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DOE OSTI2016

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. This third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

From Data to Models and Analytics: An Integrated Scientific Computing Platform to Accelerate Environmental Research SBIR Phase I (Final Technical Report)

Phase I research was conducted to investigate the technical feasibility of an integrated open source platform GeoLib to provide turnkey solutions for model-data integration for environmental systems science (ESS), using modern web technologies, advances in HPC and cloud computing and high-performance visualization. A key feature of our platform is that it minimizes and automates data movement between data storage and computing systems. Another critical feature of the design is that it enables users to perform high-fidelity post-processing by performing high-performance visualization server-side and in-situ on the compute cluster close to the data. The investigation, which was performed over a 12-month period ending April 2019, centered on developing prototype software to demonstrate the key enabling technologies required for this system. This included: (i) rapid access to data from multiple remote sources, via a unified data interface; (ii) software for scalable geospatial visualization of raster, vector, and point cloud data on the web; (iii) development of an easy-to-use API for creating simulation and modeling workflows; (iv) remote data visualization and processing on middle-tier servers; and (v) remote data processing on high-performance computing systems. A critical part of this work is that all of these capabilities be accessible to end users through standard desktop tools such as Project Jupyter, which is widely adopted for ESS simulation and modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

A programmable shared-memory system for an array of processing-in-memory devices

Processing in memory (PIM), the concept of integrating processing directly with memory has been attracting a lot of attention, since PIM can assist in overcoming the throughput limitation caused by data movement between CPU and memory. The challenge, however, is that it requires the programmers to have a deep understanding of the PIM architecture to maximize the benefits such as data locality and parallel thread execution on multiple PIM devices. In this study, we present AnalyzeThat, a programmable shared-memory system for parallel data processing with PIM devices. Thematic to AnalyzeThat is a rich PIM-aware data structure (PADS), which is an encapsulation that integrally ties together the data, the analysis tasks and the runtime needed to interface with the PIM device array. The PADS abstraction provides (i) a sophisticated key-value data container that allows programmers to easily store data on multiple PIMs, (ii) a suite of parallel operations with which users can easily implement data analysis applications, and (iii) a runtime, hidden to programmers, which provides the mechanisms needed to overlay both the data and the tasks on the PIM device array in an intelligent fashion, based on PIM-specific information collected from the hardware. We have developed a PIM emulation framework called AnalyzeThat. In conclusion, our experimental evaluation with representative data analytics applications suggests that the proposed system can significantly reduce the PIM programming effort without losing its technology benefits.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK

SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.

CHAN, HENRYT↗

DOE OSTI2020

Status Report on IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENviroment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report provides discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity is maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In addition to the investigative work being conducted on FMUs and FMIs, a series of updates to the hybrid repository has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and opensourcing the HYBRID repository with an integrated regression system.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Development of Optimized Controls and Hardware for Synchrotron Hard X-ray Microscopes with Advanced Spectroscopic Capabilities

The technical objectives of the program were to develop an integrated, fully automated command and data interface between the TXM-Wizard developed at SLAC and the Xradia control software that is used on the Xradia Nano-TXM x-ray microscope with the goal of allowing non-experts including industry users to routinely access the advanced imaging modes that employ collection of images with spectroscopic information. The major accomplishment associated with this goal was the development of a plan to convert the TXM-Wizard software from MatLab to Python and the hiring of an expert Python programmer under contract to perform the conversion.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Development of Optimized Controls and Hardware for Synchrotron Hard X-ray Microscopes with Advanced Spectroscopic Capabilities

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

How systems engineering and human factors can assist SMR vendors with the licensing process - 345

There is growing interest in the development of small modular reactors (SMRs) as a cost-effective renewable source of energy. Most of the current conceptual designs propose advanced and automated control and monitoring technologies which would require complex human system interfaces. The proposals also include a reduction in the number of staff, and partial or full remote control of the facilities. The human factors challenges of such a design philosophy range from identification of information requirements of users to assessing workload to deciding on best information visualization techniques to ensure situation awareness is maintained in a remote control facility. Addressing these challenges will require a systems engineering approach where user requirements are identified through a systematic approach for various contexts, including normal, abnormal, and accident conditions. A systems engineering process will integrate human factors as well as other specialty disciplines such as reliability and design optimization in a coherent fashion that would lead to realization of a successful system that addresses user requirements. The licensing model in Canada is based upon a graded approach and is largely technology neutral. A key factor in ensuring effective licensing effort is identification of regulatory requirements. This paper discusses how adopting a systems engineering approach and early consideration of human factors principles and requirements will not only ensure an efficient design process, but will also help with developing a design that meets the regulatory requirements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

TH-AB-BRA-05: Lung Cannot Be Treated as Homogeneous in Radiation Transport Simulations in Magnetic Fields

