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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Studying the Random Number Generators in MCNP6 using an Analytic Benchmark

An analytic solution to a previously studied toy problem is derived and used as a code verification benchmark. Using various Random Number Generators (RNGs) in MCNP6, including the newest SFC64 RNG available in MCNP6.3.1, and their various properties (e.g., RNG stride), we show how these RNGs perform and how to correct or workaround potential issues with respect to the analytic benchmark problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Advanced Pellet Cladding Interaction Modeling Using the US DOE CASL Fuel Performance Code: Peregrine

The US DOE’s Consortium for Advanced Simulation of LWRs (CASL) program has undertaken an effort to enhance and develop modeling and simulation tools for a virtual reactor application, including high fidelity neutronics, fluid flow/thermal hydraulics, and fuel and material behavior. The fuel performance analysis efforts aim to provide 3-dimensional capabilities for single and multiple rods to assess safety margins and the impact of plant operation and fuel rod design on the fuel thermomechanical- chemical behavior, including Pellet-Cladding Interaction (PCI) failures and CRUD-Induced Localized Corrosion (CILC) failures in PWRs. [1-3] The CASL fuel performance code, Peregrine, is an engineering scale code that is built upon the MOOSE/ELK/FOX computational FEM framework, which is also common to the fuel modeling framework, BISON [4,5]. Peregrine uses both 2-D and 3-D geometric fuel rod representations and contains a materials properties and fuel behavior model library for the UO2 and Zircaloy system common to PWR fuel derived from both open literature sources and the FALCON code [6]. The primary purpose of Peregrine is to accurately calculate the thermal, mechanical, and chemical processes active throughout a single fuel rod during operation in a reactor, for both steady state and off-normal conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Neutronics Analysis of Cold Critical KRUSTY Experiments using MCNP and Serpent

Kilowatt Reactor Using Stirling Technology (KRUSTY) is a prototype designed as a proof of concept for NASA’s Kilo power program, which was funded in order to create a small reactor for various space applications such as providing power for a colony on Mars or the moon and eventually as a possible option for powering rockets on deep space missions. KRUSTY was tested at the National Criticality Experiments Research Center (NCERC) located at the Nevada National Security Site (NNSS) from November 2017, through March 2018. The experimental campaign was conducted in four phases: com ponent critical experiments, cold critical experiments, warm critical runs, and high temperature demonstration. The component critical and cold critical experiments were used to determine the worth of the beryllium oxide (BeO) reflector rings and the boron carbide (B4C) control rod disks under different conditions. These conditions were altered by the addition and subtraction of other components in the assembly. The component critical phase was performed at atmospheric pressure and had four solid support rods spanning the center core; whereas the cold critical phase had the center core placed in a vacuum chamber and eight sodium-filled heat pipes spanning the center core region. This summary discusses the static neutronic analysis completed on the cold critical phase of the campaign using MCNP ® and Serpent. These two codes were used to assess any potential differences or biases in the simulation results. Understanding these potential biases is a key step toward the final goal of being able to fully analyze the transient experiments performed during phases 3 and 4 of the campaign.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A MLIR Dialect for Quantum Assembly Languages

We demonstrate the utility of the Multi-Level Intermediate Representation (MLIR) for quantum computing. Specifically, we extend MLIR with a new quantum dialect that enables the expression and compilation of common quantum assembly languages. The true utility of this dialect is in its ability to be lowered to the LLVM intermediate representation (IR) in a manner that is adherent to the quantum intermediate representation (QIR) specification recently proposed by Microsoft. We leverage a qcor-enabled implementation of the QIR quantum runtime API to enable a retargetable (quantum hardware agnostic) compiler workflow mapping quantum languages to hybrid quantum-classical binary executables and object code. We evaluate and demonstrate this novel compiler workflow with quantum programs written in OpenQASM 2.0. We provide concrete examples detailing the generation of MLIR from OpenQASM source files, the lowering process from MLIR to LLVM IR, and ultimately the generation of executable binaries targeting available quantum processors.

