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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
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.
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.
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.
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
Flutter of a Low-Aspect-Ratio Rectangular Wing
A flutter test of a low-aspect-ratio rectangular wing was conducted in the Langley Transonic Dynamics Tunnel (TDT). The model used in this flutter test consisted of a rigid wing mounted to the wind-tunnel wall by a flexible, rectangular beam. The flexible support shaft was connected to the wing root and was cantilever mounted to the wind-tunnel wall. The wing had an aspect ratio of 1.5 based on the wing semispan and an NACA 64A010 airfoil shape. The flutter boundary of the model was determined for a Mach number range of 0.5 to 0.97. The shape of the transonic flutter boundary was determined. Actual flutter points were obtained on both the subsonic and supersonic sides of the flutter bucket. The model exhibited a deep transonic flutter bucket over a narrow range of Mach number. At some Mach numbers, the flutter conditions were extrapolated using a subcritical response technique. In addition to the basic configuration, modifications were made to the model structure such that the first bending frequency was changed without significantly affecting the first torsion frequency. The experiment showed that increasing the bending stiffness of the model support shaft through these modifications lowered the flutter dynamic pressure. Flutter analysis was conducted for the basic model as a comparison with the experimental results. This flutter analysis was conducted with subsonic lifting-surface (kernel function) aerodynamics using the k method for the flutter solution.
Static Analysis Using Abstract Interpretation
Lecture about abstract interpretation. This lecture starts with a brief introduction to validation and verification using formal methods. It then demonstrates IKOS (Inference Kernel for Open Static Analyzers), a static analyzer for C/C++ based on Abstract Interpretation. Then, it describes in details the theory of Abstract Interpretation, a mathematical framework to over-approximate the reachable states of a program.
All-sky Retrieval of Atmospheric Temperature, Water Vapor, Clouds, Trace Gases, and Surface Properties from Operational Hyperspectral IR Sounders
Operational IR sounders such AIRS, CrIS, and IASI provide high quality hyperspectral measurements for weather and climate applications. We will describe a new all-sky Single Field-of-view Sounder Atmospheric Product (SiFSAP). The uniqueness of this product is that it uses all available channels from hyperspectral sounders and the optimal estimation retrieval is done at a single FOV spatial resolution. The SiFSAP includes atmospheric temperature, water vapor, clouds, trace gases, surface skin, and surface emissivity and will be produced operationally at NASA GES DISC. We will describe the core component of the SiFSAP algorithm, which is the Principal Component-based Radiative Transfer Model (PCRTM), and will show example applications of the SiFSAP product for various atmospheric weather and dynamics studies. We also describe a new Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides fast and accurate 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. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.
Climate Data Record Derived from Hyperspectral Sounders on AQUA, S-NPP and NOAA 20
Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. It eliminates or reduces the errors due to inconsistent L2 algorithms. 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. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.
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.
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.
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.
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
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.
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)
GPU Acceleration of Kernel Density Estimators in Monte Carlo Neutron Transport Simulations
Kernel Density Estimators (KDEs) have recently been explored for use in Monte Carlo radiation transport simulations as an alternative to histogram tallies for capturing spatially-resolved quantities such as neutron flux and reaction rates. Histogram tallies suffer from large uncertainties when detailed spatial resolution of the quantity of interest is required; increasing the resolution of the underlying mesh increases the uncertainty in each histogram bin. KDEs obtain estimates of underlying densities on user-defined points, with the uncertainty at those points being independent of the spatial resolution desired since collisions and particle-track segments are allowed to contribute to the score at multiple tally points. Thus, KDEs show potential for obtaining estimates of a smoother spatially-resolved with reduced variance when compared to a histogram. However, this ability that enables KDEs to obtain lower uncertainties per particle history is more computationally expensive than using a traditional histogram bins on a structured mesh. While KDEs are capable of producing lower tally uncertainties compared to histogram binning for a given number of histories, their increased computational cost may make them less efficient. Even so, it is possible to reduce this additional cost by exporting the KDE tally routines onto Graphics Processing Units (GPUs). GPUs are commonly found on high-performance computing machines as a means of increasing performance without adding additional compute nodes. While it is difficult for existing Monte Carlo radiation transport codes to take advantage of GPUs without rewriting large portions of the code, it is possible to leverage GPUs through heterogeneous computing. This work uses a modified version of OpenMC and exports the KDE tally routines onto a GPU to obtain problem-dependent speedups ranging between 1.6 and 5.0 for the problem studied in this paper. While this methodology is applied to KDEs, the same ideas can be applied to other computationally expensive vectorizable portions of Monte Carlo algorithms. (authors)
Sharp front tracking with geometric interface reconstruction
Here, this paper presents a novel sharp front-tracking method designed to address limitations in classical front-tracking approaches, specifically their reliance on smooth interpolation kernels and extended stencils for coupling the front and fluid mesh. In contrast, the proposed method employs exclusively sharp, localized interpolation and spreading kernels, restricting the coupling to the interfacial fluid cells–those containing the interface/front. This localized coupling is achieved by integrating a divergence-preserving velocity interpolation method with a piecewise parabolic interface calculation (PPIC) and a polyhedron intersection algorithm to compute the indicator function and local interface curvature. Surface tension is computed using the Continuum Surface Force (CSF) method, maintaining consistency with the sharp representation. Additionally, we propose an efficient local roughness smoothing implementation to account for surface mesh undulations, which is easily applicable to any triangulated surface mesh. Building on our previous work, the primary innovation of this study lies in the localization of the coupling for both the indicator function and surface tension calculations. By reducing the interface thickness on the fluid mesh to a single cell, as opposed to the 4–5 cell spans typical in classical methods, the proposed sharp front-tracking method achieves a highly localized and accurate representation of the interface. This sharper representation mitigates parasitic currents and improves force balancing, making it particularly suitable for scenarios where the interface plays a critical role, such as microfluidics, fluid-fluid interactions, and fluid-structure interactions. The proposed method is comprehensively validated and tested on canonical interfacial flow problems, including stationary and translating Laplace equilibria, oscillating droplets, and rising bubbles. The presented results demonstrate that the sharp front-tracking method significantly outperforms the classical approach in terms of accuracy, stability, and computational efficiency. Notably, parasitic currents are reduced by approximately two orders of magnitude and stable results are obtained for parameter ranges where classical front tracking fails to converge.
A fast band–Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors
We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel. The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousands degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures.