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At least 1,009 records · Page 56

A new multi-energy neutrino radiation-hydrodynamics code in full general relativity and its application to the gravitational collapse of massive stars

We present a new multi-dimensional radiation-hydrodynamics code for massive stellar core-collapse in full general relativity (GR). Employing an M1 analytical closure scheme, we solve spectral neutrino transport of the radiation energy and momentum based on a truncated moment formalism. Regarding neutrino opacities, we take into account a baseline set in state-of-the-art simulations, in which inelastic neutrino–electron scattering, thermal neutrino production via pair annihilation, and nucleon–nucleon bremsstrahlung are included. While the Einstein field equations and the spatial advection terms in the radiation-hydrodynamics equations are evolved explicitly, the source terms due to neutrino–matter interactions and energy shift in the radiation moment equations are integrated implicitly by an iteration method. To verify our code, we first perform a series of standard radiation tests with analytical solutions that include the check of gravitational redshift and Doppler shift. A good agreement in these tests supports the reliability of the GR multi-energy neutrino transport scheme. We then conduct several test simulations of core-collapse, bounce, and shock stall of a 15M{sub ⊙} star in the Cartesian coordinates and make a detailed comparison with published results. Our code performs quite well to reproduce the results of full Boltzmann neutrino transport especially before bounce. In the postbounce phase, our code basically performs well, however, there are several differences that are most likely to come from the insufficient spatial resolution in our current 3D-GR models. For clarifying the resolution dependence and extending the code comparison in the late postbounce phase, we discuss that next-generation Exaflops class supercomputers are needed at least.

79 ASTRONOMY AND ASTROPHYSICS↗

JavaGenes and Condor: Cycle-Scavenging Genetic Algorithms

A genetic algorithm code, JavaGenes, was written in Java and used to evolve pharmaceutical drug molecules and digital circuits. JavaGenes was run under the Condor cycle-scavenging batch system managing 100-170 desktop SGI workstations. Genetic algorithms mimic biological evolution by evolving solutions to problems using crossover and mutation. While most genetic algorithms evolve strings or trees, JavaGenes evolves graphs representing (currently) molecules and circuits. Java was chosen as the implementation language because the genetic algorithm requires random splitting and recombining of graphs, a complex data structure manipulation with ample opportunities for memory leaks, loose pointers, out-of-bound indices, and other hard to find bugs. Java garbage-collection memory management, lack of pointer arithmetic, and array-bounds index checking prevents these bugs from occurring, substantially reducing development time. While a run-time performance penalty must be paid, the only unacceptable performance we encountered was using standard Java serialization to checkpoint and restart the code. This was fixed by a two-day implementation of custom checkpointing. JavaGenes is minimally integrated with Condor; in other words, JavaGenes must do its own checkpointing and I/O redirection. A prototype Java-aware version of Condor was developed using standard Java serialization for checkpointing. For the prototype to be useful, standard Java serialization must be significantly optimized. JavaGenes is approximately 8700 lines of code and a few thousand JavaGenes jobs have been run. Most jobs ran for a few days. Results include proof that genetic algorithms can evolve directed and undirected graphs, development of a novel crossover operator for graphs, a paper in the journal Nanotechnology, and another paper in preparation.

Globus, Al↗

Architecture for the Performance of Nuclear Fuel Depletion Calculations

Computational analysis of the depletion of nuclear fuel is crucial to the accurate modeling of the time-dependent behavior of nuclear reactors. The reactor physics application MAMMOTH is modified to compute radioactive decay and neutron transmutation in order to model physical processes which occur within nuclear reactors as reactor fuel is burned. The ability to read decay and cross-section data files of other codes are also added and the addition of a standardized decay and transmutation XML file format for MAMMOTH, known as ISOXML. Comparisons between MAMMOTH and the Oak Ridge Isotope Generation (ORIGEN) code are performed to demonstrate the improved precision possible with MAMMOTH. In addition, several tests are run to demonstrate the ability of MAMMOTH to model decay and transmutation processes involving hundreds of isotopes. Future work will focus on solving depletion problems with multiple neutron energy groups and the implementation of predictor-corrector methods, several of which are described in this work.

07 ISOTOPE AND RADIATION SOURCES↗

Radiometric characterization process for locating radioactivity hold-up and measuring non-uniformly distributed sources - 15342

A novel approach to facility radiometric characterization for non-uniformly distributed radiation sources has been developed by ANTECH and is currently being employed at the Argonne National Laboratory. It is being applied to the measurement of a wide range of objects and the interiors and contents of laboratories and buildings. The integrated non destructive assay measurement process involves the use of a scanning spectroscopic gamma ray camera as well as high purity Germanium detectors with different collimators and hence differing detector fields of view to measure and quantify non-uniformly distributed sources of radioactivity in laboratory equipment, glove boxes, storage tanks, pipework and general laboratory objects and process components. The purpose of the radiometric characterization is to quantify radiation sources and radioactive contamination levels in facilities containing nuclear material and to ensure compliance with facility characterization requirements and for decontamination and decommissioning planning and execution. The integrated measurement process also involves automated data capture and processing software and a database with which both measurement instrument operators and subject matter expert analysts can interact. An appropriate measuring instrument (gamma camera, scintillation detector, high purity Germanium detector system, neutron detector or alpha-beta counter) records the measurement data and the measurement site is recorded in a photograph. All of the data relevant to the measurement (or set of measurements for a particular object) are recorded in the database including measured gamma ray spectra, equipment description and relevant calibration, measurement site photograph and measurement descriptive data. Once data analysis protocols are established for specific geometries and measurement situations they can be applied to the measured data in a partially automated manner, reducing analysis and transcription errors. In addition to measurements and data analysis the process also utilises radiometric modelling computer codes including MicroShield and Monte Carlo Neutrons Photons in order to perform model calculations where appropriate. In a typical measurement, the ANTECH RadSearch spectroscopic gamma camera is utilized to find areas of concentrated activity so that these areas can be measured and calculated separately from areas with diffuse contamination. The use of the gamma camera in scanning mode helps to ensure that the assay does not overestimate the detected radiation source, which is a frequent consequence of using standard far field geometry and attenuation analysis codes that assume uniformity of both density and radioactive source distribution. Once the hot spots are identified, high purity Germanium detector measurements are made using various collimators with wide or narrow fields of view as required. These measurements are then processed through a semi-automatic calculation process assuming an appropriate source configuration as identified by RadSearch. These source configurations include point sources, line sources or surface sources. The Generalized Geometry Hold-up algorithms are employed to determine an estimate of the activity of the various sources that are identified in a measurement. The ANTECH integrated measurement process provides an automated calculation procedure where the analyst can select the source type, geometry and appropriate input data, and then the software calculates the activity by radionuclide for all sources identified in the measurement. The measurement and analysis process is controlled under the ANTECH ISO9001: 2008 Quality Assurance System and managed by a site specific Quality Assurance Plan. Both Argonne National Laboratory and Department of Energy technical reviewers have vetted the Integrated Measurement and Analysis Process. The application of the measurement and analysis process is described and measurement examples are provided. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Commercial Building Prototypes Based on ANSI/ASHRAE/IES Standard 90.1-2019 Appendix G PRM: Technical Support Document

The two paths for documenting compliance with ANSI/ASHRAE/IES Standard 90.1 are the prescriptive path and the performance path. Beyond code programs and rating systems (for example, USGBC-LEED ) are primarily known to use a third path – the Appendix G Performance Rating Method. An update in the 2016 edition of Standard 90.1 approved the Appendix G Performance Rating System for code compliance, extending its application and allowing for greater consistency of modeling rules for code and beyond code building energy modeling. The Appendix G PRM provides rules for the development of whole building energy models of baseline and proposed models for calculating the “performance cost index target” value using the simulated energy results of the baseline and proposed models and the building performance factors published in Table 4.2.1.1 of the Standard. This report documents (1) the methodology used for development of the baseline and proposed energy models of the Pacific Northwest National Laboratory and U.S. Department of Energy commercial building prototypes using the Appendix G Performance Rating Method; and (2) the building performance factors that were calculated using those models.