Mccaskey, Alex↗
DOE OSTI2015

The Monte Carlo estimation of an effect of uncertainties in initial data on solving the transport equation by means of the MCU code

A new version of the tally module of the MCU software package is developed in which the approach for taking directly into account the uncertainty in initial data is implemented that is recommended by the international standard on estimating the uncertainty in results of measuring (ISO 13005). The new module makes it possible to evaluate the effect of uncertainty in initial data (caused by technological tolerances in fabrication of structural members of the core) on neutronic characteristics of the reactor. The developed software is adapted to parallel computing with the use of multiprocessor computers, which significantly reduces the computation time: the parallelization coefficient is almost equal to 1. Testing is performed by examples of solving the problem on criticality for the Godiva benchmark experiment and also for the infinite lattice of fuel assemblies of the VVER-440, VVER-1000, and VVER-1200. The results of calculations of the uncertainty in neutronic characteristics (effective multiplication factor, fission reaction rate), which is caused by uncertainties in initial data due to technological tolerances, are compared (in the first case) to the published results obtained using the precision MCNP5 code and (in the second case) to those obtained by means of the RADAR engineering program. A good agreement of results is achieved for all cases.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

ITS version 6.4: The Integrated TIGER Series of Monte Carlo Electron/Photon Radiation Transport Codes - Paper 40

ITS (Integrated TIGER Series) is a suite of fully coupled electron/photon Monte Carlo radiation transport codes. The package contains programs to perform 1D, 2D and 3D simulations. The 3D geometry representations include the traditional combinatorial geometry (CG), facet-based models, CAD models for those users who have a license for the ACIS{sup R} CAD libraries, and hybrid models of any combination. There is a multigroup version which permits adjoint analysis. The availability of source code permits the more sophisticated user to tailor the code to specific applications and to extend the capabilities of the codes to more complex applications. ITS is presently available only through a U.S.-government-use license. It is available once again through the Radiation Safety Information Computational Center (RSICC). (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

VERAOUT - VERA HDF5 Output Specification (Revision 1)

This document describes the revised specification (Revision 1) for the format of the common VERA Output file (VERAOUT). VERAOUT is a binary HDF5 file that all of the physics codes in VERA-CS produce. Having all physics codes write to a single file simplifies post-processing and data comparison. The edits and format written to the VERAOUT file is described below. This specification covers common scalar and array data typically produced by neutronic and fuel performance codes. This document will be periodically revised to add additional data as more physics codes and/or more data is added to VERA-CS. A version number is written to the HDF file to keep track of different versions of the VERAOUT so that backwards compatibility may be maintained. A sample VERAOUT reader has been written to serve as an example for users wishing to do data postprocessing. Information on this program is included below.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

XtalCAMP: a comprehensive program for the analysis and visualization of scanning Laue X-ray micro-/nanodiffraction data

XtalCAMP is a software package based on the MATLAB platform, which is suitable for, but not limited to, the analysis and visualization of scanning Laue X-ray micro-/nanodiffraction data. The main objective of the software is to provide complementary functionalities to the Laue indexing software packages used at several synchrotron beamlines. Here, the graphical user interfaces allow the easy analysis of characteristic microstructure features, including real-time intensity mapping for a quick examination of phase, grain and defect distribution, 2D color-coded mapping of microstructural properties from the output of other Laue indexing software, crystal orientation visualization, grain boundary characterization based on orientation/misorientation calculation, principal strain/stress analysis, and strain ellipsoid representation, as well as a series of additional toolkits. As an example, XtalCAMP is applied to the microstructural investigation of a solution-heat-treated Ni-based superalloy manufactured using a laser 3D-printing technique, and a deformed natural quartzite from Val Bregaglia in the Central Alps.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Generalized Bayesian Framework for Evaluation of Integral Benchmark Experiments

