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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Validation of Actuator Line and Actuator Disk Models with Filtered Lifting Line Corrections Implemented in Nalu-Wind Large Eddy Simulations of the Atmospheric Boundary Layer

Turbine generator power from simulations using Actuator Line Models and Actuator Disk Models with a Filtered Lifting Line Correction are compared to field data of a V27 turbine. Preliminary results of the wake characteristics are also presented. Turbine quantities of interest from traditional ALM and ADM with the Gaussian kernel (..epsilon..) set at the optimum value for matching power production and that resolve the kernel at all mesh sizes are also presented. The atmospheric boundary layer is simulated using Nalu-Wind, a Large Eddy Simulation code which is part of the ExaWind code suite. The effect of mesh resolution on quantities of interest is also examined.

Actuator Disk Models↗
DOE OSTI2022

Projecting the Thermal Response in a HTGR-Type System during Conduction Cooldown Using Graph-Laplacian Based Machine Learning

Accurate prediction of an off-normal event in a nuclear reactor is dependent upon the availability of sensory data, reactor core physical condition, and understanding of the underlying phenomenon. This work presents a method to project the data from some discrete sensory locations to the overall reactor domain during conduction cooldown scenarios similar to High Temperature Gas-cooled Reactors (HTGRs). The existing models for conductive cooldown in a heterogeneous multi-body system, such as an assembly of prismatic blocks or pebble beds relies on knowledge of the thermal contact conductance, requiring significant knowledge of local thermal contacts and heat transport possibilities across those contacts. With a priori knowledge of bulk geometry features and some discrete sensors, a machine learning approach was devised. The presented work uses an experimental facility to mimic conduction cooldown with an assembly of 68 cylindrical rods initially heated to 1200 K. High-fidelity temperature data were collected using an infrared (IR) camera to provide training data to the model and validate the predicted temperature data. The machine learning approach used here first converts the macroscopic bulk geometry information into Graph-Laplacian, and then uses the eigenvectors of the Graph-Laplacian to develop Kernel functions. Support vector regression (SVR) was implemented on the obtained Kernels and used to predict the thermal response in a packed rod assembly during a conduction cooldown experiment. The usage of SVR modeling differs from most models today because of its representation of thermal coupling between rods in the core. When trained with thermographic data, the average normalized error is less than 2% over 400 s, during which temperatures of the assembly have dropped by more than 500 K. The rod temperature prediction performance was significantly better for rods in the interior of the assembly compared to those near the exterior, likely due to the model simplification of the surroundings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

EXAMINING THE ACCURACY OF ASTROPHYSICAL DISK SIMULATIONS WITH A GENERALIZED HYDRODYNAMICAL TEST PROBLEM

We discuss a generalization of the classic Keplerian disk test problem allowing for both pressure and rotational support, as a method of testing astrophysical codes incorporating both gravitation and hydrodynamics. We argue for the inclusion of pressure in rotating disk simulations on the grounds that realistic, astrophysical disks exhibit non-negligible pressure support. We then apply this test problem to examine the performance of various smoothed particle hydrodynamics (SPH) methods incorporating a number of improvements proposed over the years to address problems noted in modeling the classical gravitation-only Keplerian disk. We also apply this test to a newly developed extension of SPH based on reproducing kernels called CRKSPH. Counterintuitively, we find that pressure support worsens the performance of traditional SPH on this problem, causing unphysical collapse away from the steady-state disk solution even more rapidly than the purely gravitational problem, whereas CRKSPH greatly reduces this error.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

IRIS , Hinode , SDO , and RHESSI Observations of a White Light Flare Produced Directly by Non-thermal Electrons

An X1.6 flare occurred in active region AR 12192 on 2014 October 22 at 14:02 UT and was observed by Hinode , IRIS , SDO , and RHESSI . We analyze a bright kernel that produces a white light (WL) flare with continuum enhancement and a hard X-ray (HXR) peak. Taking advantage of the spectroscopic observations of IRIS and Hinode /EIS, we measure the temporal variation of the plasma properties in the bright kernel in the chromosphere and corona. We find that explosive evaporation was observed when the WL emission occurred, even though the intensity enhancement in hotter lines is quite weak. The temporal correlation of the WL emission, HXR peak, and evaporation flows indicates that the WL emission was produced by accelerated electrons. To understand the WL emission process, we calculated the energy flux deposited by non-thermal electrons (observed by RHESSI ) and compared it to the dissipated energy estimated from a chromospheric line (Mg ii triplet) observed by IRIS . The deposited energy flux from the non-thermal electrons is about (3–7.7) × 10{sup 10} erg cm{sup −2} s{sup −1} for a given low-energy cutoff of 30–40 keV, assuming the thick-target model. The energy flux estimated from the changes in temperature in the chromosphere measured using the Mg ii subordinate line is about (4.6–6.7) × 10{sup 9} erg cm{sup −2} s{sup −1}: ∼6%–22% of the deposited energy. This comparison of estimated energy fluxes implies that the continuum enhancement was directly produced by the non-thermal electrons.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

