SEARCH · Search NASA

Results for “Kernel methods”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Delegated Regressor, A Robust Approach for Automated Anomaly Detection in the Soil Radon Time Series Data

We propose a new method based on the idea of delegating regressors for predicting the soil radon gas concentration (SRGC) and anomalies in radon or any other time series data. The proposed method is compared to different traditional boosting e.g., Extreme Gradient Boosting (EGB) and simple regression methods e.g., support vector regressors with linear kernel and radial kernel in terms of accurate predictions. R language has been used for the statistical analysis of radon time series (RTS) data. The results obtained show that the proposed methodology predicts SRGC more accurately when compared to different traditional boosting and regression methods. The best correlation is found between the actual and predicted radon concentration for window size of 2 i.e., two days before and after the start of seismic activities. RTS data was collected from 05 February 2017 to 16 February 2018, including 7 seismic events recorded during the study period. Findings of study show that the proposed methodology predicts the SRGC with more precision, for all the window sizes, by overlapping predicted with the actual radon time series concentrations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Contributions From Cloud Morphological Changes to the Interannual Shortwave Cloud Feedback Based on MODIS and ISCCP Satellite Observations

The surface temperature-mediated change in cloud properties, referred to as the cloud feedback, continues to dominate the uncertainty in climate projections. A larger number of contemporary global climate models (GCMs) project a higher degree of warming than the previous generation of GCMs. This greater projected warming has been attributed to a less negative cloud feedback in the Southern Ocean. Here, we apply a novel “double decomposition method” that employs the “cloud radiative kernel” and “cloud regime” concepts, to two data sets of satellite observations to decompose the interannual cloud feedback into contributions arising from changes within and shifts between cloud morphologies. Our results show that contributions from the latter to the cloud feedback are large for certain regimes. We then focus on interpreting how both changes within and between cloud morphologies impact the shortwave cloud optical depth feedback over the Southern Ocean in light of additional observations. Results from the former cloud morphological changes reveal the importance of the wind response to warming increases low- and mid-level cloud optical thickness in the same region. Results from the latter cloud morphological changes reveal that a general shift from thick storm-track clouds to thinner oceanic low-level clouds contributes to a positive feedback over the Southern Ocean that is offset by shifts from thinner broken clouds to thicker mid- and low-level clouds. Our novel analysis can be applied to evaluate GCMs and potentially diagnose shortcomings pertaining to their physical parameterizations of particular cloud morphologies.

58 GEOSCIENCES↗

DOE OSTI2015

Ion aggregation in high salt solutions. III. Computational vibrational spectroscopy of HDO in aqueous salt solutions

The vibrational frequency, frequency fluctuation dynamics, and transition dipole moment of the O—D stretch mode of HDO molecule in aqueous solutions are strongly dependent on its local electrostatic environment and hydrogen-bond network structure. Therefore, the time-resolved vibrational spectroscopy the O—D stretch mode has been particularly used to investigate specific ion effects on water structure. Despite prolonged efforts to understand the interplay of O—D vibrational dynamics with local water hydrogen-bond network and ion aggregate structures in high salt solutions, still there exists a gap between theory and experiment due to a lack of quantitative model for accurately describing O—D stretch frequency in high salt solutions. To fill this gap, we have performed numerical simulations of Raman scattering and IR absorption spectra of the O—D stretch mode of HDO in highly concentrated NaCl and KSCN solutions and compared them with experimental results. Carrying out extensive quantum chemistry calculations on not only water clusters but also ion-water clusters, we first developed a distributed vibrational solvatochromic charge model for the O—D stretch mode in aqueous salt solutions. Furthermore, the non-Condon effect on the vibrational transition dipole moment of the O—D stretch mode was fully taken into consideration with the charge response kernel that is non-local polarizability density. From the fluctuating O—D stretch mode frequencies and transition dipole vectors obtained from the molecular dynamics simulations, the O—D stretch Raman scattering and IR absorption spectra of HDO in salt solutions could be calculated. The polarization effect on the transition dipole vector of the O—D stretch mode is shown to be important and the asymmetric line shapes of the O—D stretch Raman scattering and IR absorption spectra of HDO especially in highly concentrated NaCl and KSCN solutions are in quantitative agreement with experimental results. We anticipate that this computational approach will be of critical use in interpreting linear and nonlinear vibrational spectroscopies of HDO molecule that is considered as an excellent local probe for monitoring local electrostatic and hydrogen-bonding environment in not just salt but also other confined and crowded solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.

