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At least 343 records · Page 19

DFTT report for Signal Analysis (2023)

The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.

58 GEOSCIENCES↗

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗

A Prospective Design Method for Nuclear Power: The Evaluation, Requirements, and Goals Outline for Nuclear (ERGON) Method

Human factors researchers at Idaho National Laboratory (INL) have worked on projects spanning control room modernization, operator support systems, visualization design, and novel system creation. These projects demonstrated the need for an explicit design method for nuclear power. Human factors teams found a high standard in the Human Factors Engineering Program Review Model (NUREG-0711) and needed a design methodology which could be successful in gaining approval. Previous work has been synthesized as the Evaluation, Requirements, and Goals Outline for Nuclear (ERGON) method here. Design tasks are broken into four phases: Context and Orientation, Human Factors Review, Prototyping and Evaluation, Iteration and Improvement. ERGON is intended as a flexible and direct design method for many applications in nuclear power. ERGON has been vetted through collaborative research and development with nuclear utilities and as such, the ERGON method can assist utilities to achieve approval from a NUREG-0711 summative evaluation for HSI implementations.

42 ENGINEERING↗

Post-Service Examination of PWR Baffle Bolts, Part I. Examination and Test Plan

In support of extended service and current operations of the US nuclear reactor plants, the Oak Ridge National Laboratory (ORNL), through the Department of Energy (DOE), Light Water Reactor Sustainability (LWRS) Program, is coordinating with Ginna Nuclear Power Plant, The Westinghouse Electric Company, LLC, and ATI Consulting, the selective procurement of baffle bolts that were withdrawn from service in 2011 and currently stored on site at Ginna. The goal of this program is to perform detailed microstructural and mechanical property characterization of baffle former bolts following in-service exposures. This report outlines the selection criteria of the bolts and the techniques to be used in this study. The bolts available are the original alloy 347 steel fasteners used in holding the baffle plates to the baffle former structures within the lower portion of the pressurized water reactor vessel. Of the eleven possible bolts made available for this work, none were identified to have specific damage. The bolts, however, did show varying levels of breakaway torque required in their removal. The bolts available for this study varied in peak fluence (highest dose within the head of the bolt) between 9.9 and 27.8x10 21 n/cm 2 (E>1MeV). As no evidence for crack initiation was determined for the available bolts from preliminary visual examination, two bolts with the higher fluence values were selected for further post-irradiation examination. The two bolts showed different breakaway torque levels necessary in their removal. The information from these bolts will be integral to the LWRS program initiatives in evaluating end of life microstructure and properties. Furthermore, valuable data will be obtained that can be incorporated into model predictions of long-term irradiation behavior and compared to results obtained in high flux experimental reactor conditions. The two bolts selected for the ORNL study will be shipped to Westinghouse with bolts of interest to their collaborative efforts with the Electric Power Research Institute. Westinghouse will section the ORNL bolts into samples specified in this report and return them to ORNL. Samples will include bend bars for fracture toughness and crack propagation studies along with thin sections from which specimens for bend testing, subscale tensile and microstructural analysis can be obtained. Additional material from the high stress concentration region at the transition between the bolt head and shank will also be preserved to allow for further investigation of possible crack initiation sites.

42 ENGINEERING↗

SISGR: Chemomechanics of Far-From-Equilibrium Interfaces (COFFEI)

Portable, reliable, and deployable devices for energy storage and conversion require fundamental changes in design of solid-state composites comprising ceramics and metals. These materials comprise the electrodes and electrolytes of next-generation solid-oxide fuel cells and all solid-state batteries, forming solid-state functional composites. The advent of solid-state batteries – which replace liquid electrolytes with solid electrolytes capable of lithium ion transport for reliable energy storage in portable batteries – and the increased demand space for all solid-state fuel cells capable of oxygen reduction at intermediate temperatures remain important challenges for improved material stability and decreased system cost. However, little is understood about three fundamental facets of materials that enable such solid-state energy applications. First, how do such materials deform, fracture, or delaminate under operando conditions? Second, how does such mechanical deformation limit or facilitate electronic and ionic transport within and across such material interfaces? Third, how we can predictably design interface-rich composites to engineer both structural and electrochemical stability? This COFFEI Group comprised expertise from Materials Science & Engineering and Nuclear Science & Engineering to integrate unique in situ experiments, simulations, and fabricated interfaces that address these fundamental questions in solid-state interfaces of nanoscale composites that will guide solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric materials that enable such applications. In particular, we built on COFFEI’s understanding of chemomechanical coupling among defect concentrations, ionic transport, electron transport, and stored elastic energy that is particularly acute in the far-from-equilibrium conditions typical of energy device applications. By tailoring our focus to solid-state interfaces, we addressed these important issues by (a) developing and applying advanced in situ and ex situ characterization tools to characterize model materials and interfaces synthesized with molecular-level control, under both laboratory-controlled and extreme environments representative of energy device operation; and (b) employing computational modeling and simulation frameworks to predict transport mechanisms, reactivity and stability of these model materials and interfaces under significant chemical strains typical of energy device operation. Recent progress provided insights to additional materials systems and electrochemomechanical fatigue and fracture that were not fully envisioned when the program was initiated. Specifically, in the final three years of COFFEI we pursued two integrated thrusts, with complementary focus. Thrust I focused on failure-resistant electrochemomechanical composites, while Thrust II focused on strain-modulated conductivity and reactivity across interfaces. In contrast to our initial COFFEI focus, these thrusts concentrated wholly on solid-state material interfacial interactions and included greater integration of multiscale visualization including in situ electron microscopy of strained structures/interactions and mesoscale simulations. Successful development of functionally superior and long-lived battery and fuel cell systems and stress adaptable oxides requires a deeper, fundamental understanding of the coupling among the historically important subfields of solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric metal oxide electrodes. In this program, the understanding and the application of chemomechanical coupling of defect concentrations, ionic transport, electro-catalytic activity and stored elastic energy, particularly acute in the far-from-equilibrium conditions typical of energy device applications, are being refined and implications for device operation clarified, including for miniaturized solid-state batteries and fuel cells.

