Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Gaussian distribution”

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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Characterization of groove density variation of VLS gratings with ALS XROL LTP-II in different operation modes

The long trace profiler, LTP-II, available at the Advanced Light Source (ALS) X-ray Optics Laboratory (XROL), was recently upgraded by replacing a multimode diode laser light source with a single-mode, wavelength-stabilized, fibercoupled diode laser system. The upgrade enables us to reliably characterize the lateral variation of groove density of variable-line-spacing (VLS) x-ray diffraction gratings. Here, we discuss the LTP-II performance with an example of measurements with a VLS grating with the groove density at the grating center of 300 lines/mm. For the measurements, we use the LTP-II in two different operation arrangements, the single Gaussian beam and the pencil beam interferometer arrangements. For each operation arrangement, we apply two data processing algorithms: with calculating the centroid position and with determining the position of a characteristic features of the detected beam intensity distributions. Additionally, we discuss the observed strong correlation between the LTP-II modes of operation and the resulted (extracted) groove density variations. We also speculate on possible origin of the correlation.

42 ENGINEERING↗
DOE OSTI2022

Tsuchinoko v1.0.0

Tsuchinoko is a Qt application for adaptive experiment execution and tuning. Live visualizations show details of measurements, and provide feedback on the adaptive engine's decision-making process. The parameters of the adaptive engine can also be tuned live to explore and optimize the search procedure. While Tsuchinoko is designed to allow custom adaptive engines to drive experiments, the gpCAM engine is a featured inclusion. This tool is based on a flexible and powerful Gaussian process regression at the core. A Tsuchinoko system includes 4 distinct components: the GUI client, an adaptive engine, and execution engine, and a core service. These components are separable to allow flexibility with a variety of distributed designs.

Pandolfi, Ronald↗
NASA NTRS1986

Unified control/structure design and modeling research

To demonstrate the applicability of the control theory for distributed systems to large flexible space structures, research was focused on a model of a space antenna which consists of a rigid hub, flexible ribs, and a mesh reflecting surface. The space antenna model used is discussed along with the finite element approximation of the distributed model. The basic control problem is to design an optimal or near-optimal compensator to suppress the linear vibrations and rigid-body displacements of the structure. The application of an infinite dimensional Linear Quadratic Gaussian (LQG) control theory to flexible structure is discussed. Two basic approaches for robustness enhancement were investigated: loop transfer recovery and sensitivity optimization. A third approach synthesized from elements of these two basic approaches is currently under development. The control driven finite element approximation of flexible structures is discussed. Three sets of finite element basic vectors for computing functional control gains are compared. The possibility of constructing a finite element scheme to approximate the infinite dimensional Hamiltonian system directly, instead of indirectly is discussed.

Mingori, D. L.↗
NASA NTRS2008

Mitigating Photon Jitter in Optical PPM Communication

A theoretical analysis of photon-arrival jitter in an optical pulse-position-modulation (PPM) communication channel has been performed, and now constitutes the basis of a methodology for designing receivers to compensate so that errors attributable to photon-arrival jitter would be minimized or nearly minimized. Photon-arrival jitter is an uncertainty in the estimated time of arrival of a photon relative to the boundaries of a PPM time slot. Photon-arrival jitter is attributable to two main causes: (1) receiver synchronization error [error in the receiver operation of partitioning time into PPM slots] and (2) random delay between the time of arrival of a photon at a detector and the generation, by the detector circuitry, of a pulse in response to the photon. For channels with sufficiently long time slots, photon-arrival jitter is negligible. However, as durations of PPM time slots are reduced in efforts to increase throughputs of optical PPM communication channels, photon-arrival jitter becomes a significant source of error, leading to significant degradation of performance if not taken into account in design. For the purpose of the analysis, a receiver was assumed to operate in a photon- starved regime, in which photon counts follow a Poisson distribution. The analysis included derivation of exact equations for symbol likelihoods in the presence of photon-arrival jitter. These equations describe what is well known in the art as a matched filter for a channel containing Gaussian noise. These equations would yield an optimum receiver if they could be implemented in practice. Because the exact equations may be too complex to implement in practice, approximations that would yield suboptimal receivers were also derived.

