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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Calculation of natural convection test at Phenix using the NETFLOW++ code

The present paper describes modeling and analyses of a natural convection of the pool-type fast breeder reactor Phenix. The natural convection test was carried out as one of the End of Life Tests of the Phenix. Objective of the present study is to assess the applicability of the NETFLOW++ code which has been verified thus far using various water facilities and validated using the plant data of the loop-type FBR 'Monju' and the loop-type experimental fast reactor 'Joyo'. The Phenix primary heat transport system is modeled based on the benchmark documents available from IAEA. The calculational model consists of only the primary heat transport system with boundary conditions on the secondary-side of IHX. The coolant temperature at the primary pump inlet, the primary coolant temperature at the IHX inlet and outlet, the secondary coolant temperatures and other parameters are calculated by the code where the heat transfer between the hot and cold pools is explicitly taken into account. A model including the secondary and tertiary systems was prepared, and the calculated results also agree well with the measured data in general. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2010

Objectives and layout of a high-resolution x-ray imaging crystal spectrometer for the large helical device

A high-resolution x-ray imaging crystal spectrometer, whose concept was tested on NSTX and Alcator C-Mod, is being designed for the large helical device (LHD). This instrument will record spatially resolved spectra of helium-like Ar{sup 16+} and will provide ion temperature profiles with spatial and temporal resolutions of <2 cm and {>=}10 ms, respectively. The spectrometer layout and instrumental features are largely determined by the magnetic field structure of LHD. The stellarator equilibrium reconstruction codes, STELLOPT and PIES, will be used for the tomographic inversion of the spectral data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2010

AZURE: An R-matrix code for nuclear astrophysics

The paper describes a multilevel, multichannel R-matrix code, AZURE, for applications in nuclear astrophysics. The code allows simultaneous analysis and extrapolation of low-energy particle scattering, capture, and reaction cross sections of relevance to stellar hydrogen, helium, and carbon burning. The paper presents a summary of R-matrix theory, code description, and a number of applications to demonstrate the applicability and versatility of AZURE.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Final Report for "Extending BOUT++ for Solution of Edge Plasma Equations for Use in Whole Device Simulation of Tokamaks"

In this Phase I project we have extended the BOUT++ code to solve edge fluid equations. We added a simple neutral fluid model, created a mesh generator as well as collected a set of difficult test problems for benchmarking edge codes. The work in this project should be useful as a starting point to build a complete set of edge fluid equations in BOUT++ that would enhance its ability to not only perform edge turbulence calculations, but also allow the coupled transport-turbulence equations evolved in an efficient manner.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

SU-F-18C-09: Assessment of OSL Dosimeter Technology in the Validation of a Monte Carlo Radiation Transport Code for CT Dosimetry

Purpose: To assess the utility of optically stimulated luminescent (OSL) dosimeter technology in calibrating and validating a Monte Carlo radiation transport code for computed tomography (CT). Methods: Exposure data were taken using both a standard CT 100-mm pencil ionization chamber and a series of 150-mm OSL CT dosimeters. Measurements were made at system isocenter in air as well as in standard 16-cm (head) and 32-cm (body) CTDI phantoms at isocenter and at the 12 o'clock positions. Scans were performed on a Philips Brilliance 64 CT scanner for 100 and 120 kVp at 300 mAs with a nominal beam width of 40 mm. A radiation transport code to simulate the CT scanner conditions was developed using the GEANT4 physics toolkit. The imaging geometry and associated parameters were simulated for each ionization chamber and phantom combination. Simulated absorbed doses were compared to both CTDI{sub 100} values determined from the ion chamber and to CTDI{sub 100} values reported from the OSLs. The dose profiles from each simulation were also compared to the physical OSL dose profiles. Results: CTDI{sub 100} values reported by the ion chamber and OSLs are generally in good agreement (average percent difference of 9%), and provide a suitable way to calibrate doses obtained from simulation to real absorbed doses. Simulated and real CTDI{sub 100} values agree to within 10% or less, and the simulated dose profiles also predict the physical profiles reported by the OSLs. Conclusion: Ionization chambers are generally considered the standard for absolute dose measurements. However, OSL dosimeters may also serve as a useful tool with the significant benefit of also assessing the radiation dose profile. This may offer an advantage to those developing simulations for assessing radiation dosimetry such as verification of spatial dose distribution and beam width.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