Blast furnace (BF)↗

DOE OSTI2024

Radiological Source Term Estimation and Isotopic Identification with Parallel Log Domain Particle Filters

This paper presents a parallel log-domain particle filtering algorithm combined with gamma spectrum unfolding to perform localization, identification, and evaluation of multiple point sources of various isotopes in an environment with attenuating obstacles. The method uses sets of precomputed attenuation kernels that map the attenuation characteristics of the environment. These kernels are specific to the energy level of a photopeak of interest. The spectral measurements are deconvolved into count measurements of each photopeak. These count measurements are fed into a set of parallel particle filters using attenuation kernels computed for that photopeak’s energy level. The individual regularized particle filters perform all likelihood calculations in the logarithmic domain to mitigate the effects of particle degeneracy. The output of each particle filter is combined to estimate which isotopes are present as well as their positions and strengths. The performance of the algorithm is characterized in a lab-scale environment using a mobile robot equipped with a gamma ray spectrometer in the presence of up to three different radioactive isotopes simultaneously. The sources were localized to within 10 cm, and their strengths were estimated within 10% of their true values. Furthermore, the isotopes were all correctly identified, and no spurious sources were reported.

42 ENGINEERING↗

DOE OSTI2016

SU-F-J-08: Quantitative SPECT Imaging of Ra-223 in a Phantom

Purpose: Ra-223 therapy of prostate cancer bone metastases is being used to treat patients routinely. However, the absorbed dose distribution at the macroscopic and microscopic scales remains elusive, due to the inability to image the small activities injected. Accurate activity quantification through imaging is essential to calculate the absorbed dose in organs and sub-units in radiopharmaceutical therapy, enabling personalized absorbed dose-based treatment planning methodologies and more effective and optimal treatments. Methods: A 22 cm diameter by 20 cm long cylindrical phantom, containing a 3.52 cm diameter sphere, was used. A total of 2.01 MBq of Ra-223 was placed in the phantom with 177.6 kBq in the sphere. Images were acquired on a dual-head Siemens Symbia T16 gamma camera using three 20% full-width energy windows and centered at 84, 154, and 269 keV (120 projections, 360° rotation, 45 s per view). We have implemented reconstruction of Ra-223 SPECT projections using OS-EM (up to 20 iterations of 10 subsets) with compensation for attenuation using CT-based attenuation maps, collimator-detector response (CDR) (including septal penetration, scatter and Pb x-ray modeling), and scatter in the patient using the effective source scatter estimation (ESSE) method. The CDR functions and scatter kernels required for ESSE were computed using the SIMIND MC simulation code. All Ra-223 photon emissions as well as gamma rays from the daughters Rn-219 and Bi-211 were modeled. Results: The sensitivity of the camera in the three combined windows was 107.3 cps/MBq. The visual quality of the SPECT images was reasonably good and the activity in the sphere was 27% smaller than the true activity. This underestimation is likely due to partial volume effect. Conclusion: Absolute quantitative Ra-223 SPECT imaging is achievable with careful attention to compensate for image degrading factors and system calibration.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

BASIC HARTREE-FOCK PROXY APPLICTION

This proxy application simulates the compute load and data-movement of the kernel of the Hartree-Fock method in quantum chemistry. The proxy features a simplified algorithm for computing electron repulsion integrals that is easily offloaded to GPUs.

FLETCHER, GRAHAMD↗

DOE OSTI2025

KeNary

A Probabilistic Kernel-Based n-ary Classification Method for Sets of Observations

