIIP syndrome are related to cephalad fluid shifts resulting in altered fluid pressures [1]. In particular, we hypothesize that increased intracranial pressure (ICP) drives connective tissue remodeling of the posterior eye and optic nerve sheath (ONS). We describe here finite element (FE) modeling designed to understand how altered pressures, particularly altered ICP, affect the tissues of the posterior eye and optic nerve sheath (ONS) in VIIP. METHODS: Additional description of the modeling methodology is provided in the companion IWS abstract by Feola et al. In brief, a geometric model of the posterior eye and optic nerve, including the ONS, was created and the effects of fluid pressures on tissue deformations were simulated. We considered three ICP scenarios: an elevated ICP assumed to occur in chronic microgravity, and ICP in the upright and supine positions on earth. Within each scenario we used Latin hypercube sampling (LHS) to consider a range of ICPs, ONH tissue mechanical properties, intraocular pressures (IOPs) and mean arterial pressures (MAPs). The outcome measures were biomechanical strains in the lamina cribrosa, optic nerve and retina; here we focus on peak values of these strains, since elevated strain alters cell phenotype and induce tissue remodeling. In 3D, the strain field can be decomposed into three orthogonal components, denoted as first, second and third principal strains. RESULTS AND CONCLUSIONS: For baseline material properties, increasing ICP from 0 to 20 mmHg significantly changed strains within the posterior eye and ONS (Fig. 1), indicating that elevated ICP affects ocular tissue biomechanics. Notably, strains in the lamina cribrosa and retina became less extreme as ICP increased; however, within the optic nerve, the occurrence of such extreme strains greatly increased as ICP was elevated (Fig. 2). In particular, c. 48 of simulations in the elevated ICP condition showed peak strains in the optic nerve that exceeded the strains expected on earth. Such extreme strains are likely important, since they represent a larger signal for mechano-responsive resident cells [2]. The models predicted little to no anterior motion of the prelaminar neural tissue (optic nerve swelling, or papilledema, secondary to axoplasmic stasis), typically seen with elevated ICP. Specialized FE models to capture axoplasmic stasis would be required to study papilledema. These results suggest that the most notable effect of elevated ICP may occur via direct optic nerve loading, rather than through connective tissue deformation. These FE models can inform the design of future studies designed to bridge the gap between biomechanics and pathophysiological function in VIIP.

biomechanics↗

To the Moon! Space Launch System Modal Testing with Video and Motion Magnification

MIT Lincoln Laboratory and NASA Marshall Space Flight Center have been collaborating on using video camera measurements and motion magnification for modal testing of large aerospace components for several years. This presentation will discuss results from the Space Launch System Integrated Modal Test (IMT) and Dynamic Rollout/Rollback Test (DRRT) in support of the Artemis I mission. During the IMT, the data collection focused on operational mode shapes. In addition, the cameras were repositioned mid-test to better understand the physics of a low-frequency torsion mode. The non-contact nature of video data capture allowed for the quick redeployment of the cameras while not causing any delay in test schedule, whereas traditional instrumentation would have required a pause in testing to attach the sensors to the test article. The motion magnification analysis was able to find the low-frequency operational mode shapes and help the test team better understand the physics of the torsion mode. Building upon the success of the IMT motion magnification work, a camera system was used during the DRRT to find operational mode shapes, if the physics of the low-frequency torsion mode remained with different boundary conditions, and relative deflection of the vehicle and ML tower during the roll. In this paper we will present operational mode shape results, discuss the physics of the torsion mode, and review experimental setup idiosyncrasies to help the community in designing video camera measurement systems.

optical↗

Dynamical eigenfunction decomposition of turbulent channel flow

The results of an analysis of low-Reynolds-number turbulent channel flow based on the Karhunen-Loeve (K-L) expansion are presented. The turbulent flow field is generated by a direct numerical simulation of the Navier-Stokes equations at a Reynolds number Re(tau) = 80 (based on the wall shear velocity and channel half-width). The K-L procedure is then applied to determine the eigenvalues and eigenfunctions for this flow. The random coefficients of the K-L expansion are subsequently found by projecting the numerical flow field onto these eigenfunctions. The resulting expansion captures 90 percent of the turbulent energy with significantly fewer modes than the original trigonometric expansion. The eigenfunctions, which appear either as rolls or shearing motions, possess viscous boundary layers at the walls and are much richer in harmonics than the original basis functions.

