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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Frequency-Domain Identification With Composite Curve Fitting

Improved method of parameter identification based on decomposing single wide-band model into two or more component systems in parallel. Each component model predominates in specific frequency range. Wide-band mathematical model of system identified as two narrow-band models: one containing most of information on high-frequency components of dynamics, and one containing most of information on low-frequency components. Applicable to diverse systems, including vibrating structures, electronic circuits, and control systems.

Bayard, David S.↗
NASA NTRS2003

Curve Fitting Solar Cell Degradation Due to Hard Particle Radiation

This paper investigates the suitability of the equation for accurately defining solar cell parameter degradation as a function of hard particle radiation. Y = Y/sub o/ + C/sub 1/ * Log(1 + /spl phi///spl phi//sub x/) + C/sub 2/ * Log(1 + /spl phi///spl phi//sub y/) The paper also provides methods for determining the constants in the equation and compares results from this equation to those obtained by the more traditionally used. Y = /spl Sigma/(a/sub i/ * [In(/spl phi/)]/sup i/)

Edward M. Gaddy↗
NASA NTRS2017

Feature Detection and Curve Fitting Using Fast Walsh Transforms for Shock Tracking: Applications

Walsh functions form an orthonormal basis set consisting of square waves. Square waves make the system well suited for detecting and representing functions with discontinuities. Given a uniform distribution of 2p cells on a one-dimensional element, it has been proven that the inner product of the Walsh Root function for group p with every polynomial of degree < or = (p - 1) across the element is identically zero. It has also been proven that the magnitude and location of a discontinuous jump, as represented by a Heaviside function, are explicitly identified by its Fast Walsh Transform (FWT) coefficients. These two proofs enable an algorithm that quickly provides a Weighted Least Squares fit to distributions across the element that include a discontinuity. The detection of a discontinuity enables analytic relations to locally describe its evolution and provide increased accuracy. Time accurate examples are provided for advection, Burgers equation, and Riemann problems (diaphragm burst) in closed tubes and de Laval nozzles. New algorithms to detect up to two C0 and/or C1 discontinuities within a single element are developed for application to the Riemann problem, in which a contact discontinuity and shock wave form after the diaphragm bursts.

Gnoffo, Peter A.↗
NASA NTRS2021

Curve Fits of the NIST-JANNAF Thermochemical Tables Fourth Edition

Piecewise polynomial coefficients providing ideal gas, temperature-dependent molar specific heat, enthalpy, and entropy are tabulated for 1,068 common elemental and molecular species from the Fourth Edition (1998) to the NIST-JANAF Thermochemical Tables. The coefficients provide predictive values covering a wide range of temperatures (in many cases for gas state species from 298.15 to 6,000 K). A total of 1,760 fits are provided covering both single states (for example, gas, liquid, and crystal) and multiple states (crystal and liquid). Appropriate units and reference states are used for the two different fit formats, but the requisite procedure to adjust the coefficients for any other units and reference states is discussed.

high temperature properities↗
DOE OSTI2024

Constrained curve fitting for semi-parametric models with radial basis function networks

Common to many analysis pipelines in lattice gauge theory and the broader scientific discipline is the need to fit a semi-parametric model to data. We propose a fit method that utilizes a radial basis function network to approximate the non-parametric component of such models. The approximate parametric model is fit to data using the basin hopping global optimization algorithm. Parameter constraints are enforced through Gaussian priors. The viability of our method is tested by examining its use in a finite-size scaling analysis of the $q$-state Potts model and $p$-state clock model with $q=2,3$ and $p=4,\infty$.

Peterson, Curtis T.↗
NASA NTRS2019

Bit Error Rate and Frame Error Rate Data Processing for Space Communications and Navigation-Related Communication System Analysis Tools

One of the capabilities that the Space Communications and Navigation (SCaN) Strategic Center for Networking, Integration, and Communications (SCENIC) user interface (UI) web application intends to provide its users is the addition of network protocol and link encryption augmentations of communication system analyses. Before any of these analyses capabilities can be modeled, the simulations of bit error rate (BER) and frame error rate (FER) against signal-to-noise ratio (SNR) have been conducted, requiring parameters from several known coding types (low-density parity-check (LDPC), convolutional, etc.), signal modulations (binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), etc.), coding rates (1/2, 1/3, etc.), and frame sizes (1,280, 3,580, etc.). However, in order to extract useful information from the results of these simulations, a curve fitting technique has been applied to each resulting dataset to extend and extrapolate the curve fit of BER and FER down to 10–30 using MATLAB® Curve Fitting Toolbox™ (The MathWorks, Inc.). This is a necessary step because simulations of BER and FER were only performed to around 10–9 due to the extensive simulation time that would be required to obtain significant simulation results at the error levels desired. Furthermore, the fitted curve results were applied to a finer resolution for the SNR at 0.01-dB interval instead of the 0.05-dB interval limitation used in the simulation. All the possible combinations of the coding types, signal modulations, coding rates, frame sizes, and the extension of BER and FER curves would enable users to capture a wide range of link performances that directly relates to the addition of higher level networking data encapsulated in a frame. The curve fitting results also led to the modeling of the optical link error rate performance by solving for coding gain, FER_BER SNR delta, coded optical BER-SNR, and coded optical FER–SNR.

