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Results for “parameter correlations”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Degradation of impact toughness in cast stainless steels during long-term thermal aging

Cast austenitic stainless steels (CASSs) have been extensively used for the large components of nuclear reactor primary coolant systems. Since the cast steels inevitably contain degradable metastable phases and replacement of the large coolant system components is impractical, the thermal embrittlement of CASS components has been a serious concern in the extended-term operation of nuclear power plants. This study aimed to systematically measure and analyze the effect of long-term thermal aging on the Charpy impact toughness to provide a comprehensive understanding of thermal degradation behavior and a practical aging model to predict the degree of thermal degradation in the cast stainless steels. Additionally, the materials tested in the research include eight CASS alloys (two CF3s, one CF3M, three CF8s, and two CF8Ms) and two reference wrought materials (304L and 316L), in which the nominal δ-ferrite content ranges from ~2% to 33%. These stainless steels have been thermally aged at two light water reactor (LWR) temperatures (290 and 330 °C) and at two accelerated-aging temperatures (360 and 400 °C) for up to 30,000 h; these include both under-aged and over-aged conditions relative to the extended service lifetime (80 years). Charpy impact testing was performed for aged and non-aged specimens, and the impact (absorbed) energy parameters were correlated with a new aging parameter (A). Both the reduction of impact fracture toughness and the shift of ductile-brittle transition temperature were strongly dependent on the δ-ferrite content and degree of thermal aging. A linear relationship was found between the increasing rate of the index transition temperature T 41J and aging parameter A; base on which an empirical model was proposed for prediction of the transition temperature as a simple function of the aging parameter (A) and δ-ferrite content (F). Finally, the critical aging parameter for embrittlement (AC) was evaluated and compared with the existing δ-ferrite content criteria.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Operation and Optimization of Microwave-Heated Continuous-Flow Microfluidics

Microwave (MW) technology can be powerful for electrification and process intensification but limited fundamental understanding of scalability and design principles hinders its effective use. In this work, we build a continuous-flow microreactor inside a commercial single-mode MW applicator and the corresponding computational fluid dynamics model to simulate the temperature profile. The model is in good agreement with experiments for various microreactor dimensions and operating conditions. The model indicates that MW heating is greatly influenced by reactor geometry as well as the operating parameters. We observe a strong correlation between parameters and develop a gradient boost regression tree model to predict the outlet temperature accurately. This model is then applied to optimize the dimensions and operating conditions to maximize the outlet temperature and energy efficiency, resulting in a Pareto optimal. We demonstrate computationally and experimentally that it is possible to surpass the Pareto optimal and achieve an energy efficiency of ~90% or greater at temperatures relevant for liquid-phase chemistry via salting of the solvent. The present methodology can be applied to other complex MW reactors. Lastly, the combined numerical and experimental approach provides insights into and a framework for scale-up and optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗
NASA NTRS1991

Sensor data validation and reconstruction. Phase 1: System architecture study

The sensor validation and data reconstruction task reviewed relevant literature and selected applicable validation and reconstruction techniques for further study; analyzed the selected techniques and emphasized those which could be used for both validation and reconstruction; analyzed Space Shuttle Main Engine (SSME) hot fire test data to determine statistical and physical relationships between various parameters; developed statistical and empirical correlations between parameters to perform validation and reconstruction tasks, using a computer aided engineering (CAE) package; and conceptually designed an expert system based knowledge fusion tool, which allows the user to relate diverse types of information when validating sensor data. The host hardware for the system is intended to be a Sun SPARCstation, but could be any RISC workstation with a UNIX operating system and a windowing/graphics system such as Motif or Dataviews. The information fusion tool is intended to be developed using the NEXPERT Object expert system shell, and the C programming language.