Ball, K. S.↗

Freestream capturing for moving coordinates in three dimensions

A detailed formula is developed that can be used in both finite-volume (FV) and finite-difference (FD) methods for constructing freestream capturing metrics in space and time. It is shown that, considering an FV cell on the FD grid, the freestream capturing metrics in space and time can be constructed from the FD formulation. The approach is costly but guarantees the global conservation for an arbitrary motion of the grid.

Obayashi, Shigeru↗

Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations

New numerical algorithms are devised (PSC algorithms) for following fronts propagating with curvature-dependent speed. The speed may be an arbitrary function of curvature, and the front can also be passively advected by an underlying flow. These algorithms approximate the equations of motion, which resemble Hamilton-Jacobi equations with parabolic right-hand-sides, by using techniques from the hyperbolic conservation laws. Non-oscillatory schemes of various orders of accuracy are used to solve the equations, providing methods that accurately capture the formation of sharp gradients and cusps in the moving fronts. The algorithms handle topological merging and breaking naturally, work in any number of space dimensions, and do not require that the moving surface be written as a function. The methods can be used also for more general Hamilton-Jacobi-type problems. The algorithms are demonstrated by computing the solution to a variety of surface motion problems.

Osher, Stanley↗

Asymptotic-preserving gyrokinetic implicit particle-orbit integrator for arbitrary electromagnetic fields

We extend the asymptotic preserving and energy conserving time integrator for charged-particle motion developed in Ricketson and Chacón (2020) to include finite Larmor-radius (FLR) effects in the presence of electric-field length-scales comparable to the particle gyro-radius (the gyro-kinetic limit). We introduce two modifications to the earlier scheme. The first is the explicit gyro-averaging of the electric field at the half time-step, along with an analogous modification to the current deposition, which we show preserves total energy conservation in implicit PIC schemes. The number of gyrophase samples is chosen adaptively, ensuring proper averaging for large timesteps and the recovery of full-orbit dynamics in the small time-step limit. The second modification is an alternating large and small time-step strategy that ensures the particle trajectory samples gyrophases evenly. We show that this strategy relaxes the time-step restrictions on the scheme, allowing even larger speed-ups than previously achievable. We demonstrate the new method with several single-particle motion tests in a variety of electromagnetic field configurations featuring gyro-scale variation in the electric field. Finally, the results demonstrate the advertised ability to capture FLR effects accurately even when significantly stepping over the gyration time-scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring Li-Ion Transport Properties of Li 3 TiCl 6 : A Machine Learning Molecular Dynamics Study

We performed large-scale molecular dynamics simulations based on a machine-learning force field (MLFF) to investigate the Li-ion transport mechanism in cation-disordered Li 3 TiCl 6 cathode at six different temperatures, ranging from 25°C to 100°C. In this work, deep neural network method and data generated by ab − initio molecular dynamics (AIMD) simulations were deployed to build a high-fidelity MLFF. Radial distribution functions, Li-ion mean square displacements (MSD), diffusion coefficients, ionic conductivity, activation energy, and crystallographic direction-dependent migration barriers were calculated and compared with corresponding AIMD and experimental data to benchmark the accuracy of the MLFF. From MSD analysis, we captured both the self and distinct parts of Li-ion dynamics. The latter reveals that the Li-ions are involved in anti-correlation motion that was rarely reported for solid-state materials. Similarly, the self and distinct parts of Li-ion dynamics were used to determine Haven’s ratio to describe the Li-ion transport mechanism in Li 3 TiCl 6 . Obtained trajectory from molecular dynamics infers that the Li-ion transportation is mainly through interstitial hopping which was confirmed by intra- and inter-layer Li-ion displacement with respect to simulation time. Ionic conductivity (1.06 mS/cm) and activation energy (0.29eV) calculated by our simulation are highly comparable with that of experimental values. Overall, the combination of machine-learning methods and AIMD simulations explains the intricate electrochemical properties of the Li 3 TiCl 6 cathode with remarkably reduced computational time. Thus, our work strongly suggests that the deep neural network-based MLFF could be a promising method for large-scale complex materials.