Communication link analysis↗
DOE OSTI2024

Irradiation Results of Commercial Neutron and Gamma Sensors at the Ohio State University Research Reactor

This report serves to present the evaluation results of commercial radiation detectors (SPNDs) with the potential to accomplish the data objectives—having sufficient gamma and fast neutron sensitivity—at temperatures near 650°C. The detectors chosen for evaluation are gamma ion chambers from Exosens (previously known as Photonis) models CRGA11 and CRGE32 and tantalum-based self-powered neutron detectors (Ta-SPND) from Mirion. The evaluation was performed in a series of heat irradiations from ambient to 850°C in the 9.5-inch dry tube furnace at the Ohio State University Research Reactor (OSURR). Ion chamber counting curves were measured to evaluate sensor operability at temperature. Detector sensitivity to reactor power and temperature were measured and presented in curve fit parameters. The curve fit equations were used to identify the suggested operational temperatures based on reactor power. Overall, it was evaluated that the CRGA11 was not significantly affected by temperatures up to 650°C and is operable—with higher temperature-contributed signals—up to 700°C. The CRGE32 was more affected by the high temperatures compared to the CRGA11. As a result of increasing temperature, the leakage current was a dominating factor. While the detector can operate up to 600°C and 700°C with lowered high voltage, it is not recommended unless a suitably strong gamma flux field is present. Finally, Ta SPND did not demonstrate good performance beyond 350°C due to the presence of an unknown phenomenon at changing temperatures. The study of the phenomenon is an active research topic outside the scope of this project.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Single Grid Error Estimation for Neutron Transport Solvers

The method of nearby problems (MNP) is a solution verification technique that does not require the use of multiple spatial grids. To estimate spatial discretization error without requiring a high-fidelity spatial grid, an analytical curve fit is interpolated from the numerical solution. The residual between the curve fit solution and numerical solution is calculated and added as an additional source term to the governing equation. The nearby solution is estimated using the updated source term and boundary conditions to remain consistent with the curve fit interpolation. The nearby solution can be compared to the curve fit solution as a discretization error estimation while using a single spatial grid. Without the use of higher fidelity spatial grids, the MNP is able to approximate the spatial discretization error, a facet of solution verification. The application of the method of nearby problems is presented for one- and two-dimensional neutron transport problems for both fixed source and criticality problems on the spatial variable. The fixed source results demonstrate the effectiveness of nearby problems for spatial error identification using the discrete ordinates method. Criticality results are shown to identify area of high spatial error for the C5G7 problem as well as for the discrete ordinates solver. A novel approach of combining the capabilities of Monte Carlo with the discrete ordinates nearby problems is presented for one- and two-dimensional fixed source problems. In conclusion, the MNP demonstrates its effectiveness at identifying spatial error on a single structured grid with a wide variety of neutron transport problems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1975

On the cost of approximating and recognizing a noise perturbed straight line or a quadratic curve segment in the plane

Approximation of noisy data in the plane by straight lines or elliptic or single-branch hyperbolic curve segments arises in pattern recognition, data compaction, and other problems. The efficient search for and approximation of data by such curves were examined. Recursive least-squares linear curve-fitting was used, and ellipses and hyperbolas are parameterized as quadratic functions in x and y. The error minimized by the algorithm is interpreted, and central processing unit (CPU) times for estimating parameters for fitting straight lines and quadratic curves were determined and compared. CPU time for data search was also determined for the case of straight line fitting. Quadratic curve fitting is shown to require about six times as much CPU time as does straight line fitting, and curves relating CPU time and fitting error were determined for straight line fitting. Results are derived on early sequential determination of whether or not the underlying curve is a straight line.

Cooper, D. B.↗
DOE OSTI2022

Surface analysis insight note: Differentiation methods applicable to noisy data for determination of sp2‐ versus sp3‐hybridization of carbon allotropes and AES signal strengths

The derivatives of the spectra are commonly used for quantification in Auger Electron Spectroscopy (AES) spectra, while the derivative of the KLL C Auger line has proven to be valuable in obtaining a measure of the relative proportions of sp 2 ‐ and sp 3 ‐hybridization using the D‐parameter in both AES and X‐ray Photoelectron Spectroscopy (XPS). Differentiation of X‐ray Photoelectron Spectroscopy (XPS) and Auger Electron Spectroscopy (AES) spectra by numerical means is presented and illustrated for polymeric, such as PEEK and Nylon, as well as for graphitic materials including highly ordered pyrolytic graphite and graphene oxide. The most commonly available Savitzky–Golay method is explained mathematically and developed through the case of constructing a 5‐point quadratic polynomial convolution kernel suitable for differentiating spectra of adequate signal to noise. The concept of differentiation of spectra where signal to noise is less than adequate is also developed. Two alternative strategies to Savitzky–Golay differentiation are presented, which fit curves to data that allow derivatives to be obtained where Savitzky–Golay would otherwise fail. These alternative methods involve constructing a parametric curve that fits data over the entire energy interval of interest. Derivatives of spectra are then obtained by differentiating these parametric curves directly. A comparison of results for different materials for which specific sp 2 ‐ vs sp 3 ‐hybridized carbon proportions are of interest is used to emphasize the importance of characterizing methods used to differentiate spectra and understanding the characteristics of instrumentation used to measure spectra. The case for using Principal Component Analysis noise reduction with C KLL spectra is made for spectra collected from a heterogeneous graphene oxide sample.

