Search NASA⌕ Search

SEARCH · Search NASA

Results for “Methods:data analysis”

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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Small-crack effects in high-strength aluminum alloys

The National Aeronautics and Space Administration and the Chinese Aeronautical Establishment participated in a Fatigue and Fracture Mechanics Cooperative Program. The program objectives were to identify and characterize crack initiation and growth of small cracks (10 microns to 2 mm long) in commonly used US and PRC aluminum alloys, to improve fracture mechanics analyses of surface- and corner-crack configurations, and to develop improved life-prediction methods. Fatigue and small-crack tests were performed on single-edgenotch tension (SENT) specimens and large-crack tests were conducted on center-crack tension specimens for constant-amplitude (stress ratios of -1, 0, and 0.5) and Mini-TWIST spectrum loading. The plastic replica method was used to monitor the initiation and growth of small fatigue cracks at the semicircular notch. Crack growth results from each laboratory on 7075-T6 bare and LC9cs clad aluminum alloys agreed well and showed that fatigue life was mostly crack propagation from a material defect (inclusion particles or void) or from the cladding layer. Finite-element and weight-function methods were used to determine stress intensity factors for surface and corner cracks in the SENT specimens. Equations were then developed and used in a crack growth and crack-closure model to correlate small- and large-crack data and to make life predictions for various load histories. The cooperative program produced useful experimental data and efficient analysis methods for improving life predictions. The results should ultimately improve aircraft structural reliability and safety.

Newman, J. C., Jr.↗
NASA NTRS2010

Combustion Stability Analyses of Coaxial Element Injectors with Liquid Oxygen/Liquid Methane Propellants

Liquid rocket engines using oxygen and methane propellants are being considered by the National Aeronautics and Space Administration (NASA) for in-space vehicles. This propellant combination has not been previously used in a flight-qualified engine system, so limited test data and analysis results are available at this stage of early development. NASA has funded several hardware-oriented activities with oxygen and methane propellants over the past several years with the Propulsion and Cryogenic Advanced Development (PCAD) project, under the Exploration Technology Development Program. As part of this effort, the NASA Marshall Space Flight Center has conducted combustion stability analyses of several of the configurations. This paper presents test data and analyses of combustion stability from the recent PCAD-funded test programs at the NASA MSFC. These test programs used swirl coaxial element injectors with liquid oxygen and liquid methane propellants. Oxygen was injected conventionally in the center of the coaxial element, and swirl was provided by tangential entry slots. Injectors with 28-element and 40-element patterns were tested with several configurations of combustion chambers, including ablative and calorimeter spool sections, and several configurations of fuel injection design. Low frequency combustion instability (chug) occurred with both injectors, and high-frequency combustion instability occurred at the first tangential (1T) transverse mode with the 40-element injector. In most tests, a transition between high-amplitude chug with gaseous methane flow and low-amplitude chug with liquid methane flow was readily observed. Chug analyses of both conditions were conducted using techniques from Wenzel and Szuch and from the Rocket Combustor Interactive Design and Analysis (ROCCID) code. The 1T mode instability occurred in several tests and was apparent by high-frequency pressure measurements as well as dramatic increases in calorimeter-measured heat flux throughout the chamber. Analyses of the transverse mode were conducted with ROCCID and empirical methods such as Hewitt d/V. This paper describes the test hardware configurations, test data, analysis methods, and presents results of the various analyses.