Purpose: Magnetic fields in MRgRT are known to induce dose perturbations near lung-tissue interfaces. The goal of this study is to determine if the heterogeneous structure of the lung influences the dose distribution in a magnetic field. Method: The dose distribution from a 4 cm X 4 cm 6 MV photon beam in a 0, 0.6, or 1.5 T magnetic field in a homogeneous lung density (0.333 g/cm{sup 3}) geometry is compared to that in a heterogeneous segmented slab configuration. The heterogeneous phantom is composed of 2/3 water vapour and 1/3 liquid water such that the overall density of the lung regions in the two phantoms are equivalent. The EGSnrc DOSXYZnrc user code is used with a previously implemented magnetic field transport code. Results: For water vapour gap thickness of 2 mm, compared to the homogeneous lung case (which already exhibits significant dose perturbations in a magnetic field) differences as large as 12.3 ± 0.2 % are observed for a 0.6 T field and 9.3 ± 0.1 % for a 1.5 T field at the tissuelung interface, and on the order of several percent within the lung-like tissue region for both magnetic fields. Thicker gaps produced larger deviations while a gap thickness of 0.2 mm does not result in notable differences. Regardless of gap thickness, the heterogeneities had little effect on the 0 T simulations. Further, using smaller scoring regions revealed that dose averaging effects could obscure dose differences as large as 10 – 20 % within the heterogeneous structures of the lung-like media. Conclusions: This simple model demonstrates that media heterogeneities can play an important role in MRgRT dose distributions, and care must be taken in setting up any dose calculation in the lung in the presence of a magnetic field, especially for air regions larger than 2 mm.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Practical Probabilistic Programming

Recent advances in probabilistic programming languages (PPLs) have provided the capability for exact inference: computing a closed-form probability distribution for a given probabilistic program. In particular, the new language Roulette uses a language oriented programming (LOP) approach, wherein analysts build new programming languages on top of a set of primitives provided by Roulette, which then translates these structures into a weighted model counting problem which can be solved by automated reasoning tools. However, because Roulette provides few convenience features, developing these new languages is challenging even for expert users. We developed a standard library of common probability functions for Roulette with the goal of improved usability. This included approximation of continuous probability density functions using discrete probability mass functions. We demonstrated this approach by modeling a cosmic ray striking a RAM controller. We found that Roulette provides a powerful interface for highly expressive probabilistic programs to be generated. In collaboration with the NNSA Advanced Simulation and Computing program, which resulted in development of a tool called Circulette, we were able to model complex circuits expressed in Verilog using probabilistic programs with an expressivity not previously possible. Our research question that motivated the development of a Roulette standard library was to determine whether non-experts could use a PPL to model relevant problems regarding radiation effects on microelectronics. This standard library improved the expressivity of Roulette by implementing common probability density functions, mathematical operators on distributions, and support for empirical distributions. While Roulette is a powerful modeling language, the untyped, LOP approach makes error messages difficult to understand and requires expert aid. We recommend further research on Roulette, especially with its error messages, to enable improved usability. At the same time, this project demonstrated that for users familiar with Roulette and the LOP approach, Roulette provides powerful new capabilities that can be integrated with other Sandia modeling capabilities.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Kip, Version 1.0

This high-performance ray tracing library provides very fast rendering, compact code, type flexibility via C++ 'generic programming' techniques, and ease of use through an application programming interface (API) that functions independently of any GUI, on-screen display, or other enclosing application. Kip supports constructive solid geometry models based on any of several built-in shapes and operators and allows for new, user-defined shapes and operators. Additional features include basic texturing, input/output of models using a simple human-readable file format with full error checking and detailed diagnostics, and support for shared data parallelism. Kip is written in pure, ANSI Standard C++, is entirely platform independent, and is very easy to use, as it requires no build system, configuration or installation scripts, wizards, special preprocessing, makefiles, or external libraries.

Staley, Martin↗

DOE OSTI2016

General Line Ampacity State Solver

INL’s General Line Ampacity State Solver (GLASS) is a high performance software platform that enables advanced grid system operations and planning efforts to be computed in real time. It enables the combination of advanced sensors and sensor networks, communication and data transfer channels, secure and reliable data management, and real-time processing through a flexible system architecture, with the ability to support and integrate with any utility enterprise system. GLASS is designed to help resolve the problems associated with thermally limited transmission and distribution networks, namely bare overhead power transmission lines. GLASS enables the methodology of Concurrent Cooling (Dynamic Line Rating) by reducing the need of using a cost-prohibited number of weather stations (reduce the number of weather stations per mile of overhead power line) to achieve the resolution necessary for individual electric transmission line span capacity calculations. GLASS achieves this by coupling real-time grid operations data and infrastructure architecture information with real-time field deployed weather station measurements and pre-computed Computational Fluid Dynamics (CFD)-based wind modeling interpolation parameters (look-up tables). GLASS uses mathematical models based on the IEEE 738 standard and builds off of the provided iterative solution using modern software paradigms and programming styles to provide a more robust and modular software system. GLASS also interfaces in real-time with utility companies using known transmission line spans and structures. GLASS provides real-time ampacity calculations based on recent weather station data as well as transmission line specifications. GLASS also allows the user to interact graphically with internal databases, which include information such as transmission line conductor types and thermal rating limits, weather station names and locations, specific transmission line span and structure locations, as well as recent ampacity calculations.