97 MATHEMATICS AND COMPUTING↗

Impacts of Model Building Energy Codes – Interim Update

The U.S. Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates state and national impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, assessed the prospective impacts of national model building energy codes from 2010 through 2040. The model codes of interest in this report are the International Energy Conservation Code (IECC) for residential buildings and ASHRAE Standard 90.1 for commercial buildings. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO 2 emissions at the state and national levels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

WRLES: Wave Resolving Large-Eddy Simulation Code, Theory and Usage

A computational fluid dynamics code has been developed for large-eddy simulations (LES) of turbulent flow. The code uses high-order of accuracy and high-resolution numerical methods to minimize solution error and maximize the resolution of the turbulent structures. Spatial discretization is performed using explicit central differencing. The central differencing schemes in the code include 2nd- to 12th-order standard central difference methods as well as 7-, 9-, 11- and 13-point dispersion relation preserving schemes. Solution filtering and high-order shock capturing are included for stability. Time discretization is performed using multistage Runge-Kutta methods that are up to 4th order accurate. Several options are available to model turbulence including: Baldwin-Lomax and Spalart-Allmaras Reynolds-averaged Navier-Stokes turbulence models, and Smagorinsky, Dynamic Smagorinsky and Vreman sub-grid scale models for LES. This report presents the theory behind the numerical and physical models used in the code and provides a user's manual to the operation of the code.

High-Order↗

Impacts of Model Building Energy Codes

The Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates state and national impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, assessed the prospective impacts of national model building energy codes from 2010 through 2040. The model codes of interest in this report are the International Energy Conservation Code (IECC) for residential buildings and ASHRAE Standard 90.1 for commercial buildings. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO 2 emissions at the state and national levels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Uncertainty Analysis and Error Propagation Methodology for Reporting Thermophysical Properties Measurement of Gen3 CSP Materials

This document describe multiple-measurement uncertainty analysis that is implemented to the thermophysical properties measurement or dataset of Gen3 CSP materials curated in an online database (http://gen3csp.gatech.edu/). This uncertainty analysis is based on a textbook method, that follows the American National Standard Institute/American Society of Mechanical Engineering (ANSI/ASME) Power Test Codes (PTC) 19.1 Test Uncertainty and NIST Technical Note 1297. It is also consistent with the international guidelines established by the International Organization for Standardization (ISO).

14 SOLAR ENERGY↗

COG User's Manual: A Multiparticle Monte Carlo Transport Code (Sixth Edition)

COG is a high-resolution code for the Monte Carlo simulation of coupled particle transport in arbitrary 3-D geometry. COG will transport neutrons, protons, deuterons, alpha particles with energies up to hundreds of GeV, and photons with energy ranges limited by the available cross section sets and physics models. Electrons can be transported via the EGS5 electron transport kernel, electrons can also be transported. The COG code is a significant upgrade from earlier Monte Carlo transport codes and has been written specifically to make it more versatile, accurate, and easy to use. COG has provisions for calculating deep penetration (shielding) problems, criticality problems, and neutron activation problems while retains all of the standard capabilities found in other Monte Carlo transport codes. COG uses high-resolution pointwise cross-section databases and makes no compromises in the transport physics, so that the results of a COG run are limited only by the accuracy of the databases used. COG runs primarily on Linux Operating System workstations with MPICH software installed – currently, Red Hat 7 & 8, Windows 10 (Windows Subsystem for Linux –WSL), Ubuntu 16, 18 & 20, OpenSUSE Leap 15.2, Fedora 32, Apple Power Mac with Intel CPU (with MacPorts installed) workstations, and LLNL LC supercomputer CTS-1 cluster with TOSS 3 are supported.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Oak Ridge Reservation Environmental Protection Rad Neshaps Radionuclide Inventory Web Database and Rad Neshaps Source and Dose Database

