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DOE OSTI2022

Quantum Networks for Resilient Power Grids: Theory and Simulated Evaluation

Quantum networks are considered the future of secure communication in the coming quantum era. Yet there lack significant efforts on developing practical quantum networks for power grids. Here, in this paper, we establish a quantum network-based power grid (QNetGrid) framework and develops a real-time, reliable, flexible, programmable, and cost-effective QNetGrid software testbed containing repeater-based quantum communication, quantum routing, real software-defined networking (SDN) switches, and real-time networked microgrids (NMs) operations. It makes the following contributions: 1) a repeater and routing based quantum network simulator (QNSim) is developed, 2) repeaters with and without quantum memories are respectively simulated in QNSim, 3) different routing scenarios in QNetGrid are investigated, 4) a real-time QNetGrid software testbed is built in RTDS incorporating QNSim and real SDN switches, and 5) various test cases are designed, and experimental results produced with the QNetGrid testbed provide valuable insights for building quantum networks in power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Idaho National Laboratory Advanced Reactor Technologies Quality Assurance Program Plan

This QAPP covers INL ART R&D, licensing, and program support activities. QA implementing procedures will be identified for all activities to ensure work is documented and the results are capable of successfully completing a technical review by DOE. For work performed by other organizations under contract or other agreements with INL, applicable requirements will be flowed down through the contract or other agreements, but the organizations will be responsible to implement the flowed down requirements through their own specific implementing procedures. This QAPP also covers implementation of software QA (SQA) requirements for software used exclusively by INL ART. Software that is used to support multiple INL programs/projects is not covered by this QAPP; the responsibility for implementing SQA requirements for that software resides with the owners and respective managers of the software. This QAPP does not cover activities for installing and operating experiments in the Advanced Test Reactor (ATR) at INL, nor does it cover ATR facility modifications designed to meet INL ART testing needs (such as temperature, pressure, gas flow, and control systems). Those activities are controlled by the INL QAP and specific ATR implementing procedures. ATR facility management and INL ART management jointly approve experiment designs and functional system requirements. This QAPP does apply to INL ART R&D experiments that will be inserted into ATR and any support activities associated with those R&D activities. This QAPP does not cover activities for installing and operating general post irradiation examination (PIE) test equipment in Materials and Fuels Complex (MFC) facilities. Those activities are controlled by the INL QAP and MFC implementing procedures. However, this QAPP does apply to MFC facility modifications designed to meet specific INL ART testing needs. It also applies to INL ART experiments that will have PIE performed on them and any support activities associated with the PIE activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗

DOE OSTI2024

Initial Development of Fusion Magnet Simulation Capabilities for Performance and Safety Evaluation Using the MOOSE Framework

Fusion energy holds the promise of being a transformative technology as a carbon-neutral, sustainable source of energy. Whole device modeling and the development of fusion digital twins will be increasingly important for emerging fusion device concepts at both national laboratories and within the commercial fusion industry. However, meeting the challenge of whole device modeling of fusion energy devices requires robust, multiphysics, multiscale modeling and simulation technologies capable of running on large-scale supercomputers. Detailed analysis of individual systems at-scale is also required to ensure safe and efficient operation as well as provide the safety basis for future device designs and licensing activities. In a tokamak, toroidal and poloidal magnets confine and shape the fusion plasma to promote the fusion reaction. High plasma temperatures and high magnetic field requirements in modern design concepts (leading to high amounts of energy stored within each magnet) impose electrical, thermal, and mechanical loads on the magnet components, which in turn impacts the safety considerations of the magnet and their supporting systems. Idaho National Laboratory (INL) has a history of working in this space, including development and benchmarking of the Magnetic System Circuitry Analysis Program (MSCAP) and Magnet Arcing (MAGARC) codes to study magnet quench events; notably, MAGARC was used to study quenching during the ITER Engineering Design Activity. However, these legacy codes and capabilities are not parallel and scalable, and new tools are required for future advances in this area, which leads to the INL-developed Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Developed originally for fission reactor systems under United States Department of Energy, Office of Nuclear Energy modeling and simulation programs, the MOOSE framework has been well-suited to multiscale, multiphysics modeling and simulation needs for nuclear systems. The framework is open-source, well-tested, under continuous development and deployment, and developed to a Nuclear Quality Assurance, Level 1 software quality standard. MOOSE has also been used in the fusion space previously in several projects: INL’s Tritium Migration Analysis Program, Version 8 (TMAP8) for tritium migration, UK Atomic Energy Authority’s A Unified Resource for OpenMC (fusion) Reactor Applications (AURORA) code for fusion thermo-mechanical and neutronics analysis, and Argonne National Laboratory’s Cardinal for high-fidelity computational fluid dynamics and neutronics. However, to model superconducting magnets, several MOOSE enhancements are required: additions to the current MOOSE electromagnetic capabilities, new material libraries for superconductors of interest (such as YBCO), as well as fusion-specific models for thermo-mechanics. This talk will discuss initial development activities to build these capabilities in MOOSE, focusing on initial validation and benchmarking activities. Proposed coupling workflows and future work to support the simulation of fusion magnets and magnet structural assemblies for performance and safety evaluation in MOOSE will also be discussed.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Stabilizing a strongly nonlinear structure through shaker dynamics in fixed frequency voltage control tests

