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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Ascent Aborts 2 Flight, Reconstruction of Structural Dynamics (Couple Loads Transients)

- This work describes the elements of AA2 post-flight data analysis, couple loads analysis, and comparisons of the flight data with the results of analytical methods transiently. - The measured transient responses ranged from rigid body frequencies (zero Hz) to 150 Hz. - The analytical methods consisted of defining and determining all forcing functions, i.e., buffet, aerodynamics, thrusts from the abort motor and the carrier lunch vehicle motor, and the initial conditions at pre-separation. - Mathematical models representing the mechanics of Orion abort is relatively complex because 1) two motors (carrier’s and LAS’s) are operating at the same time at pre-separation, and 2) the separation occurs in atmosphere. - Other challenges consist of determining the aerodynamics with plume-on condition at every millisecond of the flight ranging from transonic to supersonic (i.e., Mach 1.1 to Mach 1.6), and defining the mechanics of separation of LAS from the launch vehicle.

Launch Vehicle↗
DOE OSTI2020

Synthesis of Seismic Methods in Southern Kansas (Milestone G)

We proposed to conduct the following activities in Budget Period 2 with respect to Task 2.1 of the overall project management plan: 1) Local SWS using microseismicity catalog. 2) Continuation of VSM analysis. 3) Synthesis of seismic data and uncertainty analyses. Milestone G: Apply ANT, VSM, and SWS methods to Kansas microseismicity catalog. Calculate 3D model and moment tensor elements and meet milestone E.

58 GEOSCIENCES↗
NASA NTRS1992

Gamma ray pulsar analysis from photon probability maps

A new method is presented of analyzing skymap-type gamma ray data. Each photon event is replaced by a probability distribution on the sky corresponding to the observing instrument's point spread function. The skymap produced by this process may be used for source detection or identification. Most important, the use of these photon weights for pulsar analysis promises significant improvement over traditional techniques.

Brown, Lawrence E.↗
DOE OSTI2025

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1968

Guidance and control analysis and integration

Automation of variational methods for solution of optimum control problems, optical data sources for Mars-encounter earth-based orbit determination, and operational support equipment

Source record↗
NASA NTRS1972

Magnetic dipole moment determination by near-field analysis

A method for determining the magnetic moment of a spacecraft from magnetic field data taken in a limited region of space close to the spacecraft. The spacecraft's magnetic field equations are derived from first principles. With measurements of this field restricted to certain points in space, the near-field equations for the spacecraft are derived. These equations are solved for the dipole moment by a least squares procedure. A method by which one can estimate the magnitude of the error in the calculations is also presented. This technique was thoroughly tested on a computer. The test program is described and evaluated, and partial results are presented.

Eichhorn, W. L.↗
NASA NTRS2003

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Huang, Norden E.↗
DOE OSTI2026

Investigation of the isoscalar monopole response in the proton-rich nucleus 14 O

Deuteron inelastic scattering on 14 O was measured in inverse kinematics using an active-target time projection chamber and a magnetic spectrograph. The experimental technique enabled precise measurements of deuteron recoiling particles in coincidence with beam-like fragments detected in the spectrograph focal plane. The double differential cross section was reconstructed for scattering angles of 3–6 degrees and excitation energies up to 26 MeV. The monopole strength distribution was obtained from the data using a multipole decomposition analysis. The results were compared to quasiparticle random-phase approximation (QRPA) and generator coordinate method (GCM) calculations. The QRPA calculation accurately describes experimental data in the energy range of 13 to 26 MeV. GCM calculations assuming a 12 C (g . s .) + p + p cluster configuration were used to determine the 0 + strength in 14 O below 13 MeV. The monopole transition strength of these cluster states provides a good description of the experimental distribution in the 9–11 MeV region, while the 0$^{+}_{2}$ state accounts for only a small fraction of the experimental strength around 6 MeV.