The U.S. Environmental Protection Agency promulgated national emission standards for emissions of radionuclides other than radon from US Department of Energy facilities in Chapter 40 of the Code of Federal Regulations (CFR) 61, Subpart H. This regulatory standard limits the annual effective dose that any member of the public can receive from Department of Energy facilities to 0.1 mSv. As defined in the preamble of the final rule, all of the facilities on the Oak Ridge Reservation, i.e., the Y–12 National Security Complex, Oak Ridge National Laboratory, East Tennessee Technology Park, and any other U.S. Department of Energy operations on Oak Ridge Reservation, combined, must meet the annual dose limit of 0.1 mSv. At Oak Ridge National Laboratory, there are monitored sources and numerous unmonitored sources. To maintain radiological source and inventory information for these unmonitored sources, e.g., laboratory hoods, equipment exhausts, and room exhausts not currently venting to monitored stacks on the Oak Ridge National Laboratory campus, the Environmental Protection Rad NESHAPs Inventory Web Database was developed. This database is updated annually and is used to compile emissions data for the annual Radionuclide National Emission Standards for Hazardous Air Pollutants (Rad NESHAPs) report required by 40 CFR 61.94. It also provides supporting documentation for facility compliance audits. In addition, a Rad NESHAPs source and dose database was developed to import the source and dose summary data from Clean Air Act Assessment Package—1988 computer model files. As a result, this database provides Oak Ridge Reservation and facility-specific source inventory; doses associated with each source and facility; and total doses for the Oak Ridge Reservation dose.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Program for User-Friendly Management of Input and Output Data Sets

A computer program manages large, hierarchical sets of input and output (I/O) parameters (typically, sequences of alphanumeric data) involved in computational simulations in a variety of technological disciplines. This program represents sets of parameters as structures coded in object-oriented but otherwise standard American National Standards Institute C language. Each structure contains a group of I/O parameters that make sense as a unit in the simulation program with which this program is used. The addition of options and/or elements to sets of parameters amounts to the addition of new elements to data structures. By association of child data generated in response to a particular user input, a hierarchical ordering of input parameters can be achieved. Associated with child data structures are the creation and description mechanisms within the parent data structures. Child data structures can spawn further child data structures. In this program, the creation and representation of a sequence of data structures is effected by one line of code that looks for children of a sequence of structures until there are no more children to be found. A linked list of structures is created dynamically and is completely represented in the data structures themselves. Such hierarchical data presentation can guide users through otherwise complex setup procedures and it can be integrated within a variety of graphical representations.

Klimeck, Gerhard↗

Charliecloud: Unprivileged containers for user-defined software stacks in HPC

Supercomputing centers are seeing increasing demand for user-defined software stacks (UDSS), instead of or in addition to the stack provided by the center. These UDSS support user needs such as complex dependencies or build requirements, externally required configurations, portability, and consistency. The challenge for centers is to provide these services in a usable manner while minimizing the risks: security, support burden, missing functionality, and performance. We present Charliecloud, which uses the Linux user and mount namespaces to run industry-standard Docker containers with no privileged operations or daemons on center resources. Our simple approach avoids most security risks while maintaining access to the performance and functionality already on offer, doing so in less than 500 lines of code. Charliecloud promises to bring an industry-standard UDSS user workflow to existing, minimally altered HPC resources.

97 MATHEMATICS AND COMPUTING↗

ExactPack Documentation

For code verification, one compares the code output against known exact solutions. There are many standard test problems used in this capacity, such as the Noh and Sedov problems. ExactPack is a utility that integrates many of these exact solution codes into a common API (application program interface), and can be used as a stand-alone code or as a python package. ExactPack consists of python driver scripts that access a library of exact solutions written in Fortran or Python. The spatial profiles of the relevant physical quantities, such as the density, fluid velocity, sound speed, or internal energy, are returned at a time specified by the user. The solution profiles can be viewed and examined by a command line interface or a graphical user interface, and a number of analysis tools and unit tests are also provided. We have documented the physics of each problem in the solution library, and provided complete documentation on how to extend the library to include additional exact solutions. ExactPack’s code architecture makes it easy to extend the solution-code library to include additional exact solutions in a robust, reliable, and maintainable manner.

