Curve fitting complex X-ray photoelectron spectra of graphite-supported copper nanoparticles using informed line shapes
Not provided.
catalysis (heterogeneous), defects, membrane, carb↗
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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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Fast Automatic Knot Placement Method for Accurate B-spline Curve Fitting
The choice of knot vector has immense influence on the resulting accuracy of a B-spline approximation of a curve. However, despite the significance of this problem and the various solutions that were proposed in the literature, optimizing the number and placement of knots remains a difficult task. This paper presents a novel method for the approximation of a curve by a B-spline of arbitrary order, which automatically determines a knot vector that achieves high approximation quality. Additionally, at the core of our approach is a feature function that characterizes the amount and spatial distribution of geometric details in the input curve by estimating its derivatives. Knots are then selected in such a way as to evenly distribute the feature contents across their intervals. A comparison to the state of the art for a wide variety of curves shows that our method is faster and achieves more accurate reconstruction results, while typically reducing the number of necessary knots.
97 MATHEMATICS AND COMPUTING↗
A Prony-based curve-fitting method for characterization of RF pulses from optoelectronic devices
Not Available
42 ENGINEERING↗
Hybrid Curve Fitting For Reducing Motion Commands In Object Construction
Existing slicing software for additive manufacturing typically requires a triangulated mesh as its input. Triangulated meshes are approximate representations of exact CAD models. Despite the loss in dimensional accuracy, triangulated meshes are used because they are computationally easier to cross-section and offset than the exact geometry in CAD format. When a triangulated object is prepared, the resulting machine instructions include only linear motion commands. Numerous modern motion controllers can move in arc and spline motions; however, the absence of slicing software that supports curvature prevents these commands from being leveraged. To address this limitation, this paper presents a method for the hybrid reconstruction of arcs and splines as a post-processing step to traditional slicing. This method can greatly reduce the number of motion commands required to construct an object by printing smooth curved surfaces. This concise representation of tool-pathing allows for more even extrusion and is computed without a major impact on slicing time.
Wade, Charles↗
Reanalysis of subjective crackle ratings using a logistic curve fit.
Abstract not provided.
Swift, Stephen Hales↗
Two Views of the Radius Gap and the Role of Light Curve Fitting
Recently, several groups have resolved a gap that bifurcates planets between the size of Earth and Neptune into two populations. The location and depth of this feature is an important signature of the physical processes that form and sculpt planets. In particular, planets residing in the radius gap are valuable probes of these processes as they may be undergoing the final stages of envelope loss. Here, we discuss two views of the radius gap by Fulton & Petigura (F18) and Van Eylen et al. (V18). In V18, the gap is wider and more devoid of planets. This is due, in part, to V18's more precise measurements of planet radius R{sub p}. Thanks to Gaia, uncertainties in stellar radii R{sub ⋆} are no longer the limiting uncertainties in determining R{sub p} for the majority of Kepler planets; instead, errors in R{sub p}/R{sub ⋆} dominate. V18's analysis incorporated short-cadence photometry along with constraints on mean stellar density that enabled more accurate determinations of R{sub p}/R{sub ⋆}. In the F18 analysis, less accurate R{sub p}/R{sub ⋆} blurs the boundary the radius gap. The differences in R{sub p}/R{sub ⋆} are largest at high impact parameter (b≳0.8) and often exceed 10%. This motivates excluding high-b planets from demographic studies, but identifying such planets from long-cadence photometry alone is challenging. We show that transit duration can serve as an effective proxy, and we leverage this information to enhance the contrast between the super-Earth and sub-Neptune populations.
