Results for “Kernel methods” — Page 15

DOE OSTI2013

Preparation and characterization of plasticized palm-based polyurethane solid polymer electrolyte

Palm-based polyurethane solid polymer electrolyte was prepared via prepolymerization method between palm kernel oil based polyols (PKO-p) and 2,4’-diphenylmethane diisocyanate (2,4’-MDI) in acetone at room temperature with the vary amount of lithium trifuoromethanesulfonate (LiCF{sub 3}SO{sub 3}) salt and polyethylene glycol (PEG). The film was analyzed using attenuated total reflection infrared (ATR-IR) spectroscopy, electrochemical impedance spectroscopy (EIS) and X-ray diffractometry (XRD). EIS result indicated ionic conductivity obtained with 30 wt% LiCF3SO3 increased to 6.55 × 10{sup −6} S cm{sup −1} when 10 wt.% of plasticizer was added into the system. FTIR analysis showed the interaction between lithium ions and amine (-N-H) at 3600–3100 cm{sup −1}, carbonyl (-C=O) at 1750–1650 cm{sup −1} and ether (-C-O-C-) at 1150–1000 cm{sup −1} of the polyurethane forming polymer-salt complexes. The XRD result confirmed that LiCF{sub 3}SO{sub 3} salt completely dissociated within the polyurethane film with the absence of crystalline peaks of LiCF{sub 3}SO{sub 3}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Computational study of collisions between O({sup 3}P) and NO({sup 2}Π) at temperatures relevant to the hypersonic flight regime

Reactions involving N and O atoms dominate the energetics of the reactive air flow around spacecraft when reentering the atmosphere in the hypersonic flight regime. For this reason, the thermal rate coefficients for reactive processes involving O({sup 3}P) and NO({sup 2}Π) are relevant over a wide range of temperatures. For this purpose, a potential energy surface (PES) for the ground state of the NO{sub 2} molecule is constructed based on high-level ab initio calculations. These ab initio energies are represented using the reproducible kernel Hilbert space method and Legendre polynomials. The global PES of NO{sub 2} in the ground state is constructed by smoothly connecting the surfaces of the grids of various channels around the equilibrium NO{sub 2} geometry by a distance-dependent weighting function. The rate coefficients were calculated using Monte Carlo integration. The results indicate that at high temperatures only the lowest A-symmetry PES is relevant. At the highest temperatures investigated (20 000 K), the rate coefficient for the “O1O2+N” channel becomes comparable (to within a factor of around three) to the rate coefficient of the oxygen exchange reaction. A state resolved analysis shows that the smaller the vibrational quantum number of NO in the reactants, the higher the relative translational energy required to open it and conversely with higher vibrational quantum number, less translational energy is required. This is in accordance with Polanyi's rules. However, the oxygen exchange channel (NO2+O1) is accessible at any collision energy. Finally, this work introduces an efficient computational protocol for the investigation of three-atom collisions in general.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

A Probabilistic Data-Driven Method for Photovoltaic Pseudo-Measurement Generation in Distribution Systems

This paper presents a probabilistic data-driven method to model the uncertainty of distributed photovoltaic (PV) generation to enhance the observability of distribution grids with a high penetration of renewable resources. The proposed method employs a kernel density estimation (KDE) technique to develop the conditional probability density function (PDF) of PV outputs given the time of the day, using the measurement data from observed PV systems. Then time series of output power of unmeasured PV generators, located at the same grid, are generated according to the corresponding PDF and used as pseudo-measurements in distribution system state estimation (DSSE). The proposed model has been tested and verified using real PV data and utility networks.

Yuan, Yuxuan↗

DOE OSTI2016

Towards Achieving Performance Portability Using Directives for Accelerators

In this paper we explore the performance portability of directives provided by OpenMP 4 and OpenACC to program various types of node architectures with attached accelerators, both self-hosted multicore and offload multicore/GPU. Our goal is to examine how successful OpenACC and the newer offload features of OpenMP 4.5 are for moving codes between architectures, how much tuning might be required and what lessons we can learn from this experience. To do this, we use examples of algorithms with varying computational intensities for our evaluation, as both compute and data access efficiency are important considerations for overall application performance. We implement these kernels using various methods provided by newer OpenACC and OpenMP implementations, and we evaluate their performance on various platforms including both X86_64 with attached NVIDIA GPUs, self-hosted Intel Xeon Phi KNL, as well as an X86_64 host system with Intel Xeon Phi coprocessors. In this paper, we explain what factors affected the performance portability such as how to pick the right programming model, its programming style, its availability on different platforms, and how well compilers can optimize and target to multiple platforms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Discovery of a Protocluster Associated with a Lyα Blob Pair at z = 2.3

