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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry

Sample return capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 2023 September 24 arrival of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing, and Global Positioning System technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the data set collected during this campaign will improve entry and propagation models and augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1973

Input frequency requirements for identification through Liapunov methods

A theorem is derived which specifies a sufficient number of input frequencies to guarantee identification of an unknown noise free linear plant. Since all of the referenced work relates to sufficient conditions for nulling of the parameter error vector, it is to be expected that various conditions on the system to be identified will have been imposed. It was found that some of these conditions appear to be necessary while others do not. The main contribution is to provide a theorem which considers the effect of unknown parameters in the state equation upon the frequency requirements.

Kim, C. H.↗
NASA NTRS1980

The energy coupling function and the power generated by the solar wind-magnetosphere dynamo

A solar wind parameter epsilon, known as the energy coupling function, has been shown to correlate with the power consumption in the magnetosphere. It is shown in the present paper that the parameter epsilon can be identified semi-quantitatively as the dynamo power delivered from the solar wind to an open magnetosphere. This identification not only provides a theoretical basis for the energy coupling function, but also constitutes an observational verification of the solar wind-magnetosphere dynamo along the magnetotail. Moreover, one can now conclude that a substorm results when the dynamo power exceeds 10 to the 18th erg/s.

Kan, J. R.↗
NASA NTRS1982

Rotational and vibrational spectra of ethynol from quantum-mechanical calculations

It is noted that ethynol (HCCOH), despite the theoretical prediction of its stability to tautomerization to ketene, has thus far not been observed. It is shown here that the identification of this unknown molecule, both in space and in the laboratory, can be aided by an ab initio calculation of spectroscopic parameters. At the HF/3-21G level, harmonic vibrational frequencies are computed by way of analytic second differentiation of the Hartee-Fock (HF) energy with respect to the nuclear coordinates. After applying an empirical scale factor, the resultant frequencies are (per cm) 473, 517, 773, 841, 1003, 1217, 2206, 3285, and 3418. The computed dipole moment at the CISD/DZ+P level is 1.79 D. At the CISD+Q/DZ+P level, the molecule's rotational constants are determined. After scaling by empirical correction factors, they are used in deriving the 4(04) - 3(03) frequency of 76.81 + or - 0.3 GHz with a triplet splitting of 0.30 + or - 0.01 GHz. The triplet splitting involves 4(14) - 3(13) and 4(13) - 3(12) relative to the 4(04) - 3(03) transition as the central line.

Defrees, D. J.↗
NASA NTRS1984

Test bed ion engine development

A test bed ion (TBI) engine was developed to serve as a tool in exploring the limits of electrostatic ion thruster performance. A description of three key ion engine components, the decoupled extraction and amplified current (DE-AC) accelerator system, field enhanced refractory metal (FERM) hollow cathode and divergent line cusp (DLC) discharge chamber, whose designs and operating philosophies differ markedly from conventional thruster technology is given. Significant program achievements were: (1) high current density DE-AC accelerator system operation at low electric field stress with indicated feasibility of a 60 mA/sq cm argon ion beam; (2) reliable FERM cathode start up times of 1 to 2 secs. and demonstrated 35 ampere emission levels; (3) DLC discharge chamber plasma potentials negative of anode potential; and (4) identification of an efficient high plasma density engine operating mode. Using the performance projections of this program and reasonable estimates of other parameter values, a 1.0 Newton thrust ion engine is identified as a realizable technology goal. Calculations show that such an engine, comparable in beam area to a J series 30 cm thruster, could, operating on Xe or Hg, have thruster efficiencies as high as 0.76 and 0.78 respectively, with a 100 eV/ion discharge loss.

Aston, G.↗
NASA NTRS1990

Satellite sweeping of electrons at Neptune and Uranus

Knowledge of satellite sweeping parameters at Neptune and Uranus, and of their functional dependences on particle energy and pitch angle, can be critical in the proper identification of parent absorbers for observed absorption signatures in regions where OTD (offset, tilted dipole) models are valid representations of the measured magnetic fields. In this paper, critical electron energies are calculated for longitudinal drift resonance, snowplow (i.e., strong) absorption, leapfrog, and corkscrew effects, using a reduced version of OTD that neglects nonaxial dipole offsets. Earlier analytic work on sweeping rates is extended to give the radial dependence of these rates within the minimum-L region and to set limits on diffusion of electrons with the simplifying approximation that leapfrog effects are ignored.

Cooper, John F.↗
NASA NTRS1989

Scene identification probabilities for evaluating earth radiation measurements

Alongtrack data from the Earth Radiation Budget Experiment (ERBE) satellite are used here to derive scene identification probabilities empirically. These error probabilities are shown to be functions of view zenith angle and scene type, but not of other parameters such as solar zenith angle and relative azimuth angle, except in the sunglint region. The standard deviations of the resulting errors in radiative fluxes are also presented.