79 ASTRONOMY AND ASTROPHYSICS↗
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.↗
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↗
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↗
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↗
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↗
Low-Cost Heliostat for High-Flux Small-Area Receivers (Final Technical Report)
This project analyzed a two-stage heliostat concept consisting of a tracking stage and a concentrating stage. The tracking stage uses mirrors mounted on a common drive that move to track the sun. The concentrating stage consists of stationary mirrors that each have a unique angle to direct rays towards a small-area, high-flux, point-focused receiver. By splitting the collection and concentrating process into two stages, multiple small, inexpensive mirrors can share a structure and be controlled by a single drive in the tracking stage. The project effort developed modeling techniques that were specifically relevant to this two-stage heliostat concept. Both field-level and unit-level models were developed. The field-level model does not explicitly consider unit-level losses which are predicted by the unit-level model and then integrated into the field-level model through a correlation referred to as an efficiency modifier. This approach is referred to as the two-model approach; the development and demonstration of this two-model approach for a multi-stage heliostat technology is a key outcome of this work. The field-level model is used to design a field that hits a specific design day power given a set of heliostat design parameters. An oversized field is simulated and then heliostat units are removed based on their annual energy production in order to generate the highest performing field. The field reduction procedure fits a smooth curve fit to annual energy production as a function of position in the field which has the effect of reducing the noise that is otherwise caused by the Monte Carlo ray tracing technique. This approach is referred to as the annual energy fit method and substantially reduces computational run time for a given field level modeling accuracy. The annual energy fit approach enables the selection of a properly sized, high-performing field using orders of magnitude fewer rays than would otherwise be possible and the development of this approach is a second key outcome of this work. These models are used within a genetic optimization algorithm in order to optimize the geometric parameters associated with a heliostat in order to achieve the lowest cost per unit of collected design day power. The cost modeling that underlies the optimization is a simple, scaling type analysis backed up by a much more detailed Design for Manufacture and Assembly (DFMA) analysis. Although the figure of merit used for optimization was not cost per mirror area, this metric is reasonable to use as a means of comparison. The optimally designed 500 kW design has a tracking mirror specific cost of $181.85/m 2 , which is significantly larger than the target value and also larger than the current state of the art. The cost of the torque-tube type linkages contributed substantially to the overall cost. Based on this observation, potentially attractive alternative design configuration utilizing a capstan type actuation system should be investigated. Finally, NREL compared the performance of the two-stage heliostat to the performance of a focused and different sized flat conventional heliostats and showed that, as expected, additional losses versus the convention heliostat caused by a worse cosine efficiency, two stages of reflection, and interstage interactions. The two-stage heliostat requires around 75% more reflective area than a flat 1x1 meter conventional heliostat (similar to a focused heliostat) and 40% more than a flat 2x2 meter conventional heliostat.
14 SOLAR ENERGY↗
Extracting single fiber transverse and shear moduli from off-axis misalignment fiber tensile testing
Small diameter (<100 μm) fibers (e.g. carbon fibers, Kevlar, and fiberglass) and wires (e.g. ultrafine copper and aluminum wires) are frequently used in many different engineering applications, such as for light weighting structures, electromagnetic shielding for aircraft/infrastructure/EVs, vibration damping, biological sensors, aerospace electrical devices, and electric windings just to name a few. Due to the manufacturing process, the fibers and wires are pulled and stretched to produce a preferential alignment. Therefore, thin fibers and wires typically display different properties along the length of the fiber as opposed to their cross section and many fibers/wires are considered transversely isotropic. The axial properties of fibers/wires can be ascertained via tensile testing of single-filaments or fiber tows, but the radial properties require much more effort to measure. Knowing these properties is important for the accurate prediction of micromechanical models and manipulation of fibers during micromanufacturing. In this paper, a new technique was developed to determine the transverse/shear moduli and strength of a material by conducting tensile tests of the material at increasing misalignment angles from the tensile axis. Due to the transversely isotropic nature of the material, the transverse/shear moduli and strength influence the experimental results recorded by the test machine to different degrees based on the amount of misalignment in the test setup. An equation was derived to determine the influence of each of the material properties based on the misalignment angle by manipulating the stiffness matrix for transversely isotropic materials using the transformation matrices. Then, curve fitted coefficients were used to identify the material properties. Here, the strengths were similarly determined by curve fitting an off-axis Tsai-Hill failure criteria to determine the influence of transverse, shear, and tensile strengths based on the complex loading condition provided by the off-axis tensile test. Zoltek Panex 35 carbon fibers were used to demonstrate this new technique and the determined properties were then compared to those obtained from nanoindentation and from literature. Fracture surfaces provide insight into the different failure mechanisms at various misalignment angles.
