Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic sampling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Nanoscale rheology at solid-complex fluid interfaces

Here we present an approach to measure dynamic membrane properties of phospholipid membranes close to an interface. As an example we show results of the membrane dynamics of a phospholipid membrane multilayer-stack on a solid substrate (silicon). On this sample we were able to measure local interaction and friction parameters using Grazing Incidence Neutron Spin Echo Spectroscopy (GINSES), where an evanescent neutron wave probes the fluctuations close to a rigid interface. With this method it is possible to access length scales in the nano to micrometer region as well as energies in the μeV range. Using a new neutron resonator structure we achieved the required intensity gain for this experiment. During our investigations we found an excitation mode of the phospholipid membrane that has not been reported previously and only became visible using the new methodology. We speculate that the energy transported by that undulation can also serve to distribute energy over a larger area of the membrane, stabilizing it. This new methodology has the capability to probe the viscoelastic effects of biological membranes, becoming a new tool for tribology on the nanoscale and has allowed the observation of the hitherto invisible property of phospholipid membranes using neutrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Refractive index of lithium fluoride to 900 gigapascal and implications for dynamic equation of state measurements

Lithium fluoride (LiF) is a unique crystal possessing the largest reported bandgap of any material and is predicted to remain transparent to visible light under stresses in excess of 1000 GPa. Dynamic compression experiments often utilize LiF as a window material to maintain stress on a sample while enabling direct measurements of interface velocity. However, typical velocimetry diagnostics measure changes in the optical path length; therefore, an accurate understanding of LiF’s equation of state and refractive index is needed. Here, we present a measurement of the LiF refractive index up to 900 GPa from a low-temperature ramp-compression experiment at the National Ignition Facility. To demonstrate propagation of optical uncertainty from this work to equation of state measurements, simulations in which a tin–LiF interface reaches a peak stress of 825 GPa show that the principal isentrope of tin can be determined up to 1450 GPa with a 1.2% uncertainty in density while considering uncertainties in the optical response of LiF.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Simulation of adiabatic quantum computing for molecular ground states

Quantum computation promises to provide substantial speedups in many practical applications with a particularly exciting one being the simulation of quantum many-body systems. Adiabatic state preparation (ASP) is one way that quantum computers could recreate and simulate the ground state of a physical system. In this paper, we explore a novel approach for classically simulating the time dynamics of ASP with high accuracy and with only modest computational resources via an adaptive sampling configuration interaction scheme for truncating the Hilbert space to only the most important determinants. We verify that this truncation introduces negligible error and use this new approach to simulate ASP for sets of small molecular systems and Hubbard models. Furthermore, we examine two approaches to speeding up ASP when performed on quantum hardware: (i) using the complete active space configuration interaction (CASCI) wave function instead of the Hartree–Fock initial state and (ii) a nonlinear interpolation between the initial and target Hamiltonians. We find that starting with a CASCI wave function with a limited active space yields substantial speedups for many of the systems examined, while nonlinear interpolation does not. In additional, we observe interesting trends in the minimum gap location (based on the initial state) as well as how state preparation time can depend on certain molecular properties, such as the number of valence electrons. Importantly, we find that the required state preparation times do not show an immediate exponential wall that would preclude an efficient run of ASP on actual hardware.

Kremenetski, Vladimir↗
DOE OSTI2022

Effect of proton irradiation temperature on persistent photoconductivity in zinc oxide metal-semiconductor-metal ultraviolet photodetectors

The electrical and structural characteristics of 50-nm-thick zinc oxide (ZnO) metal-semiconductor-metal ultraviolet (UV) photodetectors subjected to proton irradiation at different temperatures are reported and compared. The devices were irradiated with 200 keV protons to a fluence of 1016 cm−2. Examination of the x-ray diffraction (XRD) rocking curves indicates a preferred (100) orientation prior to irradiation, with decrease in crystal quality afterward. Additionally, peak shifts in XRD and Raman spectra of the control sample relative to well-known theoretical positions are indicative of tensile strain in the as-deposited ZnO films. Shifts toward theoretical unstrained positions are observed in the irradiated films, which indicates partial relaxation. Raman spectra also indicate increase in oxygen vacancies (VO) and zinc interstitial defects (Zni) compared to the control sample. Additionally, transient photocurrent measurements performed on each sample at different temperatures showed up to 2× increase in photocurrent decay time constants for irradiated samples vs the control. This persistent photoconductive behavior is linked to the activation of electron and hole traps near the surface, and to the desorption and reabsorption of O2 molecules on the ZnO surface under the influence of UV light. Using an Arrhenius model, trap activation energies were extracted and, by comparing with known energies from the literature, the dominant defects contributing to persistent photoconductivity for each irradiation condition were identified. The persistence of differences in photocurrent transients between different samples months after irradiation indicates that the defects introduced by the suppression of thermally activated dynamic annealing processes have a long-term deleterious effect on device performance.