On a Spectral Method for β -particle Bound Excitation Collisions in Kilonovae

The interaction of β-particles with the weakly ionized plasma background is an important mechanism for powering the kilonova (KN) transient signal from neutron star mergers. For this purpose, we present an implementation of the approximate fast-particle collision kernel, described by Inokuti following the seminal formulation of Bethe, in a spectral solver of the Vlasov–Maxwell–Boltzmann equation. In particular, we expand the fast-particle plane-wave atomic excitation kernel into coefficients of the Hermite basis, and derive the relevant discrete spectral system. In this fast-particle limit, the approach permits the direct use of atomic data, including optical oscillator strengths, normally applied to photon–matter interaction. The resulting spectral matrix is implemented in the MASS-APP spectral solver framework, in a way that avoids full matrix storage per spatial zone. We numerically verify aspects of the matrix construction, and present a proof-of-principle 3D simulation of a 2D axisymmetric KN ejecta snapshot. Our preliminary numerical results indicate that a reasonable choice of Hermite basis parameters for β-particles in the KN is a bulk velocity parameter u = 0, a thermal velocity parameter α = 0.5c, and a 9 × 9 × 9 mode velocity basis set (Hermite orders of 0–8 in each dimension). For interior-ejecta sample zones, we estimate that the ratio of thermalization from large-angle (≳2fdg5) bound excitation scattering to total thermalization is ~0.002–0.003.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Multi-objective optimization of peel and shear strengths in ultrasonic metal welding using machine learning-based response surface methodology

Ultrasonic metal welding (UMW) is a solid-state joining technique with varied industrial applications. Despite of its numerous advantages, UMW has a relative narrow operating window and is sensitive to variations in process conditions. As such, it is imperative to quantitatively characterize the influence of welding parameters on the resulting joint quality. The quantification model can be subsequently used to optimize the parameters. Conventional response surface methodology (RSM) usually employs linear or polynomial models, which may not be able to capture the intricate, nonlinear input-output relationships in UMW. Furthermore, some UMW applications call for simultaneous optimization of multiple quality indices such as peel strength, shear strength, electrical conductivity, and thermal conductivity. To address these challenges, this paper develops a machine learning (ML)-based RSM to model the input-output relationships in UMW and jointly optimize two quality indices, namely, peel and shear strengths. The performance of various ML methods including spline regression, Gaussian process regression (GPR), support vector regression (SVR), and conventional polynomial regression models with different orders is compared. A case study using experimental data shows that GPR with radial basis function (RBF) kernel and SVR with RBF kernel achieve the best prediction accuracy. The obtained response surface models are then used to optimize a compound joint strength indicator that is defined as the average of normalized shear and peel strengths. In addition, the case study reveals different patterns in the response surfaces of shear and peel strengths, which has not been systematically studied in the literature. While developed for the UMW application, the method can be extended to other manufacturing processes.