AeroDyn V15.04: Design Tool for Wind and MHK Turbines

AeroDyn is a time-domain wind and MHK turbine aerodynamics module that can be coupled into the FAST version 8 multi-physics engineering tool to enable aero-elastic simulation of horizontal-axis wind turbines. AeroDyn V15.04 has been updated to include a cavitation check for MHK turbines, and can be driven as a standalone code to compute wind turbine aerodynamic response uncoupled from FAST. Note that while AeroDyn has been updated to v15.04, FAST v8.16 has not yet been updated and still uses AeroDyn v15.03.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

PDQ Users Manual. Manual Version 2, for PDQ Code Version 1.20

PDQ is a tool for the management of the input and execution of batch jobs for simulation codes that use a text based input system. It accomplishes this goal by operating at two levels. First, it takes input file templates (commonly known at LANL as input deck templates) and creates multiple instantiations by performing substitutions of data from table files into symbols (variables) found in the template. Second, it provides commands to submit the created files to the SLURM batch system for execution. These two activities taken together produce a whole that is greater than the sum of its parts and provides an elegant way of executing studies across multiple similar simulations while minimizing the risk of typographical errors in the input files. PDQ was originally developed as a job management system called XVS by Jeff McAninch while he was at LANL. Besides the capabilities described here, XVS had many other features specific for interactions with particular simulation codes. After Jeff’s departure, maintenance of XVS was taken over by Rendell Carver; he added some new features as well as kept it functioning as the batch system at LANL was changed from LSF to MOAB to SLURM. In 2017, Rob Pelak decided to develop a different version that removed the additional features (many of which were rendered obsolete with the retirement of the simulation code or batch system that they supported) and produced a cleaner “bare bones” version of XVS. A few other behaviors of XVS that Rob found irksome were altered. Rob gave the resulting code a new name: PDQ. In 2022 Danielle McDermott developed a version that runs under Python 3.X. As suggested by Rob, she used the python2to3 utility to identify most changes. Given that PDQ continues to operate with Python version 2.7 we have advanced the version number to 1.20.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Reflector modelling of small high leakage cores making use of multi-group nodal equivalence theory

This research focuses on modelling reflectors in typical material testing reactors (MTRs). Equivalence theory is used to homogenise and collapse detailed transport solutions to generate equivalent nodal parameters and albedo boundary conditions for reflectors, for subsequent use in full core nodal diffusion codes. This approach to reflector modelling has been shown to be accurate for two-group large commercial light water reactor (LWR) analysis, but has not been investigated for MTRs. MTRs are smaller, with much larger leakage, environment sensitivity and multi-group spectrum dependencies than LWRs. This study aims to determine if this approach to reflector modelling is an accurate and plausible homogenisation technique for the modelling of small MTR cores. The successful implementation will result in simplified core models, better accuracy and improved efficiency of computer simulations. Codes used in this study include SCALE 6.1, OSCAR-4 and EQUIVA (the last two codes are developed and used at Necsa). The results show a five times reduction in calculational time for the proposed reduced reactor model compared to the traditional explicit model. The calculated equivalent parameters however show some sensitivity to the environment used to generate them. Differences in the results compared to the current explicit model, require more careful investigation including comparisons with a reference result, before its implementation can be recommended. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2010

Efficient Modeling of Laser-Plasma Accelerators with INF and RNO

The numerical modeling code INF and RNO (INtegrated Fluid and paRticle simulatioN cOde, pronounced 'inferno') is presented. INF and RNO is an efficient 2D cylindrical code to model the interaction of a short laser pulse with an underdense plasma. The code is based on an envelope model for the laser while either a PIC or a fluid description can be used for the plasma. The effect of the laser pulse on the plasma is modeled with the time-averaged poderomotive force. These and other features allow for a speedup of 2-4 orders of magnitude compared to standard full PIC simulations while still retaining physical fidelity. The code has been benchmarked against analytical solutions and 3D PIC simulations and here a set of validation tests together with a discussion of the performances are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analy- sis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncer- tainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is in- terested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assess- ment capability to RELAP-7, currently under develop-ment at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explaination of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Leading-order electroweak corrections to the Drell-Yan process in the CMS experiment at LHC