Bright Lyα blobs (LABs)—extended nebulae with sizes of ∼100 kpc and Lyα luminosities of ∼10{sup 44} erg s{sup −1}—often reside in overdensities of compact Lyα emitters (LAEs) that may be galaxy protoclusters. The number density, variance, and internal kinematics of LABs suggest that they themselves trace group-like halos. Here, we test this hierarchical picture, presenting deep, wide-field Lyα narrowband imaging of a 1° × 0.°5 region around a LAB pair at z = 2.3 discovered previously by a blind survey. We find 183 Lyα emitters, including the original LAB pair and three new LABs with Lyα luminosities of (0.9--1.3)×10{sup 43} erg s{sup −1} and isophotal areas of 16–24 arcsec{sup 2}. Using the LAEs as tracers and a new kernel density estimation method, we discover a large-scale overdensity (Boötes J1430+3522) with a surface density contrast of δ{sub Σ}=2.7, a volume density contrast of δ ∼10.4, and a projected diameter of ≈20 comoving Mpc. Comparing with cosmological simulations, we conclude that this LAE overdensity will evolve into a present-day Coma-like cluster with log(M/M{sub ⊙}) ∼ 15.1 ± 0.2. In this and three other wide-field LAE surveys re-analyzed here, the extents and peak amplitudes of the largest LAE overdensities are similar, not increasing with survey size, and implying that they were indeed the largest structures then and today evolve into rich clusters. Intriguingly, LABs favor the outskirts of the densest LAE concentrations, i.e., intermediate LAE overdensities of δ{sub Σ}=1--2. We speculate that these LABs mark infalling protogroups being accreted by the more massive protocluster.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

17 WIND ENERGY↗

DOE OSTI2015

fastKDE

This software implements the fast, self-consistent probability density estimation described by O'Brien et al. (2014, doi: ). It uses a non-uniform fast Fourier transform technique to reduce the computational cost of an objective and self-consistent kernel density estimation method.

O'Brien, Travis A.↗

DOE OSTI2011

A general framework and review of scatter correction methods in cone beam CT. Part 2: Scatter estimation approaches

The main components of scatter correction procedures are scatter estimation and a scatter compensation algorithm. This paper completes a previous paper where a general framework for scatter compensation was presented under the prerequisite that a scatter estimation method is already available. In the current paper, the authors give a systematic review of the variety of scatter estimation approaches. Scatter estimation methods are based on measurements, mathematical-physical models, or combinations of both. For completeness they present an overview of measurement-based methods, but the main topic is the theoretically more demanding models, as analytical, Monte-Carlo, and hybrid models. Further classifications are 3D image-based and 2D projection-based approaches. The authors present a system-theoretic framework, which allows to proceed top-down from a general 3D formulation, by successive approximations, to efficient 2D approaches. A widely useful method is the beam-scatter-kernel superposition approach. Together with the review of standard methods, the authors discuss their limitations and how to take into account the issues of object dependency, spatial variance, deformation of scatter kernels, external and internal absorbers. Open questions for further investigations are indicated. Finally, the authors refer on some special issues and applications, such as bow-tie filter, offset detector, truncated data, and dual-source CT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2019

An Approach to Retrieve BRDF from Satellite and Airborne Measurements of Surface-Reflected Radiance Based on Decoupling of Atmospheric Radiative Transfer and Surface Reflection

Bi-directional Reflection Distribution Function (BRDF) defines anisotropy of the surface reflection. It is required to specify the boundary condition for radiative transfer (RT) modeling. Measurements of reflected radiance by satellite- and air-borne sensors provide information about anisotropy of surface reflection. Atmospheric correction needs to be performed to derive BRDF from the reflected radiance. Common approach for BRDF retrievals consists of the use of kernel-based BRDF and RT modeling that needs to be done anew at every step of the iterative process. The kernels’ weights are obtained by minimization of the difference between measured and modeled radiance. This study develops a new method of retrieving kernel-based BRDF that requires RT calculations to be done only once. The method employs the exact analytical expression of radiance at any atmospheric level through the solutions of two auxiliary atmosphere-only RT problems and the surface-reflected radiance at the surface level. The latter is related to BRDF and solutions of the auxiliary RT problems by a Fredholm integral equation of the second kind. The approach requires to perform RT calculations one time before the iterations. It can use observations taken at different atmospheric conditions assuming that surface conditions remain unchanged during the time span of observations. The algorithm accurately catches zero weights of the kernels that may be a concern if the number of kernels is greater than 3 in current mainstream approaches. The study presents numerical tests of the BRDF retrieval algorithm for various surface and atmospheric conditions.

