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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77

Probing the edge states of Chern insulators using microwave impedance microscopy

Microwave impedance microscopy (MIM) has been utilized to directly visualize topological edge states in many quantum materials. While the microwave response for conventional metals and insulators can be accurately quantified using simple lumped-element circuits, whose applicability to more exotic quantum systems remain limited. In this work, we present a general theoretical framework of the MIM response of arbitrary quantum materials. Applying it to topological edge states in a Chern insulator predicts an enhanced MIM response at the crystal boundaries due to collective edge magnetoplasmon (EMP) excitations. The unique resonance frequency of these plasmonic modes allows one to disentangle the signatures of topological versus trivial edge states. To benchmark our analytical predictions, we experimentally probe the MIM response of quantum anomalous Hall edge states in a Cr-doped (Bi,Sb) 2 Te 3 topological insulator and perform numerical simulations using a classical formulation of the EMP modes based on this realistic tip-sample geometry, both of which yield results consistent with our theoretical picture. Here we also show how the technique of MIM can be used to quantitatively extract the topological invariant of a Chern insulator and shed light on the microscopic nature of dissipation along the crystal boundaries.

36 MATERIALS SCIENCE↗

Visualizing effective potentials and using the IBM-Q to study quantum field theory models in 0+1 dimensions

This work explores the utility of two novel techniques applied to studying quantum field theory, namely quantum computing and visualizing effective potentials. We studied the ground state properties of the anharmonic oscillator and the Wess-Zumino model using the variational quantum eigensolver algorithm. We performed calculations for three and four qubit systems using IBM’s open source quantum computing simulation software. Using effective potentials, we study a simple dark mat-ter system with a Higgs and dark Higgs like particle interacting through a porthole fermion.

97 MATHEMATICS AND COMPUTING↗

Battery Lifecycle Framework

The Battery Lifecycle (BLC) Framework is an open-source platform that provides tools to visualize and share battery data from material characterization, cell testing, manufacturing, and field testing through the technology development cycle. BLC has three components: data importers, a front-end for querying the data and creating visualizations, and an application programming interface to provide access to the data from Python. BLC has been deployed for tracking the development of a battery from the lab to a manufacturing line and systems installed in the field and for comparing studies of multiple cells of the same battery chemistry and configuration. The code was developed around Redash, a robust open-source extract-transform-load engine. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4546 O

De Angelis, Valerio↗

Collection And Analysis Of Telemetry For The Cyote Heuristic

CATCH CLI focuses on gathering telemetry data, storing it in the Neo4j database, querying for Mitre ATT&CK patterns, and creating STIX 2.1 reports. Key Components: Analysis Modules: Analyze data to detect attack patterns. GoSTOTS Collection Engines: Collect telemetry data. These tools can be used together or individually. Analysis modules rely on data from specific engines to identify attack patterns. Source Code Organization: Engines: CATCH/catch/cmd/collection Modules: CATCH/catch/cmd/analysis CGUI Overview CATCH Graphical User Interface (CGUI) offers a graphical shell to execute CATCH CLI, allowing easy editing of: Analysis Modules Database configurations Profiles (collection and device settings) Neo4j Overview Neo4j is a graph database using the Cypher query language, storing data in JSON. It seamlessly integrates with STIX 2.1 data for: Data Submission: CATCH Collection Engines Data Querying: Analysis Modules CATCH modifies STIX 2.1 data for Neo4j submission and reverts it back during querying. STIG Overview Structured Threat Intelligence Graph (STIG) is a tool for creating, editing, querying, analyzing, and visualizing threat intelligence using STIX 2.1 and storing data in Neo4j. Usage Tools can be run: Manually (CLI): Refer to CATCH documentation User Interface: Run ./cgui/CGUI or go run ./cgui/ Additional Information Logging System: Detailed in the config documentation Further Documentation: Available for CATCH and CGUI

Madsen, MichaelJ. [Idaho National Laboratory (INL)↗

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↗

Distributed Resources for the Earth System Grid Advanced Management (DREAM). Final Report