Bifurcations are commonly encountered during force controlled swept and stepped sine testing of nonlinear structures, which generally leads to the so-called jump-down or jump-up phenomena between stable solutions. There are various experimental closed-loop control algorithms, such as control-based continuation and phase-locked loop, to stabilize dynamical systems through these bifurcations, but they generally rely on specialized control algorithms that are not readily available with many commercial data acquisition software packages. A recent method was developed to experimentally apply sequential continuation using the shaker voltage that can be readily deployed using commercially available software. By utilizing the stabilizing effects of electrodynamic shakers and the force dropout phenomena in fixed frequency voltage control sine tests, this approach has been demonstrated to stabilize the unstable branch of a nonlinear system with three branches, allowing for three multivalued solutions to be identified within a specific frequency bandwidth near resonance. Recent testing on a strongly nonlinear system with vibro-impact nonlinearity has revealed jumping behavior when performing sequential continuation along the voltage parameter, like the jump phenomena seen during more traditional force controlled swept and stepped sine testing. Here, this paper investigates the stabilizing effects of an electrodynamic shaker on strongly nonlinear structures in fixed frequency voltage control tests using both numerical and experimental methods. The harmonic balance method is applied to the coupled shaker-structure system with an electromechanical model to simulate the fixed voltage control tests and predict the stabilization for different parameters of the model. The simulated results are leveraged to inform the design of a set of experiments to demonstrate the stabilization characteristics on a fixture-pylon assembly with a vibro-impact nonlinearity. Through numerical simulation and experimental testing on two different strongly nonlinear systems, the various parameters that influence the stability of the coupled shaker-structure are revealed to better understand the performance of fixed frequency voltage control tests.

42 ENGINEERING↗

DOE OSTI2023

TDCOSMO. X. Automated modeling of nine strongly lensed quasars and comparison between lens-modeling software

When strong gravitational lenses are to be used as an astrophysical or cosmological probe, models of their mass distributions are often needed. We present a new, time-efficient automation code for the uniform modeling of strongly lensed quasars with GLEE, a lens-modeling software for multiband data. By using the observed positions of the lensed quasars and the spatially extended surface brightness distribution of the host galaxy of the lensed quasar, we obtain a model of the mass distribution of the lens galaxy. We applied this uniform modeling pipeline to a sample of nine strongly lensed quasars for which images were obtained with the Wide Field Camera 3 of the Hubble Space Telescope. The models show well-reconstructed light components and a good alignment between mass and light centroids in most cases. We find that the automated modeling code significantly reduces the input time during the modeling process for the user. The time for preparing the required input files is reduced by a factor of 3 from ~3 h to about one hour. The active input time during the modeling process for the user is reduced by a factor of 10 from ~ 10 h to about one hour per lens system. This automated uniform modeling pipeline can efficiently produce uniform models of extensive lens-system samples that can be used for further cosmological analysis. A blind test that compared our results with those of an independent automated modeling pipeline based on the modeling software Lenstronomy revealed important lessons. Quantities such as Einstein radius, astrometry, mass flattening, and position angle are generally robustly determined. Other quantities, such as the radial slope of the mass density profile and predicted time delays, depend crucially on the quality of the data and on the accuracy with which the point spread function is reconstructed. Better data and/or a more detailed analysis are necessary to elevate our automated models to cosmography grade. Nevertheless, our pipeline enables the quick selection of lenses for follow-up and further modeling, which significantly speeds up the construction of cosmography-grade models. This important step forward will help us to take advantage of the increase in the number of lenses that is expected in the coming decade, which is an increase of several orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Yeast Transformation on Hamilton Vantage (YT Vantage) v1