Hulka, J. R.↗
NASA NTRS2008

Verification of Atmospheric Signals Associated with Major Seismicity by Space and Terrestrial Observations

Observations from the last twenty years suggest the existence of electromagnetic (EM) phenomena during or preceding some earthquakes [Haykawa et a!, 2004; Pulinets at al, 1999,2004, 2006, Ouzounov et all 2007 and Liu et all 20041. Both our previous studies [Pulinets at al, 2005, 2006, Ouzounov et al, 2006, 20071 and the latest review by the Earthquake Remote Precursor Sensing panel [ERPS; 2003- 20051; have shown that there were precursory atmospheric TIR signals observed on the ground and in space associated with several recent earthquakes. [Tramutoli at al, 2005, 2006, Cervone et al, 2006, Ouzounov et all 2004,2006JT.o study these signals, we applied both multi parameter statistical analysis and data mining methods that require systematic measurements from an Integrated Sensor Web of observations of several physical and environmental parameters. These include long wave earth infra-red radiation, ionospheric electrical and magnetic parameters, temperature and humidity of the boundary layer, seismicity and may be associated with major earthquakes. Our goal is to verify the earthquake atmospheric correlation in two cases: (i) backward analysis - 2000-2008 hindcast monitoring of multi atmospheric parameters over the Kamchatka region, Russia ; and (ii) forward real-time alert analysis over different seismo-tectonic regions for California, Turkey, Taiwan and Japan. Our latest results, from several post-earthquake independent analyses of more then 100 major earthquakes, show that joint satellite and some ground measurements, using an integrated web, could provide a capability for observing pre-earthquake atmospheric signals by combining the information from multiple sensors into a common framework. Using our methodology, we evaluated and compared the observed signals preceding the latest M7.9 Sichuan earthquake (0511212008), M8.0 earthquake in Peru (0811512007), M7.6 Kashmir earthquake (1010812005) and M9.0 Sumatra earthquake (1212812004). We found evidence of the systematic appearance of both atmospheric and ionospheric anomalies preceding most of the major events during the period of our analysis 2001 -2008.

Taylor, Patrick↗
DOE OSTI2021

Beyond optimization—supervised learning applications in relativistic laser-plasma experiments

We explore the applications of machine learning techniques in relativistic laser-plasma experiments beyond optimization purposes. We predict the beam charge of electrons produced in a laser wakefield accelerator given the laser wavefront change caused by a deformable mirror. Machine learning enables feature analysis beyond merely searching for an optimal beam charge, showing that specific aberrations in the laser wavefront are favored in generating higher beam charges. Supervised learning models allow characterizing the measured data quality as well as recognizing irreproducible data and potential outliers. Furthermore, we also include virtual measurement errors in the experimental data to examine the model robustness under these conditions. This work demonstrates how machine learning methods can benefit data analysis and physics interpretation in a highly nonlinear problem of relativistic laser-plasma interaction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2019

Cloud Giovanni: Reining in Costs and Improving Performance with Analytical Data Stores Using Scalable Serverless Architecture

Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.

Zhang, Hailiang↗
DOE OSTI2017

Electric load shape benchmarking for small- and medium-sized commercial buildings

Small- and medium-sized commercial buildings owners and utility managers often look for opportunities for energy cost savings through energy efficiency and energy waste minimization. However, they currently lack easy access to low-cost tools that help interpret the massive amount of data needed to improve understanding of their energy use behaviors. Benchmarking is one of the techniques used in energy audits to identify which buildings are priorities for an energy analysis. Traditional energy performance indicators, such as the energy use intensity (annual energy per unit of floor area), consider only the total annual energy consumption, lacking consideration of the fluctuation of energy use behavior over time, which reveals the time of use information and represents distinct energy use behaviors during different time spans. To fill the gap, this study developed a general statistical method using 24-hour electric load shape benchmarking to compare a building or business/tenant space against peers. Specifically, the study developed new forms of benchmarking metrics and data analysis methods to infer the energy performance of a building based on its load shape. We first performed a data experiment with collected smart meter data using over 2,000 small- and medium-sized businesses in California. We then conducted a cluster analysis of the source data, and determined and interpreted the load shape features and parameters with peer group analysis. Finally, we implemented the load shape benchmarking feature in an open-access web-based toolkit (the Commercial Building Energy Saver) to provide straightforward and practical recommendations to users. The analysis techniques were generic and flexible for future datasets of other building types and in other utility territories.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
NASA NTRS1990

Information and problem report usage in system saftey engineering division

Five basic problems or question areas are examined. They are as follows: (1) Evaluate adequacy of current problem/performance data base; (2) Evaluate methods of performing trend analysis; (3) Methods and sources of data for probabilistic risk assessment; and (4) How is risk assessment documentation upgraded and/or updated. The fifth problem was to provide recommendations for each of the above four areas.