Gentle, Jake↗

DOE OSTI2022

FLIR Infrared Camera Effective Use, Data Collection, and Tips [Slides]

The FLIR Infrared Camera features include: the ability to capture infrared and visible images, passive measurement, the E series cameras can measure temperature differences between multiple user-specified locations, the E Series has a max-min and auto range function, a laser pointer for reference, picture-in-picture and MSX infrared/digital camera capability, the E Series uses touch-screen and button interface, and two temp ranges are available: 0-650C (32-1202F) and -20-120C (-4-248F).

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

Dual-Slab Verification Detector (DSVD) Operations Software User Guide

The Dual-Slab Verification Detector (DSVD) is used with a MiniGRAND to acquire data at different positions on a spent-fuel cask and then to make a determination regarding the safeguards status of the fuel stored in the cask. The software described in this document, the DSVD Operations Software, provides an interface to perform the various activities required to use the DSVD to make safeguards determinations. Data acquired by the software is saved in a set of worksheets in an Excel spreadsheet. Plateau, background, and calibration data are each placed on separate pages, and each cask has its own page containing data acquired for that cask. The spreadsheet is backed up each time the software begins executing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2020

Correction to Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

This errata is to correct the acknowledgment in the original published article. G.B. (partial support), V.-A.G., M.-T.N., and R.R. were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division. Computer resources were provided by Research Computing at Pacific Northwest National Laboratory and the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. G.B. acknowledges the EPSRC for partial support in PhD funding. The authors acknowledge the use of the IRIDIS High Performance Computing Facility (IRIDIS 5) and associated support services at the University of Southampton in the completion of this work. We are grateful to the UK Materials and Molecular Modeling Hub (Thomas HPC) for computational resources, which is partially funded by EPSRC (EP/P020194/1).

continuum solvation, metal/water interfaces, ab in↗

DOE OSTI2018

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks

Hyperparameters employed by deep learning (DL) methods play a substantial role in the performance and reliability of these methods in practice. Unfortunately, finding performance-optimizing hyperparameter settings is a notoriously difficult task. Hyperparameter search methods typically have limited production-strength implementations or do not target scalability within a highly parallel machine, portability across different machines, experimental comparison between different methods, and tighter integration with workflow systems. In this paper, we present DeepHyper, a Python package that provides a common interface for the implementation and study of scalable hyperparameter search methods. It adopts the Balsam workflow system to hide the complexities of running large numbers of hyperparameter configurations in parallel on high-performance computing (HPC) systems. We implement and study asynchronous model-based search methods that consist of sampling a small number of input hyperparameter configurations and progressively fitting surrogate models over the input-output space until exhausting a user-defined budget of evaluations. We evaluate the efficacy of these methods relative to approaches such as random search, genetic algorithms, Bayesian optimization, and hyperband on DL benchmarks on CPU- and GPU-based HPC systems.

Balaprakash, Prasanna↗

DOE OSTI2014

High density, multi-range analog output Versa Module Europa board for control system applications

A new VMEDAC64, 12-bit 64 channel digital-to-analog converter, a Versa Module Europa (VME) module, features 64 analog voltage outputs with user selectable multiple ranges, has been developed for control system applications at Inter University Accelerator Centre. The FPGA (Field Programmable Gate Array) is the module's core, i.e., it implements the DAC control logic and complexity of VMEbus slave interface logic. The VMEbus slave interface and DAC control logic are completely designed and implemented on a single FPGA chip to achieve high density of 64 channels in a single width VME module and will reduce the module count in the control system applications, and hence will reduce the power consumption and cost of overall system. One of our early design goals was to develop the VME interface such that it can be easily integrated with the peripheral devices and satisfy the timing specifications of VME standard. The modular design of this module reduces the amount of time required to develop other custom modules for control system. The VME slave interface is written as a single component inside FPGA which will be used as a basic building block for any VMEbus interface project. The module offers multiple output voltage ranges depending upon the requirement. The output voltage range can be reduced or expanded by writing range selection bits in the control register. The module has programmable refresh rate and by default hold capacitors in the sample and hold circuit for each channel are charged periodically every 7.040 ms (i.e., update frequency 284 Hz). Each channel has software controlled output switch which disconnects analog output from the field. The modularity in the firmware design on FPGA makes the debugging very easy. On-board DC/DC converters are incorporated for isolated power supply for the analog section of the board.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations

To realize the full potential of machine learning in diverse real- world domains, it is necessary for model predictions to be readily interpretable and actionable for the human in the loop. Analysts, who are the users but not the developers of machine learning models, often do not trust a model because of the lack of transparency in associating predictions with the underlying data space. To address this problem, we propose Rivelo, a visual analytic interface that enables analysts to understand the causes behind predictions of binary classifiers by interactively exploring a set of instance-level explanations. These explanations are model-agnostic, treating a model as a black box, and they help analysts in interactively probing the high-dimensional binary data space for detecting features relevant to predictions. We demonstrate the utility of the interface with a case study analyzing a random forest model on the sentiment of Yelp reviews about doctors.

Tamagnini, Paolo↗