The DREAM project was funded more than 3 years ago to design and implement a next generation ESGF (Earth System Grid Federation) architecture which would be suitable for managing and accessing data and services resources on a distributed and scalable environment. In particular, the project intended to focus on the computing and visualization capabilities of the stack, which at the time were rather primitive. At the beginning, the team had the general notion that a better ESGF architecture could be built by modularizing each component, and redefining its interaction with other components by defining and exposing a well defined API. Although this was still the high level principle that guided the work, the DREAM project was able to accomplish its goals by leveraging new practices in IT that started just about 3 or 4 years ago: the advent of containerization technologies (specifically, Docker), the development of frameworks to manage containers at scale (Docker Swarm and Kubernetes), and their application to the commercial Cloud. Thanks to these new technologies, DREAM was able to improve the ESGF architecture (including its computing and visualization services) to a level of deployability and scalability beyond the original expectations.

54 ENVIRONMENTAL SCIENCES↗

TCF-20-20213: Advanced Power Distribution Sensing and Communications through the Cable TV Broadband Network (Final Report. Period of Performance: June 2020 to June 2022)

To enable the rapid, widespread commercial availability of secondary distribution grid voltage and phase angle data, the DOE OE Technology Commercialization Fund (TCF) project: 1) created a new American National Standard for next-generation grid power quality sensing and communications, 2) created a new prototype broadband-based standard-compliant grid power sensing system for use by utilities and others, and 3) improved by several orders of magnitude the spatiotemporal scale of the in-progress DOE CESER project: Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Characteristics of a Reacting Jet-in-Crossflow at Elevated Pressures

Flow behavior of a reacting methane jet injected normal to a lean vitiated crossflow (RJIC) is experimentally characterized using a high pressure axial staged facility. The focus of this investigation is to analyze the flow dynamic of the reacting jet as it interacts with a lean vitiated crossflow at 5atm by examining several reacting jet conditions varying the momentum flux ratio (J) and the equivalence ratio (Φ∞) of the vitiated crossflow. Vitiated crossflow temperatures ranged from 1675K to 1825K, to simulate operate conditions of a practical combustor system. The global equivalent ratio (Φ∞) at the headend of the facility ranged from 0.57 to 0.70 to attain the desired engine temperatures. RJIC flow dynamics were characterized utilizing measurements acquired from flow visualization techniques such as OH* chemiluminescence.

03 NATURAL GAS↗

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

Carbon capture and storage (CCS) is one approach being studied by the U.S. Department of Energy to help mitigate global warming. The process involves capturing CO 2 emissions from industrial sources and permanently storing them in deep geologic formations (storage reservoirs). However, CCS projects generally target “green field sites,” where there is often little characterization data and therefore large uncertainty about the petrophysical properties and other geologic attributes of the storage reservoir. Consequently, ensemble-based approaches are often used to forecast multiple realizations prior to CO 2 injection to visualize a range of potential outcomes. In addition, monitoring data during injection operations are used to update the pre-injection forecasts and thereby improve agreement between forecasted and observed behavior. Thus, a system for generating accurate, timely forecasts of pressure buildup and CO 2 movement and distribution within the storage reservoir and for updating those forecasts via monitoring measurements becomes crucial. This study proposes a learning-based prediction method that can accurately and rapidly forecast spatial distribution of CO 2 concentration and pressure with uncertainty quantification without relying on traditional inverse modeling. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO 2 storage site operators with an effective tool for timely and informative decision making based on limited simulation and monitoring data.

58 GEOSCIENCES↗

CO2 Storage Site Analysis, Screening, and Resource Estimation for Cenozoic Offshore Reservoirs in the Central Gulf of Mexico

The storage potential of hydrocarbon reservoirs in the central Gulf of Mexico (GOM) makes future development of CO2 storage projects in those areas promising for secure, large-scale, and long-term storage purposes. Focusing on the producing and depleted hydrocarbon fields in the continental slope of the central GOM, this paper analyzed, assessed, and screened the producing sands and evaluated their CO2 storage potential. A live interactive CO2 storage site screening system was built in the SAS® Viya system with a broad range of screening criteria combined from published studies. This offers the users a real-time assessment of the storage sites and enables them to adjust the filters and visualize the results to determine the most suitable filter range. The CO2 storage resources of the sands were estimated using a volumetric equation and the correlation developed by the National Energy Technology Laboratory (NETL). The results of this study indicate that 1.05 gigatons of CO2 storage resources are available in the developed reservoirs at the upper slope area of the central GOM. The Mississippi Canyon and Green Canyon protraction areas contain the fields with the largest storage resources.

