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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development of Instrumented Advanced Test Reactor Irradiation Capsule Experiment for In-situ Thermal Conductivity Measurements of High-Density Fuels

Idaho National Laboratory (INL) is developing a first-of-a-kind leadout instrumented capsule experiment design to enable in-situ measurement capabilities in the Advanced Test Reactor (ATR) core. The Ceramic Advanced Thermal Evolution Research (CRATER) experiment supports the aLEU program objective to accelerate fuel performance irradiation testing for identifying alternative high-assay, low enriched uranium (HALEU) fuel systems. CRATER is a fueled, instrumented capsule experiment to measure in-situ temperature and thermal conductivity of ceramic fuels. Two ceramic fuel types will be used, uranium mono-nitride (UN) and uranium mono-carbide (UC), with a third metallic fuel used for comparison (UMo). The three fuel specimens will use a stainless-steel cladding. Programmatic objectives include linear heat generation rates (LHGR) of 210 ± 25 Watts per cm. and an inner clad temperature of 300-450 °C. The evolution of fuel thermal conductivity during irradiation has never been successfully measured in-situ for these systems and this experiment is designed to use advances in measurement sciences to characterize how thermal transport properties evolve while in reactor. Neutronic simulations of the experiment and its surrounding reactor environment were conducted using the Monte Carlo N-Particle Transport code (MCNP) and result in optimized fuel enrichment to meet target linear heat generation rates (LHGRs) influencing fuel temperatures, and fuel burnup requirements. Fabrication research and development (R&D) efforts are underway to produce annular right cylinder UC and UN pellets using carbothermic reduction and nitridation (or hydride-dehydride-nitride) synthesis methods, followed double-action die cold isostatic pressing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Multi-objective optimization of a PCHE-type intermediate heat exchanger using genetic algorithms

For the advanced nuclear reactor systems and power conversion units, it is important to optimize the design of intermediate heat exchangers (IHXs) which transfer heat from the primary loop to the secondary or intermediate loop. For a multi-objective optimization problem, a printed circuit heat exchanger-type IHX with zigzag and S-shaped fin channels is selected to be optimized in terms of both the total cost and the heat exchanger thermal effectiveness using genetic algorithms. A computer code is developed to search a set of optimized designs of the zigzag channel geometry. It is found that among the Pareto-optimal solutions, the total cost is approximately linearly related to the thermal effectiveness between 88 and 95% while it rises rapidly after the effectiveness exceeds 95%. An optimal flow channel diameter is also determined through the optimization. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Collaborating CPU and GPU for large-scale high-order CFD simulations with complex grids on the TianHe-1A supercomputer

Programming and optimizing complex, real-world CFD codes on current many-core accelerated HPC systems is very challenging, especially when collaborating CPUs and accelerators to fully tap the potential of heterogeneous systems. In this paper, with a tri-level hybrid and heterogeneous programming model using MPI + OpenMP + CUDA, we port and optimize our high-order multi-block structured CFD software HOSTA on the GPU-accelerated TianHe-1A supercomputer. HOSTA adopts two self-developed high-order compact definite difference schemes WCNS and HDCS that can simulate flows with complex geometries. We present a dual-level parallelization scheme for efficient multi-block computation on GPUs and perform particular kernel optimizations for high-order CFD schemes. The GPU-only approach achieves a speedup of about 1.3 when comparing one Tesla M2050 GPU with two Xeon X5670 CPUs. To achieve a greater speedup, we collaborate CPU and GPU for HOSTA instead of using a naive GPU-only approach. We present a novel scheme to balance the loads between the store-poor GPU and the store-rich CPU. Taking CPU and GPU load balance into account, we improve the maximum simulation problem size per TianHe-1A node for HOSTA by 2.3×, meanwhile the collaborative approach can improve the performance by around 45% compared to the GPU-only approach. Further, to scale HOSTA on TianHe-1A, we propose a gather/scatter optimization to minimize PCI-e data transfer times for ghost and singularity data of 3D grid blocks, and overlap the collaborative computation and communication as far as possible using some advanced CUDA and MPI features. Scalability tests show that HOSTA can achieve a parallel efficiency of above 60% on 1024 TianHe-1A nodes. With our method, we have successfully simulated an EET high-lift airfoil configuration containing 800M cells and China's large civil airplane configuration containing 150M cells. To our best knowledge, those are the largest-scale CPU–GPU collaborative simulations that solve realistic CFD problems with both complex configurations and high-order schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