Moision, Bruce↗
DOE OSTI2020

Reinforcement Learning via Gaussian Processes with Neural Network Dual Kernels

While deep neural networks (DNNs) and Gaussian Processes (GPs) are both popularly utilized to solve problems in reinforcement learning, both approaches feature undesirable drawbacks for challenging problems. DNNs learn complex non-linear embeddings, but do not naturally quantify uncertainty and are often data-inefficient to train. GPs infer posterior distributions over functions, but popular kernels exhibit limited expressivity on complex and high-dimensional data. Fortunately, recently discovered conjugate and neural tangent kernel functions encode the behavior of overparameterized neural networks in the kernel domain. We demonstrate that these kernels can be efficiently applied to regression and reinforcement learning problems by analyzing a baseline case study.We apply GPs with neural network dual kernels to solve reinforcement learning tasks for the first time. We demonstrate, using the well understood mountain-car problem, that GPs empowered with dual kernels perform at least as well as those using the conventional radial basis function kernel. Finally, we conjecture that by inheriting the probabilistic rigor of GPs and the powerful embedding properties of DNNs, GPs using NN dual kernels will empower future reinforcement learning models on difficult domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Differential Privacy in Grid Kitchen: Implementation & Software Documentation

Sharing of power grid feeder models faces significant challenges due to the potential risk of exposing sensitive operational information. Traditional anonymization techniques have shown notable limitations in other sensitive domains, as evidenced by documented re-identification attacks that combine supposedly anonymized datasets with auxiliary information, raising concerns that similar vulnerabilities could affect power grid data. Consequently, there is a pressing need for a more rigorous privacy protection strategy that not only delivers formal mathematical guarantees but also preserves the analytical value of the shared models. To address this challenge, we have enhanced the Grid Kitchen framework by implementing differential privacy mechanisms within the distribution model dehydration pipeline. This implementation carefully calibrates and applies noise to sensitive attributes in feeder models according to configurable privacy levels—low, moderate, and high—each offering different balances between data utility and privacy protection. Our approach uses established noise functions (Gaussian for continuous data and Discrete Laplace for integer values) with parameters carefully calibrated so that the impact of individual data points is effectively masked in the final output. The integration leverages our Noise Catalog, which we developed to categorize feeder model properties by component type, data type, and sensitivity. This catalog guides the application of appropriate noise functions and privacy parameters ($\varepsilon$ and $\delta$) to each attribute, ensuring consistent privacy protection across the model while maintaining its structural integrity and analytical usefulness. This implementation also includes evaluation tools that allow model owners to assess the impact of privacy-preserving transformations before sharing data with external parties. This report provides documentation for the differential privacy capabilities added to the Grid Kitchen project. It includes a primer on differential privacy concepts and their importance in modern data sharing, details the architecture of our implementation, explains the privacy modes and parameter configurations, and offers practical guidance on using the code for applying differential privacy to grid feeder models. Through examples and code snippets, we demonstrate the effective application of these privacy-enhancing technologies, enabling utility operators and researchers to confidently share grid data while protecting sensitive information.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1996

Covisualization by computational optical-sectioning microscopy of integrin and associated proteins at the cell membrane of living onion protoplasts