Heuser, Thomas A. (ORCID:0000000225642400)↗
DOE OSTI2019

Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

Significance A major challenge in biology is characterizing the structural flexibility of intrinsically disordered proteins (IDPs). Ensemble-averaged experimental data do not provide the underlying protein structures. Here, we performed independently small-angle neutron and X-ray scattering experiments and unbiased molecular dynamics simulations to probe the solution structure of an IDP. We report that enhancing the sampling of the simulations can generate an ensemble of IDP structures in quantitative agreement with scattering and NMR, without the need for biasing the simulation or reweighting the results. The demonstration of established simulation technology that produces accurate physical models of flexible biosystems may pave the way to relating conformational flexibility to biological function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Improving Ligand Geometry in Protein Data Bank Structures Computationally

Information about the three‐dimensional structures of complex biological molecules is an indispensable research tool for many fields of study, including biology, chemistry, pharmacology, and computer science. The Protein Data Bank (PDB) is an public digital archive providing access to structures of nucleic acids, proteins, and large macromolecular machines determined experimentally by X‐ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and 3‐dimensional electron microscopy (3DEM). PDB structures undergo validation for structural plausibility upon their deposition into the PDB using the program Mogul, which cross references each deposited structure against similar data in the Cambridge Structural Database (CSD). Ligands associated with PDB structures are a common source of structural inaccuracy. In this study, a programmatic pipeline was developed to determine if ligand geometric accuracy could be improved using known computational tools. Ligands with dubious geometry were identified through a Python mining code. A sample set of the identified structures was remodeled into minimum energy conformations using the molecular dynamics program AMBER and then fit to the original experimental density maps using the molecular modeling program Coot. The refined models were compared to the original models in the PDB as well as to similar structures in the CSD using the deposition statistical validation server. Preliminary results suggest that the pipeline effectively identifies and improves ligand structures that possess inaccurate geometry. This method can be used to evaluate and improve the accuracy of specific ligands in structures both archived and pending deposition. Support or Funding Information This work was supported by an NSF REU and the RCSB PDB [NSF (DBI‐1338415), NIH, and DOE.] This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Miller, Beck↗
DOE OSTI2019

Estimates of Ta strength at ultrahigh pressures and strain rates using thin-film graded-density impactors

In this paper, we present results from an experimental technique used to estimate the strength of Ta at extreme pressures (150 GPa) and strain rates (10 7 s -1 ). A graded-density impactor (GDI) was fabricated using sputter deposition to produce an approximately 40-μm-thick film containing alternating layers of Al and Cu. The thicknesses of the respective layers are adjusted to give an effective density gradient through the film. The GDIs were launched with a 2-stage light gas gun, and shock-ramp-release velocity profiles were measured over timescales of ~10 ns. Results are presented for the direct impact of the film onto LiF windows, which allows for a dynamic characterization of the GDI, as well as from impact onto thin (~40μm) sputtered Ta samples backed by a LiF window. The measurements were coupled with mesoscale numerical simulations to infer the strength of Ta, and the results agree well with other high-pressure platforms, particularly when strain-rate, microstructural, and thermodynamic-path differences are considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Interpretable AI forecasting for numerical relativity waveforms of quasicircular, spinning, nonprecessing binary black hole mergers