TU-C-17A-12: Towards a Passively Optimized Phase-Space Monte Carlo (POPMC) Treatment Planning Method: A Proof of Principle

Purpose: The advent of on-line/off-line adaptive, and biologically-conformal radiation therapy has led to a need for treatment planning solutions that utilize voxel-specific penalties, requiring optimization over a large solution space that is performed quickly, and the dose in each voxel calculated accurately. This work proposes a “passive” optimization framework, which is executed concurrently during Monte Carlo dose calculation, evaluating the cost/benefit of each history during transport, and creates a passively optimized fluence map. Methods: The Monte Carlo code Geant4 v9.6 was used for this study. The standard voxel geometry implementation was modified to support the passive optimization framework, with voxel-specific optimization parameters. Dose-benefit functions, which will increase a particle history’s weight upon dose deposition, were defined in a central collection of voxels to effectively create target structures. Histories that deposit energy to voxels are reweighted based on a voxel’s dose multiplied by its cost/benefit value. Upon full termination of each history, the dose contributions of that history are reweighted to reflect a contribution proportional to the history’s final weight. A parallel-planar 1.25 MeV photon fluence is transported through the geometry, and re-weighted at each dose deposition step. The resulting weight is tallied with the incident spatial and directional coordinates in a phase-space distribution. Results: A uniform incident fluence was reweighted during MC dose calculations to create an optimized fluence map which would generate dose profiles in target volumes that exhibit the same dose characteristics as the prescribed optimization parameters. An optimized dose profile, calculated concurrently with the phase-space, reflects the resulting dose distribution. Conclusion: This study demonstrated the feasibility of passively optimizing an incident fluence map during Monte Carlo dose calculations. The flexibility of the voxel-specific optimization framework allows a variety and combination of optimization parameters to be calculated for each voxel at every transportation step. This work is partially supported by Varian. This work is partially supported by the NIH.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Coupled Target-Beam-Moderator Optimization for the Second Target Station

This report describes the results for a coupled target-beam-moderator optimization analysis for the Second Target Station (STS) at ORNL's Spallation Neutron Source. This study is a continuation of the optimization analysis for the moderators in the preliminary design of STS performed in 2022. In the 2022 analysis the dimensions of the moderators are parameterized, while the target and the proton beam profile are kept constant. In this analysis the target height and the proton beam profile are added as parameters. This allows to study the coupled effects of changing target, moderator and beam dimensions. Similar to the 2022 analysis, this work is performed with an automated optimization workflow that uses the optimization toolbox DAKOTA, parameterized geometries in CREO and SpaceClaim, the unstructured mesh generation in Attila4MC, and the particle transport code MCNP6.2©. This workflow enables an efficient optimization using high-fidelity geometries. The main conclusions of this analysis are the following: • Coupled beam-target-moderator optimization provides a few additional percent performance gain over stand-alone moderator optimization. • The moderator performance is not very sensitive to the target height (between ≈60 and ≈80 mm) as long as the beam profile is chosen adequately. • The moderator performance is sensitive to the choice of beam spatial standard deviations, even when the footprint is kept constant. • The optimal moderator radius is the same for a beam footprint of 30 cm 2 , 62.5 cm 2 , and 90 cm 2 . Also the slope of the super-gaussian beam profile does not significantly impact the optimal moderator radius. • The optimal parameters and sensitivities are very similar to the 2022 optimization analysis. These results only indicate a a difference in the optimal radius of the cylindrical moderator, however, this has been corrected in the final design moderator optimization. The main purpose of this report is to document the simulations, results and lessons learned. The most impactful results are summarized in. We also note that the target geometry used in this work is not the final design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Hands-on Performance Tuning of 3D Finite Difference Earthquake Simulation on GPU Fermi Chipset