A recently published generalized Bayesian optimization framework has provided a way to retract any or all of the three common assumptions underlying the conventional Generalized Linear Least Squares (GLLS) optimization method based on the concepts introduced in Ref. [2]. These assumptions are: 1. Perfection: The model used for data evaluation and the prior probability distribution function (PDF) of generalized data are perfect. 2. Normality: The prior and posterior PDF are normal. 3. Linearity: The model is linear. In this work we outline how the framework in [1] could be directly adopted for improved evaluation of nuclear criticality integral benchmark experiments (IBEs) by: 1. Removing the first assumption alone by utilizing the concept of imperfections introduced in [1] to enable evaluation in the presence of discrepancies between the data and model or of missing covariance information by a GLLS method that will be seen as a generalization of the conventional GLLS method employed by the TSURFER code, and by 2. Removing the remaining two assumptions by implementing a Markov Chain Monte Carlo method for computation of the posterior PDF in the SAMPLER code, where TSURFER and SAMPLER are the uncertainty quantification (UQ) codes for IBEs in the SCALE code system based on the GLLS and the stochastic method, respectively. The graphic in Figure 1 categorizes the methods discussed in terms of the assumptions that they employ to determine posterior PDFs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

SU-E-T-570: New Quality Assurance Method Using Motion Tracking for 6D Robotic Couches

Purpose: To accommodate geometrically accurate patient positioning, a robotic couch that is capable of 6-degrees of freedom has been introduced. However, conventional couch QA methods are not sufficient to enable the necessary accuracy of tests. Therefore, we have developed a camera based motion detection and geometry calibration system for couch QA. Methods: Employing a Visual-Tracking System (VTS, BonitaB10, Vicon, UK) which tracks infrared reflective(IR) markers, camera calibration was conducted using a 5.7 × 5.7 × 5.7 cm{sup 3} cube attached with IR markers at each corner. After positioning a robotic-couch at the origin with the cube on the table top, 3D coordinates of the cube’s eight corners were acquired by VTS in the VTS coordinate system. Next, positions in reference coordinates (roomcoordinates) were assigned using the known relation between each point. Finally, camera calibration was completed by finding a transformation matrix between VTS and reference coordinate systems and by applying a pseudo inverse matrix method. After the calibration, the accuracy of linear and rotational motions as well as couch sagging could be measured by analyzing the continuously acquired data of the cube while the couch moves to a designated position. Accuracy of the developed software was verified through comparison with measurement data when using a Laser tracker (FARO, Lake Mary, USA) for a robotic-couch installed for proton therapy. Results: VTS system could track couch motion accurately and measured position in room-coordinates. The VTS measurements and Laser tracker data agreed within 1% of difference for linear and rotational motions. Also because the program analyzes motion in 3-Dimension, it can compute couch sagging. Conclusion: Developed QA system provides submillimeter/ degree accuracy which fulfills the high-end couch QA. This work was supported by the National Research Foundation of Korea funded by Ministry of Science, ICT & Future Planning. (2013M2A2A7043507 and 2012M3A9B6055201)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-G-TeP1-06: Fast GPU Framework for Four-Dimensional Monte Carlo in Adaptive Intensity Modulated Proton Therapy (IMPT) for Mobile Tumors

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) treatment planning and verification using four-dimensional CT (4DCT) for adaptive IMPT for lung cancer patients. Methods: A validated GPU MC code, gPMC, has been linked to the patient database at our institution and employed to compute the dose-influence matrices (Dij) on the planning CT (pCT). The pCT is an average of the respiratory motion of the patient. The Dijs and patient structures were fed to the optimizer to calculate a treatment plan. To validate the plan against motion, a 4D dose distribution averaged over the possible starting phases is calculated using the 4DCT and a model of the time structure of the delivered spot map. The dose is accumulated using vector maps created by a GPU-accelerated deformable image registration program (DIR) from each phase of the 4DCT to the reference phase using the B-spline method. Calculation of the Dij matrices and the DIR are performed on a cluster, with each field and vector map calculated in parallel. Results: The Dij production takes ∼3.5s per beamlet for 10e6 protons, depending on the energy and the CT size. Generating a plan with 4D simulation of 1000 spots in 4 fields takes approximately 1h. To test the framework, IMPT plans for 10 lung cancer patients were generated for validation. Differences between the planned and the delivered dose of 19% in dose to some organs at risk and 1.4/21.1% in target mean dose/homogeneity with respect to the plan were observed, suggesting potential for improvement if adaptation is considered. Conclusion: A fast MC treatment planning framework has been developed that allows reliable plan design and verification for mobile targets and adaptation of treatment plans. This will significantly impact treatments for lung tumors, as 4D-MC dose calculations can now become part of planning strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Advanced Pellet-Cladding Interaction Modeling using the US DOE CASL Fuel Performance Code: Peregrine