We present a deep-learning artificial intelligence model (AI) that is capable of learning and forecasting the late-inspiral, merger and ringdown of numerical relativity waveforms that describe quasicircular, spinning, nonprecessing binary black hole mergers. We used the NRHybSur3dq8 surrogate model to produce train, validation and test sets of ℓ = |m| = 2 waveforms that cover the parameter space of binary black hole mergers with mass ratios q ≤ 8 and individual spins |s$^{z}_ {(1,2)}$| ≤ 0.8. These waveforms cover the time range t ∊ [-5000 M, 130 M], where t = 0M marks the merger event, defined as the maximum value of the waveform amplitude. We harnessed the ThetaGPU supercomputer at the Argonne Leadership Computing Facility to train our AI model using a training set of 1.5 million waveforms. We used 16 NVIDIA DGX A100 nodes, each consisting of 8 NVIDIA A100 Tensor Core GPUs and 2 AMD Rome CPUs, to fully train our model within 3.5 h. Our findings show that artificial intelligence can accurately forecast the dynamical evolution of numerical relativity waveforms in the time range t ∊ [-100 M, 130 M]. Sampling a test set of 190,000 waveforms, we find that the average overlap between target and predicted waveforms is ≳99% over the entire parameter space under consideration. We also combined scientific visualization and accelerated computing to identify what components of our model take in knowledge from the early and late-time waveform evolution to accurately forecast the latter part of numerical relativity waveforms. This work aims to accelerate the creation of scalable, computationally efficient and interpretable artificial intelligence models for gravitational wave astrophysics

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A general Bayesian algorithm for the autonomous alignment of beamlines

Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics. Bayesian optimization is a strategy of efficient global optimization that has proved successful in similar regimes in a wide variety of beamline alignment applications, though it has typically been implemented for particular beamlines and optimization tasks. In this paper, we present a basic formulation of Bayesian inference and Gaussian process models as they relate to multi-objective Bayesian optimization, as well as the practical challenges presented by beamline alignment. We show that the same general implementation of Bayesian optimization with special consideration for beamline alignment can quickly learn the dynamics of particular beamlines in an online fashion through hyperparameter fitting with no prior information. We present the implementation of a concise software framework for beamline alignment and test it on four different optimization problems for experiments on X-ray beamlines at the National Synchrotron Light Source II and the Advanced Light Source, and an electron beam at the Accelerator Test Facility, along with benchmarking on a simulated digital twin. We discuss new applications of the framework, and the potential for a unified approach to beamline alignment at synchrotron facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Voronoi Diagram Based Optimization of Dynamic Reactive Power Sources

Dynamic var sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues or even voltage collapse. This paper proposes a new approach to optimization of the sizes of dynamic var sources at candidate locations by a Voronoi diagram based algorithm. It first disperses sample points of potential solutions in a searching space, evaluates a cost function at each point by barycentric interpolation for the subspaces around the point, and then constructs a Voronoi diagram about cost function values over the entire space. Accordingly, the final optimal solution can be obtained. Case studies on the WSCC 9-bus system and NPCC 140-bus system have validated that the new approach can quickly identify the boundary of feasible solutions in searching space and converge to the global optimal solution.

25 ENERGY STORAGE↗
DOE OSTI2016

FORMATION AND EVOLUTION OF BLUE STRAGGLERS IN 47 TUCANAE

Blue stragglers (BSS) are stars whose position in the color–magnitude diagram (CMD) places them above the main sequence (MS) turn-off (TO) point of a star cluster. Using data from the core of 47 Tuc in the ultraviolet (UV), we have identified various stellar populations in the CMD, and used their radial distributions to study the evolution and origin of BSS, and obtain a dynamical estimate of the mass of BSS systems. When we separate the BSS into two samples by their magnitude, we find that the bright BSS show a much more centrally concentrated radial distribution and thus higher mass estimate (over twice the TO mass for these BSS systems), suggesting an origin involving triple or multiple stellar systems. In contrast, the faint BSS are less concentrated, with a radial distribution similar to the MS binaries, pointing to the MS binaries as the likely progenitors of these BSS. Putting our data together with available photometric data in the visible and using MESA evolutionary models, we calculate the expected number of stars in each evolutionary stage for the normal evolution of stars and the number of stars coming from the evolution of BSS. The results indicate that BSS have a post-MS evolution comparable to that of a normal star of the same mass and a MS BSS lifetime of about 200–300 Myr. We also find that the excess population of asymptotic giant branch stars in 47 Tuc is due to evolved BSS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network

Solar energetic particles (SEPs) are an essential source of space radiation, and are hazardous for humans in space, spacecraft, and technology in general. In this paper, we propose a deep-learning method, specifically a bidirectional long short-term memory (biLSTM) network, to predict if an active region (AR) would produce an SEP event given that (i) the AR will produce an M- or X-class flare and a coronal mass ejection (CME) associated with the flare, or (ii) the AR will produce an M- or X-class flare regardless of whether or not the flare is associated with a CME. The data samples used in this study are collected from the Geostationary Operational Environmental Satellite's X-ray flare catalogs provided by the National Centers for Environmental Information. We select M- and X-class flares with identified ARs in the catalogs for the period between 2010 and 2021, and find the associations of flares, CMEs, and SEPs in the Space Weather Database of Notifications, Knowledge, Information during the same period. Each data sample contains physical parameters collected from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Experimental results based on different performance metrics demonstrate that the proposed biLSTM network is better than related machine-learning algorithms for the two SEP prediction tasks studied here. We also discuss extensions of our approach for probabilistic forecasting and calibration with empirical evaluation

