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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A survey of the radio continuum emission of RS Canum Venaticorum and related active binary systems

Observations of 77 RS CVn and related active binary systems were made with VLA at a continuum frequency of 4.86 GHz. The results are combined with other VLA observations to produce a total number of observed sources of 122. A search for correlations of radio properties with various systemic and stellar parameters is performed. Significant correlations are found between the normalized radio luminosity L(6)/L(bol) and the normalized soft X-ray luminosity L(x)/L(bol). It is suggested that the close correlation between low-level 6-cm emission and the hot component of the soft X-ray emission observed by the Einstein solid state spectrometer is caused by both emissions being produced by the same thermal electrons.

Drake, Stephen A.↗
NASA NTRS2017

Creep, Fatigue and Environmental Interactions and Their Effect on Crack Growth in Superalloys

Complex interactions of creep/fatigue/environment control dwell fatigue crack growth (DFCG) in superalloys. Crack tip stress relaxation during dwells significantly changes the crack driving force and influence DFCG. Linear Elastic Fracture Mechanics, Kmax, parameter unsuitable for correlating DFCG behavior due to extensive visco-plastic deformation. Magnitude of remaining crack tip axial stresses controls DFCG resistance due to the brittle-intergranular nature of the crack growth process. Proposed a new empirical parameter, Ksrf, which incorporates visco-plastic evolution of the magnitude of remaining crack tip stresses. Previous work performed at 704C, extend the work to 760C.

environmental interactions↗
NASA NTRS1995

The fundamental plane correlations for globular clusters

In the parameter space whose axes include a radius (core, or half-light), a surface brightness (central, or average within the half-light radius), and the central projected velocity dispersion, globular clusters lie on a two-dimensional surface (a plane, if the logarithmic quantities are used). This is analogous to the 'fundamental plane' of elliptical galaxies. The implied bivariate correlations are the best now known for globular clusters. The derived scaling laws for the core properties imply that cluster cores are fully virialized, homologous systems, with a constant (M/L) ratio. The corresponding scaling laws on the half-light scale are differrent, but are nearly identical to those derived from the 'fundamental plane' of ellipticals. This may be due to the range of cluster concentrations, which are correlated with other parameters. A similar explanation for elliptical galaxies may be viable. These correlations provide new empirical constraints for models of globular cluster formation and evolution, and may also be usable as rough distance-indicator relations for globular clusters.

Djorgovski, S.↗
DOE OSTI2024

Centrality definition in e + A collisions at the electron–ion collider

Here, in this work, we investigate the feasibility of defining centrality in electron–ion collisions at the electron–ion collider (EIC) by examining the correlation between the impact parameter and several observables, including total energy, total transverse momentum, and total number of particles. Using the BeAGLE Monte Carlo generator, we simulate e + Au and e + Ru collisions at different energies and analyze the correlation between the impact parameter and these observables across different kinematic regions. Our findings indicate that the correlation is weak in the central rapidity region but becomes stronger in the forward and far-forward rapidity regions. However, the correlation is not sufficiently robust to allow for precise centrality determination. We conclude that defining centrality in electron–ion collisions is more challenging than in ion–ion collisions, necessitating further studies to develop a robust centrality definition for the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

DBD plasma-assisted ethanol steam reforming for green H 2 production: Process optimization through response surface methodology (RSM)

Herein this work investigates ethanol steam reforming (ESR) to produce hydrogen (H 2 ) in a dielectric barrier discharge (DBD) plasma reactor. A five-level, three-factor experiment design was performed using a response surface methodology (RSM) to evaluate the combined effects of the three process parameters, including discharge power, total flow rate, and ethanol-to-water (EtOH/H 2 O) molar ratio on the plasma-assisted ESR reaction. Quadratic regression models were employed in RSM to fit the experimental results and present the correlation between process parameters and targeted responses (EtOH conversion, H 2 yield, H 2 selectivity, and specific energy requirement (SER) for H 2 production). The results suggested that the EtOH/H 2 O molar ratio is considered to have the most significant effect on the EtOH conversion and H 2 , H 2 selectivity, while the total flow rate is the most significant parameter determining SER for H 2 production. Process optimization demonstrated the optimal process conditions, including a discharge power of 55.9 W, a total flow rate of 26.7 ml/min, and an EtOH/H 2 O molar ratio equal to 0.34. A validation test was performed and confirmed the feasibility of the optimization process.

08 HYDROGEN↗
NASA NTRS1986

JPL pulsar timing observations. IV - Excess phase noise

Previously published tables of geocentric arrival times for 24 pulsars covering a 12 year span are extended here to 14.5 years. The list of pulsars is extended by nine, most of which were observed for about 4 years. Known positins of these new objects are confirmed, and limits on the proper motions are obtained. Large phase excursions in PSR 0525 + 21 are found. The orbital parameters of the binary pulsar 0820 + 02 are tentatively confirmed. Short-term timing noise in excess of that expected from receiver considerations alone is established. Variations in the timing residuals for the original 24 pulsars are analyzed for correlations with other observable parameters. Little significant correlation with changes in pulse shape or energy or with the drift correction is found on time scales of 500 pulses or longer.