Stricklin, PhD, Madeline [Los Alamos National Labo↗

DOE OSTI2014

Enhancing Kokkos with OpenACC

C++ template metaprogramming has emerged as a prominent approach for achieving performance portability in heterogeneous computing. Kokkos represents a notable paradigm in this domain, offering programmers a suite of high-level abstractions for generic programming while deferring much of the device-specific code generation and optimization to the compiler through template specializations. Kokkos furnishes a range of device-specific code specializations across multiple back ends, including CUDA and HIP. Diverging from conventional back ends, the OpenACC implementation presents a high-level, multicompiler, multidevice, and directive-based programming model. This paper presents recent advancements in the OpenACC back end for Kokkos (i.e., KokkACC) and focuses on its integration into the Kokkos ecosystem, exploration of automatic device selection capabilities to enhance productivity, and performance evaluation on modern hardware such as NVIDIA H100 GPUs. The study includes implementation details and a thorough performance assessment across various computational benchmarks, including minibenchmarks (AXPY and DOT product), miniapps (LULESH, MiniFE, and SNAP-LAMMPS), and a scientific kernel based on the lattice Boltzmann method.

Valero Lara, Pedro↗

DOE OSTI2013

A comparison of methods for representing sparsely sampled random quantities.

This report discusses the treatment of uncertainties stemming from relatively few samples of random quantities. The importance of this topic extends beyond experimental data uncertainty to situations involving uncertainty in model calibration, validation, and prediction. With very sparse data samples it is not practical to have a goal of accurately estimating the underlying probability density function (PDF). Rather, a pragmatic goal is that the uncertainty representation should be conservative so as to bound a specified percentile range of the actual PDF, say the range between 0.025 and .975 percentiles, with reasonable reliability. A second, opposing objective is that the representation not be overly conservative; that it minimally over-estimate the desired percentile range of the actual PDF. The presence of the two opposing objectives makes the sparse-data uncertainty representation problem interesting and difficult. In this report, five uncertainty representation techniques are characterized for their performance on twenty-one test problems (over thousands of trials for each problem) according to these two opposing objectives and other performance measures. Two of the methods, statistical Tolerance Intervals and a kernel density approach specifically developed for handling sparse data, exhibit significantly better overall performance than the others.

Romero, Vicente Jose↗

DOE OSTI2014

AGR-1 Daily As-run Thermal Analyses

This report documents the results of thermal analyses to predict the daily as-run temperatures for the AGR-1 experiment. Control gas gaps and compact-graphite holder gas gaps were modeled to change linearly with time. The control gas gap widths were determined by comparison to measured R/B data. The compact graphite holder gas gaps were determined from PIE measurements. Daily heat rates for each compact and component in the models were input from daily as-run physics analyses. Daily gas compositions and component fast neutron fluences were also input. Six different finite element models were created for the six different AGR-1 capsules. Each capsule had a different gas gap that was implemented to control the temperature of the experiment. Capsules on the top and bottom had larger gas gaps, while capsules in the middle were smaller.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

AGR-5/6/7 Fuel Fabrication Feedstock Chemical Purity Specifications

This specification has been prepared to provide fuel fabricators with minimum chemical purity specifications intended to ensure that fuel components have consistent properties and that impurity levels in the as-fabricated fuel is sufficiently low to minimize in-pile TRISO particle failures and to enhance fission product retention. Process chemical purity specifications are given for the following processes: • Kernel forming and sintering • TRISO particle coating • Matrix preparation • TRISO overcoating • Compact carbonization and heat treatment

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

AGR-5/6/7 Fuel Specification

The Idaho National Laboratory (INL) Advanced Reactor Technologies (ART) Technology Development Office (TDO) program is developing and qualifying fuel for a first of a kind high temperature gas-cooled reactor (HTGR) and associated systems to generate electrical power and produce hydrogen or process heat. One of the critical technology development areas of the program is nuclear fuel development and qualification. Fuel qualification is needed to support licensing, operation, and near term deployment of an HTGR reactor.5 Toward this end, the Advanced Gas Reactor (AGR) program includes manufacturing fuels for a series of irradiation experiments in the Advanced Test Reactor (ATR) at INL.5 The fifth, sixth, and seventh irradiation experiments, called “AGR 5/6/7,” will use fuel manufactured entirely in engineering scale equipment to demonstrate the performance of fuels fabricated in a production environment. This fuel will be composited from multiple low enriched uranium carbide/oxide (LEUCO) kernel forming runs, multiple tristructural isotropic (TRISO) coating runs, and multiple overcoating runs. The fuel will be composited into lots as kernels, TRISO particles, and compacts. Previous AGR fuel specifications1,2,8,9 provide the basis for most of the following fuel specifications, which are specific to the AGR 5/6/7 experiment, and may not be immediately applicable to fuel produced for an HTGR reactor. Fuel specifications will be influenced by the final reactor design.