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. Melting ice has been detected in Lake Erie by comparison of visible and near infrared differential reflectance. This melting condition is confirmed by meteorological ground truth data and concurrent NOAA-2 thermal infrared data. Using near-synchronous ERTS-1 data, it was possible to determine the approximate ground resolution of NOAA-2 very high resolution radiometer by comparing the smallest identifiable ice crack in the imagery and measuring the same crack on the ERTS-1 image. It was determined that photointerpretation and analysis of a single Lake Erie image can, under certain conditions, provide meaningful data on ice dynamics. ERTS-1 imagery is effective for icepack monitoring of the Great Lakes, but the sampling interval of 18 days imposes a severe limitation. Maps of the snow cover in the American River basin for 16 March 1973 have been prepared using all four bands.

Wiesnet, D. R.↗
NASA NTRS1978

Sampling analysis for the Earth Radiation Budget Satellite System mission based on orbital coverage and cloud variability

The reported study represents an extension of an investigation by Harrison et al. (1976). Based on the results of sampling studies, two 98 deg inclined orbits coupled with a 56 deg inclination orbit appear to satisfy the science requirements on both regional and zonal scales. The NOAA sun-synchronous satellites in the TIROS-N series could adequately cover the high latitudes and a satellite having an inclination of 56 deg could provide sampling in the mid and low latitude areas where variations in radiation energetics are most dynamic. Attention is given to studies of time and space coverage, zonal evaluations, a regional analysis, and statistics describing the regional variations of cloud cover. A table is presented with data concerning the uncertainty of monthly mean reflected irradiance due to cloud variability for selected northern hemisphere regions.

Harrison, E. F.↗
NASA NTRS1983

Space Processing Applications Rocket (SPAR) project SPAR 7

The postflight reports of each of the Principal Investigators of three selected science payloads are presented in addition to the engineering report as documented by the Marshall Space Flight Center (MSFC). Pertinent portions of ground-based research leading to the ultimate selection of the flight sample composition are described including design, fabrication and testing. Containerless processing technology, containerless processing bubble dynamics, and comparative alloy solidification are the experiments discussed.

Poorman, R. M.↗
NASA NTRS1986

Modeling of multi-rotor torsional vibrations in rotating machinery using substructuring

The application of FEM modeling techniques to the analysis of torsional vibrations in complex rotating systems is described and demonstrated, summarizing results reported by Soares (1985). A substructuring approach is used for determination of torsional natural frequencies and resonant-mode shapes, steady-state frequency-sweep analysis, identification of dynamically unstable speed ranges, and characterization of transient linear and nonlinear systems. Results for several sample problems are presented in diagrams, graphs, and tables. STORV, a computer code based on this approach, is in use as a preliminary design tool for drive-train torsional analysis in the High Altitude Wind Tunnel at NASA Lewis.

Soares, Fola R.↗
NASA NTRS1995

NASA wiring for space applications program test results

The objective of this test is to examine the mechanical and electrical properties of PFPI insulation. Some of the parameters considered during the test are: AC corona (400 Hz), wire fusing time, abrasion resistance, dynamic cut through, notch propagation, and weight loss (outgassing). In addition the degradation of the samples caused by the immature manufacturing status of the PFPI materials for wiring is considered.

Ide, Jim↗
NASA NTRS1995

Thermal Characterization of the Universal Multizone Crystallizator

The Universal Multizone Crystallizator (UMC) is a special apparatus for crystal growth under terrestrial and microgravity conditions. The use of twenty-five zones allows the, UMC to be used for several normal freezing growth techniques. The thermal profile is electronically translated along the stationary sample by systematically reducing the power to the control zones. Elimination of mechanical translation devices increases the systems reliability while simultaneously reducing the size and weight. This paper addresses the UMC furnace design, sample cartridge, typical thermal profiles and corresponding power requirements necessary for two normal freezing techniques: dynamic gradient freeze and zone melting crystal growth.

Watring, D. A.↗