Active target↗
NASA NTRS2001

Ground Test of the Urine Processing Assembly for Accelerations and Transfer Functions

This viewgraph presentation gives an overview of the ground test of the urine processing assembly for accelerations and transfer functions. Details are given on the test setup, test data, data analysis, analytical results, and microgravity assessment. The conclusions of the tests include the following: (1) the single input/multiple output method is useful if the data is acquired by tri-axial accelerometers and inputs can be considered uncorrelated; (2) tying coherence with the matrix yields higher confidence in results; (3) the WRS#2 rack ORUs need to be isolated; (4) and future work includes a plan for characterizing performance of isolation materials.

Houston, Janice↗
NASA NTRS1974

A statistical approach to deriving subsystem specifications

In order to produce cost effective environmental test programs, the test specifications must be realistic and to be useful, they must be available early in the life of a program. This paper describes a method for achieving such specifications for subsystems by utilizing the results of a statistical analysis of data acquired at subsystem mounting locations during system level environmental tests. The paper describes the details of this statistical analysis. The resultant recommended levels are a function of the subsystems' mounting location in the spacecraft. Methods of determining this mounting 'zone' are described. Recommendations are then made as to which of the various problem areas encountered should be pursued further.

Keegan, W. B.↗
DOE OSTI2026

Development and implementation of high-throughput proteomic and metabolomics assays by using advanced chromatographic and mass spectrometric systems (CRADA Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOFMS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Overall, the project advanced rapid metabolomics by combining liquid chromatography, ion mobility spectrometry, and data-independent mass spectrometry with machine learning. This multidimensional approach uses retention time, collision cross-section, precursor mass, and fragment-ion information to distinguish chemically similar metabolites that can be difficult to resolve using conventional liquid- or gas-chromatography methods. The resulting workflow also provided automated metabolite-identification error estimates, addressing a recognized need for statistical confidence measures in metabolomics.

Petzold, Christopher [Lawrence Berkeley National L↗
NASA NTRSDate not supplied

Analysis and Evaluation of NASA's MK40B Six-Component Task Balance

The MK40B balance is NASA's newest balance of Task design. Its load range was optimized for use in the NASA Ames 11-ft Transonic Wind Tunnel. The balance was calibrated in 2019 in Calspan's Automatic Balance Calibration System. The data analysis was performed at the Ames Balance Calibration Laboratory. First, bi-directional characteristics of the six gage outputs of the balance were assessed by applying a semi-empirical test to the calibration data. These tests indicated that four of the six gages have bi-directional characteristics. Therefore, the use of absolute value terms in the regression models of the calibration data is justified. Then, the machine calibration data was analyzed using both the Non-Iterative and the Iterative Method. Analysis results for the two methods were compared using the percent contributions, the calibration load residuals, the primary sensitivities, and the principle linear terms. These results confirmed that the two methods describe bi-directional characteristics of the balance gages correctly. In addition, it was concluded that the load prediction accuracies of the two methods are the same for all practical purposes.

wind tunnel balance↗
NASA NTRS2001

Determining the Mass Density Along Magnetic Field Lines from Toroida Eigenfrequencies

Toroidal eigenfrequencies can be used to remotely sense the equatorial mass density rho(sub eq) and the density dependence along a magnetic field line. Here we present improvements to the method of Schulz [1996], which allows rho(sub eq) and the power law index alpha (for mass density along a field line proportional to R(sup -alpha), where R is the radial distance from the center of the Earth) to be determined from the y intercept and slope of a plot of toroidal frequency versus toroidal harmonic number n. Our modifications include a model form for eigenfrequencies with a fractional precision of 0.0005 for -6 less than or = alpha less than or = 6 and 2 less than or = L less than or = 8 (accuracy is doubtful beyond L = 5) and an iterative procedure for getting more accurate results than those found using Schulz's method. In addition, we do an analysis of the effect of random measurement errors. Observed frequencies need to be accurate to approx. 6% (3%) of the fundamental frequency in order to determine rho(sub eq) (alpha) to a precision of 30% (unity). We then apply our method to data generated using the Global Core Plasma Model for plasmaspheric mass density; our analysis demonstrates clearly bow the alpha index represents the mass density dependence on the outer part of the field line (R/(LR(sub E)) greater than or approx. 2/3).