+↗

DOE OSTI2019

Complete One-Loop Renormalization of the Higgs-Electroweak Chiral Lagrangian

The electroweak sector of the Standard Model can be formulated in a way similar to Chiral Perturbation Theory (ChPT), but extended by a singlet scalar. The resulting effective field theory (EFT) is called Higgs-Electroweak Chiral Lagrangian (EWCh$\mathcal{L}$) and is the most general approach to new physics in the Higgs sector. It solely assumes the pattern of symmetry breaking leading to the three electroweak Goldstone bosons (i.e. massive $W$ and $Z$) and the existence of a Higgs-like scalar particle. The power counting of the EWCh$\mathcal{L}$ is given by a generalization of the momentum expansion of ChPT. It is connected to a loop expansion, making the theory renormalizable order by order in the EFT. I will briefly review the construction of the EWCh$\mathcal{L}$ and its power counting. Then, I will discuss the complete one-loop renormalization of the EWCh$\mathcal{L}$ employing the background-field method and the super-heat-kernel expansion. This computation confirms the power counting assumptions, is consistent with the completeness of the operator basis, and reproduces known results of subsectors in the appropriate limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Support for Fuel Fabrication and Characterization

Oak Ridge National Laboratory (ORNL) has participated in the Advanced Gas Reactor (AGR) program for the Next Generation Nuclear Plant (NGNP) and the transition to the Idaho National Laboratory (INL) Advanced Reactor Technologies (ART) Technology Development Office (TDO) since the inception of the program. In this effort, ORNL has fabricated tristructural isotropic (TRISO) fuel and fuel compacts for AGR-1, AGR-2, and AGR-3/4 experiments, provided matrix only components for AGC-2, AGC-4, and AGR 3/4 experiments and for university studies, and provided characterization, coating, and compaction support for INL and BWX Technologies Nuclear Operations Group (BWXT). In fiscal year (FY) 2018, the activities for the INL ART TDO fuel development are focused on final characterization to support the AGR-5/6/7 experiments and technical support to the Generation-IV International Forum (GIF) pre-irradiation leach-burn-leach (LBL) round robin effort with China and South Korea.

+↗

DOE OSTI2017

AGR-5/6/7 Fuel Fabrication Feedstock Chemical Purity Specifications

+↗

DOE OSTI2020

NDMAS System and Process Description

The U. S. Department of Energy (DOE) has made a significant investment in research to develop the next generation of reactor technologies as well as to improve the performance and lengthen the life cycle of existing nuclear reactors. Data collected to demonstrate new concepts may also be used in the future to support licensing of these technologies. Provenance of these data must be preserved. The Nuclear Data Management and Analysis System (NDMAS) was established to manage and preserve data collected by fuels and materials research conducted by the high-temperature, gas-cooled reactor program. The scope of NDMAS is expanding to include other nuclear research programs that have the shared need to preserve the provenance of research data. Nuclear research funded by DOE is conducted by Idaho National Laboratory (INL), universities, other national laboratories, foreign research partners, and private companies. This research will generate a large amount of data from a variety of sources over a period of many years. Managing the data generated by the research and development projects presents a significant challenge for retaining data integrity and availability.

+↗

DOE OSTI2012

Interpolations of nuclide-specific scattering kernels generated with Serpent

The neutron group-to-group scattering cross section is an essential input parameter for any multi-energy group physics model. However, if the analyst prefers to use Monte Carlo transport to generate group constants this data is difficult to obtain for a single species of a material. Here, the Monte Carlo code Serpent was modified to return the group transfer probabilities on a per-nuclide basis. This ability is demonstrated in conjunction with an essential physics reactor model where cross section perturbations are used to dynamically generate reactor state dependent group constants via interpolation from pre-computed libraries. The modified version of Serpent was therefore verified with three interpolation cases designed to test the resilience of the interpolation scheme to changes in intra-group fluxes. For most species, interpolation resulted in errors of less than 5% of transport-computed values. For important scatterers, such as {sup 1}H, errors less than 2% were observed. For nuclides with high errors ( > 10%), the scattering channel typically only had a small probability of occurring. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