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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Sampling Microbial Dynamics in the Salish Sea Estuary: Evaluating Methods to Capture Cyanobacteria and Cyanophage

Introduction: Picocyanobacteria from the genera Prochlorococcus and Synechococcus thrive across the globe in aquatic environments, have relatively small genomes, and have growth dynamics regulated by both viral interactions and abiotic conditions, making them excellent model organisms for exploring host-pathogencoevolution. Methods: We developed and refined methods to sample and sequence cyanobacteria, cyanophages, and measured features of their abiotic environment. Results: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons. Our preferred final protocol from this exploratory effort included a combination of in-line and single vacuum flask filtrations, which reduced filtration processing time by over threefold in some cases compared to other tested methods, such as a fully in-line sequence or in-site filtrations. We successfully extracted an average of approximately 400–1200 ng for all filter fractions, with some variations between kits. Discussion: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons.

Salish Sea↗
NASA NTRS2020

Analysis of Sample Acquisition Dynamics Using Discrete Element Method

The analysis presented in this paper is conducted in the framework of the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) project, currently under development at NASA Ames Research Center. OceanWATERS aims at designing a simulation environment which allows for testing autonomy of scientific lander missions to the icy moons of our solar system. Mainly focused on reproducing the end effector interaction with the inherent terrain, this paper introduces a novel discrete element method (DEM)-based approach to determine forces and torques acting on the lander’s scoop during the sample acquisition process. An accurate force feedback from the terrain on the scoop is required by fault-detection and autonomous decision-making algorithms to identify when the requested torque on the robotic arm’s joints exceeds the maximum available torque. Knowledge of the terrain force feedback significantly helps evaluating the arm’s links structural properties and properly selecting actuators for the joints. Models available in literature constitute a partial representation of the dynamics of the interaction. As an example, Balovnev derived an analytical expression of the vertical and horizontal force acting on a bucket while collecting a sample as a function of its geometry and velocity, soil parameters and reached depth. Although the model represents an adequate approximation of the two force components, it ignores the direction orthogonal to the scoop motion and neglects the torque. This work relies on DEM analysis to compensate for analytical models’ deficiencies and inaccuracies, i. e. provide force and torque 3D vectors, defined in the moving reference (body) frame attached to the scoop, at each instant of the sample collection process. Results from the first presented analysis relate to the specific OceanWATERS sampling strategy, which consists of collecting the sample through five consecutive passes with increasing depth, each pass following the same circularlinear- circular trajectory. Data is collected given a specific scoop design interacting with two types of bulk materials, which may characterize the surface of icy planetary bodies: snow and ice. Although specifically concerned with the OceanWATERS design, this first analysis provides the expected force trends for similar sampling strategies and allows to deduce phenomenological information about the general scooping process. In order to further instruct the community on the use of DEM tools as a solution to the sampling collection problem, two more analyses have been carried out, mainly focused on reducing the DEM computation time, which increases with a decrease in particle size. After running a set of identical simulations, where the only changing parameter is the size of the spherical particle, it is observed that the resulting force trajectories, starting from a given particle size, converge to the true trend. It is deducible that a further decrease in size yields negligible improvements in the accuracy, while it sensibly increases computation time. A final analysis aims at discussing limitations of approximating bulk material particles having a complex shape, e. g. ice fragments, with spheres, by comparing force trends resulting in the two cases for the same simulation scenario.

Catanoso, Damiana↗
NASA NTRS2006

Small Body GN and C Research Report: G-SAMPLE - An In-Flight Dynamical Method for Identifying Sample Mass [External Release Version]

G-SAMPLE is an in-flight dynamical method for use by sample collection missions to identify the presence and quantity of collected sample material. The G-SAMPLE method implements a maximum-likelihood estimator to identify the collected sample mass, based on onboard force sensor measurements, thruster firings, and a dynamics model of the spacecraft. With G-SAMPLE, sample mass identification becomes a computation rather than an extra hardware requirement; the added cost of cameras or other sensors for sample mass detection is avoided. Realistic simulation examples are provided for a spacecraft configuration with a sample collection device mounted on the end of an extended boom. In one representative example, a 1000 gram sample mass is estimated to within 110 grams (95% confidence) under realistic assumptions of thruster profile error, spacecraft parameter uncertainty, and sensor noise. For convenience to future mission design, an overall sample-mass estimation error budget is developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