Source record↗
NASA NTRS2004

Experiences with Probabilistic Analysis Applied to Controlled Systems

This paper presents a semi-analytic method for computing frequency dependent means, variances, and failure probabilities for arbitrarily large-order closed-loop dynamical systems possessing a single uncertain parameter or with multiple highly correlated uncertain parameters. The approach will be shown to not suffer from the same computational challenges associated with computing failure probabilities using conventional FORM/SORM techniques. The approach is demonstrated by computing the probabilistic frequency domain performance of an optimal feed-forward disturbance rejection scheme.

Kenny, Sean P.↗
NASA NTRSDate not supplied

A Sample/Jitter Monte Carlo Technique for Main Parachute Loads Predictions

Models for Orion parachute performance are based on reconstructions of the Capsule Parachute Assembly System (CPAS) drop test campaign and were documented in the CPAS “Model Memo.” Experience with similar Commercial Crew Program (CCP) parachute systems resulted in some updates to the Orion models in preparation for Artemis missions. The reefing cutter dispersion model for the drogues and mains had been overly-conservative by producing wide timing differences within clusters. A higher-fidelity timing model was generated by separating out in-lot variation and temperature effects. The main parachute inflation model had accounted for some correlations between parameters using complicated 2-D geometric bounding, but the results tended to exaggerate individual peak loads from fast (leading) inflations and under-emphasize actual lagging experience. Several flight tests were reconstructed again with an emphasis on matching peak load magnitudes using a search algorithm. A simpler method for generating inflation parameters uses the 3-D correlated reconstructed “samples” with some random “jitter” applied. Dispersed Monte Carlo inputs are then checked against flight test data to evaluate whether they represent reality.

parachutes↗
NASA NTRS1981

Correlations between solar wind parameters and auroral kilometric radiation intensity

The relationship between solar wind properties and the influx of energy into the nightside auroral region as indicated by the intensity of auroral kilometric radiation is investigated. Smoothed Hawkeye satellite observations of auroral radiation at 178, 100 and 56.2 kHz for days 160 through 365 of 1974 are compared with solar wind data from the composite Solar Wind Plasma Data Set, most of which was supplied by the IMP-8 spacecraft. Correlations are made between smoothed daily averages of solar wind ion density, bulk flow speed, total IMF strength, electric field, solar wind speed in the southward direction, solar wind speed multiplied by total IMF strength, the substorm parameter epsilon and the Kp index. The greatest correlation is found between solar wind bulk flow speed and auroral radiation intensity, with a linear correlation coefficient of 0.78 for the 203 daily averages examined. A possible mechanism for the relationship may be related to the propagation into the nightside magnetosphere of low-frequency long-wavelength electrostatic waves produced in the magnetosheath by the solar wind.

Gallagher, D. L.↗
NASA NTRS1977

Investigation of real-gas and viscous effects on the aerodynamic characteristics of a 40 deg half-cone with suggested correlations for the shuttle orbiter

Parameters were evaluated that might be used to correlate shuttle orbiter aerodynamic data to be used in extrapolating from wind-tunnel to flight conditions. Preliminary calculations indicate that the lee-side forces will have an insignificant influence on the aerodynamic characteristics of the orbiter for moderate angle-of-attack entries; therefore, this work is focused on phenomena which have an overriding influence on windward forces, namely, real-gas (equilibrium and nonequilibrium) and viscous-interaction effects. Analytically determined flow fields previously obtained on 40 deg blunted cones were used as a data source to evaluate various correlation parameters. Inviscid effects were found to be the dominant contributor to the aerodynamic coefficients in the altitude range of 64 to 76.2 km. The most suitable correlation of the aerodynamic forces on these cones is based on local dynamic pressure and local Mach number.

