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DOE OSTI2016

Plant model of KIPT neutron source facility simulator

Argonne National Laboratory (ANL) of the United States and Kharkov Institute of Physics and Technology (KIPT) of Ukraine are collaborating on constructing a neutron source facility at KIPT, Kharkov, Ukraine. The facility has 100-kW electron beam driving a subcritical assembly (SCA). The electron beam interacts with a natural uranium target or a tungsten target to generate neutrons, and deposits its power in the target zone. The total fission power generated in SCA is about 300 kW. Two primary cooling loops are designed to remove 100-kW and 300-kW from the target zone and the SCA, respectively. A secondary cooling system is coupled with the primary cooling system to dispose of the generated heat outside the facility buildings to the atmosphere. In addition, the electron accelerator has a low efficiency for generating the electron beam, which uses another secondary cooling loop to remove the generated heat from the accelerator primary cooling loop. One of the main functions the KIPT neutron source facility is to train young nuclear specialists; therefore, ANL has developed the KIPT Neutron Source Facility Simulator for this function. In this simulator, a Plant Control System and a Plant Protection System were developed to perform proper control and to provide automatic protection against unsafe and improper operation of the facility during the steady-state and the transient states using a facility plant model. This report focuses on describing the physics of the plant model and provides several test cases to demonstrate its capabilities. The plant facility model uses the PYTHON script language. It is consistent with the computer language of the plant control system. It is easy to integrate with the simulator without an additional interface, and it is able to simulate the transients of the cooling systems with system control variables changing on real-time.

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development. Final Technical Report.

The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projections of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.

58 GEOSCIENCES↗

DOE OSTI2016

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↗

DOE OSTI2016

SHARP User Manual

SHARP is an advanced modeling and simulation toolkit for the analysis of nuclear reactors. It is comprised of several components including physical modeling tools, tools to integrate the physics codes for multi-physics analyses, and a set of tools to couple the codes within the MOAB framework. Physics modules currently include the neutronics code PROTEUS, the thermal-hydraulics code Nek5000, and the structural mechanics code Diablo. This manual focuses on performing multi-physics calculations with the SHARP ToolKit. Manuals for the three individual physics modules are available with the SHARP distribution to help the user to either carry out the primary multi-physics calculation with basic knowledge or perform further advanced development with in-depth knowledge of these codes. This manual provides step-by-step instructions on employing SHARP, including how to download and install the code, how to build the drivers for a test case, how to perform a calculation and how to visualize the results. Since SHARP has some specific library and environment dependencies, it is highly recommended that the user read this manual prior to installing SHARP. Verification tests cases are included to check proper installation of each module. It is suggested that the new user should first follow the step-by-step instructions provided for a test problem in this manual to understand the basic procedure of using SHARP before using SHARP for his/her own analysis. Both reference output and scripts are provided along with the test cases in order to verify correct installation and execution of the SHARP package. At the end of this manual, detailed instructions are provided on how to create a new test case so that user can perform novel multi-physics calculations with SHARP. Frequently asked questions are listed at the end of this manual to help the user to troubleshoot issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

VERA and VERA-EDU 3.5 Release Notes

The Virtual Environment for Reactor Applications components included in this distribution include selected computational tools and supporting infrastructure that solve neutronics, thermal-hydraulics, fuel performance, and coupled neutronics-thermal hydraulics problems. The infrastructure components provide a simplified common user input capability and provide for the physics integration with data transfer and coupled-physics iterative solution algorithms. Neutronics analysis can be performed for 2D lattices, 2D core and 3D core problems for pressurized water reactor geometries that can be used to calculate criticality and fission rate distributions by pin for input fuel compositions. MPACT uses the Method of Characteristics transport approach for 2D problems. For 3D problems, MPACT uses the 2D/1D method which uses 2D MOC in a radial plane and diffusion or SPn in the axial direction. MPACT includes integrated cross section capabilities that provide problem-specific cross sections generated using the subgroup methodology. The code can be executed both 2D and 3D problems in parallel to reduce overall run time. A thermal-hydraulics capability is provided with CTF (an updated version of COBRA-TF) that allows thermal-hydraulics analyses for single and multiple assemblies using the simplified VERA common input. This distribution also includes coupled neutronics/thermal-hydraulics capabilities to allow calculations using MPACT coupled with CTF. The VERA fuel rod performance component BISON calculates, on a 2D or 3D basis, fuel rod temperature, fuel rod internal pressure, free gas volume, clad integrity and fuel rod waterside diameter. These capabilities allow simulation of power cycling, fuel conditioning and deconditioning, high burnup performance, power uprate scoping studies, and accident performance. Input/Output capabilities include the VERA Common Input (VERAIn) script which converts the ASCII common input file to the intermediate XML used to drive all of the physics codes in the VERA Core Simulator (VERA-CS). VERA component codes either input the VERA XML format directly, or provide a preprocessor which can convert the XML into native input. VERAView is an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The python-based software is easy to install and intuitive to use, and provides instantaneous 2D and 3D images, 1D plots, and alpha-numeric data from VERA multi-physics simulations. Testing within CASL has focused primarily on Westinghouse four-loop reactor geometries and conditions with example problems included in the distribution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