in-flight sample-mass identification↗
NASA NTRS1997

Subsonic Dynamics of Stardust Sample Return Capsule

Subsonic dynamic stability tests performed in the NASA Langley 20-Foot Vertical Spin-Tunnel on a 0.238 scale model of the Stardust Sample Return Capsule are discussed. The tests reveal that the blunted 60 degree half-angle cone capsule is dynamically unstable at low subsonic conditions due to the aft location of the center-of-gravity (0.351 body diameters back from the nose). The divergent behavior of the capsule continued when the center-of-gravity was moved to 0.337 and 0.313 body diameters back from the nose. When the center-of-gravity was moved further forward to 0.290 body diameters back from the nose, the vehicle established itself in a limit cycle with amplitude around 10 degrees. Two afterbody modifications were examined which proved unsuccessful in alleviating the instability of the original design. Finally, the addition of different sized parachutes was examined as a means to stabilize the vehicle. The parachute tests indicate that a parachute with equivalent full scale drag area of at least 2.24 ft. is necessary to assure large perturbations are damped.

Mitcheltree, Robert A.↗
DOE OSTI2018

Quantitative Mapping of Nanoscale Chemical Dynamics in Sub-sampled Operando (S)TEM Images Using Spatio-Temporal Analytics

One of the main limitations in the use of operando scanning transmission electron microscopes to study dynamic chemical processes is the effect of the electron beam on the kinetics of the reaction being observed. Here we demonstrate that a flexible Gaussian mixture model can be used to extract quantitative information directly from sub-sampled images, i.e.~images where not all the pixels in the image are illuminated with the beam. The use of this method is demonstrated for the charge/discharge cycle of a Li-battery, where the deposition and dissolution of Li at the anode can be accurately quantified for sub-sampling levels down to 1%. Performing operando imaging using a small fraction of the pixels means that the observations can significantly reduce the effect of the beam, automatically increase the imaging speed and decrease the total data transfer rate required. Such new software capabilities offer the potential to significantly widen the application of operando hardware approaches to study nanoscale dynamics in materials.

Stanfill, Bryan A.↗
DOE OSTI2021

Efficient Sampling Allocation Procedures for Optimal Quantile Selection

We propose a dynamic sampling allocation and selection paradigm for finding the alternative with the optimal quantile in a Bayesian framework. Myopic allocation policies (MAPs), analogous to existing methods in classic ranking and selection for selecting the alternative with the optimal mean, and computationally efficient selection policies are derived for selecting the alternative with the optimal quantile. Under certain conditions, we prove that the proposed MAPs and selection procedures are consistent, which means that the best quantile would be eventually correctly selected as the sample size goes to infinity. Numerical experiments demonstrate that the proposed schemes can significantly improve the performance.

Computer Science↗
DOE OSTI2021

Ab initio molecular dynamics with enhanced sampling in heterogeneous catalysis

Ab initio molecular dynamics simulations combined with enhanced sampling techniques are becoming widespread methods to investigate chemical phenomena in catalytic systems. These techniques automatically include finite temperature effects, anharmonicity, and collective dynamics in their robust description of enthalpic and entropic contributions, which can have significant impact on reaction free energy landscapes. This contrasts with standard ab initio static approaches that are based on assessing reaction free energies from various coarse-grained descriptions of the reaction potential energy surface. Enhanced sampling ab initio molecular dynamics opens the way to first principles simulations of systems of increasing complexity like solid/liquid catalytic interfaces. Here, we aim at guiding the reader through the basis of these techniques, summarizing their fundamental theoretical and practical aspects, and reviewing the relevant literature in the field. After a brief introduction to the problem, we will illustrate the advantage of using molecular simulations to include finite temperature effects, examine the most common ab initio techniques currently in use, describe their application to solid state heterogeneous catalysts, and finally critically review the most popular enhanced sampling techniques used in computational catalysis.