Our software program is designed for the Hamilton Vantage liquid handling robot, automating the Build step in the Design-Build-Test-Learn (DBTL) cycle for Saccharomyces cerevisiae. This program minimizes human intervention, enabling rapid identification of pathway bottlenecks and genes that enhance verazine production. The program takes competent yeast and plasmid DNA as input and generates an output library of engineered strains compatible with automated colony picking, high-throughput culturing, and chemical extraction for downstream LC-MS analysis. A user-friendly interface, developed using the Hamilton Method Editor software, allows for on-demand parameter customization. By automating this process, our program streamlines the construction of Saccharomyces cerevisiae, reducing manual labor and increasing efficiency. While the manual process is well-documented, integration with robotic automation is less common, making our program a valuable tool for researchers. With this software, we achieved 2-5 fold increases in verazine production, demonstrating its potential to accelerate research in this field.

Louie, Randy [Lawrence Berkeley National Laborator↗

DOE OSTI2023

Post Access Report: Initial testing of wave energy powered UV-C LED anti-biofouling system

In the experiment entitled “Initial Testing of Wave Energy Powered UV-C LED Anti-Biofouling System,” a UV-C LED was used to treat platinum-coated titanium coupons emulating CTD electrode material. An additional control set of coupons were exposed to seawater without the LED treatment. The experimental setup was deployed in seawater tanks at PNNL-Sequim’s Marine and Coastal Research Laboratory (MCRL) for the duration of six months. Tank seawater temperature data were collected for the duration of the experimental campaign. At two-month intervals triplicate sets of coupons were removed from both treatment and control test chambers and weighed to characterize biomass accumulation. After weighing, the coupons were photographed in initial condition, with a stain applied to highlight biofouling growth, and after rinsing off excess stain. These photographs were analyzed using PNNL’s Biofouling Growth Index (BGI) software and with a calculation of percentage dark pixels after conversion to grayscale. Additionally, at the final 6-month datapoint triplicate sets of control and test coupons were sent to PNNL-Richland’s Environmental Molecular Sciences Laboratory (EMSL) for scanning electron microscopy. All data organization and collection methods are described in further detail in the document “TEAMER_3newable_Data_Guide.pdf.” Biomass accumulation increased over time on both sets of coupons, and percent area biofouled demonstrated a similar trend. Analysis of the collected data resulted in the findings that treatment method has an impact on biofouling growth, though to a much less significant extent than time does. Additionally, qualitative findings included the presence of advanced life forms such as worms in the control test chamber, but not in the treated test chamber.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Advanced System Thermal Fluids Solver Development for SAM

This work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key is the implementation of a high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. Leveraging the existing capabilities of the SAM code, significant code coverages were established in the finite volume method code. This in turn allows for a suite of test problems with different problem sizes and levels of complexity to be used to quantify the performance improvement of the finite volume method code. As evidently shown in this study, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE for the wide range of selected problems. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. In addition, for a complex reactor model, transient simulation was performed using the finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development. In this work, short-term priority development and testing items were identified, and long-term code adoption and integration plans were made for the eventual deployment of the finite volume method in the SAM code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Hardware-in-the-Loop Evaluation of an Advanced Distributed Energy Resource Management Algorithm

This paper presents the laboratory performance evaluation of voltage regulation under a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-tbe-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale real-world distribution system from a utility partner, the DERMS software controller, and power hardware photovoltaic (PV) inverters. The new DERMS algorithm is developed based on online multiobjective optimization (OMOO) algorithms that perform fast dispatch of distributed solar PV simulated in a real-time digital simulator and real physical hardware devices. Experimental tests confirm the correct functioning of the HIL platform for evaluating controller algorithms and satisfactory voltage regulation performance of the developed OMOO algorithms.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2023

HamLib: A Library of Hamiltonians for Benchmarking Quantum Algorithms and Hardware

For a considerable time, large datasets containing problem instances have proven valuable for analyzing computer hardware, software, and algorithms. One notable example of the value of large datasets is ImageNet [1], a vast repository of images that has been instrumental in testing numerous deep learning packages. Similarly, in the domain of computational chemistry and materials science, the availability of extensive datasets such as the Protein Data Bank [2], the Materials Project [3], and QM9 [4] has greatly facilitated the evaluation of new algorithms and software approaches, while also promoting standardization within the field. These well-defined datasets and problem instances, in turn, serve as the foundation for creating benchmarking suites like MLPerf [5] and LINPACK [6], [7]. These suites enable fair and rigorous comparisons of different methodologies and solutions, fostering continuous advancements in various areas of computer science and beyond.