Hunt, J. L.↗
DOE OSTI2024

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗
NASA NTRS2014

Liquid Oxygen Thermodynamic Vent System Testing with Helium Pressurization

This report presents the results of several thermodynamic vent system (TVS) tests with liquid oxygen plus a test with liquid nitrogen. In all tests, the liquid was heated above its normal boiling point to 111 K for oxygen and 100 K for nitrogen. The elevated temperature was representative of tank conditions for a candidate lunar lander ascent stage. An initial test series was conducted with saturated oxygen liquid and vapor at 0.6 MPa. The initial series was followed by tests where the test tank was pressurized with gaseous helium to 1.4 to 1.6 MPa. For these tests, the helium mole fraction in the ullage was quite high, about 0.57 to 0.62. TVS behavior is different when helium is present than when helium is absent. The tank pressure becomes the sum of the vapor pressure and the partial pressure of helium. Therefore, tank pressure depends not only on temperature, as is the case for a pure liquid-vapor system, but also on helium density (i.e., the mass of helium divided by the ullage volume). Thus, properly controlling TVS operation is more challenging with helium pressurization than without helium pressurization. When helium was present, the liquid temperature would rise with each successive TVS cycle if tank pressure was kept within a constant control band. Alternatively, if the liquid temperature was maintained within a constant TVS control band, the tank pressure would drop with each TVS cycle. The final test series, which was conducted with liquid nitrogen pressurized with helium, demonstrated simultaneous pressure and temperature control during TVS operation. The simultaneous control was achieved by systematic injection of additional helium during each TVS cycle. Adding helium maintained the helium partial pressure as the liquid volume decreased because of TVS operation. The TVS demonstrations with liquid oxygen pressurized with helium were conducted with three different fluid-mixer configurations-a submerged axial jet mixer, a pair of spray hoops in the tank ullage, and combined use of the axial jet and spray hoops. A submerged liquid pump and compact heat exchanger located inside the test tank were used with all the mixer configurations. The initial series without helium and the final series with liquid nitrogen both used the axial jet mixer. The axial jet configuration successfully demonstrated the ability to control tank pressure; but in the normal-gravity environment, the temperature in the upper tank region (ullage and unwetted wall) was not controlled. The spray hoops and axial jet combination also successfully demonstrated pressure control as well as temperature control of the entire tank and contents. The spray-hoops-only configuration was not expected to be a reliable means of tank mixing because there was no direct means to produce liquid circulation. However, surprisingly good results also were obtained with the sprayhoops- only configuration (i.e., performance metrics such as cycle-averaged vent flowrate were similar to those obtained with the other configurations). A simple thermodynamic model was developed that correctly predicted the TVS behavior (temperature rise or pressure drop per TVS cycle) when helium was present in the ullage. The model predictions were correlated over a range of input parameters. The correlations show that temperature rise or pressure drop per cycle was proportional to both helium mole fraction and tank heat input. The response also depended on the tank fill fraction: the temperature rise or pressure drop (per TVS cycle) increased as the ullage volume decreased.

Thermodynamic vent system↗
DOE OSTI2018

Parameter constraints from cross-correlation of CMB lensing with galaxy clustering

The lensing convergence measurable with future CMB surveys like CMB-S4 will be highly correlated with the clustering observed by deep photometric large scale structure (LSS) surveys such as the LSST, with cross-correlation coefficient as high as 95%. This will enable use of sample variance cancellation techniques to determine cosmological parameters, and use of cross-correlation measurements to break parameter degeneracies. Assuming large sky overlap between CMB-S4 and LSST, we show that a joint analysis of CMB-S4 lensing and LSST clustering can yield very tight constraints on the matter amplitude σ 8 (z), halo bias, and f NL , competitive with the best stage IV experiment predictions, but using complementary methods, which may carry different and possibly lower systematics. Having no sky overlap between experiments degrades the precision of σ 8 (z) by a factor of 20, and that of f NL by a factor of 1.5 to 2. Without CMB lensing, the precision always degrades by an order of magnitude or more, showing that a joint analysis is critical. Here, our results also suggest that CMB lensing in combination with LSS photometric surveys is a competitive probe of the evolution of structure in the redshift range z ≃ 1–7, probing a regime that is not well tested observationally. We explore predictions against other surveys and experiment configurations, finding that wide patches with maximal sky overlap between CMB and LSS surveys are most powerful for σ 8 (z) and f NL .