Morrissey, Stephen J.↗
NASA NTRS1986

Sequential estimation and satellite data assimilation in meteorology and oceanography

The central theme of this review article is the role that dynamics plays in estimating the state of the atmosphere and of the ocean from incomplete and noisy data. Objective analysis and inverse methods represent an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Four-dimensional data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric or oceanic model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and oceanic sciences, namely, mesoscale meteorology, medium and long-range forecasting, and upper-ocean dynamics.

Ghil, M.↗
NASA NTRS2021

Analysis of Nonlinear Shrinkage for the Bound Metal Deposition Manufacturing using Multi-scale Approach

We consider problem of nonlinear shrinkage of the metal part during bound metal deposition manufacturing on the ground and in zero-G. To analyze this problem we developed multi-scale physics-based approach that spans atomistic dynamics at the scale of nanoseconds and the full part shrinkage at the time scale of hours. Using this approach we estimated the key parameters of the problem including grain boundary width, coefficient of surface diffusion, initial redistribution of particles during debinding stage, micro-structure evolution from round particles to densely packed grains and corresponding change of the total and chemical free energy, and sintering stress. The introduced method was used to predict shrinkage at the level of two particles, filament cross-section, sub-model, and the whole green, brown, and metal parts. To further improve accuracy and reliability of the shrinkage predictions we propose concept of intelligent additive manufacturing of metal powders in space that combines the strengths of both physics-based and data-driven methods of analysis of AM.

bound metal deposition↗
NASA NTRS1990

Buckling analysis and test correlation of hat stiffened panels for hypersonic vehicles

The paper discusses the design, analysis, and test of hat stiffened panels subjected to a variety of thermal and mechanical load conditions. The panels were designed using data from structural optimization computer codes and finite element analysis. Test methods included the grid shadow moire method and a single gage force stiffness method. The agreement between the test data and analysis provides confidence in the methods that are currently being used to design structures for hypersonic vehicles. The agreement also indicates that post buckled strength may potentially be used to reduce the vehicle weight.

Percy, Wendy C.↗
DOE OSTI2018

First‐principles study in an inter‐granular glassy film model of silicon nitride

Abstract Based on a previously constructed intergranular glassy film ( IGF ) model for bulk silicon nitride, a large periodic model of 3864 atoms containing 2 grains of different orientations from the main bulk β‐Si 3 N 4 and 2 IGF s was fully relaxed using the ab initio density‐functional theory package VASP . The relaxed structure was then used to calculate the electronic structure, density of states, interatomic bonding, partial charge distribution, and electron localization using the OLCAO method. Analysis of the data focuses on the interfacial regions between bulk β‐Si 3 N 4 and the Si‐O‐N glass layer with different orientations. The total bond order density ( TBOD ) is evaluated in different interfacial and bulk regions. We show minor differences in the internal cohesion between crystalline grains of different facets. However, the overall charges in the bulk crystal grains and in the glassy regions are electropositive which are balanced by the negatively charged interfacial region between the two. The presence of a less rigid glassy layer is the reason for structural flexibility in ceramics without a huge penalty in the steric energy. The optimization of the interfacial structure and bonding via the creation of defective sites is the atomic origin for the existence of the IGF in silicon nitride. The insights obtained from this detailed quantum mechanical analysis of a realistic IGF model are discussed including implications on the strength, fracture toughness, and processing methods. We also discuss the potential applications of our method to other complex materials systems.

