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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluating the Effectiveness of a Detection and Deterrent System in Reducing Golden Eagle Fatalities at Operational Wind Facilities

The Renewable Energy Wildlife Institute (REWI) was appointed as the prime awardee of DOE award number DE-EE0007883 to lead a team of scientists, wind developers, and technology manufacturers toward the overarching goal of evaluating the effectiveness of the current DTBird system in minimizing the risk of golden eagles (Aquila chrysaetos) and other large soaring raptors from approaching the rotor-swept zone (RSZ) of operating wind turbines. As part of this goal, the team set out to 1) quantify the expected reduction in collision risk for golden eagles from operation of the detection and deterrence modules in a manner that supports the approach used by the U.S. Fish and Wildlife Service (USFWS) to assess and credit facility operators for their efforts to minimize predicted collision fatalities and 2) provide information to help improve the technology to maximize its effectiveness. DTBird is an automated detection and audio deterrent system created by the Spanish company Liquen, designed to discourage birds from entering the RSZ of spinning wind turbines. The system uses cameras to automatically detect airborne targets of interest, records each such event in an online database, and triggers a warning signal (loud sound) if the tracked object has moved close to the turbine. If the object moves even closer to the RSZ, a more aggressive dissuasion signal is broadcast. To meet our objectives, the team conducted a two-year experiment at the Goodnoe Hills wind facility in Washington state, in which 14 turbines were outfitted with DTBird units. Daily, each DTBird-equipped turbine was randomly assigned to a control or treatment group. Treatment turbines operated with DTBird running as intended—broadcasting warning or deterrent signals when DTBird detected a target within range. On control turbines, no sound signals were broadcast if a moving target triggered the DTBird system. The team also flew unmanned aerial vehicles (UAVs) designed to coarsely mimic the general size, weight, and coloration of golden eagles in programmed flight transects across DTBird detection ranges to quantify DTBird’s ability to detect intended targets and to evaluate factors that influence the probability of detection and DTBird’s response distances. Additionally, the team evaluated the behavioral responses of in situ eagles exposed to spinning turbines alone (visual and sound influences) versus spinning turbines plus broadcasted DTBird audio deterrents, to estimate the effectiveness of deterrence by the DTBird system. The data and results from these investigations were combined with those from a pilot study conducted at the Manzana Wind Power Project in California to better evaluate DTBird’s effectiveness across different landscapes.

17 WIND ENERGY↗
DOE OSTI2013

Overview of Scale 6.2

SCALE is an industry-leading suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a plug-and-play framework that includes three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 provides several new capabilities and significant improvements in many existing features, especially with expanded CE Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. A brief overview of SCALE capabilities is provided with emphasis on new features for SCALE 6.2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Enhancements in Continuous-Energy Monte Carlo Capabilities for SCALE 6.2

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, industry, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a plug-and-play framework that includes three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 provides several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, sensitivity and uncertainty analysis, and improved fidelity in nuclear data libraries. A brief overview of SCALE capabilities is provided with emphasis on new features for SCALE 6.2.

Continuous-Energy↗
DOE OSTI2014

Tessera: Open source software for accelerated data science

Extracting useful, actionable information from data can be a formidable challenge for the safeguards, nonproliferation, and arms control verification communities. Data scientists are often on the “front-lines” of making sense of complex and large datasets. They require flexible tools that make it easy to rapidly reformat large datasets, interactively explore and visualize data, develop statistical algorithms, and validate their approaches—and they need to perform these activities with minimal lines of code. Existing commercial software solutions often lack extensibility and the flexibility required to address the nuances of the demanding and dynamic environments where data scientists work. To address this need, Pacific Northwest National Laboratory developed Tessera, an open source software suite designed to enable data scientists to interactively perform their craft at the terabyte scale. Tessera automatically manages the complicated tasks of distributed storage and computation, empowering data scientists to do what they do best: tackling critical research and mission objectives by deriving insight from data. We illustrate the use of Tessera with an example analysis of computer network data.

Sego, Landon H.↗
DOE OSTI2018

Sensing and Sampling of Trace Contaminations by a Dexterous Hexrotor UAV at Nuclear Facilities - 18600

Safe and efficient cleanups are a priority for decontamination and decommissioning of nuclear facilities. The contaminations of byproducts and wastes in such nuclear facilities pose a serious problems while decommissioning, to both the operators and public. Sensing these contaminations and cleaning them is an essential part of the safety procedures. The contaminations might range from low-energy to high-energy byproducts. Sensing these byproducts would require contact based or non-contact based sensing, based on its energy levels. Byproducts such as americium, are low-energy which makes it difficult to sense and sample without contact. Therefore, the workers need to physically swab the surfaces to collect the samples of these contaminations. These tasks pose a great danger for the safety of the human workers which includes the risk to reach greater heights, exposure to the radiation and sampling the entire building. A robotic solution is much more desirable in these cases, where the worker can safely handle the contaminations from a safe area. Use of robotic technologies inside these hazardous environments ensures the safety and enhances the performance. The more suitable robotic solution for reaching great heights and covering large areas of nuclear facilities, are aerial vehicles. Multi-rotor unmanned aerial vehicle (UAV) are chosen for their ability to hover at a position and also fly around in confined spaces. Quadrotors are a common choice of multi-rotor UAVs both research and industry because of its ease to fly and commercial availability. For the applications during the cleanups we need the UAV to not only hover and fly in confined spaces, but also interact with the physical world. Despite of quadrotor's advantages, they are not a best suit as they can't interact with the physical world. The tasks involving physical interactions would require the UAV to apply arbitrary forces and torques in all six degrees of freedom (DOF). As quadrotors are under-actuated and non-holonomic in motion, they cannot exert all the required forces. At Collaborative Robotics Lab, Purdue University, we developed a novel multi-rotor UAV solution, Dexterous Hexrotor, which can exert arbitrary forces and torques in all six DOF, independently and instantaneously. This enables the UAV platform to quickly respond to the external disturbances and precisely hold its position during the mission. The Dexterous Hexrotor serves as a robotic tool for the workers to perform sensing and sampling during the cleanups. Workers can operate Dexterous Hexrotor manually and/or semi-autonomously with human intervention. Manual control requires the worker to fly the Dexterous Hexrotor using a remote control. So the workers should possess knowledge on flying the UAV and to perform physical interaction. A semiautonomous Dexterous Hexrotor requires human input to some extent and requires very less knowledge of flying. The autonomy is designed to operate in flight mode and sampling mode. In flight mode, Dexterous Hexrotor takes off from a 'safe' area, reaches the desired altitude, and fly autonomously towards a sampling point. This sampling point is the target position specified on the 2D reference map. This mode also includes navigation towards the sampling point, avoiding the obstacles in the constrained environment. After reaching a stopping point, Dexterous Hexrotor waits for the human input for a target location to swab and collect samples. The Dexterous Hexrotor is now in sampling mode and waits for the human input. The human operator selects the swabbing location through the live streaming video from onboard camera. Through visual servoing, aided by the map, the UAV will move closer towards the target position. It then transitions to the impact control scheme to perform physical interaction with the wall and collects samples. Once the sample is collected, it autonomously returns back to the takeoff position in 'safe' area for the analysis by mass spectrometry. In this paper, we majorly focus on the physical interaction strategy and the required components which enables the autonomy. Decommissioning of nuclear facilities requires decontamination inside the entire buildings. Decontamination of nuclear facilities involves sensing and sampling the huge buildings, long shafts, etc. Sampling the entire facility is not possible due to the limitation in Dexterous Hexrotor's flight time. But this can be achieved by using a swarm of Dexterous Hexrotors to cover larger areas. The onboard robotic arm can be designed based on the applications such as cleaning, applying sealants, etc. The modularity of the design allows us to switch components as per the requirements of the task. These kind of robotic solutions functioning as tools for the workers, aims to make the work environment safer and playful. (authors)

42 ENGINEERING↗
DOE OSTI2022

Design of a Combined Proportional Integral Derivative Controller to Regulate the Temperature Inside a High-Temperature Tubular Solar Reactor

Solar fuels are proven to be promising candidates for thermochemical energy storage. However, the transient nature of solar radiation is an obstacle to maintaining a stable operational temperature inside a solar reactor. To overcome this challenge, the temperature of a solar reactor can be regulated by controlling the incoming solar radiation or the feedstock flowrate inside the reactor. In this work, a combined proportional integral derivative (PID) controller is implemented to regulate the temperature inside a high-temperature tubular solar reactor with counter-current flowing gas/particles. The control model incorporates two control systems to regulate incoming solar radiation and gas flow simultaneously. The design of the controller is based on a reduced-order numerical model of a high-temperature tubular solar reactor that is vertically oriented with an upward gas flow and downward particle flow. The reactor receives heat circumferentially through its wall over a finite segment of its length. Formulation of the heat transfer model is presented by applying the energy balance for the reactor tube and considering heat and mass transfer inside. A set of governing differential equations are solved numerically by using the finite volume method to obtain reactor wall, particles, and gas temperatures along the reactor length with various boundary conditions. Simulation results are used to tune the PID controller parameters by utilizing the Ziegler–Nichols tuning method. Both the simulation results and the controller performance are visualized on the LABVIEW platform. The controller is challenged to track different temperature setpoints with different scenarios of transient solar radiation. Here, the performance of the PID controller was compared to experimental results obtained from an industrial PID controller embedded in a 7 kW electric furnace. Results show that the combined PID controller is successful in maintaining a stable temperature inside the reactor by regulating the incoming solar radiation and the flowrate via small steady-state error and reasonable settling time and overshoot.