42 ENGINEERING↗
DOE OSTI2021

EGR Dilution and Fuel Property Effects on High-Efficiency Spark-Ignition Flames

Modern spark ignition internal combustion engines rely on fast combustion rates and high dilution to achieve high brake thermal efficiencies. To accomplish this, new engine designs have moved towards increased tumble ratios and stroke-to-bore ratios. Increased tumble ratios correlate positively with increases in turbulent kinetic energy and improved fuel and residual gas mixing, all of which favor faster and more efficient combustion. Longer stroke-to-bore ratios allow higher geometric compression ratios and use of late intake valve closing to control peak compression pressures and temperatures. The addition of dilution to improve efficiency is limited by the resulting increase in combustion instabilities manifested by cycle-to-cycle variability. A number of effects - preferential diffusion, turbulence-combustion interactions, stochastic flow patterns, laminar-turbulent flame kernel transitions, and relative length and velocity scales between flame and turbulence - are believed to be responsible for the increase in cycle-to-cycle variations, where their contributions are likely interlinked. Several studies have shown the influence of stochastic flow characteristics on the nature of combustion instabilities, such as velocity patterns on flame kernel formation and cycle-to-cycle variations in residual gas. However, few have focused on the specific effects of fuel properties. The objective of this work is to contrast the effects of dilution on propane stoichiometric combustion against gasoline. Dilution tolerance experiments were conducted in a purpose-built high stroke-to-bore ratio single cylinder engine with both gasoline and LPG. Three-dimensional full cycle computational fluid dynamics (CFD) simulations employing a level-set combustion approach and Reynolds averaged Navier-Stokes (RANS) turbulence modeling was used to qualitatively assess the changes in length and velocity scales for turbulence and the flame. The experimental results showed that LPG can tolerate higher exhaust gas recirculation (EGR) dilution under a variety of conditions. Analysis of CFD simulations showed that propane flames are likely less sensitive to influences from the flow field due to less thickening of the flame and higher effective flame speeds.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

A double copy from twisted (co)homology at genus g

We study a family of generalized hypergeometric integrals defined on punctured Riemann surfaces of genus g. These integrals are closely related to g-loop string amplitudes in chiral splitting, where one leaves the loop-momenta, moduli and all but one puncture un-integrated. We study the twisted homology groups associated to these integrals, and determine their intersection numbers. We make use of these homology intersection numbers to write a double-copy formula for the "complex" version of these integrals -- their closed-string analogues. To verify our findings, we develop numerical tools for the evaluation of the integrals in this work. This includes the recently introduced Enriquez kernels -- integration kernels for higher-genus polylogarithms.

Pokraka, Andrejz [Brown University; Amsterdam Univ↗
DOE OSTI2021

TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets

TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth system datasets on either rectilinear or unstructured/native grids. Version 2.1 of the TE framework now provides extensive support for examining both nodal (i.e., pointwise) and areal features, including tropical and extratropical cyclones, monsoonal lows and depressions, atmospheric rivers, atmospheric blocking, precipitation clusters, and heat waves. Available operations include nodal and areal thresholding, calculations of quantities related to nodal features such as accumulated cyclone energy and azimuthal wind profiles, filtering data based on the characteristics of nodal features, and stereographic compositing. This paper describes the core algorithms (kernels) that have been added to the TE framework since version 1.0, including algorithms for editing pointwise trajectory files, composition of fields around nodal features, generation of areal masks via thresholding and nodal features, and tracking of areal features in time. Several examples are provided of how these kernels can be combined to produce composite algorithms for evaluating and understanding common atmospheric features and their underlying processes. These examples include analyzing the fraction of precipitation from tropical cyclones, compositing meteorological fields around extratropical cyclones, calculating fractional contribution to poleward vapor transport from atmospheric rivers, and building a climatology of atmospheric blocks.

58 GEOSCIENCES↗
DOE OSTI2018

Fault Diagnosis of Hybrid Computing Systems Using Chaotic-Map Method

Computing systems are becoming increasingly complex with nodes consisting of a combination of multi-core central processing units (CPUs), many integrated core (MIC) and graphics processing unit (GPU) accelerators. These computing units and their interconnections are subject to different classes of hardware and software faults, which should be detected to support mitigation measures. We present the chaotic-map method that uses the exponential divergence and wide Fourier properties of the trajectories, combined with memory allocations and assignments to diagnose component-level faults in these hybrid computing systems. We propose lightweight codes that utilize highly parallel chaotic-map computations tailored to isolate faults in arithmetic units, memory elements and interconnects. The diagnosis module on a node utilizes pthreads to place chaotic-map threads on CPU and MIC cores, and CUDA C and OpenCL kernels on GPU blocks. We present experimental diagnosis results on five multi-core CPUs; one MIC; and, seven GPUs with typical diagnosis run-times under a minute.