Sawaya, Nicolas PD↗

DOE OSTI2021

Hardware-in-the-Loop Evaluation of an Advanced Distributed Energy Resource Management Algorithm: Preprint

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

Oak Ridge Spoofing and Interference Test Battery (OAKBAT) - Pure Tones

This dataset contains the pure 1.57542 GHz (L1) pure tone recordings provided to allow characterization of the recording equipment used to digitize the OAKBAT scenarios. The equipment includes the cable, two LNAs, and the software-defined radio. The files are binary data in the format described in the paper: Albright, A., Powers, S. Bonior, J., and Combs, F., A Tool for Furthering GNSS Security Research: The Oak Ridge Spoofing and Interference Test Battery (OAKBAT), in Proceedings of ION GNSS+ 2020, 2020. The metadata, equipment documentation and configuration files, collection procedures and more materials that allow the independent reproduction of the OAKBAT data are https://github.com/oakbat/. Additionally, this site includes a complete listing of all the RF data files, not just this series, available as part of OAKBAT.

42 ENGINEERING↗

DOE OSTI2021

From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape

Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units. This review explores the challenges and some of the solutions in transforming software from the terascale to the petascale and now to the upcoming exascale computers. While discussing the field in general, NWChem and its redesign, NWChemEx, will be highlighted as one of the early codesign projects to take advantage of massively parallel computers and emerging software standards to enable large scientific challenges to be tackled.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

A multi-agent approach to distribution system fault section estimation in smart grid environment

We report that Multi-Agent Systems (MAS) are seen from different areas as one of the paramount trends for the next generation of power systems. Numerous published studies about MAS discuss its utilization in power distribution networks but none focuses on the prior step to restoration and self-healing that is fault section estimation. This paper aims to show how MAS can improve the utilities’ reliability indexes and consumer satisfaction by overcoming the multiple fault section estimation problem. In order to do this, the authors considered using MAS as a means of communication between smart meters. The purpose of smart meters usage is to employ devices that are already present in smart grids, mainly because of their reading and saving data capacity. The proposed method was tested on a radial feeder generated by the authors. The network was built on HYPERSIM, a software platform of OPAL-RT Technologies. The simulation results show that this MAS provides speed, efficiency, and automation for the process of fault section estimation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

International database of reference gamma spectra for nuclear safeguards applications

Nuclear safeguards missions use gamma spectroscopy as a non-destructive measurement technique for examining nuclear materials. Despite advances in the development of detection equipment as well as software codes, one of the concerns is the lack of well-documented spectra needed to test and validate isotopic analysis codes for their applicability. To address this need, this work introduces IDB, an international database of the reference gamma spectra of uranium, plutonium and mixed oxide nuclear material samples. IDB provides access to well-characterized sets of gamma spectra described by rich metadata, including information on the sample, measurement configuration and detector specifications. These spectra are accessible in different formats, also compatible with analysis code standards, thus promoting their sustainability and maintenance.

None, Dipti [International Atomic Energy Agency (I↗

DOE OSTI2024

Robust Iterative Method for Symmetric Quantum Signal Processing in All Parameter Regimes

Here, this paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on quantum computers. Symmetric QSP focuses on representing target polynomials as products of matrices in SU(2) that possess symmetry properties. We present a novel Newton’s method tailored for efficiently solving the nonlinear system involved in determining the phase factors within the symmetric QSP framework. Our method demonstrates rapid and robust convergence in all parameter regimes, including the challenging scenario with ill-conditioned Jacobian matrices, using standard double precision arithmetic operations. For instance, solving symmetric QSP for a highly oscillatory target function α cos(1000x) (polynomial degree ≈ 1433) takes 6 iterations to converge to machine precision when α = 0.9, and the number of iterations only increases to 18 iterations when α = 1 – 10 -9 with a highly ill-conditioned Jacobian matrix. Leveraging the matrix product state structure of symmetric QSP, the computation of the Jacobian matrix incurs a computational cost comparable to a single function evaluation. Moreover, we introduce a reformulation of symmetric QSP using real-number arithmetics, further enhancing the method’s efficiency. Extensive numerical tests validate the effectiveness and robustness of our approach, which has been implemented in the QSPPACK software package.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Neuromorphic Backpropagation Algorithm Software

This software is an implementation of the backpropagation algorithm for Intel's neuromorphic research processor, Loihi. The software implements the neural circuit itself and a demonstration application where the MNIST dataset (a standard test problem) is used to train a neural network.

Sornborger, Andrew↗