3D simulation of earthquake ground motion is one of the most challenging computational problems in science. The emergence of graphic processing units (GPU) as an effective alternative to traditional general purpose processors has become increasingly capable in terms of accelerating scientific computing research. In this paper, we describe our experiences in porting AWP-ODC, a 3D finite difference seismic wave propagation code, to the latest GPU Fermi chipset. We completely rewrote this Fortran-based 13-point asymmetric stencil computation code in C and MPI-CUDA in order to take advantage of the powerful GPU computing capabilities. Our new CUDA code implemented the asymmetric 3D stencil on Fermi to make the best use of GPU on-chip memory for an aggressive parallel efficiency. Benchmark on NVIDIA Tesla M2090 demonstrated 10x speedup versus the original fully optimized AWP-ODC FORTRAN MPI code running on a single Intel Nehalem 2.4 GHz CPU socket (4 cores/CPU), and 15x speedup versus the same MPI code running on a single AMD Istanbul 2.6 GHz CPU socket (6 cores/CPU). Sustained single-GPU performance of 143.8 GFLOPS in single precision is benchmarked for the testing case of 128x128x960 mesh size.

3D Stencil Computation↗
DOE OSTI2011

Simulation and optimization of the NSLS-II SRX beamline combining ray-tracing and wavefront propagation

The Sub-micron Resolution X-ray spectroscopy (SRX) beamline will benefit from the ultralow emittance of the National Synchrotron Light Source II to address a wide variety of scientific applications studying heterogeneous systems at the sub-micrometer scale. This work focuses on the KB branch ({Delta}E: 4.65-28 keV). Its main optical components include a horizontally focusing mirror forming an adjustable secondary source, a horizontally deflecting monochromator and two sets of Kirkpatrick-Baez mirrors as focusing optics of two distinct inline stations for operations requiring either high flux or high resolution. In the first approach, the beamline layout was optimized with ray-tracing calculations involving Shadowvui computer codes. As a result, the location and characteristics of optics were specified for achieving either the most intense or the smallest monochromatic beam possible on the target (10{sup 13} ph/s or 10{sup 12} ph/s respectively in a 500 nm or 65 nm focal spot). At the nanoprobe station, the diffraction limited focusing of X-rays is governed by the beam coherence. Hence, a classical geometric approach is not anymore adapted. To get reliable estimates of the Nanoprobe performances, a wavefront propagation study was performed using Synchrotron Radiation Workshop (SRW) code. At 7.2 keV, calculations show an intense (10{sup 12} ph/s) 67 nm wide diffraction limited spot achieved with actual metrological data of mirrors.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

SU-F-BRD-13: Quantum Annealing Applied to IMRT Beamlet Intensity Optimization

Purpose: We report on the first application of quantum annealing (QA) to the process of beamlet intensity optimization for IMRT. QA is a new technology, which employs novel hardware and software techniques to address various discrete optimization problems in many fields. Methods: We apply the D-Wave Inc. proprietary hardware, which natively exploits quantum mechanical effects for improved optimization. The new QA algorithm, running on this hardware, is most similar to simulated annealing, but relies on natural processes to directly minimize the free energy of a system. A simple quantum system is slowly evolved into a classical system, representing the objective function. To apply QA to IMRT-type optimization, two prostate cases were considered. A reduced number of beamlets were employed, due to the current QA hardware limitation of ∼500 binary variables. The beamlet dose matrices were computed using CERR, and an objective function was defined based on typical clinical constraints, including dose-volume objectives. The objective function was discretized, and the QA method was compared to two standard optimization Methods: simulated annealing and Tabu search, run on a conventional computing cluster. Results: Based on several runs, the average final objective function value achieved by the QA was 16.9 for the first patient, compared with 10.0 for Tabu and 6.7 for the SA. For the second patient, the values were 70.7 for the QA, 120.0 for Tabu, and 22.9 for the SA. The QA algorithm required 27–38% of the time required by the other two methods. Conclusion: In terms of objective function value, the QA performance was similar to Tabu but less effective than the SA. However, its speed was 3–4 times faster than the other two methods. This initial experiment suggests that QA-based heuristics may offer significant speedup over conventional clinical optimization methods, as quantum annealing hardware scales to larger sizes.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2011