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

Nonlinear Dynamics of Cantilever-Sample Interactions in Atomic Force Microscopy

The interaction of the cantilever tip of an atomic force microscope (AFM) with the sample surface is obtained by treating the cantilever and sample as independent systems coupled by a nonlinear force acting between the cantilever tip and a volume element of the sample surface. The volume element is subjected to a restoring force from the remainder of the sample that provides dynamical equilibrium for the combined systems. The model accounts for the positions on the cantilever of the cantilever tip, laser probe, and excitation force (if any) via a basis set of set of orthogonal functions that may be generalized to account for arbitrary cantilever shapes. The basis set is extended to include nonlinear cantilever modes. The model leads to a pair of coupled nonlinear differential equations that are solved analytically using a matrix iteration procedure. The effects of oscillatory excitation forces applied either to the cantilever or to the sample surface (or to both) are obtained from the solution set and applied to the to the assessment of phase and amplitude signals generated by various acoustic-atomic force microscope (A-AFM) modalities. The influence of bistable cantilever modes of on AFM signal generation is discussed. The effects on the cantilever-sample surface dynamics of subsurface features embedded in the sample that are perturbed by surface-generated oscillatory excitation forces and carried to the cantilever via wave propagation are accounted by the Bolef-Miller propagating wave model. Expressions pertaining to signal generation and image contrast in A-AFM are obtained and applied to amplitude modulation (intermittent contact) atomic force microscopy and resonant difference-frequency atomic force ultrasonic microscopy (RDF-AFUM). The influence of phase accumulation in A-AFM on image contrast is discussed, as is the effect of hard contact and maximum nonlinearity regimes of A-AFM operation.

Cantrell, John H.↗
DOE OSTI2022

Sub-10 second fly-scan nano-tomography using machine learning

Abstract X-ray computed tomography is a versatile technique for 3D structure characterization. However, conventional reconstruction algorithms require that the sample not change throughout the scan, and the timescale of sample dynamics must be longer than the data acquisition time to fulfill the stable sample requirement. Meanwhile, concerns about X-ray-induced parasite reaction and sample damage have driven research efforts to reduce beam dosage. Here, we report a machine-learning-based image processing method that can significantly reduce data acquisition time and X-ray dose, outperforming conventional approaches like Filtered-Back Projection, maximum-likelihood, and model-based maximum-a-posteriori probability. Applying machine learning, we achieve ultrafast nano-tomography with sub-10 second data acquisition time and sub-50 nm pixel resolution in a transmission X-ray microscope. We apply our algorithm to study dynamic morphology changes in a lithium-ion battery cathode under a heating rate of 50 o C min −1 , revealing crack self-healing during thermal annealing. The proposed method can be applied to various tomography modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Validating the Use of Gaussian Process Regression for Adaptive Mapping of Residual Stress Fields

Probing the stress state using a high density of measurement points is time intensive and presents a limitation for what is experimentally feasible. Alternatively, individual strain fields used for determining stresses can be reconstructed from a subset of points using a Gaussian process regression (GPR). Results presented in this paper evidence that determining stresses from reconstructed strain fields is a viable approach for reducing the number of measurements needed to fully sample a component’s stress state. The approach was demonstrated by reconstructing the stress fields in wire-arc additively manufactured walls fabricated using either a mild steel or low-temperature transition feedstock. Effects of errors in individual GP reconstructed strain maps and how these errors propagate to the final stress maps were assessed. Implications of the initial sampling approach and how localized strains affect convergence are explored to give guidance on how best to implement a dynamic sampling experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗
NASA NTRS1994

Multi-Flight-Phase GPS Navigation Filter Applications to Terrestrial Vehicle Navigation and Positioning

A candidate onboard space navigation filter demonstrated excellent performance (less than 8 meter level RMS semi-major axis accuracy) in performing orbit determination of a low-Earth orbit Explorer satellite using single-frequency real GPS data. This performance is significantly better than predicted by other simulation studies using dual-frequency GPS data. The study results revealed the significance of two new modeling approaches evaluated in the work. One approach introduces a single-frequency ionospheric correction through pseudo-range and phase range averaging implementation. The other approach demonstrates a precise axis-dependent characterization of dynamic sample space uncertainty to compute a more accurate Kalman filter gain. Additionally, this navigation filter demonstrates a flexibility to accommodate both perturbational dynamic and observational biases required for multi-flight phase and inhomogeneous application environments. This paper reviews the potential application of these methods and the filter structure to terrestrial vehicle and positioning applications. Both the single-frequency ionospheric correction method and the axis-dependent state noise modeling approach offer valuable contributions in cost and accuracy improvements for terrestrial GPS receivers. With a modular design approach to either 'plug-in' or 'unplug' various force models, this multi-flight phase navigation filter design structure also provides a versatile GPS navigation software engine for both atmospheric and exo-atmospheric navigation or positioning use, thereby streamlining the flight phase or application-dependent software requirements. Thus, a standardized GPS navigation software engine that can reduce the development and maintenance cost of commercial GPS receivers is now possible.