Using higher-resolution wide-field computational optical-sectioning fluorescence microscopy, the distribution of antigens recognized by antibodies against animal beta 1 integrin, fibronectin, and vitronectin has been visualized at the outer surface of enzymatically protoplasted onion epidermis cells and in depectinated cell wall fragments. On the protoplast all three antigens are colocalized in an array of small spots, as seen in raw images, in Gaussian filtered images, and in images restored by two different algorithms. Fibronectin and vitronectin but not beta 1 integrin antigenicities colocalize as puncta in comparably prepared and processed images of the wall fragments. Several control visualizations suggest considerable specifity of antibody recognition. Affinity purification of onion cell extract with the same anti-integrin used for visualization has yielded protein that separates in SDS-PAGE into two bands of about 105-110 and 115-125 kDa. These bands are again recognized by the visualization antibody, which was raised against the extracellular domain of chicken beta 1 integrin, and are also recognized by an antibody against the intracellular domain of chicken beta 1 integrin. Because beta 1 integrin is a key protein in numerous animal adhesion sites, it appears that the punctate distribution of this protein in the cell membranes of onion epidermis represents the adhesion sites long known to occur in cells of this tissue. Because vitronectin and fibronection are matrix proteins that bind to integrin in animals, the punctate occurrence of antigenically similar proteins both in the wall (matrix) and on enzymatically prepared protoplasts reinforces the concept that onion cells have adhesion sites with some similarity to certain kinds of adhesion sites in animals.

NASA Discipline Plant Biology↗
DOE OSTI2024

Comprehensive Dynamics in a Polyelectrolyte Complex Coacervate

The linear viscoelastic response, LVR, of a hydrated polyelectrolyte complex coacervate, PEC, was evaluated over a range of frequencies, temperatures, and salt concentrations. The PEC was a nearly stoichiometric blend of a quaternary ammonium poly([3-(methacrylamido)propyl]trimethylammonium chloride), PMAPTAC, and poly(2-acrylamido-2-methyl-1-propanesulfonic acid sodium salt), PAMPS, an aliphatic sulfonate, selected because they remain fully charged over the conditions of use. Narrow molecular weight distribution polyelectrolytes were prepared using fractionation techniques. A partially deuterated version of PMAPTAC was incorporated to determine its coil radius of gyration, R g , within PECs using small-angle neutron scattering. Chain dimensions were determined to be Gaussian with a Kuhn length of 2.37 nm, which remained constant from 25 to 65 °C. The LVR for a series of matched molecular weight PECs, mostly above the entanglement threshold, exhibited crossovers of modulus versus frequency classically attributed to the reptation time, relaxation between entanglements, and the relaxation of a Kuhn length of units (the “monomer” time). The scaling for zero shear viscosity, η 0 , versus chain length, N, was η 0 ~ N 3.1 , in agreement with “sticky reptation” theory. The lifetime and activation energy, E p , of a pair between polyanion and polycation repeat units, Pol + Pol – , were determined from diffusion coefficients of salt ions within the PEC. The activation energy for LVR of salt-free PECs was 2E p , showing that the key mechanism limiting the dynamics of undoped PECs is pair exchange. An FTIR technique was used to distinguish whether SCN– acts as a counterion or a co-ion within PECs. Doping of PECs with NaSCN breaks Pol + Pol – pairing efficiently, which decreases effective cross-linking and decreases viscosity. Finally, an equation was derived that quantitatively predicts this effect.

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

Learning from many collider events at once

There have been a number of recent proposals to enhance the performance of machine learning strategies for collider physics by combining many distinct events into a single ensemble feature. To evaluate the efficacy of these proposals, we study the connection between single-event classifiers and multievent classifiers under the assumption that collider events are independent and identically distributed. We show how one can build optimal multievent classifiers from single-event classifiers, and we also show how to construct multievent classifiers such that they produce optimal single-event classifiers. This is illustrated for a Gaussian example as well as for classification tasks relevant for searches and measurements at the Large Hadron Collider. We extend our discussion to regression tasks by showing how they can be phrased in terms of parametrized classifiers. Empirically, we find that training a single-event (per-instance) classifier is more effective than training a multievent (per-ensemble) classifier, as least for the cases we studied, and we relate this fact to properties of the loss function gradient in the two cases. While we did not identify a clear benefit from using multievent classifiers in the collider context, we speculate on the potential value of these methods in cases involving only approximate independence, as relevant for jet substructure studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