Downs, G. S.↗
NASA NTRS1997

Prediction of human gait parameters from temporal measures of foot-ground contact

Investigation of the influence of human physical activity on bone functional adaptation requires long-term histories of gait-related ground reaction force (GRF). Towards a simpler portable GRF measurement, we hypothesized that: 1) the reciprocal of foot-ground contact time (1/tc); or 2) the reciprocal of stride-period-normalized contact time (T/tc) predict peak vertical and horizontal GRF, loading rates, and horizontal speed during gait. GRF data were collected from 24 subjects while they walked and ran at a variety of speeds. Linear regression and ANCOVA determined the dependence of gait parameters on 1/tc and T/tc, and prediction SE. All parameters were significantly correlated to 1/tc and T/tc. The closest pooled relationship existed between peak running vertical GRF and T/tc (r2 = 0.896; SE = 3.6%) and improved with subject-specific regression (r2 = 0.970; SE = 2.2%). We conclude that temporal measures can predict force parameters of gait and may represent an alternative to direct GRF measurements for determining daily histories of habitual lower limb loading quantities necessary to quantify a bone remodeling stimulus.

NASA Center ARC↗
DOE OSTI2022

Microstructural Development in Inconel 718 Nickel-Based Superalloy Additively Manufactured by Laser Powder Bed Fusion

Excellent weldability and high temperature stability make Inconel 718 (IN718) one of the most popular alloys to be produced by additive manufacturing. Here in this study, we investigated the effects of laser powder bed fusion (LPBF) parameters on the microstructure and relative density of IN718. The samples were fabricated with independently varied laser power (125 - 350W), laser scan speed (200 - 2200 mm/s), and laser scan rotation (0° - 90°). Archimedes’ method, optical microscopy, and scanning electron microscopy were employed to assess the influence of LPBF parameters on the relative density and microstructure. Optimal processing windows were identified for a wide range of processing parameters and relative density greater than 99.5% was achieved using volumetric energy density between 50 and 100 J/mm3. Microstructural features including melt pool geometry, lack of fusion defect, keyhole porosity, and sub-grain cellular microstructure were examined and quantified to correlate to LPBF parameters. A simple empirical model was postulated to relate relative sample density and LPBF volumetric energy density. Melt pool dimensions were quantitatively measured and compared to estimations based on Rosenthal solution, which yielded a good agreement with the width, but underestimated the depth, particularly at high energy input, due to lack of consideration for keyhole mode. In addition, the sub-grain cellular-dendritic microstructure in the as-built samples was observed to decrease with increasing laser scan speed. Quantification of the sub-micron cellular-dendritic microstructure yielded estimated cooling rate in the order of 10 5 – 10 7 K/s.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Process Optimization of Carbon Electrode Materials Manufacturing by Experimental Study and Machine Learning Techniques

Electrospun carbon fibers from coal have been investigated as electrodes for batteries and supercapacitors. Despite the excellent properties of coal-derived carbon fibers (CCNF) for energy storage devices, there still lacks systematic understanding on how various process parameters affect final electrode performances, which poses challenges to scale from pilot to high volume manufacturing. The goals of this project are twofold. First, we focuse on process optimization for converting a new precursor from powder river basin (PRB) coal, referred to as coal-based polyurethane (CPU) to CCNF using electrospinning. Second, different machine learning techniques will be examined using experimental data from this work and open literature. Specifically, for CPU the following process parameters need to be characterized and optimized in order to produce CCNFs with desirable mechanical integrity and physiochemical properties: precursor composition and viscosity, operating voltage and distance, oxidation and carbonization temperature and duration. Consequently, physiochemical properties of the fibers were characterized to correlate these process parameters with desirable electrochemical performance. Given the complex nature of the fiber production process, ML models are assessed for their ability to capture the nonlinear relationship between process parameters and the electrochemical properties in applications including supercapacitors. As such, we applied various machine learning techniques, to determine which technique produces a model that best predicts device function.

Cincotta, Robert E.F.↗
NASA NTRS1988

Basic research for the geodynamics program

Additional results are presented concerning a study that considers improvements over present Earth Rotation Parameter (ERP) determination methods by directly combining observations from various space geodetic systems in one adjustment. Earlier results are extended, showing that in addition to slight improvements in accuracy, substantial (a factor of three or more) improvements in precision and significant reductions in correlations between various parameters can be obtained (by combining Lunar Laser Ranging - LLR, Satellite Laser Ranging - SLR to Lageos, and Very Long Baseline Interferometry - VLBI data in one adjustment) as compared to results from individual systems. Smaller improvements are also seen over the weighted means of the individual system results. Although data transmission would not be significantly reduced, negligible additional computer time would be required if (standardized) normal equations were available from individual solutions. Suggestions for future work and implications for the New Earth Rotation Service (IERS) are also presented.