36 MATERIALS SCIENCE↗

Validation of Criticality Analysis Capability of SuperMC with ICSBEP

SuperMC is a general purpose, intelligent and multifunctional, continuous energy Monte Carlo program for the design and safety evaluation of nuclear systems. It is designed to perform the comprehensive neutronics calculation, taking the radiation transport as the core and including the depletion, radiation source term/dose/biohazard, material activation and transmutation, etc. The latest version of SuperMC can perform the simulation of neutron, photon and coupled neutron and photon transport, and also equipped with the functions of automatic modeling and visualization. SuperMC has been verified by more than 2000 benchmark models and experiments including the handbook of International Criticality Safety Benchmark Evaluation Project (ICSBEP), the Shielding Integral Benchmark Archive Database (SINBAD), etc. The fusion reactor (ITER benchmark model, FDS Fusion Reactors), fast reactors (BN600, CLEAR-I), PWR reactors (HM, BEAVRS) and cases from the International Reactor Physics handbook Evaluation Program (IRPhEP) were employed for validating the comprehensive capability for reactor applications. In this paper, the validation of SuperMC based on the handbook of ICSBEP will be presented. ICSBEP, released by OECD/NEA, contains criticality safety benchmark specifications derived from experiments that were performed at various nuclear critical facilities around the world, which was widely used to verify neutronic codes and associated nuclear data libraries for criticality safety analysis. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Sharing of Good Practices and Lessons Learned [Slides]

This presentation shares good practices and lessons that were learned. Particularly highlighted is the Learning from Experience Database (LFE). Provided are additional slides walking through a visual representation of this system.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Final Report for the Advanced Outage Control Center Dashboard with Predictive Tools

The “Advanced Outage Control Center” (AOCC) pilot project was part of the Light Water Reactor Sustainability (LWRS) program and was a multi-year effort targeted at NPP outage improvement. The primary purpose of this pilot project was to improve management of NPP outages through the development of AOCC features and facilities designed specifically to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. Later stages of the project focused more on tools that utilize technology to improve the outage manager’s understanding of the true outage status. The primary tool that resulted from this research was an innovative outage information dashboard with built-in data analysis and predictive capabilities. In its present form, the dashboard specifically takes advantage of visualization techniques that allow users to view and understand the status of the outage at a glance, without the need to drill down to find detail information. The dashboard also incorporates historical performance data to help evaluate current performance. The key innovation in this dashboard concept is not only its ability to avoid the complexity of raw data presentation, but also to predict the completion of the current outage using data analysis of the current schedule and historical performance of the plant. Through the LWRS program, a relationship between Idaho National Laboratory and Arizona Public Service (APS) was established to investigate the application of specialized techniques to analyze and visualize complex outage information. APS has supported efforts to implement advanced methods to improve the management of outages at the three units of the Palo Verde Nuclear Generating Station (PVNGS). The project has produced the basic principles and methodology for the development of sophisticated outage information analysis and presentation tools.