Manalo, N.↗
NASA NTRS1999

A Comparison Of Cloud Microphysical Properties Derived Using VIRS 3.7 Micron and 1.6 Micron Data

One of the main objectives of the Clouds and the Earth's Radiant Energy System (CERES) project is the retrieval of cloud physical and microphysical properties simultaneously with observations of broadband radiative fluxes. These cloud parameter sare used for three main purposes: 1) to provide data for radiation-cloud climate feedback studies; 2) to provide scene identification data for the construction and application of angular distribution models; and 3) to be used as input to radiative transfer calculations of intra-atmospheric fluxes

Young, David F.↗
NASA NTRS2011

Orbital Debris Characterization via Laboratory Optical Measurements

Optical observations of orbital debris offer insights that differ from radar measurements (specifically the size parameter,wavelength regime,and altitude range). For example, time-dependent photometric data yield lightcurves in multiple bandpasses that aid in material identification and possible periodic orientations. These data can also be used to help identify shapes and optical properties at multiple phase angles. Capitalizing on optical data products and applying them to generate a more complete understanding of orbital objects is a key objective of NASA's Optical Measurement Program, and the primary reason for the creation of the Optical Measurements Center(OMC). The OMC attempts to emulate space-based illumination conditions using equipment and techniques that parallel telescopic observations and source-target-sensor orientations.

Cowardin, Healther↗
DOE OSTI2022

Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

Anomaly detection is a widely studied task for a broad variety of data types; among them, multiple time series appear frequently in applications, including for example, power grids and traffic networks. Detecting anomalies for multiple time series, however, is a challenging subject, owing to the intricate interdependencies among the constituent series. We hypothesize that anomalies occur in low density regions of a distribution and explore the use of normalizing flows for unsupervised anomaly detection, because of their superior quality in density estimation. Moreover, we propose a novel flow model by imposing a Bayesian network among constituent series. A Bayesian network is a directed acyclic graph (DAG) that models causal relationships; it factorizes the joint probability of the series into the product of easy-to-evaluate conditional probabilities. We call such a graph-augmented normalizing flow approach GANF and propose joint estimation of the DAG with flow parameters. We conduct extensive experiments on real-world datasets and demonstrate the effectiveness of GANF for density estimation, anomaly detection, and identification of time series distribution drift.

Dai, Enyan↗
NASA NTRS1982

Adaptive identification for the dynamics of large space structures

A new approach for identifying the dynamics of large space structures using noisy measurements is presented. In this approach, a modal system description is avoided and, hence, the a priori specification of model order. Instead, the system's order is recursively determined on-line, along with its parameters, using recursive lattice filters which are widely used in adaptive signal processing. The order determination is carried out based on statistical hypothesis testing theory. The approach is illustrated for the problem of identifying the structural dynamic characteristics of a free-free beam. Results on the effectiveness and accuracy of the identification scheme with respect to noise levels, sampling rates, and data window sizes are presented

Sundararajan, N.↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
DOE OSTI2021

Nuclear Data Sheets for A=100

Here, evaluated experimental data are presented for 15 known nuclides of mass 100 (Kr, Rb, Sr, Y, Zr, Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, In, Sn). Recommended values are given for level parameters, γ and β radiations, and other spectroscopic information. No excited states are known in 100 Rb and 100 Sn. Except for isotopic identification, no information is available for the decay of the 100 Kr isotope, and limited information is known about the decay properties of the 100 Sn isotope. According to Fig. 2 (A/Q versus counts plot) and as mentioned in the text in 2021Su01, 100 Br isotope was not observed, although, discovery of 101 Br was claimed in this work. In the case of 100 Pd, the agreement in the orderings of the γ-ray cascades and γ-ray inventory between various studies of high-spin structures remains poor at high excitation energies (>9 MeV). For 100 Y, the assignments of the two previously known half-lives to the respective states (g.s. and the 145-keV isomer) remain to be established. Here, this work supersedes earlier full evaluations of A=100 by 2008Si01, 1997Si09, 1990Si05 and 1974Ko37.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Single-shot ionization-based monitor for pulsed electron beams

In this work, we present an experimental demonstration of a single-shot, nondestructive electron beam diagnostic based on the ionization of a low-density pulsed gas jet. In our study, 7 MeV electron bunches from a radio-frequency photoinjector, carrying up to 100 pC of charge, traversed a localized distribution of nitrogen gas (N 2 ). The interaction of the electron bunches with the N 2 gas generated a correlated signature in the ionized particle distribution, which was spatially magnified using a series of electrostatic lenses and recorded with a microchannel-plate detector. Various modalities, including point-to-point imaging and velocity mapping, are investigated. A temporal trace of the detector current enabled the identification of single- and double-ionization events. The characteristics of the ionization distribution, dependence on gas density, total bunch charge, and other parameters, are described. Approaches to scaling to higher electron bunch density and energy are suggested. Additionally, the instrument proves useful for comprehensive studies of the ionization process itself.

47 OTHER INSTRUMENTATION↗
NASA NTRS1982

Direct measurements of plasma characteristics in space-simulation beam-plasma interactions

Recent laboratory investigations of space-simulated electron-beam-plasma interactions are discussed. The plasma has been characterized with respect to its spatial distributions in density, temperature, and density fluctuation power spectra. The latter results have been further classified in terms of amplitude and spectral distributions. The overall results include: (1) detailed radial profiles of plasma density as a function of beam parameters; (2) the association of low-frequency large amplitude fluctuations with ion acoustic, ion cyclotron, and drift-wave modes; (3) the identification and spatial mapping of suprathermal electrons in the beam core; and (4) the experimental definition of a density-dependent criterion for the ignition of the beam-plasma-discharge.

Szuszczewicz, E. P.↗
NASA NTRS1983

Simulation Aspects in the Study of Rectification of Satellite Scanner Data

Complete sensor/platform modelling is derived and used for the generation of synthetic data and for rectification studies of satellite scanner data. All satellite position and sensor attitude parameters are recovered. Rectification accuracy improves marginally when using more than 25 control points, and is highly sensitive to errors in image point identification.

Mikhail, E. M.↗