On the Properties of Cosmological Ionization Fronts

We investigate the properties of cosmological ionization fronts during the epoch of reionization using the Cosmic Reionization on Computers simulations. By analyzing reionization timing maps, we characterize ionization front velocities and curvatures and their dependence on the density structure of the intergalactic medium (IGM). The velocity distribution of ionization fronts in the simulations indicates that while the barrier-crossing analytical model captures the overall shape in high-velocity regions, it fails to reproduce the low-velocity tail, highlighting the non-Gaussian nature of the IGM’s density field. Ionization front velocities are inversely correlated with local density, propagating faster in underdense regions and more slowly in overdense environments. Faster ionization fronts also lead to higher postionization temperatures, reaching a plateau at ∼2 × 10$^{4}$ K for velocities exceeding 3000 km s$^{−1}$. Examining curvature statistics further establishes a connection between ionization front structure and the normalized density contrast ν, with trends in overdense regions aligning well with barrier-crossing model predictions, while deviations appear in underdense environments due to model limitations. These results provide a detailed characterization of ionization front dynamics and their interaction with the underlying density field, bridging small-scale reionization physics with large-scale observables such as the 21 cm signal and the IGM’s thermal history.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Augmented Gaussian random field: Theory and computation

We propose the novel augmented Gaussian random field (AGRF), which is a universal framework incorporating the data of observable and derivatives of any order. Rigorous theory is established. We prove that under certain conditions, the observable and its derivatives of any order are governed by a single Gaussian random field, which is the aforementioned AGRF. As a corollary, the statement "the derivative of a Gaussian process remains a Gaussian process" is validated, since the derivative is represented by a part of the AGRF. Moreover, a computational method corresponding to the universal AGRF framework is constructed. Both noiseless and noisy scenarios are considered. Formulas of the posterior distributions are deduced in a nice closed form. A significant advantage of our computational method is that the universal AGRF framework provides a natural way to incorporate arbitrary order derivatives and deal with missing data. We use four numerical examples to demonstrate the effectiveness of the computational method. The numerical examples are composite function, damped harmonic oscillator, Korteweg-De Vries equation, and Burgers' equation.

Mathematics↗
NASA NTRS1974

Numerical modelling of instantaneous plate tectonics

Assuming lithospheric plates to be rigid, 68 spreading rates, 62 fracture zones trends, and 106 earthquake slip vectors are systematically inverted to obtain a self-consistent model of instantaneous relative motions for eleven major plates. The inverse problem is linearized and solved iteratively by a maximum-likelihood procedure. Because the uncertainties in the data are small, Gaussian statistics are shown to be adequate. The use of a linear theory permits (1) the calculation of the uncertainties in the various angular velocity vectors caused by uncertainties in the data, and (2) quantitative examination of the distribution of information within the data set. The existence of a self-consistent model satisfying all the data is strong justification of the rigid plate assumption. Slow movement between North and South America is shown to be resolvable.

Minster, J. B.↗
NASA NTRS1986

Boundary layer measurements on an airfoil in cascade using laser Doppler anemometry

Laser Doppler anemometry (LDA) was used to obtain detailed boundary layer data at 89.3 percent chord on the pressure surface of a double circular arc compressor blade in cascade. The measurements were taken at a chord Reynolds number of 5.0 x 10 to the 5th and a cascade angle of 53 degrees. The mean velocity, local turbulence intensity, skewness, and kurtosis were determined from the measured velocity probability distributions. The mean velocity profile and the local turbulence intensity profile had classical shapes. Also, the skewness and kurtosis had commonly observed shapes through out the boundary layer, reaching maximum values for Y/delta between 0.5 and 1.1 and Gaussian values for Y/delta greater than 1.1. A comparison was made between data taken with and without the Bragg cell and no significant differences were found.

Williams, F. W.↗
NASA NTRS1992

Large-scale clustering of galaxies in the CfA Redshift Survey

The power spectrum of the galaxy distribution in the Center for Astrophysics Redshift Survey (de Lapparent et al., 1986; Geller and Huchra, 1989; and Huchra et al., 1992) is measured up to wavelengths of 200/h Mpc. Results are compared with several cosmological simulations with Gaussian initial conditions. It is shown that the power spectrum of the standard CDM model is inconsistent with the observed power spectrum at the 99 percent confidence level.