99 GENERAL AND MISCELLANEOUS↗

Dataset of U.S. School Bus Depots

A large body of public health literature describes how undesirable or dangerous facilities, such as truck depots and industrial plants, located in or near communities can lead to health harms. Research also describes the high levels of traffic-related air and noise pollution that is linked to health harms and may be disproportionately distributed near many schools. Therefore, a primary use case for this dataset is to analyze the location of school bus depots and to create an evidence base that would better enable the work of community members, advocates, and other stakeholders toward improving air quality and public health. Other possible uses for this school bus depot dataset include electricity grid planning and reliability, given recent momentum toward school bus electrification. This dataset was created using an object-based approach with remote sensing data. The primary source of aerial imagery was the National Agriculture Imagery Program (NAIP) dataset. NAIP imagery was analyzed to locate individual school buses based on their color and size, and then classified clusters of school buses as potential depots, which were then verified visually. The resulting dataset contains 11,309 depots across the 48 contiguous U.S. states and Washington, D.C. Fifty-one percent (5,730 depots) are at schools, defined as being 350 meters or less from the nearest school. The accuracy of the dataset was assessed by comparing it with independent reference datasets containing 506 depots from the records of two school transportation companies. We found good agreement, with an omission error rate of 15.2% (77 depots). This dataset represents one of the only remote sensing projects to conduct object detection using data at the sub-meter to 1-meter resolution for a continental-scale application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Status of the NEAMS and ARC fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to facilitate the transition from conventional tools to high-fidelity tools. The NEAMS Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench through the PyARC module was initiated in FY-2017. The ARC codes, which focus on fast reactor multiphysics analysis, contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC 2 -3, PERSENT, and PROTEUS. Recent work expended this integration to other tools to support the U.S. fast reactor community such as DASSH for sub-channel thermal-hydraulics, Griffin for high-fidelity deterministic transport calculations, and OpenMC for Monte Carlo simulations (with Shift integration planned for FY-2023). The integration of the “extended ARC” suite of codes into the NEAMS Workbench interface relies on the PyARC and PyGriffin modules to handles the pre- and post-processing of these codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

WinPSSP : a revamp of the computer program PSSP and its performance solving the crystal structures of small organic compounds and solids of biological and pharmaceutical interest

The direct-space methods software Powder Structure Solution Program ( PSSP ) [Pagola & Stephens (2010). J. Appl. Cryst. 43 , 370–376] has been migrated to the Windows OS and the code has been optimized for fast runs. WinPSSP is a user-friendly graphical user interface that allows the input of preliminary crystal structure information, integrated intensities of the reflections and FWHM, the definition of structural parameters and a simulated annealing schedule, and the visualization of the calculated and experimental diffraction data overlaid for each individual solution. The solutions are reported as filename.cif files, which can be used to analyze packing motifs and chemical bonding, and to input the atomic coordinates into the Rietveld analysis software GSAS. WinPSSP performance in straightforward crystal structure determinations has been evaluated using 18 molecular solids with 6–20 degrees of freedom. The free-distribution program as well as multimedia tutorials can be accessed at http://users.uoi.gr/nkourkou/winpssp/.

60 APPLIED LIFE SCIENCES↗

High spatial resolution mass spectrometry imaging reveals the genetically programmed, developmental modification of the distribution of thylakoid membrane lipids among individual cells of maize leaf

Metabolism in plants is compartmentalized among different tissues, cells and subcellular organelles. Mass spectrometry imaging (MSI) with matrix-assisted laser desorption ionization (MALDI) has recently advanced to allow for the visualization of metabolites at single-cell resolution. Here we applied 5- and 10 μm high spatial resolution MALDI-MSI to the asymmetric Kranz anatomy of Zea mays (maize) leaves to study the differential localization of two major anionic lipids in thylakoid membranes, sulfoquinovosyldiacylglycerols (SQDG) and phosphatidylglycerols (PG). The quantification and localization of SQDG and PG molecular species, among mesophyll (M) and bundle sheath (BS) cells, are compared across the leaf developmental gradient from four maize genotypes (the inbreds B73 and Mo17, and the reciprocal hybrids B73 × Mo17 and Mo17 × B73). SQDG species are uniformly distributed in both photosynthetic cell types, regardless of leaf development or genotype; however, PG shows photosynthetic cell-specific differential localization depending on the genotype and the fatty acyl chain constituent. Overall, 16:1-containing PGs primarily contribute to the thylakoid membranes of M cells, whereas BS chloroplasts are mostly composed of 16:0-containing PGs. Furthermore, PG 32:0 shows genotype-specific differences in cellular distribution, with preferential localization in BS cells for B73, but more uniform distribution between BS and M cells in Mo17. Maternal inheritance is exhibited within the hybrids, such that the localization of PG 32:0 in B73 × Mo17 is similar to the distribution in the B73 parental inbred, whereas that of Mo17 × B73 resembles the Mo17 parent. As a result, this study demonstrates the power of MALDI-MSI to reveal unprecedented insights on metabolic outcomes in multicellular organisms at single-cell resolution.