36 MATERIALS SCIENCE↗
Implementation of Stochastic Gradient Descent in an Automated Glow Peak Identification Software for Multiple Thermoluminescent Dosimeter Types
A glow-curve analysis code was previously developed in C++ to analyze thermoluminescent dosimeter glow curves using automated peak detection while applying a first-order kinetics model. A newer version of this code was implemented to improve the automated peak detection and curve fitting models. The Stochastic Gradient Descent Algorithm was introduced to replace the prior approach of taking first and second-order derivatives for peak detection. Additionally, early stopping mechanisms were invoked to improve the previously used Levenberg-Marquardt Algorithm employed for curve fitting. The two software versions were compared through glow curve analysis of different thermoluminescent dosimeter materials and calculation of the corresponding figures of merit. Altogether improvements were shown, namely an increase in the number of peaks detected and a reduction of the mean figure of merit by approximately 46%.
137Cs↗
Quantitative XPS of plutonium: Evaluation of the Pu4f peak shape, relative sensitivity factors and estimated detection limits
We report that high-resolution X-ray photoelectron spectra have been acquired from sputter cleaned and in situ oxidized samples of α-plutonium and a face-centred cubic δ-plutonium–gallium alloy. The differences in the Pu4f peak shape in these two materials have been investigated, and the poorly screened satellite peaks have been quantified. Curve fitting parameters for the Pu4p 3/2 , Pu4d 5/2 , Pu4f and Pu6p 3/2 photoelectron peaks are reported, and relative sensitivity factors have been determined. The Pu4f curve fit model has been applied to data acquired using different spectrometers and alloys. Examples of quantification of the plutonium spectra are provided and minimum detection limits are calculated for common impurities in plutonium metal.
36 MATERIALS SCIENCE↗
Machine Learning Calabi–Yau Metrics
We apply machine learning to the problem of finding numerical Calabi–Yau metrics. Building on Donaldson's algorithm for calculating balanced metrics on Kähler manifolds, we combine conventional curve fitting and machine-learning techniques to numerically approximate Ricci-flat metrics. We show that machine learning is able to predict the Calabi–Yau metric and quantities associated with it, such as its determinant, having seen only a small sample of training data. Using this in conjunction with a straightforward curve fitting routine, we demonstrate that it is possible to find highly accurate numerical metrics much more quickly than by using Donaldson's algorithm alone, with our new machine-learning algorithm decreasing the time required by between one and two orders of magnitude.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Union through UNITY: Cosmology with 2000 SNe Using a Unified Bayesian Framework
Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the Universe’s expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of 2 in redshift, so compilations of multiple SN data sets are strongly beneficial. We assemble an up-to-date “Union” compilation of 2087 cosmologically useful SNe Ia from 24 data sets (“Union3”). We take care to put all SNe on the same distance scale and update the light-curve fitting with SALT3 to use the full rest-frame optical. Over the next few years, the number of cosmologically useful SNe Ia will increase by more than a factor of 10, and keeping systematic uncertainties subdominant will be more challenging than ever. We discuss the importance of treating outliers, selection effects, light-curve shape/color populations/standardization relations, unexplained dispersion, and heterogeneous observations simultaneously. We present an updated Bayesian framework, called UNITY1.5 (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to model selection effects, standardization, and systematic uncertainties compared to earlier analyses. As an analysis byproduct, we also recover the posterior of the SN-only peculiar-velocity field, although we do not interpret it in this work. We compute updated cosmological constraints with Union3 and UNITY1.5, finding weak 1.7σ–2.6σ tension with flat cold dark matter and possible evidence for thawing dark energy (w0 > − 1, wa < 0). We release our SN distances, light-curve fits, and UNITY1.5 framework to the community.
Rubin, David↗