Parallel File System I/O Performance Testing On LANL Clusters

These are slides from a presentation on parallel file system I/O performance testing on LANL clusters. I/O is a known bottleneck for HPC applications. Performance optimization of I/O is often required. This summer project entailed integrating IOR under Pavilion and automating the results analysis. The slides cover the following topics: scope of the work, tools utilized, IOR-Pavilion test workflow, build script, IOR parameters, how parameters are passed to IOR, *run_ior: functionality, Python IOR-Output Parser, Splunk data format, Splunk dashboard and features, and future work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Investigating Marine Boundary Layer Parameterizations by Combining Observations with Models via State Estimation

In this project we have improved numerical weather prediction analyses and forecasts of low level winds in the marine boundary layer. This has been accomplished with the following tools; The National Center for Atmospheric Research (NCAR) Weather and Research Forecasting model, WRF, both in his single column (SCM) and three-dimensional (3D) versions; The National Oceanic and Atmospheric Administration (NOAA) Wave Watch III (WWIII); SE algorithms from the Data Assimilation Research Testbed (DART, Anderson et al. 2009); and Observations of key quantities of the lower MBL, including temperature and winds at multiple levels above the sea surface. The experiments with the WRF SCM / DART system have lead to large improvements with respect to a standard WRF configuration, which is currently commonly used by the wind energy industry. The single column model appears to be a tool particularly suitable for off-shore wind energy applications given its accuracy, the ability to quantify uncertainty, and the minimal computational resource requirements. In situations where the impact of an upwind wind park may be of interest in a downwind location, a 3D approach may be more suitable. We have demonstrated that with the WRF 3D / DART system the accuracy of wind predictions (and other meteorological parameters) can be improved over a 3D computational domain, and not only at specific locations. All the scripting systems developed in this project (i.e., to run WRF SCM / DART, WRF 3D / DART, and the coupling between WRF and WWIII) and the several modifications and upgrades made to the WRF SCM model will be shared with the broader community.

17 WIND ENERGY↗

DOE OSTI2016

Feeder Voltage Regulation with High-Penetration PV Using Advanced Inverters and a Distribution Management System: A Duke Energy Case Study

Duke Energy, Alstom Grid, and the National Renewable Energy Laboratory teamed up to better understand the impacts of solar photovoltaics (PV) on distribution system operations. The core goal of the project is to compare the operational - specifically, voltage regulation - impacts of three classes of PV inverter operations: 1.) Active power only (Baseline); 2.) Local inverter control (e.g., PF...not equal...1, Q(V), etc.); and 3.) Integrated volt-VAR control (centralized through the distribution management system). These comparisons were made using multiple approaches, each of which represents an important research-and-development effort on its own: a) Quasi-steady-state time-series modeling for approximately 1 year of operations using the Alstom eTerra (DOTS) system as a simulation engine, augmented by Python scripting for scenario and time-series control and using external models for an advanced inverter; b) Power-hardware-in-the-loop (PHIL) testing of a 500-kVA-class advanced inverter and traditional voltage regulating equipment. This PHIL testing used cosimulation to link full-scale feeder simulation using DOTS in real time to hardware testing; c) Advanced visualization to provide improved insights into time-series results and other PV operational impacts; and d) Cost-benefit analysis to compare the financial and business-model impacts of each integration approach.

14 SOLAR ENERGY↗

DOE OSTI2016

Neutron Detector Signal Processing to Calculate the Effective Neutron Multiplication Factor of Subcritical Assemblies

This report describes different methodologies to calculate the effective neutron multiplication factor of subcritical assemblies by processing the neutron detector signals using MATLAB scripts. The subcritical assembly can be driven either by a spontaneous fission neutron source (e.g. californium) or by a neutron source generated from the interactions of accelerated particles with target materials. In the latter case, when the particle accelerator operates in a pulsed mode, the signals are typically stored into two files. One file contains the time when neutron reactions occur and the other contains the times when the neutron pulses start. In both files, the time is given by an integer representing the number of time bins since the start of the counting. These signal files are used to construct the neutron count distribution from a single neutron pulse. The built-in functions of MATLAB are used to calculate the effective neutron multiplication factor through the application of the prompt decay fitting or the area method to the neutron count distribution. If the subcritical assembly is driven by a spontaneous fission neutron source, then the effective multiplication factor can be evaluated either using the prompt neutron decay constant obtained from Rossi or Feynman distributions or the Modified Source Multiplication (MSM) method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Echo