Fairley, Neal↗
DOE OSTI2025

Brillouin Sensing with PCA, and PCA-Based Neural Networks for Efficient Temperature Monitoring

This work explores peak estimation techniques in Brillouin Optical Time Domain Analysis (BOTDA), emphasizing both accuracy and efficiency. Euclidean distance measurement method is applied to principal components derived from Brillouin Gain Spectrum data. It offers a major speed advantage being 180 170 times faster than traditional curve fitting methods such as Lorentzian curve fitting, while maintaining similar accuracy. Additionally, a PCA- based neural network model shows significant reduction of peak estimation time compared to Lorentzian fitting. Results show Brillouin frequency shift errors lie under 0.75 MHz in both Euclidean distance-based and neural network-based methods, both of which utilize PCA components. For large data sets and long length fibers, PCA- assisted neural network for peak estimation would be an efficient solution.

Distributed optical fiber sensing↗
NASA NTRS1990

Scaling laws for light-weight optics

Scaling laws for light-weight optical systems are examined. A cubic relationship between mirror diameter and weight has been suggested and used by many designers of optical systems as the best description for all light-weight mirrors. A survey of existing light-weight systems in the open literature has been made to clarify this issue. Fifty existing optical systems were surveyed with all varieties of light-weight mirrors including glass and beryllium structured mirrors, contoured mirrors, and very thin solid mirrors. These mirrors were then categorized and weight to diameter ratio was plotted to find a best fit curve for each case. A best fitting curve program tests nineteen different equations and ranks a 'goodness of fit' for each of these equations. The resulting relationship found for each light-weight mirror category helps to quantify light-weight optical systems and methods of fabrication and provides comparisons between mirror types.

Valente, Tina M.↗
NASA NTRS1990

Computer codes for the evaluation of thermodynamic properties, transport properties, and equilibrium constants of an 11-species air model

The computer codes developed provide data to 30000 K for the thermodynamic and transport properties of individual species and reaction rates for the prominent reactions occurring in an 11-species nonequilibrium air model. These properties and the reaction-rate data are computed through the use of curve-fit relations which are functions of temperature (and number density for the equilibrium constant). The curve fits were made using the most accurate data believed available. A detailed review and discussion of the sources and accuracy of the curve-fitted data used herein are given in NASA RP 1232.

Thompson, Richard A.↗
NASA NTRS1991

Computer codes for the evaluation of thermodynamic and transport properties for equilibrium air to 30000 K

The computer codes developed here provide self-consistent thermodynamic and transport properties for equilibrium air for temperatures from 500 to 30000 K over a temperature range of 10 (exp -4) to 10 (exp -2) atm. These properties are computed through the use of temperature dependent curve fits for discrete values of pressure. Interpolation is employed for intermediate values of pressure. The curve fits are based on mixture values calculated from an 11-species air model. Individual species properties used in the mixture relations are obtained from a recent study by the present authors. A review and discussion of the sources and accuracy of the curve fitted data used herein are given in NASA RP 1260.

Thompson, Richard A.↗
NASA NTRS1972

Development of equilibrium air computer programs suitable for numerical computation using time-dependent or shock-capturing methods

Computer programs were developed which compute the thermodynamic properties of equilibrium air for use in either the time-dependent or shock-capturing computational methods. For the time-dependent method, tne NASA-ARC RGAS computer program was modified to allow internal energy and density to be used as the independent variables. In addition, simplified-curve fits for p = p(e,rho), a = a(e,rho), and T = T(p,rho) were devised to reduce computer time. For the shock-capturing method a simplified curve fit for h = h(p,rho) was made. These approximate curve fits may be particularly useful when employed on advanced computers such as the Illiac 4 or the CDC Star since they avoid the cumbersome table-lookup feature of the RGAS program.

Tannehill, J. C.↗
NASA NTRS1986

Three-Dimensional Turbomachine-Blade-Row Analysis Code

Computer program (MERNEW3D) developed that prepares bulk of input data set required for Denton three-dimensional inviscid turbomachine-blade-row analysis code. Denton input generated from minimum of geometry and flow-variable information by using cubic spline curve fits for interpolation and extrapolation. Curve-fitting procedures taken from previously developed and widely used NASA computer program (MERIDL), which performs meridional streamsurface analysis.

Glassman, A. J.↗