Ching, Wai‐Yim↗
NASA NTRS2017

Methods for Probabilistic Uncertainty Analysis and Bayesian Analysis with Examples of Statistically Analyzing Data to Revise MMOD Risk Estimates and Compare Models

Probabilistic methods are presented for characterizing and quantifying uncertainties in models and model predictions. Techniques are given for constructing specific uncertainty distributions based on available information. Alternative techniques are given for propagating uncertainties in model inputs to obtain the uncertainty in the model result or prediction. Bayesian techniques are also described for utilizing data and information to update and revise model results and predictions. The focus is on applications with numerous specific examples given. The use of data to revise Micrometeoroid and Orbital Debris (MMOD) risk prediction models are among the examples given.

Risk↗
DOE OSTI2018

Relationships between physical–geographical factors and soil degradation on agricultural land

Highlights: • Connection of soil degradation to seven physical-geographical variables was revealed. • New method of threshold data analysis was proposed. • Precise treshold values where soil degradation starts and ends were revealed. • Study area covered the entire area of Czech agricultural land – 13027 cadastres (78,866 km{sup 2}). It is a well-known fact that soil degradation is dramatically increasing and currently threatens agricultural soils all around the world. The objective of this study was to reveal the possible connection between soil degradation and seven physical-geographical factors - slope steepness, altitude, elevation differences, rainfall, temperature, soil texture and solar radiation – in the form of threshold values (if these exist), where soil degradation begins and ends. The analysis involved the whole area of the Czech Republic which consists of 13,027 cadasters (78,866 km{sup 2}). The greatest total degradation threat occurs in areas with slope steepness >7 degrees, average annual temperature 10.54, altitude >766 m a.s.l. Similarly, the results for water erosion, wind erosion, soil compaction, loss of organic matter, acidification and heavy metal contamination were processed. The results enable us to identify the relationships of different levels of threats which could consequently be used in various ways – for classification of threatened areas, for more effective implementation of anti-degradation measures, or purely for a better understanding of the role of physical geographical factors in soil degradation in the Czech Republic, and thus could increase the chances of reducing vulnerability to land degradation not only in the Czech Republic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

X-ray Absorption Spectroscopy Studies of a Molecular CO 2 -Reduction Catalyst Deposited on Graphitic Carbon Nitride

Metal-ligand complexes have been extensively explored as well-defined molecular catalysts in small molecule activation reactions such as carbon dioxide (CO 2 ) reduction. Many hybrid photocatalysts have been prepared by coupling such complexes with photoactive surfaces for use in solar CO 2 reduction. In this work, we employ X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopies, density functional theory (DFT) and computational XANES modeling to interrogate the structure of a hybrid photocatalyst consisting of a macrocyclic cobalt complex deposited on graphitic carbon nitride (C 3 N 4 ). Results show that the cobalt complex binds on C 3 N 4 through surface OH or NH 2 groups. By refining the local geometry and binding sites of this well-defined molecular cobalt complex on C 3 N 4 , here we established an important benchmark for modeling a large class of molecular catalysts that can be adapted to in situ/operando studies and further enhanced by applying chemometrics-based approaches and machine learning methods of XANES data analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Convolutional neural networks on the HEALPix sphere: a pixel-based algorithm and its application to CMB data analysis