This document is a white paper marketing proposal for Echo™ is a data analysis platform designed for efficient, robust, and scalable creation and execution of complex workflows. Echo’s analysis management system refers to the ability to track, understand, and reproduce workflows used for arriving at results and decisions. Echo improves on traditional scripted data analysis in MATLAB, Python, R, and other languages to allow analysts to make better use of their time. Additionally, the Echo platform provides a powerful data management and curation solution allowing analysts to quickly find, access, and consume datasets. After two years of development and a first release in early 2016, Echo is now available for use with many data types in a wide range of application domains. Echo provides tools that allow users to focus on data analysis and decisions with confidence that results are reported accurately.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

User Manual for Whisper-1.1

Whisper is a statistical analysis package developed in 2014 to support nuclear criticality safety (NCS) validation [1-3]. It uses the sensitivity profile data for an application as computed by MCNP6 [4-6] along with covariance files [7,8] for the nuclear data to determine a baseline upper-subcritical-limit (USL) for the application. Whisper version 1.0 was first developed and used at LANL in 2014 [3]. During 2015- 2016, Whisper was updated to version 1.1 and is to be included with the upcoming release of MCNP6.2. This document describes the user input and options for running whisper-1.1, including 2 perl utility scripts that simplify ordinary NCS work, whisper_mcnp.pl and whisper_usl.pl. For many detailed references on the theory, applications, nuclear data & covariances, SQA, verification-validation, adjointbased methods for sensitivity-uncertainty analysis, and more – see the Whisper – NCS Validation section of the MCNP Reference Collection at mcnp.lanl.gov. There are currently over 50 Whisper reference documents available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Diurnal Cycle Computations

Directory /export_backup/covey1/CMIP5/Precipitation/DiurnalCycle/GridpointTimeseries/CMCCBCM_etal/ on crunchy.llnl.gov contains Python / UV-CDAT scripts compositeDiurnalStatistics.py and fourierDiurB nalAllGrid.py. compositeDiurnalStatistics.py reads high-time-frequency climate data from one or more years and computes 24 hour composite-mean and composite-standard-deviation cycles for one requested month.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Requirements Document for Development of a Livermore Tomography Tools Interface

In this document, we outline an exercise performed at LLNL to evaluate the user interface deficits of a LLNL-developed CT reconstruction software package, Livermore Tomography Tools (LTT). We observe that a difficult-to-use command line interface and the lack of support functions compound to generate a bottleneck in the CT reconstruction process when input parameters to key functions are not well known. Through the exercise of systems engineering best practices, we generate key performance parameters for a LTT interface refresh, and specify a combination of back-end (“test-mode” functions) and front-end (graphical user interface visualization and command scripting tools) solutions to LTT’s poor user interface that aim to mitigate issues and lower costs associated with CT reconstruction using LTT. Key functional and non-functional requirements and risk mitigation strategies for the solution are outlined and discussed.

42 ENGINEERING↗

DOE OSTI2017

Software Comparison for Renewable Energy Deployment in a Distribution Network

The main objective of this report is to evaluate different software options for performing robust distributed generation (DG) power system modeling. The features and capabilities of four simulation tools, OpenDSS, GridLAB-D, CYMDIST, and PowerWorld Simulator, are compared to analyze their effectiveness in analyzing distribution networks with DG. OpenDSS and GridLAB-D, two open source software, have the capability to simulate networks with fluctuating data values. These packages allow the running of a simulation each time instant by iterating only the main script file. CYMDIST, a commercial software, allows for time-series simulation to study variations on network controls. PowerWorld Simulator, another commercial tool, has a batch mode simulation function through the 'Time Step Simulation' tool, which obtains solutions for a list of specified time points. PowerWorld Simulator is intended for analysis of transmission-level systems, while the other three are designed for distribution systems. CYMDIST and PowerWorld Simulator feature easy-to-use graphical user interfaces (GUIs). OpenDSS and GridLAB-D, on the other hand, are based on command-line programs, which increase the time necessary to become familiar with the software packages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Introduction to Python for CMF Authority Users