Rao, Nageswara↗
DOE OSTI2014

3D and 4D magnetic susceptibility tomography based on complex MR images

Magnetic susceptibility is the physical property for T2*-weighted magnetic resonance imaging (T2*MRI). The invention relates to methods for reconstructing an internal distribution (3D map) of magnetic susceptibility values, .chi. (x,y,z), of an object, from 3D T2*MRI phase images, by using Computed Inverse Magnetic Resonance Imaging (CIMRI) tomography. The CIMRI technique solves the inverse problem of the 3D convolution by executing a 3D Total Variation (TV) regularized iterative convolution scheme, using a split Bregman iteration algorithm. The reconstruction of .chi. (x,y,z) can be designed for low-pass, band-pass, and high-pass features by using a convolution kernel that is modified from the standard dipole kernel. Multiple reconstructions can be implemented in parallel, and averaging the reconstructions can suppress noise. 4D dynamic magnetic susceptibility tomography can be implemented by reconstructing a 3D susceptibility volume from a 3D phase volume by performing 3D CIMRI magnetic susceptibility tomography at each snapshot time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Architecture for removable media USB-ARM

A storage device is coupled to a computing system comprising an operating system and application software. Access to the storage device is blocked by a kernel filter driver, except exclusive access is granted to a first anti-virus engine. The first anti-virus engine is directed to scan the storage device for malicious software and report results. Exclusive access may be granted to one or more other anti-virus engines and they may be directed to scan the storage device and report results. Approval of all or a portion of the information on the storage device is based on the results from the first anti-virus engine and the other anti-virus engines. The storage device is presented to the operating system and access is granted to the approved information. The operating system may be a Microsoft Windows operating system. The kernel filter driver and usage of anti-virus engines may be configurable by a user.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SSCA1-K1

SSCA1-K1 is a parallel implementation of kernel 1 of the SSCA1 benchmark suite released by the DARPA HPCS program. This kernel is able to run in parallel on a distributed shared memory system at extreme scales using OpenSHMEM.

Baker, Matthew↗
DOE OSTI2016

Balancing Particle and Mesh Computation in a Particle-In-Cell Code

The XGC1 plasma microturbulence particle-in-cell simulation code has both particle-based and mesh-based computational kernels that dominate performance. Both of these are subject to load imbalances that can degrade performance and that evolve during a simulation. Each separately can be addressed adequately, but optimizing just for one can introduce significant load imbalances in the other, degrading overall performance. A technique has been developed based on Golden Section Search that minimizes wallclock time given prior information on wallclock time, and on current particle distribution and mesh cost per cell, and also adapts to evolution in load imbalance in both particle and mesh work. In problems of interest this doubled the performance on full system runs on the XK7 at the Oak Ridge Leadership Computing Facility compared to load balancing only one of the kernels.

Worley, Patrick H↗
DOE OSTI2016

Early Experiences Writing Performance Portable OpenMP 4 Codes

In this paper, we evaluate the recently available directives in OpenMP 4 to parallelize a computational kernel using both the traditional shared memory approach and the newer accelerator targeting capabilities. In addition, we explore various transformations that attempt to increase application performance portability, and examine the expressiveness and performance implications of using these approaches. For example, we want to understand if the target map directives in OpenMP 4 improve data locality when mapped to a shared memory system, as opposed to the traditional first touch policy approach in traditional OpenMP. To that end, we use recent Cray and Intel compilers to measure the performance variations of a simple application kernel when executed on the OLCF s Titan supercomputer with NVIDIA GPUs and the Beacon system with Intel Xeon Phi accelerators attached. To better understand these trade-offs, we compare our results from traditional OpenMP shared memory implementations to the newer accelerator programming model when it is used to target both the CPU and an attached heterogeneous device. We believe the results and lessons learned as presented in this paper will be useful to the larger user community by providing guidelines that can assist programmers in the development of performance portable code.