Density profile sensitivity study of ASDEX Upgrade ICRF Antennas with the TOPICA code

During operation of the ASDEX Upgrade (AUG) ion cyclotron radio frequency (ICRF) system, Tungsten (W)-coated poloidal limiters and structures connected along magnetic field lines to the antenna can be sources of W, which is attributed to sputtering by ions accelerated in radio frequency (RF) sheaths. In order to analyze and optimize the ICRF antenna performance, accurate and efficient simulation tools are necessary. TOPICA code was developed for analysis of ICRF antenna systems with plasma loading conditions modeled with ID FELICE code. This paper presents an initial comparative analysis of two AUG ICRF antennas for a set of model plasma density profiles (with varying density gradient and antenna cut-off distance). The antennas are presently installed in AUG and differ in that one was partially optimized using HFSS code to reduce E{sub ||} near fields. Power transferred to plasma and sheath driving RF potentials are computed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2011

Gyrokinetic toroidal simulations on leading multi- and manycore HPC systems

The gyrokinetic Particle-in-Cell (PIC) method is a critical computational tool enabling petascale fusion simulation re-search. In this work, we present novel multi- and manycore-centric optimizations to enhance performance of GTC, a PIC-based production code for studying plasma microtur-bulence in tokamak devices. Our optimizations encompass all six GTC sub-routines and include multi-level particle and grid decompositions designed to improve multi-node parallel scaling, particle binning for improved load balance, GPU acceleration of key subroutines, and memory-centric optimizations to improve single-node scaling and reduce memory utilization. The new hybrid MPI-OpenMP and MPI-OpenMP-CUDA GTC versions achieve up to a 2× speedup over the production Fortran code on four parallel systems - clusters based on the AMD Magny-Cours, Intel Nehalem-EP, IBM BlueGene/P, and NVIDIA Fermi architectures. Finally, strong scaling experiments provide insight into parallel scalability, memory utilization, and programmability trade-offs for large-scale gyrokinetic PIC simulations, while attaining a 1.6× speedup on 49,152 XE6 cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Derivative-free optimization for parameter estimation in computational nuclear physics

We consider optimization problems that arise when estimating a set of unknown parameters from experimental data, particularly in the context of nuclear density functional theory. We examine the cost of not having derivatives of these functionals with respect to the parameters. We show that the POUNDERS code for local derivative-free optimization obtains consistent solutions on a variety of computationally expensive energy density functional calibration problems. We also provide a primer on the operation of the POUNDERS software in the Toolkit for advanced optimization.

Wild, Stefan M. (ORCID:0000000260992772)↗
DOE OSTI2024

Delta-Rice: A HDF5 Compression Plugin optimized for Digitized Detector Data

Delta-Rice is an HDF5 (The HDF Group et al., 2020) filter plugin that was developed to compress digitized detector signals recorded by the Nab experiment (Fry et al., 2019), a fundamental neutron physics experiment. This is a two-step process where incoming data is passed through a pre-processing filter and then compressed with Rice coding. A routine for determining the optimal pre-processing filter for a dataset is provided along with an example GPU deployment. When applied to data collected by the Nab data acquisition system, this method produced output files 29% their initial size, and was able to do so with an average read/write throughput in excess of 2 GB/s on a single CPU. Compared to the widely used Gzip compression routine, Delta-Rice reduces the file size by 33% more with over an order of magnitude increase in read/write throughput. Delta-Rice is available on CPU to users through the HDF5 library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis.