59 BASIC BIOLOGICAL SCIENCES↗

Flexible visualization of a 3rd party Intrusion Prevention (Security) tool: A use case with the ELK stack

A difficult aspect of cyber security is the ability to achieve automated real time intrusion prevention across various sets of systems. To this extent, several companies are offering comprehensive solutions that leverage an "accuracy of scale" and moving much of the intelligence and detection on the Cloud, relying on an ever-growing set of data and analytics to increase decision accuracy. Often, they provide tools to visualize the decision workflows in attack prevention (as well as tune the algorithm) but those solutions are not always practical as companies see the problem as "global" that is, from a unified Cyber-security standpoint. However, a key to a successful Cyber-security program is transparency and trust: from an experimental team viewpoint, this specifically means having the ability to immediately see what and from where, who has been blocked and being able to inform the community in case of a revoked access without the need for filing a "ticket" (that may eventually be answered) – in other words, rapid response to their user-base is essential but solutions targeting "sub-groups" in an organization are not often available. We have come up with a versatile solution leveraging the ELK stack (Elasticsearch, Logstash, & Kibana) and an IPS (Intrusion Prevention System) based WAF (Web Application Firewall) from Signal Sciences. Signal Science allows the streaming of detailed logs in a Logstash format suitable for custom solutions for visualization. By combining these two tools, we have strengthened our security posture and enabled individual experiments to monitor their own traffic. Specifically, the IPS WAF provides unique data such as country of origin, protocol, response code, source IP, and paths accessed. In this contribution, we will show how we engineered a visualization solution so experiment groups could access a dashboard with predefined graphs but also, where they can create individual customizable dashboards used to display blocked traffic and troubleshoot latency issues. We will discuss the details and procedures for developing and configuring these tools and how it benefits cyber security postures across our scientific based environment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measured extent of agricultural expansion depends on analysis technique

Concern is rising that ecologically important, carbon-rich natural lands in the United States are losing ground to agriculture. We investigate how quantitative assessments of historical land use change to address this concern differ in their conclusions depending on the data set used. We examined land use change between 2006 and 2014 in 20 counties in the Prairie Pothole Region using the Cropland Data Layer, a modified Cropland Data Layer, data from the National Agricultural Imagery Program, and in-person ground-truthing. The Cropland Data Layer analyses overwhelmingly returned the largest amount of land use change with associated error that limits drawing conclusions from it. Analysis with visual imagery estimated a fraction of this land use change. Clearly, analysis technique drives understanding of the measured extent of land use change; different techniques produce vastly different results that would inform land management policy in strikingly different ways. As a result, best practice guidelines are needed.

60 APPLIED LIFE SCIENCES↗

XScan: An Integrated Tool for Understanding Open Source Community-Based Scientific Code

Many scientific communities have adopted community-based models that integrate multiple components to simulate whole system dynamics. The community software projects’ complexity, stems from the integration of multiple individual software components that were developed under different application requirements and various machine architectures, has become a challenge for effective software system understanding and continuous software development. The paper presents an integrated software toolkit called X-ray Software Scanner (in abbreviation, XScan) for a better understanding of large-scale community-based scientific codes. Our software tool provides support to quickly summarize the overall information of scientific codes, including the number of lines of code, programming languages, external library dependencies, as well as architecture-dependent parallel software features. The XScan toolkit also realizes a static software analysis component to collect detailed structural information and provides an interactive visualization and analysis of the functions. We use a large-scale community-based Earth System Model to demonstrate the workflow, functions and visualization of the toolkit. We also discuss the application of advanced graph analytics techniques to assist software modular design and component refactoring.

Zheng, Weijian↗

An Update on Improvements to NiCE Support for PROTEUS

The Department of Energy Office of Nuclear Energy's Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has supported the development of the NEAMS Integrated Computational Environment (NiCE), a modeling and simulation workflow environment that provides services and plugins to facilitate tasks such as code execution, model input construction, visualization, and data analysis. This report details the development of workflows for the reactor core neutronics application, PROTEUS. This advanced neutronics application (primarily developed at Argonne National Laboratory) aims to improve nuclear reactor design and analysis by providing an extensible and massively parallel, finite-element solver for current and advanced reactor fuel neutronics modeling. The integration of PROTEUS-specific tools into NiCE is intended to make the advanced capabilities that PROTEUS provides more accessible to the nuclear energy research and development community. This report will detail the work done to improve existing PROTEUS workflow support in NiCE. We will demonstrate and discuss these improvements, including the development of flexible IO services, an improved interface for input generation, and the addition of advanced Fortran development tools natively in the platform.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

VERAIO Software Management Plan

VERAIO is a set of utility codes used to provide a common set of input and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA HDF output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the Quality Assurance Program Plan (QAPP) (VERA-QA-001), and VERA Software Quality Assurance Plan (VERA-QA-002).

97 MATHEMATICS AND COMPUTING↗