The US DOE’s Consortium for Advanced Simulation of LWRs (CASL) program has undertaken an effort to enhance and develop modeling and simulation tools for a virtual reactor application, including high fidelity neutronics, fluid flow/thermal hydraulics, and fuel and material behavior. The fuel performance analysis efforts aim to provide 3-dimensional capabilities for single and multiple rods to assess safety margins and the impact of plant operation and fuel rod design on the fuel thermo-mechanical-chemical behavior, including Pellet-Cladding Interaction (PCI) failures and CRUD-Induced Localized Corrosion (CILC) failures in PWRs. [1-3] The CASL fuel performance code, Peregrine, is an engineering scale code that is built upon the MOOSE/ELK/FOX computational FEM framework, which is also common to the fuel modeling framework, BISON [4,5]. Peregrine uses both 2-D and 3-D geometric fuel rod representations and contains a materials properties and fuel behavior model library for the UO2 and Zircaloy system common to PWR fuel derived from both open literature sources and the FALCON code [6]. The primary purpose of Peregrine is to accurately calculate the thermal, mechanical, and chemical processes active throughout a single fuel rod during operation in a reactor, for both steady state and off-normal conditions.

CASL, Consortium for Advanced Simulation of LWRs, ↗
DOE OSTI2020

Multimodal Deep Learning for Flaw Detection in Software Programs

We explore the use of multiple deep learning models for detecting flaws in software programs. Current, standard approaches for flaw detection rely on a single representation of a software program (e.g., source code or a program binary). We illustrate that, by using techniques from multimodal deep learning, we can simultaneously leverage multiple representations of software programs to improve flaw detection over single representation analyses. Specifically, we adapt three deep learning models from the multimodal learning literature for use in flaw detection and demonstrate how these models outperform traditional deep learning models. We present results on detecting software flaws using the Juliet Test Suite and Linux Kernel.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

MatMCNP: A Code for Producing Material Cards for MCNP

A code for generating MCNP material cards (MatMCNP) has been written and verified for naturally occurring, stable isotopes. The program allows for material specification as either atomic or weight percent (fractions). MatMCNP also permits the specification of enriched lithium, boron, and/or uranium. In addition to producing the material cards for MCNP, the code calculates the atomic (or number) density in atoms/barn-cm as well as the multiplier that should be used to convert neutron and gamma fluences into dose in the material specified.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Status of the SAS4A/SASSYS-1 Safety Analysis Code

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced reactors. This report summarizes the current status of SAS4A/SASSYS-1, including the implementation of software quality assurance procedures for configuration management, new licenses, current users, and a gap assessment of the test suite. The existing copyright has been extended for an additional five years, which was essential so that Argonne can continue developing, distributing, and supporting the software for both domestic use and international collaborations. SAS4A/SASSYS-1 Version 5.2 was completed in March 2017 and released to users in May. The importance of SAS4A/SASSYS-1 maintenance reflects its relevance to a number of U.S. Department of Energy programs as well as domestic and international collaborations. External collaborations have also produced improvements in the SAS4A/SASSYS-1 code, and these are noted in this report. SAS4A/SASSYS-1 has a growing user base that continues to strengthen the promotion of advanced non-LWR reactor concepts. Additional users will help solidify DOE’s leadership role in fast reactor safety both domestically and in international collaborations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Verification and Validation of PARET/ANL (V.7.6)

This report documents the software testing which has been performed for the PARET/ANL version 7.6 software. The capabilities addressed in this testing were selected based on the use of the software for analysis work under the Research and Test Reactors Department quality assurance program. The verification and validation have been performed and documented to address the steady-state capabilities of the software, as described in Chapter 2, and the transient capabilities, as described in Chapter 3. Testing based on the comparison between PARET/ANL calculations and analytical solutions, hand calculations, or another code calculations of the test cases confirms that all the identified capabilities of the software were implemented correctly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