We describe a novel method for the application of convolutional neural networks (CNNs) to fields defined on the sphere, using the Hierarchical Equal Area Latitude Pixelization scheme (HEALPix). Specifically, we have developed a pixel-based approach to implement convolutional and pooling layers on the spherical surface, similarly to what is commonly done for CNNs applied to Euclidean space. The main advantage of our algorithm is to be fully integrable with existing, highly optimized libraries for NNs (e.g., PyTorch, TensorFlow, etc.). We present two applications of our method: (i) recognition of handwritten digits projected on the sphere; (ii) estimation of cosmological parameter from simulated maps of the cosmic microwave background (CMB). The latter represents the main target of this exploratory work, whose goal is to show the applicability of our CNN to CMB parameter estimation. We have built a simple NN architecture, consisting of four convolutional and pooling layers, and we have used it for all the applications explored herein. Concerning the recognition of handwritten digits, our CNN reaches an accuracy of ~95%, comparable with other existing spherical CNNs, and this is true regardless of the position and orientation of the image on the sphere. For CMB-related applications, we tested the CNN on the estimation of a mock cosmological parameter, defining the angular scale at which the power spectrum of a Gaussian field projected on the sphere peaks. We estimated the value of this parameter directly from simulated maps, in several cases: temperature and polarization maps, presence of white noise, and partially covered maps. For temperature maps, the NN performances are comparable with those from standard spectrum-based Bayesian methods. For polarization, CNNs perform about a factor four worse than standard algorithms. Nonetheless, our results demonstrate, for the first time, that CNNs are able to extract information from polarization fields, both in full-sky and masked maps, and to distinguish between E and B -modes in pixel space. Lastly, we have applied our CNN to the estimation of the Thomson scattering optical depth at reionization ( τ ) from simulated CMB maps. Even without any specific optimization of the NN architecture, we reach an accuracy comparable with standard Bayesian methods. This work represents a first step towards the exploitation of NNs in CMB parameter estimation and demonstrates the feasibility of our approach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Application of photon Doppler velocimetry to direct impact Hopkinson pressure bars

Direct impact Hopkinson pressure bar systems offer many potential advantages over split Hopkinson pressure bars, including access to higher strain rates, higher strains for equivalent striker velocity and system length, lower dispersion, and faster achievement of force equilibrium. Currently, these advantages are gained at the expense of all information about the striker impacted specimen face, preventing the experimental determination of force equilibrium, and requiring approximations to be made on the sample deformation history. In this paper, we discuss an experimental method and complementary data analysis for using photon Doppler velocimetry to measure surface velocities of the striker and output bars in a direct impact bar experiment, allowing similar data to be recorded as in a split bar system. We discuss extracting velocity and force measurements, and the precision of measurements. Results obtained using the technique are compared to equivalent split bar tests, showing improved stress measurements for the lowest and highest strains in fully dense metals, and improvement for all strains in slow and non-equilibrating materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-T-354: Efficient and Enhanced QA Testing of Linear Accelerators Using a Real-Time Beam Monitor

Purpose: To investigate the feasibility of performing routine QA tests of linear accelerators (Linac) using the Integral Quality Monitoring (IQM) system. The system, consisting of a 1-D sensitivity gradient large area ion-chamber mounted at the collimator, allows automatic collection and analysis of beam data. Methods: The IQM was investigated to perform several QA constancy tests, similar to those recommended by AAPM TG142, of a Linac including: beam output, MLC calibration, beam symmetry, relative dose factor (RDF), dose linearity, output as a function of gantry angle and dose rate. All measurements by the IQM system accompanied a reference measurement using a conventional dosimetry system and were performed on an Elekta Infinity Linac with Agility MLC. The MLC calibration check is done using a Picket-Fence type 2×10cm{sup 2} field positioned at different off-axis locations along the chamber gradient. Beam symmetry constancy values are established by signals from an 4×4cm{sup 2} aperture located at various off-axis positions; the sensitivity of the test was determined by the changes in the signals in response to a tilt in the beam. The data for various square field sizes were used to develop a functional relationship with RDF. Results: The IQM tracked the beam output well within 1% of the reference ion-chamber readings. The Picket-Fence type field test detected a 1mm shift error of one MLC bank. The system was able to detect 2.5% or greater beam asymmetry. The IQM results for all other QA tests were found to agree with the reference values to within 0.5%. Conclusion: It was demonstrated that the IQM system can effectively monitor the Linac performance parameters for the purpose of routine QA constancy tests. With minimum user interactions a comprehensive set of tests can be performed efficiently, allowing frequent monitoring of the Linac. The presenting author’s salary is funded by the manufacturer of the QA device. All the other authors have financial interests with the commercialization of this QA device.

07 ISOTOPE AND RADIATION SOURCES↗