Park, Young W.↗
DOE OSTI2018

Inverse transformation: unleashing spatially heterogeneous dynamics with an alternative approach to XPCS data analysis

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A comparison of Raman and pyrometry dynamic temperature measurements of shocked cyclohexane

Optical pyrometry is a well-developed, broadly applicable method to determine temperature in dynamic compression experiments. However, it measures radiation from only the skin depth of the radiant material, is highly susceptible to spurious backgrounds, and requires an often-unmeasurable free parameter—the sample dynamic emissivity. Raman spectroscopy offers a method to determine temperature directly from fundamental theory, but it is practically limited in applications to a small subset of shock experiments. In this work, we describe an experiment allowing simultaneous application of Raman and pyrometric temperature techniques to benchmark a specific instance of pyrometry. We attempted both measurements on multiple experiments and compare the successful temperature results between the separate but highly repeatable shots. Here, we find that dynamic shock temperatures inferred from Raman spectroscopy and pyrometry generally agree within the uncertainties of each measurement, although those uncertainties are larger than typical for a specially designed pyrometry experiment on a shocked metal sample.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Streptococcus pneumoniae HtrA is a dynamic and monomeric virulence factor capable of forming larger oligomeric complexes

Abstract High‐temperature requirement A (HtrA) proteases are a conserved family of serine proteases central to protein quality control and bacterial virulence. While Gram‐negative and human HtrAs are structurally well studied, Gram‐positive homologs remain essentially uncharacterized. Here, we present the first integrated structural and mechanistic analysis of a Gram‐positive HtrA, from Streptococcus pneumoniae , a virulence factor essential for adhesion and infection in vivo. Proteomic profiling of an htrA knockout and cleavage assays demonstrate that S. pneumoniae HtrA is required for protein quality control, with the PDZ domain mediating substrate recognition. Biochemically, S. pneumoniae HtrA exists exclusively as a monomer in solution, a striking divergence from canonical trimeric HtrAs that we show is shared with other Gram‐positive homologs. NMR analyses reveal that the monomer dynamically samples open and closed conformations, while cryo‐EM of a catalytic mutant identifies a hexamer stabilized by a unique LoopA–PDZ interaction. Together, these findings define S. pneumoniae HtrA as a dynamic monomer with interdomain coupling between its protease and PDZ domains, establishing Gram‐positive HtrAs as a mechanistically divergent subgroup within the HtrA family.

Lee, Eunjeong [Department of Biochemistry and Mole↗
DOE OSTI2018

Attosecond transient absorption instrumentation for thin film materials: Phase transitions, heat dissipation, signal stabilization, timing correction, and rapid sample rotation

We present an extreme ultraviolet (XUV) transient absorption apparatus tailored to attosecond and femtosecond measurements on bulk solid-state thin-film samples, specifically when the sample dynamics are sensitive to heating effects. The setup combines methodology for stabilizing sub-femtosecond time-resolution measurements over 48 h and techniques for mitigating heat buildup in temperature-dependent samples. Single-point beam stabilization in pump and probe arms and periodic time-zero reference measurements are described for accurate timing and stabilization. A hollow-shaft motor configuration for rapid sample rotation, raster scanning capability, and additional diagnostics are described for heat mitigation. Heat transfer simulations performed using a finite element analysis allow comparison of sample rotation and traditional raster scanning techniques for 100 Hz pulsed laser measurements on vanadium dioxide, a material that undergoes an insulator-to-metal transition at a modest temperature of 340 K. Experimental results are presented confirming that the vanadium dioxide (VO 2 ) sample cannot cool below its phase transition temperature between laser pulses without rapid rotation, in agreement with the simulations. The findings indicate the stringent conditions required to perform rigorous broadband XUV time-resolved absorption measurements on bulk solid-state samples, particularly those with temperature sensitivity, and elucidate a clear methodology to perform them.

47 OTHER INSTRUMENTATION↗