Radkevich, Alexander↗

DOE OSTI2018

Kinetic-j : A computational kernel for solving the linearized Vlasov equation applied to calculations of the kinetic, configuration space plasma current for time harmonic wave electric fields

We present the Kinetic-j code, a computational kernel for evaluating the linearized Vlasov equation withapplication to calculating the kinetic plasma response (current) to an applied time harmonic wave electricfield. This code addresses the need for a configuration space evaluation of the plasma current to enablekinetic full-wave solvers for waves in hot plasmas to move beyond the limitations of the traditional Fourierspectral methods. We benchmark the kernel via comparison with the standard k-space forms of the hotplasma conductivity tensor.

Green, David L.↗

NASA NTRSDate not supplied

20-Years of Atmospheric Temperature, Water Vapor, Cloud, and Surface Temperature Anomalies and Trends Derived From Operational Hyperspectral Ir Sounders

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The SiFSAP retrieval algorithm also uses the same climatology a priori and associated covariances, which makes it ideal for generating high quality products for both weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗

NASA NTRSDate not supplied

Two Decades of Atmospheric and Surface Temperature, Water Vapor, and Cloud Trends Derived from Satellite Remote Sensors

Satellite remote sensor such as Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

remote sensing↗

NASA NTRSDate not supplied

Remote Sensing of Atmospheric Temperature, Water Vapor, Trace Gases, Cloud, and Surface Properties on Daily and Decadal Time Scales

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗

NASA NTRSDate not supplied

Development of Radiative Transfer Models and Retrieval Algorithms for Satellite Remote Sensors

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗

DOE OSTI2019

Combination of the Laguerre Transform with the Boundary-element Method for the Solution of Integral Equations with Retarded Kernel

We apply the Laguerre transform with respect to time to a time-dependent boundary-value integral equation encountered in the solution of three-dimensional Dirichlet initial-boundary-value problems for the homogeneous wave equation with homogeneous initial conditions by using the retarded potential of single layer. The obtained system of boundary integral equations is reduced to a sequence of Fredholm integral equations of the first kind that differ solely by the recursively dependent right-hand sides. To find their numerical solution, we use the boundary-element method. We establish an asymptotic estimate of the error of numerical solution and present the results of numerical simulations aimed at finding the solutions of retarded-potential integral equations for model examples.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

The method of normal forms for singularly perturbed systems of Fredholm integro-differential equations with rapidly varying kernels

The paper deals with extending the Lomov regularization method to classes of singularly perturbed Fredholm-type integro-differential systems, which have not so far been studied. In these the limiting operator is discretely noninvertible. Such systems are commonly known as problems with unstable spectrum. Separating out the essential singularities in the solutions to these problems presents great difficulties. The principal one is to give an adequate description of the singularities induced by 'instability points' of the spectrum. A methodology for separating singularities by using normal forms is developed. It is applied to the above type of systems and is substantiated in these systems. Bibliography: 10 titles.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Transfer learning of memory kernels for transferable coarse-graining of polymer dynamics

The present work concerns the transferability of coarse-grained (CG) modeling in reproducing the dynamic properties of the reference atomistic systems across a range of parameters. In particular, we focus on implicit-solvent CG modeling of polymer solutions. The CG model is based on the generalized Langevin equation, where the memory kernel plays the critical role in determining the dynamics in all time scales. Thus, we propose methods for transfer learning of memory kernels. The key ingredient of our methods is Gaussian process regression. By integration with the model order reduction via proper orthogonal decomposition and the active learning technique, the transfer learning can be practically efficient and requires minimum training data. Through two example polymer solution systems, we demonstrate the accuracy and efficiency of the proposed transfer learning methods in the construction of transferable memory kernels. The transferability allows for out-of-sample predictions, even in the extrapolated domain of parameters. Built on the transferable memory kernels, the CG models can reproduce the dynamic properties of polymers in all time scales at different thermodynamic conditions (such as temperature and solvent viscosity) and for different systems with varying concentrations and lengths of polymers.

Ma, Zhan↗

DOE OSTI2018

Monte Carlo estimates of sensitivities to geometric perturbations for shielding problems using kernel density estimators - 25605

A Monte Carlo method to estimate the sensitivity of reaction rates like dose and flux spectra to geometric perturbations using kernel density estimators is demonstrated for shielding problems. The method is used to estimate the sensitivity of the spectrum emitted from a Cf-252 source at the center of an iron sphere as well as the sensitivity of the dose due to Cf-252 neutrons shielded using various materials. Results are compared against reference solutions obtained using Monte Carlo direct perturbations with central differences, with agreement within 5% and 3σ for the majority of results. The results indicate that a bandwidth that is 10-20% of the shielding thickness produces accurate results with statistically insignificant bias for the chosen test problems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