97 MATHEMATICS AND COMPUTING↗

Modeling Guidelines for Code Generation in the Railway Signaling Context

Modeling guidelines constitute one of the fundamental cornerstones for Model Based Development. Their relevance is essential when dealing with code generation in the safety-critical domain. This article presents the experience of a railway signaling systems manufacturer on this issue. Introduction of Model-Based Development (MBD) and code generation in the industrial safety-critical sector created a crucial paradigm shift in the development process of dependable systems. While traditional software development focuses on the code, with MBD practices the focus shifts to model abstractions. The change has fundamental implications for safety-critical systems, which still need to guarantee a high degree of confidence also at code level. Usage of the Simulink/Stateflow platform for modeling, which is a de facto standard in control software development, does not ensure by itself production of high-quality dependable code. This issue has been addressed by companies through the definition of modeling rules imposing restrictions on the usage of design tools components, in order to enable production of qualified code. The MAAB Control Algorithm Modeling Guidelines (MathWorks Automotive Advisory Board)[3] is a well established set of publicly available rules for modeling with Simulink/Stateflow. This set of recommendations has been developed by a group of OEMs and suppliers of the automotive sector with the objective of enforcing and easing the usage of the MathWorks tools within the automotive industry. The guidelines have been published in 2001 and afterwords revisited in 2007 in order to integrate some additional rules developed by the Japanese division of MAAB [5]. The scope of the current edition of the guidelines ranges from model maintainability and readability to code generation issues. The rules are conceived as a reference baseline and therefore they need to be tailored to comply with the characteristics of each industrial context. Customization of these recommendations has been performed for the automotive control systems domain in order to enforce code generation [7]. The MAAB guidelines have been found profitable also in the aerospace/avionics sector [1] and they have been adopted by the MathWorks Aerospace Leadership Council (MALC). General Electric Transportation Systems (GETS) is a well known railway signaling systems manufacturer leading in Automatic Train Protection (ATP) systems technology. Inside an effort of adopting formal methods within its own development process, GETS decided to introduce system modeling by means of the MathWorks tools [2], and in 2008 chose to move to code generation. This article reports the experience performed by GETS in developing its own modeling standard through customizing the MAAB rules for the railway signaling domain and shows the result of this experience with a successful product development story.

Ferrari, Alessio↗

Coding for Single-Line Transmission

Digital transmission code combines data and clock signals into single waveform. MADCODE needs four standard integrated circuits in generator and converter plus five small discrete components. MADCODE allows simple coding and decoding for transmission of digital signals over single line.

Madison, L. G.↗

A perturbative approach to the redshift space correlation function: beyond the Standard Model

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with ≤ 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpc h ≤ s ≤ 180Mpc/ h . Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Computing the shape gradient of stellarator coil complexity with respect to the plasma boundary

Coil complexity is a critical consideration in stellarator design. The traditional two-step optimization approach, in which the plasma boundary is optimized for physics properties and the coils are subsequently optimized to be consistent with this boundary, can result in plasma shapes which cannot be produced with sufficiently simple coils. To address this challenge, we propose a method to incorporate considerations of coil complexity in the optimization of the plasma boundary. Coil complexity metrics are computed from the current potential solution obtained with the REGCOIL code (Landreman, Nucl. Fusion , vol. 57, 2017, 046003). While such metrics have previously been included in derivative-free fixed-boundary optimization (Drevlak et al. , Nucl. Fusion , vol. 59, 2018, 016010), we compute the local sensitivity of these metrics with respect to perturbations of the plasma boundary using the shape gradient (Landreman & Paul, Nucl. Fusion , vol. 58, 2018, 076023). We extend REGCOIL to compute derivatives of these metrics with respect to parameters describing the plasma boundary. In keeping with previous research on winding surface optimization (Paul et al. , Nucl. Fusion , vol. 58, 2018, 076015), the shape derivatives are computed with a discrete adjoint method. In contrast with the previous work, derivatives are computed with respect to the plasma surface parameters rather than the winding surface parameters. To further reduce the resolution required to compute the shape gradient, we present a more efficient representation of the plasma surface which uses a single Fourier series to describe the radial distance from a coordinate axis and a spectrally condensed poloidal angle. This representation is advantageous over the standard cylindrical representation used in the VMEC code (Hirshman & Whitson, Phys. Fluids , vol. 26, 1983, pp. 3553–3568), as it provides a uniquely defined poloidal angle, eliminating a null space in the optimization of the plasma surface. In comparison with previous spectral condensation methods (Hirshman & Breslau, Phys. Plasmas , vol. 5, 1998, p. 2664), the modified poloidal angle is obtained algebraically rather than through the solution of a nonlinear optimization problem. The resulting shape gradient highlights features of the plasma boundary that are consistent with simple coils and can be used to couple coil and fixed-boundary optimization.

Physics↗