Mueller, Ivan I.↗
NASA NTRS1990

Distances of Galactic WC stars from emission-line fluxes and a quantification of the WC classification

The extent to which later-type WC stars in the Galaxy show constant flux in the carbon lines is assessed. It is found the the WC stars are an extremely 'well-behaved' sequence in terms of quantitative spectroscopic properties. The two classification parameters are closely correlated with a scatter of the order of uncertainty. There appear to be natural breaks in the sequence between subclasses, except between WC5 and 6. The classification is quantified using the C IV 5808 A/C III 5696 A ratio as the principal defining parameter for WC7-9 stars and the C III 5696 A/O V 5590 A ratio as the principal defining parameter for WC4-6 stars. Preliminary calibration of the line fluxes indicate that the flux of C IV 5808 A in Galactic WC stars is constant at F(0) 5808 = -log F(0)(5808) = 8.1 at 1 kpc for subclasses WC5-7. The intrinsic line flux ratio C(0) = log f(0)(5808/4650) is a smooth function of subclass number, decreasing from -0.22 dex for WC4 stars to -0.56 dex for WC9 stars.

Smith, Lindsey F.↗
DOE OSTI2018

Estimating the joint distribution of rate parameters across multiple reactions in the absence of experimental data

Here, a procedure for determining the joint uncertainty of Arrhenius parameters across multiple combustion reactions of interest is demonstrated. This approach is capable of constructing the joint distribution of the Arrhenius parameters arising from the uncertain measurements performed in specific target experiments without having direct access to the underlying experimental data. The method involves constructing an ensemble of hypothetical data sets with summary statistics consistent with the available information reported by the experimentalists, followed by a fitting procedure that learns the structure of the joint parameter density across reactions using this consistent hypothetical data as evidence. The procedure is formalized in a Bayesian statistical framework, employing maximum-entropy and approximate Bayesian computation methods and utilizing efficient Markov chain Monte Carlo techniques to explore data and parameter spaces in a nested algorithm. We demonstrate the application of the method in the context of experiments designed to measure the rates of selected chain reactions in the H 2 -O 2 system and highlight the utility of this approach for revealing the critical correlations between the parameters within a single reaction and across reactions, as well as for maximizing consistency when utilizing rate parameter information in predictive combustion modeling of systems of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
NASA NTRS2007

Short GRB Prompt and Afterglow Correlations

The Swift data set on short GRBs has now grown large enough to study correlations of key parameters. The goal is to compare long and short bursts to better understand similarities and differences in the burst origins. In this study we consider the both prompt and afterglow fluxes. It is found that the optical, X-ray and gamma-ray emissions are linearly correlated - stronger bursts tend to have brighter afterglows, and bursts with brighter X-ray afterglow tend to have brighter optical afterglow. Both the prompt and afterglow fluxes are, on average, lower for short bursts than for long. Although there are short GRBs with undetected optical emission, there is no evidence for "dark" short bursts with anomalously low opt/X ratios. The weakest short bursts have a low X-ray/gamma-ray ratio.

Gehrels, Neil↗
NASA NTRS2004

Maps Characterizing the Lunar Regolith Maturity

There are several parameters characterizing maturity of the lunar regolith. Most reliable of them are the ratio Is/FeO, characterizing relative concentration of nano-phase reduced iron, and the agglutinate content. The ratio Is/FeO is often called the degree of maturity of the lunar regolith. Studies of lunar samples show that the agglutinate content correlates with the maturity degree. Besides, the abundance of crystalline component, independently of its composition, anti-correlates with the maturity degree. In present paper we examine these correlations, mapping the parameter Is/FeO, the abundance of agglutinates in the lunar regolith, and the abundance of the crystalline component presented with pyroxene, plagioclase, olivine, and ilmenite. We use measurements of lunar samples made by Lunar Soil Characterization Consortium (LSCC) and multispectral lunar data of high spatial resolution available after the Clementine mission to the Moon.

V. Kaydash↗
DOE OSTI2022

Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems

Here we present the PI-CKL-NN method for parameter estimation in differential equation (DE) models given sparse measurements of the parameters and states. In the proposed approach, the space- or time-dependent parameters are approximated by Karhunen-Loeve (KL) expansions that are conditioned on the parameters’ measurements, and the states are approximated by deep neural networks (DNNs). The unknown weights in the KL expansions and DNNs are found my minimizing the cost function that enforces the measurements of the states the DE constraint. Regularization is achieved by adding the l2 norm of the conditional KL coefficients into the loss function. Our approach assumes that the parameter fields are correlated in space or time and enforces the statistical knowledge (the mean and the covariance function) in addition to the DE constraints and measurements as opposed to the physics-informed neural network (PINN) and other similar physics-informed machine learning methods where only DE constraints and data are used for parameter estimation. We use the PI-CKL-NN method for parameter estimation in an ordinary differential equation with an unknown time-dependent parameter and the one- and two-dimensional partial differential diffusion equations with unknown space-dependent diffusion coefficients. We also demonstrate that PI-CKL-NN is more accurate than the PINN method, especially when the observations of the parameters are very sparse

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