Hu, Xitong↗

Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)

Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA breeding has mostly used visual scoring of specific traits or subjective classification into different root types. While image-based methods have been developed, translation to applied breeding is limited. This research is aimed at developing and comparing image-based RSA phenotyping methods using machine and deep learning algorithms for objective classification of 617 root images from mature alfalfa plants collected from the field to support the ongoing breeding efforts. Our results show that unsupervised machine learning tends to incorrectly classify roots into a normal distribution with most lines predicted as the intermediate root type. Encouragingly, random forest and TensorFlow-based neural networks can classify the root types into branch-type, taproot-type, and an intermediate taproot-branch type with 86% accuracy. With image augmentation, the prediction accuracy was improved to 97%. Coupling the predicted root type with its prediction probability will give breeders a confidence level for better decisions to advance the best and exclude the worst lines from their breeding program. This machine and deep learning approach enables accurate classification of the RSA phenotypes for genomic breeding of climate-resilient alfalfa.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating Light Source Color Rendition using the IES TM-30-15 Method

A system for evaluating the color rendition of light sources was recently published as IES TM-30-15 IES Method for Evaluating Light Source Color Rendition. The system includes a fidelity index (Rf) to quantify similarity to a reference illuminant, a relative-gamut index (Rg) to quantify saturation relative to a reference illuminant, and a color vector icon that visually presents information about color rendition. The calculation employs CAM02-UCS and uses a newly-developed set of reflectance functions, comprising 99 color evaluation samples (CES). The CES were down-selected from 105,000 real object samples and are uniformly distributed in color space (fairly representing different colors) and wavelength space (avoiding artificial increase of color rendition values by selective optimization).

color fidelity↗

PNNL’s Building Operations Control Center

PNNL's Building Operations Control Center (BOCC) video provides an overview of the center, its capabilities, and its objectives. The BOCC was relocated to PNNL's new 3820 Systems Engineering Building in 2015. Although a key focus of the BOCC is on monitoring and improving the operations of PNNL buildings, the center's state-of-the-art computational, software and visualization resources also have provided a platform for PNNL buildings-related research projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

City Scale Modeling with OpenStudio

Assessing the impact of energy efficiency technologies at a district or city scale is of great interest to local governments, real estate developers, utility companies, and policymakers. This paper describes a flexible framework that can be used to create and run district and city scale building energy simulations. The framework is built around the new OpenStudio City Database (CityDB). Building footprints, building height, building type, and other data can be imported from public records or other sources. Missing data can be inferred or assigned from a statistical sampling of other datasets. Once all required data is available, OpenStudio Measures are used to create starting point energy models and to model energy efficiency measures for each building. Together this framework allows a user to pose several scenarios such as 'what if 30% of the commercial retail buildings added rooftop solar' or 'what if all elementary schools converted to ground source heat pumps' and then visualize the impacts at a district or city scale. This paper focuses on modeling existing building stock using public records. However, the framework is capable of supporting the evaluation of new construction, district systems, and the use of proprietary data sources.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Localized Imaging and Mapping for Underwater Fuel Storage Basins - 18364

Current methods for inspection of spent nuclear fuel storage basins involve lowering a single camera for visual inspection of walls and other structures. We present a localized inspection solution where the images are automatically annotated by localization information and a 3D model of the inspected area is generated. The system consists of an underwater sensor pod containing a stereo pair of cameras, light source, inertial measurement unit, and a pressure sensor. The sensors are time synchronized to provide precise measurements. We describe both the sensor pod and the algorithms that keep the pod localized. Preliminary results from in-air testing of a prototype are presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Radiological Verification for the Remediation of LLRW at the Port Granby Project - 19210