This talk is a very broad over view of Python that highlights key features in the language used in the Common Model Framework (CMF). I assume that the audience has some programming experience in a shell scripting language (C shell, Bash, PERL) or other high level language (C/C++/ Fortran). The talk will cover Python data types, classes (objects) and basic programming constructs. The talk concludes with slides describing how I developed the basic classes for a TITANS homework assignment.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

DOE Network 2025: Network Research Problems and Challenges for DOE Scientists (Workshop Report)

The growing investments in large science instruments and supercomputers by the US Department of Energy (DOE) hold enormous promise for accelerating the scientific discovery process. They facilitate unprecedented collaborations of geographically dispersed teams of scientists that use these resources. These collaborations critically depend on the production, sharing, moving, and management of, as well as interactive access to, large, complex data sets at sites dispersed across the country and around the globe. In particular, they call for significant enhancements in network capacities to sustain large data volumes and, equally important, the capabilities to collaboratively access the data across computing, storage, and instrument facilities by science users and automated scripts and systems. Improvements in network backbone capacities of several orders of magnitude are essential to meet these challenges, in particular, to support exascale initiatives. Yet, raw network speed represents only a part of the solution. Indeed, the speed must be matched by network and transport layer protocols and higher layer tools that scale in ways that aggregate, compose, and integrate the disparate subsystems into a complete science ecosystem. Just as important, agile monitoring and management services need to be developed to operate the network at peak performance levels. Finally, these solutions must be made an integral part of the production facilities by using sound approaches to develop, deploy, diagnose, operate, and maintain them over the science infrastructure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Compilation of the ``Atlas of Gamma-rays from the Inelastic Scattering of Reactor Fast Neutrons'' (1978DE41) by A.M. Demidov, L.I. Govor, Yu. K. Cherepantsev, M.R. Ahmed, S. Al-Najjar, M.A. Al-Amili, N. Al-Assafi, and N. Rammo

A Structured Query Language (SQL) relational database has been developed based on the original (n,n'gamma) work carried out by A.M. Demidov et al., at the Nuclear Research Institute in Baghdad, Iraq [``Atlas of Gamma-Ray Spectra from the Inelastic Scattering of Reactor Fast Neutrons'', Nuclear Research Institute, Baghdad, Iraq (Moscow, Atomizdat 1978)] for 105 independent measurements comprising 76 elemental samples of natural composition and 29 isotopically-enriched samples. The information from this ATLAS includes: gamma-ray energies and intensities; nuclide and level data corresponding to where the gamma-ray originated from; target (sample) experimental-measurement data. Taken together, this information allows for the extraction of the flux-weighted (n,n'gamma) cross sections for a given transition relative to a defined value. Currently, we are using the fast-neutron flux-weighted partial gamma-ray cross section from ENDF/B-VII.1 for the production of the 847-keV transition from the first excited 2+ state to the 0+ ground state in 56Fe, 468 mb. This value also takes into account contributions to the 847-keV transition following beta(-) decay of 56Mn formed in the 56Fe(n,p) reaction. However, this value can easily be adjusted to accommodate the user preference. The (n,n'gamma) data has been compiled into a series of ASCII comma separated value tables and a suite of Python scripts and C modules are provided to build the database. Upon building, the database can then be interacted with directly via the SQLite engine or accessed via the Jupyter Notebook Python-browser interface. Several examples exploiting these utilities are also provided with the complete software package.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Who watches the watchers?: preventing fault in a fault tolerance library

The Scalable Checkpoint/Restart library (SCR) was developed and is used by researchers at Lawrence Livermore National Laboratory to provide a fast and efficient method of saving and recovering large applications during runtime on high-performance computing (HPC) systems. Though SCR protects other programs, up until June 2017, nothing was actively protecting SCR. The goal of this project was to automate the building and testing of this library on the varying HPC architectures on which it is used. Our methods centered around the use of a continuous integration tool called Bamboo that allowed for automation agents to be installed on the HPC systems themselves. These agents provided a way for us to establish a new and unique way to automate and customize the allocation of resources and running of tests with CMake’s unit testing framework, CTest, as well as integration testing scripts though an HPC package manager called Spack. These methods provided a parallel environment in which to test the more complex features of SCR. As a result, SCR is now automatically built and tested on several HPC architectures any time changes are made by developers to the library’s source code. The results of these tests are then communicated back to the developers for immediate feedback, allowing them to fix functionality of SCR that may have broken. Hours of developers’ time are now being saved from the tedious process of manually testing and debugging, which saves money and allows the SCR project team to focus their efforts towards development. Thus, HPC system users can use SCR in conjunction with their own applications to efficiently and effectively checkpoint and restart as needed with the assurance that SCR itself is functioning properly.

97 MATHEMATICS AND COMPUTING↗