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

Koren, Ilan↗
NASA NTRS1973

Lake Superior water quality near Duluth from analysis of aerial photos and ERTS imagery

ERTS imagery of Lake Superior in the late summer of 1972 shows dirty water near the city of Duluth. Water samples and simultaneous photographs were taken on three separate days following a heavy storm which caused muddy runoff water. The water samples were analyzed for turbidity, color, and solids. Reflectance and transmittance characteristics of the water samples were determined with a spectrophotometer apparatus. This same apparatus attached to a microdensitometer was used to analyze the photographs for the approximate colors or wavelengths of reflected energy that caused the exposure. Although other parameters do correlate for any one particular day, it is only the water quality parameter of turbidity that correlates with the aerial imagery on all days, as the character of the dirty water changes due to settling and mixing.

Scherz, J. P.↗
NASA NTRS1976

Comet brightness parameters: Definition, determination, and correlations

The power-law definition of comet brightness is reviewed and possible systematic influences are discussed that can affect the derivation of m sub o and n values from visual magnitude estimates. A rationale for the Bobrovnikoff aperture correction method is given and it is demonstrated that the Beyer extrafocal method leads to large systematic effects which if uncorrected by an instrumental relationship result in values significantly higher than those derived according to the Bobrovnikoff guidelines. A series of visual brightness parameter sets are presented which have been reduced to the same photometric system. Recommendations are given to insure that future observations are reduced to the same system.

Meisel, D. D.↗
NASA NTRS1990

On the correlation between a magnetopause penetration parameter and FTE occurrence

Impulsive plasma penetration has been proposed as a means by which solar wind plasma may cross the magnetopause and enter the magnetosphere. It has been predicted that plasma entry by this means will be correlated with a magnetopause penetration parameter. One of the most important signatures of plasma entry into the magnetosphere are flux transfer events (FTEs). If plasma penetration is an important mechanism in plasma entry, then it would be expected that the occurrence of flux transfer events will correlate with the penetration parameter. On the other hand, if reconnection is, as widely believed, the dominant mechanism for the entry of solar-wind plasma into the magnetosphere, then plasma entry will be correlated with the north/south IMF component. AMPTE UKS data show that the occurrence of FTE signatures is better correlated with the direction of the IMF than with the penetration parameter. Thus, impulsive plasma penetration is unlikely to be the mechanism responsible for FTEs.

Smith, M. F.↗
DOE OSTI2020

Single-Step Shear-Based Deformation Processing of Electrical Conductor Wires

Commercial electrical conductor wires are currently produced from aluminum alloys by multi-step deformation processing involving rolling and drawing. These processes typically require 10 to 20 steps of deformation, since the plastic strain or reduction that can be imposed in a single step is limited by material workability and process mechanics. Here, we demonstrate a fundamentally different, single-step approach to produce flat wire aluminum products using machining-based deformation that also ensures adequate material workability in the formed product. Two process routes are proposed: (1) chip formation by free-machining (FM), with a post-machining, light drawing reduction (<20%) to achieve desired finish and (2) constrained chip formation by large strain extrusion machining (LSEM). Using commercially pure aluminum conductor alloys (Al 1100 and EC1350) as representative material systems, we demonstrate key features of the machining-based processing, including (a) single-step processing to achieve flat wire geometries, (b) surface finish (Ra = 0.2 to 1.0 μm) comparable to that of commercial wire products made by drawing/rolling, (c) deformation control independent of wire size, and (d) hardness increases of 50–150% over that of annealed wires, while retaining high electrical conductivity (>56% IACS). Here, the wire microstructure, which can also be varied via the large-strain deformation parameters, is correlated with mechanical and electrical properties. Implications for commercial manufacture of flat wire products are discussed.

36 MATERIALS SCIENCE↗