The Port Granby Project is part of the Port Hope Area Initiative (PHAI) that Canadian Nuclear Laboratory (CNL) is using to manage long-term historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the urban setting of Port Hope, Ontario. Port Granby remediation scope includes constructing a new, secure long-term waste management facility (LTWMF) and supporting infrastructure and excavating and relocating LLRW and marginally contaminated soil from the Port Granby Waste Management Facility (PGWMF) which accepted waste until the 1980's to the newly constructed LTWMF. The PGWMF contains an estimated 450,000 cubic meters of LLRW deposited in unmarked and unlined trenches throughout the southern portion of the site that borders Lake Ontario. Project requirements include excavating contaminated material, verifying that the trench bottoms are below action levels using Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance, and final restoration. This paper describes challenges of meeting remediation verification requirements using traditional field and laboratory confirmation methods in areas of deep trench areas located in rugged terrain with ponded water and mud and presents a process that has expedited the traditional MARSSIM method for verification with greater productivity, and with enhanced safety and reliability as compared to the use of traditional methods alone. This enhanced process has been successfully employed for in-situ verification so that the excavated area can be backfilled and returned to a vegetative state. This enhanced process has been examined by federal regulatory staff through the course of their onsite audits and outcomes from these examinations have all been positive. The method involves a visual inspection and traditional walkover of the area to identify any areas with radiation measurements above the region's background followed by a full area survey performed using Wood's proprietary Orion ScanPlotSM system. The ScanPlotSM data is evaluated, mapped and overlaid on top of an aerial image of the surveyed area allowing remaining radiological material at surface or near surface to be quickly and easily identified for removal. Field staff then collect soil samples from evenly distributed points within the surveyed area and field screen the samples using an X-ray fluorescence (XRF) analysis for the three primary contaminates of potential concern (CoPCs) (arsenic, uranium and lead) that are indicative of the historical contamination. Samples passing XRF field screening are packaged and sent to a local laboratory for a full suite of analyses and checked against the CoPC list to assess whether the soil matches the profile for nearby native soils and passes the remediation goals. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

GUIDE: A Scalable Information Directory Service to Collect, Federate, and Analyze Logs for Operational Insights into a Leadership HPC Facility

In this paper, we describe the GUIDE framework to collect, federate, and analyze log data from the Oak Ridge Leadership Computing Facility's (OLCF), and how we use it derive insights into center operations. We collectsystem logs and extract monitoring data at every level of the various OLCF subsystems, and have developed a suite of pre-processing tools to make the raw data consumable. The cleansed logs are then ingested and federated into a central, scalable data warehouse, Splunk, that offers storage, indexing, querying, and visualization capabilities. We have further developed and deployed a set of analytics tools to analyze these multiple disparate log streams in concert, and derive operational insights. We describe our experience from developing and deploying the GUIDE infrastructure, and deriving valuable insights on the various subsystems, based on two years of operations in the production OLCF environment.

Vazhkudai, Sudharshan↗

Microreactor Automated Control System - Digital Twin Models and Advanced Control Systems Updates

Automation of control systems is expected to be important in the economic and safe operation of microreactors. Therefore, there is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a nonnuclear microreactor automated control system (MACS)—a real-time, hardware-in-the-loop testbed for non-nuclear testing of microreactor control system automation. A real-time hardware-in-the-loop testbed incorporates the realistic dynamics of physical systems into control system development and testing. The collaborative effort between Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL) resulted in the development of a prototypic microreactor plant-level digital twin that includes the reactor and a balance of plant system. Advanced control strategies were incorporated to demonstrate testing of control automation solutions. The gRPC communication protocol, which was implemented in the hardware-in-the-loop testbed by INL, was coupled to a digital twin model developed using the TRANsient Simulation Framework of Reconfigurable Models (TRANSFORM) library in Modelica. This digital twin simulation was tested with the ViBRANT hardware for realistic feedback and visual representation of control action in real time. A modular Python client structure was developed to manage functional mock-up unit-based simulation and real-time gRPC communication. Hardware-in-the-loop testing indicated that the modeled reactor—a natural-convection, molten-salt coolant loop configuration—responds well to control of drum positioning for modulation of reactor core power, as well as system-level control and downstream demand changes. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