The leading part of electroweak radiative corrections to the Drell-Yan process in the CMS (compact muon solenoid detector) experiment at LHC were calculated. Analytic and numerical tests indicate that the results are independent of all nonphysical parameters. A numerical analysis of radiative effects was performed by using the FORTRAN code READY with allowance for experimental constraints at the CMS detector. The results presented for the relative correction to the fully differential cross section for the Drell-Yan process over the entire kinematical region of the CMS detector would hopefully be helpful in handling experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Advanced multiphysics coupling for LWR fuel performance analysis

Even the most basic nuclear fuel analysis is a multiphysics undertaking, as a credible simulation must consider at a minimum coupled heat conduction and mechanical deformation. The need for more realistic fuel modeling under a variety of conditions invariably leads to a desire to include coupling between a more complete set of the physical phenomena influencing fuel behavior, including neutronics, thermal hydraulics, and mechanisms occurring at lower length scales. This paper covers current efforts toward coupled multiphysics LWR fuel modeling in three main areas. The first area covered in this paper concerns thermomechanical coupling. The interaction of these two physics, particularly related to the feedback effect associated with heat transfer and mechanical contact at the fuel/clad gap, provides numerous computational challenges. An outline is provided of an effective approach used to manage the nonlinearities associated with an evolving gap in BISON, a nuclear fuel performance application. A second type of multiphysics coupling described here is that of coupling neutronics with thermomechanical LWR fuel performance. DeCART, a high-fidelity core analysis program based on the method of characteristics, has been coupled to BISON. DeCART provides sub-pin level resolution of the multigroup neutron flux, with resonance treatment, during a depletion or a fast transient simulation. Two-way coupling between these codes was achieved by mapping fission rate density and fast neutron flux fields from DeCART to BISON and the temperature field from BISON to DeCART while employing a Picard iterative algorithm. Finally, the need for multiscale coupling is considered. Fission gas production and evolution significantly impact fuel performance by causing swelling, a reduction in the thermal conductivity, and fission gas release. The mechanisms involved occur at the atomistic and grain scale and are therefore not the domain of a fuel performance code. However, it is possible to use lower length scale models such as those used in the mesoscale MARMOT code to compute average properties, e.g. swelling or thermal conductivity. These may then be used by an engineering-scale model. Examples of this type of multiscale, multiphysics modeling are shown.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Effective field theory for dark matter absorption on single phonons

Single phonon excitations, with energies in the 1–100 meV range, are a powerful probe of light dark matter (DM). Utilizing effective field theory, we derive a framework to compute DM absorption rates into single phonons starting from general DM-electron, proton, and neutron interactions. We apply the framework to a variety of DM models: Yukawa coupled scalars, axionlike particles with derivative interactions, and vector DM coupling via gauge interactions or Standard Model electric and magnetic dipole moments. We find that GaAs or Al 2 O 3 targets can set powerful constraints on a U ( 1 ) B − L model, and targets with electronic spin ordering are similarly sensitive to DM coupling to the electron magnetic dipole moment. Lastly, we make the code, (an extension of the existing code which computes general DM–single phonon scattering rates), publicly available. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

SPACE code simulation of cold leg small break LOCA in the ATLAS integral test

SPACE code is a system analysis code for pressurized water reactors. This code uses a two-fluid and three-field model. For a few years, intensive validations have been performed to secure the prediction accuracy of models and correlations for two-phase flow and heat transfer. Recently, the code version 1.0 was released. This study is to see how well SPACE code predicts thermal hydraulic phenomena of an integral effect test. The target experiment is a cold leg small break LOCA in the ATLAS facility, which has the same two-loop features as APR1400. Predicted parameters were compared with experimental observations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Barrier elision for production parallel programs