Joubert, Wayne↗
DOE OSTI2016

HIGH-TEMPERATURE SAFETY TESTING OF IRRADIATED AGR-1 TRISO FUEL

High-Temperature Safety Testing of Irradiated AGR-1 TRISO Fuel John D. Stempien, Paul A. Demkowicz, Edward L. Reber, and Cad L. Christensen Idaho National Laboratory, P.O. Box 1625 Idaho Falls, ID 83415, USA Corresponding Author: john.stempien@inl.gov, +1-208-526-8410 Two new safety tests of irradiated tristructural isotropic (TRISO) coated particle fuel have been completed in the Fuel Accident Condition Simulator (FACS) furnace at the Idaho National Laboratory (INL). In the first test, three fuel compacts from the first Advanced Gas Reactor irradiation experiment (AGR-1) were simultaneously heated in the FACS furnace. Prior to safety testing, each compact was irradiated in the Advanced Test Reactor to a burnup of approximately 15 % fissions per initial metal atom (FIMA), a fast fluence of 3×1025 n/m2 (E > 0.18 MeV), and a time-average volume-average (TAVA) irradiation temperature of about 1020 °C. In order to simulate a core-conduction cool-down event, a temperature-versus-time profile having a peak temperature of 1700 °C was programmed into the FACS furnace controllers. Gaseous fission products (i.e., Kr-85) were carried to the Fission Gas Monitoring System (FGMS) by a helium sweep gas and captured in cold traps featuring online gamma counting. By the end of the test, a total of 3.9% of an average particle’s inventory of Kr-85 was detected in the FGMS traps. Such a low Kr-85 activity indicates that no TRISO failures (failure of all three TRISO layers) occurred during the test. If released from the compacts, condensable fission products (e.g., Ag-110m, Cs-134, Cs-137, Eu-154, Eu-155, and Sr-90) were collected on condensation plates fitted to the end of the cold finger in the FACS furnace. These condensation plates were then analyzed for fission products. In the second test, five loose UCO fuel kernels, obtained from deconsolidated particles from an irradiated AGR-1 compact, were heated in the FACS furnace to a peak temperature of 1600 °C. This test had two primary goals. First, the test was intended to assess the retention of fission products in loose kernels without the effects of the other TRISO layers (buffer, IPyC, SiC, and OPyC) or the graphitic matrix material comprising the compact. Second, this test served as an evaluation of the FACS fission product condensation plate collection efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Fission Product Inventory and Burnup Evaluation of the AGR-2 Irradiation by Gamma Spectrometry

Gamma spectrometry has been used to evaluate the burnup and fission product inventory of different components from the US Advanced Gas Reactor Fuel Development and Qualification Program's second TRISO-coated particle fuel irradiation test (AGR-2). TRISO fuel in this irradiation included both uranium carbide / uranium oxide (UCO) kernels and uranium oxide (UO2) kernels. Four of the 6 capsules contained fuel from the US Advanced Gas Reactor program, and only those capsules will be discussed in this work. The inventories of gamma-emitting fission products from the fuel compacts, graphite compact holders, graphite spacers and test capsule shell were evaluated. These data were used to measure the fractional release of fission products such as Cs-137, Cs-134, Eu-154, Ce-144, and Ag-110m from the compacts. The fraction of Ag-110m retained in the compacts ranged from 1.8% to full retention. Additionally, the activities of the radioactive cesium isotopes (Cs-134 and Cs-137) have been used to evaluate the burnup of all US TRISO fuel compacts in the irradiation. The experimental burnup evaluations compare favorably with burnups predicted from physics simulations. Predicted burnups for UCO compacts range from 7.26 to 13.15 % fission per initial metal atom (FIMA) and 9.01 to 10.69 % FIMA for UO2 compacts. Measured burnup ranged from 7.3 to 13.1 % FIMA for UCO compacts and 8.5 to 10.6 % FIMA for UO2 compacts. Results from gamma emission computed tomography performed on compacts and graphite holders that reveal the distribution of different fission products in a component will also be discussed. Gamma tomography of graphite holders was also used to locate the position of TRISO fuel particles suspected of having silicon carbide layer failures that lead to in-pile cesium release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

ArrayBridge: Interweaving declarative array processing with high-performance computing

Scientists are increasingly turning to datacenter-scale computers to produce and analyze massive arrays. Despite decades of database research that extols the virtues of declarative query processing, scientists still write, debug and parallelize imperative HPC kernels even for the most mundane queries. This impedance mismatch has been partly attributed to the cumbersome data loading process; in response, the database community has proposed in situ mechanisms to access data in scientific file formats. Scientists, however, desire more than a passive access method that reads arrays from files. This paper describes ArrayBridge, a bi-directional array view mechanism for scientific file formats, that aims to make declarative array manipulations interoperable with imperative file-centric analyses. Our prototype implementation of ArrayBridge uses HDF5 as the underlying array storage library and seamlessly integrates into the SciDB open-source array database system. In addition to fast querying over external array objects, ArrayBridge produces arrays in the HDF5 file format just as easily as it can read from it. ArrayBridge also supports time travel queries from imperative kernels through the unmodified HDF5 API, and automatically deduplicates between array versions for space efficiency. Our extensive performance evaluation in NERSC, a large-scale scientific computing facility, shows that ArrayBridge exhibits statistically indistinguishable performance and I/O scalability to the native SciDB storage engine.

97 MATHEMATICS AND COMPUTING↗