Denton, R.↗
NASA NTRS1981

Sensitivity of wind analyses to barotropic energetics during summer

Three analysis schemes - the extended correction method of the University of Hawaii at Manoa (UHM), the National Meteorological Center (NMC) Hough analysis, and Sadler's subjective stream analysis (SUB) - were used to obtain grid-point winds using data for a five-day period in late summer, and barotropic energetics computations obtained using the three schemes for six limited regions in the Pacific and Indian Oceans were compared. Few differences were observed between UHM and NMC stream-function analyses, but significant differences were found in the wind fields and energetics obtained using the subjective method and the two objective methods in data-sparse regions. Major features in the local barotropic criteria field were found to be less sensitive to the analysis scheme used.

Sumi, A.↗
NASA NTRS1990

Boundary-layer stability analysis of flight-measured transition data

Correlation of in-flight boundary-layer transition experiments with linear boundary-layer stability theory contributes both to the validation of the numerical methods as well as the analysis of the measured transition process. Transition results obtained in a recent flight experiment, in which the extent of laminar flow and the transition process on the wing of a business-jet fitted with an instrumented glove section were determined, are analyzed. The experiment was conducted at freestream Mach numbers from 0.55 to 0.82, chord Reynolds numbers from 10 to 20 x 10 to the 6th, and leading-edge sweep angles 17 deg to 20 deg. The growth of both Tollmien-Schlichting and crossflow instabilities are predicted using the e exp n method for several flight conditions and the calculated n-factors at transition onset are correlated. Comparison of the measured dominant boundary-layer disturbance frequencies and the predicted unstable frequencies shows fair agreement for several of the flight conditions studied.

Obara, Clifford J.↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Environmental Effects Assessment for Proposed Offshore Wind Farm off the Coast of Grays Harbor, Washington

Grays Harbor Wind LLC (GHW) is proposing to develop a floating offshore wind farm offshore of west Grays Harbor County, Washington (Grays Harbor). The proposed GHW Offshore Wind Project (Project) would entail construction, installation and operation of a 1,000-megawatt (MW) offshore wind farm consisting of approximately 75 floating units, each containing a floating foundation and wind turbine generator (WTG). The Project location is approximately 25 miles (21.7 nautical miles [nmi]) offshore west of Grays Harbor, at waters depths of 360 to 700 feet. The Pacific Northwest National Laboratory (PNNL) was contracted by Herrera Environmental Consultants, Inc. on behalf of GHW to carry out this preliminary scoping study to evaluate baseline conditions and potential effects on fish and marine mammals from development and operation of a floating offshore wind farm installed within a designated area off the coast of Washington1. Floating offshore wind units installed in an ocean environment as part of the Project would interact with marine wildlife. This Study report provides an initial data aggregation and analysis, using publicly available data, of the Project effects, both negative and positive, on the marine environment. The scope of this assessment is limited by the fact that the Project development is presently at the conceptual level. Data on marine organisms were aggregated and evaluated; however seabirds were evaluated by Herrera Environmental Consulting and, along with bats, were not included in the scope of this study. Significant additional work is necessary to characterize ocean, seafloor, and environmental conditions; select appropriate floating offshore wind technologies; identify construction methods and locations; and assess facility locations, including electrical interconnection. Data aggregation and analysis of seabirds and bats is also needed. Evaluation of the full range of potential environmental effects would be conducted following an award of a lease from the Bureau of Ocean Energy Management (BOEM) as part of the leasing, National Environmental Policy Act (NEPA)/State Environmental Policy Act (SEPA) environmental review and permitting processes. While this initial data aggregation and analysis uses best available public scientific information and current assumptions about the Project configuration, the effects discussed herein are based on the status of review to-date and may change as Project-specific details are developed.

17 WIND ENERGY↗