Vogeley, Michael S.↗
NASA NTRS1997

Data Assimilation in the Ocean and in the Atmosphere: What Should be Next?

As part of the International Symposium on Assimilation of Observation in Meteorology and Oceanography, a panel discussion was held on the evening of 15 March 1995. The purpose of this panel discussion was focus on what the next major areas of research in data assimilation should be. The panelists had five minutes each for short presentations (Kalman filters, representers, etc.) and this was followed by an open discussion. This preprocessing will require a good understanding of the fine-scale phenomena. Least square methods such as Kalman filters and variational schemes are inefficient estimators of non-Gaussian field such as chemical traces. Regardless of the modeling technique employed (Lagrangian methods seem best), a least squares assimilation scheme will smear fine structure. The estimator of maximum likelihood must be sought, by examination of tracer probability distributions.

Kalnay, Eugenia↗
DOE OSTI2026

Tomography of Atomic Nuclei

We carry out continuum quantum Monte Carlo calculations of the quantum-mechanical Wigner distribution functions of selected nuclei, up to $^{16}$O. These distributions provide a form of quantum tomography of the spatial and momentum structure of the system. They also help identify the location of high-momentum regions in atomic nuclei and provide insight into the onset of alpha clustering. Besides their intrinsic interest, these distributions will be useful for neutrino event generators, as they correlate the positions and momenta of nucleons in the initial target state. To facilitate their application, we address the need to store them compactly by developing an accurate Gaussian Process emulator that automatically preserves their normalization.

Rocco, Noemi [Valencia U., IFIC; Fermilab]↗
DOE OSTI2023

Critical assessment of the recent report on the gigaparsec-scale correlation of the orientations of large quasar groups

ABSTRACT Recently, it was reported that large quasar groups (LQGs) identified from the Sloan Digital Sky Survey (SDSS) data release seven catalogue are not randomly oriented but preferentially aligned or orthogonal over scales 1–2 Gpc. To confirm this claim, I reproduced the same LQG sample and performed Sobolev tests of uniformity on the LQG orientation axes in the redshift space. Contrary to the original report based on the bimodal distribution of the LQG position angles in the sky, I found no departure from uniformity in the distribution of the LQG orientation axes. I also examined whether the LQGs are physical structures using a statistically more reliable data set constructed from the SDSS data release 16 (DR16) large-scale structure (LSS) quasar catalogue. Considering the Gaussian primordial density fluctuations and shot noise, I estimated the mass density contrasts of the LQGs from the number counts of the DR16 LSS quasars and found that most of the LQGs do not trace statistically significant high-density regions. I conclude that the LQG sample is a collection of unphysical chance associations and should not be used for any cosmological studies.

Fujii, Hirokazu (ORCID:0000000161473512)↗
DOE OSTI2022

An e-beam irradiation beamline at Jefferson Lab for 1,4-dioxane and per- and polyfluoroalkyl substances (PFAS) remediation in wastewater

The Upgraded Injector Test Facility (UITF) at Jefferson Lab, providing a beam energy up to 10 MeV, is suitable for wastewater remediation research. To investigate the degradation of 1,4-dioxane and per- and polyfluoroalkyl substances (PFAS), widespread in wastewater and potential to be regulated in near future, a beamline for electron-beam irradiation has been designed, installed and successfully commissioned at the UITF. A solenoid with a peak axial magnetic field of up to 0.28 T and a raster were used to obtain a Gaussian beam profile with a transverse standard deviation of 15 mm. It was applied to irradiate 1,4-dioxane sample filled in the target cell that was designed to let the entire sample receive significant irradiation doses. The dose distribution and absorbed dose, few studied in the current publications, are necessary measures for the degradation mechanism investigation and have been innovatively achieved in this work using simulations which were calibrated with opti-chromic dosimeter rods directly exposed to the electron beam. This approach provides an important way for investigating the environmental remediation impact of electron-beam irradiation.

Li, Xi↗