The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the DAKOTA software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of DAKOTA-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of DAKOTA's iterative analysis capabilities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quanti cation, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

OpenACC acceleration of the Nek5000 spectral element code

We present a case study of porting NekBone, a skeleton version of the Nek5000 code, to a parallel GPU-accelerated system. Nek5000 is a computational fluid dynamics code based on the spectral element method used for the simulation of incompressible flow. The original NekBone Fortran source code has been used as the base and enhanced by OpenACC directives. The profiling of NekBone provided an assessment of the suitability of the code for GPU systems, and indicated possible kernel optimizations. To port NekBone to GPU systems required little effort and a small number of additional lines of code (approximately one OpenACC directive per 1000 lines of code). The naïve implementation using OpenACC leads to little performance improvement: on a single node, from 16 Gflops obtained with the version without OpenACC, we reached 20 Gflops with the naïve OpenACC implementation. An optimized NekBone version leads to a 43 Gflop performance on a single node. In addition, we ported and optimized NekBone to parallel GPU systems, reaching a parallel efficiency of 79.9% on 1024 GPUs of the Titan XK7 supercomputer at the Oak Ridge National Laboratory.

Computer Science↗
DOE OSTI2014

ACDT: Architected Composite Data Types Trading-in Unfettered Data Access for Improved Execution

With Exascale performance and its challenges in mind, one ubiquitous concern among architects is energy efficiency. Petascale systems projected to Exascale systems are unsustainable at current power consumption rates. One major contributor to system-wide power consumption is the number of memory operations leading to data movement and management techniques applied by the runtime system. To address this problem, we present the concept of the Architected Composite Data Types (ACDT) framework. The framework is made aware of data composites, assigning them a specific layout, transformations and operators. Data manipulation overhead is amortized over a larger number of elements and program performance and power efficiency can be significantly improved. We developed the fundamentals of an ACDT framework on a massively multithreaded adaptive runtime system geared towards Exascale clusters. Showcasing the capability of ACDT, we exercised the framework with two representative processing kernels - Matrix Vector Multiply and the Cholesky Decomposition – applied to sparse matrices. As transformation modules, we applied optimized compress/decompress engines and configured invariant operators for maximum energy/performance efficiency. Additionally, we explored two different approaches based on transformation opaqueness in relation to the application. Under the first approach, the application is agnostic to compression and decompression activity. Such approach entails minimal changes to the original application code, but leaves out potential applicationspecific optimizations. The second approach exposes the decompression process to the application, hereby exposing optimization opportunities that can only be exploited with application knowledge. The experimental results show that the two approaches have their strengths in HW and SW respectively, where the SW approach can yield performance and power improvements that are an order of magnitude better than ACDT-oblivious, hand-optimized implementations.We consider the ACDT runtime framework an important component of compute nodes that will lead towards power efficient Exascale clusters.

exascale↗
DOE OSTI2010

Monte Carlo Studies of the Radiation Fields in the Linac Coherent Light Source Undulators and of the Corresponding Signals in the Cerenkov Beam Loss Monitors

In 2009 the Linac Coherent Light Source (LCLS) at the SLAC National Accelerator Center started free electron laser (FEL) operation. In order to continue to produce the bright and short-pulsed x-ray laser demanded by FEL scientists, this pioneer hard x-ray FEL requires a perfectly tailored magnetic field at the undulators, so that the photons generated at the electron wiggling path interact at the right phase with the electron beam. In such a precise system, small (>0.01%) radiation-induced alterations of the magnetic field in the permanent magnets could affect FEL performance. This paper describes the simulation studies of radiation fields in permanent magnets and the expected signal in the detectors. The transport of particles from the radiation sources (i.e. diagnostic insert) to the undulator magnets and to the beam loss monitors (BLM) was simulated with the intra nuclear cascade codes FLUKA and MARS15. In order to accurately reproduce the optics of LCLS, lattice capabilities and magnetic fields were enabled in FLUKA and betatron oscillations were validated against reference data. All electron events entering the BLMs were printed in data files. The paper also introduces the Radioactive Ion Beam Optimizer (RIBO) Monte Carlo 3-D code, which was used to read from the event files, to compute Cerenkov production and then to simulate the optical coupling of the BLM detectors, accounting for the transmission of light through the quartz.

COMP, SAFETY, XFEL, OTHER↗