Selvaraj, Selva Chandrasekaran (ORCID:000000029023↗

Motion Imagery and Robotics Application (MIRA): Standards-Based Robotics

This technology development originated from the need to assess the debris threat resulting from soil material erosion induced by landing spacecraft rocket plume impingement on extraterrestrial planetary surfaces. The impact of soil debris was observed to be highly detrimental during NASA s Apollo lunar missions and will pose a threat for any future landings on the Moon, Mars, and other exploration targets. The innovation developed under this program provides a simulation tool that combines modeling of the diverse disciplines of rocket plume impingement gas dynamics, granular soil material liberation, and soil debris particle kinetics into one unified simulation system. The Unified Flow Solver (UFS) developed by CFDRC enabled the efficient, seamless simulation of mixed continuum and rarefied rocket plume flow utilizing a novel direct numerical simulation technique of the Boltzmann gas dynamics equation. The characteristics of the soil granular material response and modeling of the erosion and liberation processes were enabled through novel first principle-based granular mechanics models developed by the University of Florida specifically for the highly irregularly shaped and cohesive lunar regolith material. These tools were integrated into a unique simulation system that accounts for all relevant physics aspects: (1) Modeling of spacecraft rocket plume impingement flow under lunar vacuum environment resulting in a mixed continuum and rarefied flow; (2) Modeling of lunar soil characteristics to capture soil-specific effects of particle size and shape composition, soil layer cohesion and granular flow physics; and (3) Accurate tracking of soil-borne debris particles beginning with aerodynamically driven motion inside the plume to purely ballistic motion in lunar far field conditions.

Martinez, Lindolfo↗

Imaging of dynamic processes in materials with a laser-wakefield accelerator

Betatron x rays generated from laser-wakefield accelerators are a promising source for imaging dynamic processes in materials. Here, we present proof-of-concept imaging of microstructural evolution in a hypermonotectic Al-Bi alloy, which consists of liquid Bi particles in a solid Al matrix. The images capture the elongation and fragmentation of Bi particles upon isothermal annealing. Because of the femtosecond time scale of the betatron source, the images are not subject to motion blur, whereas the accessibility of the source allows for studies of long-term processes such as annealing. The high-resolution data reveal that the evolution of Bi particles is mediated by an interplay of grain-boundary wetting and morphological instability, in stark contrast to an earlier proposal for (inverse) coarsening.

Alloys↗

Passive three-axis stabilization of the Long Duration Exposure Facility

This paper presents an analysis of the attitude dynamics of the Long Duration Exposure Facility (LDEF). LDEF is a large cylindrical gravity gradient stabilized earth satellite which is planned to be delivered to a 270-n mi circular orbit by the space shuttle. The fundamental linear stability, capture requirements, and pitch bias constraints generated by the Garber instability are discussed. Numerical simulations, based on the full nonlinear equations for the coupled orbital and attitude motion of the vehicle and the viscous magnetic damper, show stable behavior of the spacecraft and a damping time constant of 30 to 70 orbits.

Huckins, E. K., III↗

Free-wake computation of helicopter rotor flowfields in forward flight

A new method has been developed for computing advancing rotor flows. This method uses the Vorticity Embedding technique, which has been developed and validated over the last several years for hovering rotor problems. In this work, the unsteady full potential equation is solved on an Eulerian grid with an embedded vortical velocity field. This vortical velocity accounts for the influence of the wake. Dynamic grid changes that are required to accommodate prescribed blade motion and deformation are included using a novel grid blending method. Free wake computations have been performed on a two-bladed AH-1G rotor at low advance ratios including blade motion. Computed results are compared with experimental data. The sudden variations in airloads due to blade-vortex interactions on the advancing and retreating sides are well captured. The sensitivity of the computed solution to various factors like core size, time step and grids has been investigated. Computed wake geometries and their influence on the aerodynamic loads at these advance ratios are also discussed.

Ramachandran, K.↗

Recurrent convolutional neural networks for modeling nonadiabatic dynamics of quantum-classical systems

Recurrent neural networks (RNNs) have recently been extensively applied to model the time evolution in fluid dynamics, weather predictions, and even chaotic systems due to their ability to capture temporal dependencies and sequential patterns in data. Here we present an RNN model based on convolutional neural networks for modeling the nonlinear nonadiabatic dynamics of hybrid quantum-classical systems. The dynamical evolution of the hybrid systems is governed by equations of motion for classical degrees of freedom and von Neumann equation for electrons. The Physics-Aware Recurrent Convolution (PARC) neural network structure incorporates a differentiator-integrator architecture that inductively models the spatiotemporal dynamics of generic physical systems. Here, we apply our RNN approach to learn the space-time evolution of a one-dimensional semiclassical Holstein model after an interaction quench. For shallow quenches (small changes in electron-lattice coupling), the deterministic dynamics can be accurately captured using a single-CNN-based recurrent network. In contrast, deep quenches induce chaotic evolution, making long-term trajectory prediction significantly more challenging. Nonetheless, we demonstrate that the PARC-CNN architecture can effectively learn the statistical climate of the Holstein model under deep-quench conditions.

Holstein model↗