Large scientific code bases are often composed of several layers of runtime libraries, implemented in multiple programming languages. In such situation, programmers often choose conservative synchronization patterns leading to suboptimal performance. In this paper, we present context-sensitive dynamic optimizations that elide barriers redundant during the program execution. In our technique, we perform data race detection alongside the program to identify redundant barriers in their calling contexts; after an initial learning, we start eliding all future instances of barriers occurring in the same calling context. We present an automatic on-the-fly optimization and a multi-pass guided optimization. We apply our techniques to NWChem - a 6 million line computational chemistry code written in C/C++/Fortran that uses several runtime libraries such as Global Arrays, ComEx, DMAPP, and MPI. Our technique elides a surprisingly high fraction of barriers (as many as 63%) in production runs. This redundancy elimination translates to application speedups as high as 14% on 2048 cores. Our techniques also provided valuable insight about the application behavior, later used by NWChem developers. Overall, we demonstrate the value of holistic context-sensitive analyses that consider the domain science in conjunction with the associated runtime software stack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activaties are currently ongoing for coupling RAVEN with software such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

A Python Package for Fuel Cycle and Waste Management Analysis - 19545

The future of nuclear power utilization in the United States may involve a transition from the once-through light water reactor fuel cycle to a so-called advanced fuel cycle. An advanced fuel cycle may offer improvements in natural resource utilization, reactor safety, and environmental impact. In addition, adoption of an advanced fuel cycle will result in changes in the amount, composition, and disposal of the nuclear wastes they produce. Characteristics intrinsic to the wastes themselves, such as mass and radioactivity at specific times, were used as waste management metrics in the Department of Energy 2014 Fuel Cycle Evaluation and Screening (FCES) study. Binning of these metrics informed fuel cycle according to relative potential benefit. However, waste properties alone cannot qualify management strategy. Therefore, comparing fuel cycles from the perspective of waste management can provide additional insights. To that end, an object-oriented Python package has been developed to perform fuel cycle waste management calculations. The package, named nwpy (short for Nuclear Waste analysis in Python), mimics the mass flow operations reported in the FCES study and interfaces with the ORIGEN-S code to assess metric data as reported in the FCES. In addition, this Python package determines the loading of waste streams into forms suitable for final disposal in a geological repository and uses such data for repository performance assessment. This work describes the Python package methodology, assumptions, and capabilities. As input data, the package requires information about the fuel cycle such as the mass of fuel discharged, the cooling time between reactor discharge and subsequent operations, and the separations process efficiencies and waste forms it produces. In addition, the isotopic composition of the reactor discharge stream, such as that available from the FCES database, is required. With that, it can perform prescribed mass flow and decay operations throughout the back end of the fuel cycle, the latter carried out by the ORIGEN-S code distributed with the SCALE6.2 software suite. The result is time-dependent data characterizing the waste on a per-package basis. Package loading for waste streams depends on the stream form (i.e. UNF vs. HLW, or glass HLW from aqueous reprocessing vs. ceramic HLW from electrochemical processing) and is based on literature review and engineering assumption. As an example of the application of the code, calculations for the areal footprint of direct-contact repositories for different fuel cycles is shown. Development is ongoing, and the package is expected to grow incorporating capabilities for waste management analyses such as waste transportation and radionuclide transport through the biosphere. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Extension of mutation testing for the requirements and design faults - 322

Mutation Testing is a fault-based software testing technique that is considered to be the most efficient in detecting faults. It focuses on the software code level and follows a set of rules which are called mutation operators to systematically seed faults into the source code. Each seeded fault results is a new version of the software, which is called a mutant. Mutation testing promises to be effective in identifying adequate test data which can be used to find faults in the source code. However, traditional mutation testing is not geared towards the detection of requirements and design faults. To cover the full spectrum of possible faults, the mutation framework has been extended from the code level to the requirements and design level. Twenty-nine defects that appear in requirements and design documents were identified to define appropriate mutants. Then corresponding mutation operators that model the defects were developed. For each mutation operator, the strategy to generate a mutant and the evaluation of the number of possible mutants were defined. Existing code level cost reduction techniques were tailored for requirements and design mutation operators that result in a large number of mutants. With the extended mutation testing framework, the full spectrum of possible faults will be tested and identified to ensure the safety and functionality of the software. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