14 SOLAR ENERGY↗
DOE OSTI2026

Guideline for Characterizing and Evaluating a Candidate Project Site for Solar Thermal Applications

This document presents a structured procedure for characterizing and evaluating candidate project sites for concentrating solar power (CSP) and solar heat for industrial processes (SHIP) applications. The objective is to provide project developers, researchers, and other stakeholders with a consistent, technology-agnostic framework for early-stage site assessment, enabling informed decision-making prior to significant investment in project development. Site selection is a critical factor in project success or failure for both CSP and SHIP projects. Key factors such as solar resource availability, land characteristics, environmental and regulatory constraints, infrastructure availability, and community context are determined by the choice of project site and can materially impact project performance, cost, schedule, and overall viability. This procedure is designed to systematically evaluate these factors, identify potential fatal flaws, and prioritize the most favorable candidate sites for further development. The process begins with rapid screening-level evaluation, using publicly available data to assess solar resource, land availability and suitability, zoning and land-use compatibility, and exclusion zones such as protected lands or sensitive habitats. Sites that meet the minimum screening criteria advance to a more detailed characterization. Subsequent sections of this report provide guidance for a next-level assessment of the most important technical and environmental parameters, including: 1) Solar resource quality, variability, and uncertainty using multiyear datasets and, where appropriate, on-site measurement campaigns; 2) Meteorological conditions such as wind, temperature, extreme weather events, and soiling impacts; 3) Land characteristics including slope, shading, and geotechnical conditions; and 4) Environmental and regulatory considerations, including permitting processes, endangered species, cultural resources, and visual impacts. The procedure also addresses infrastructure and integration considerations, including: 1) Grid interconnection requirements for CSP power generation projects; 2) Electrical and operational integration for SHIP facilities; 3) Water availability, quality, and permitting constraints, which are particularly critical for CSP in arid regions; and 4) Site access, construction logistics, and availability of workforce and supporting services. Recognizing the importance of social and economic context, the procedure includes evaluation of community engagement factors, such as stakeholder sentiment, proximity to sensitive visual receptors, workforce development opportunities, and local economic incentives. The outputs of these assessments are synthesized in a cost and risk evaluation, translating site characteristics into expected impacts on capital cost, operating cost, schedule, and technical risk. This is complemented by screening-level performance modeling, including 8760 simulations and long-term projections, to quantify expected energy or thermal output, assess variability thereof, and support comparison between candidate sites. Finally, the procedure provides high-level guidance on a structured go/no-go decision framework, categorizing sites based on identified risks and constraints, and outlining a clear path forward to feasibility studies and front-end engineering design for viable projects. By standardizing the site characterization process across both CSP and SHIP applications, this guideline aims to: 1) Improve consistency and transparency in early-stage project evaluation; 2) Reduce development risk and avoid investment in nonviable project sites; 3) Support collaboration between developers, researchers, and public agencies; and 4) Accelerate successful deployment of concentrating solar technologies for both power generation and industrial process heat.

14 SOLAR ENERGY↗
DOE OSTI2013

A technical framework to describe occupant behavior for building energy simulations

Green buildings that fail to meet expected design performance criteria indicate that technology alone does not guarantee high performance. Human influences are quite often simplified and ignored in the design, construction, and operation of buildings. Energy-conscious human behavior has been demonstrated to be a significant positive factor for improving the indoor environment while reducing the energy use of buildings. In our study we developed a new technical framework to describe energy-related human behavior in buildings. The energy-related behavior includes accounting for individuals and groups of occupants and their interactions with building energy services systems, appliances and facilities. The technical framework consists of four key components: i. the drivers behind energy-related occupant behavior, which are biological, societal, environmental, physical, and economical in nature ii. the needs of the occupants are based on satisfying criteria that are either physical (e.g. thermal, visual and acoustic comfort) or non-physical (e.g. entertainment, privacy, and social reward) iii. the actions that building occupants perform when their needs are not fulfilled iv. the systems with which an occupant can interact to satisfy their needs The technical framework aims to provide a standardized description of a complete set of human energy-related behaviors in the form of an XML schema. For each type of behavior (e.g., occupants opening/closing windows, switching on/off lights etc.) we identify a set of common behaviors based on a literature review, survey data, and our own field study and analysis. Stochastic models are adopted or developed for each type of behavior to enable the evaluation of the impact of human behavior on energy use in buildings, during either the design or operation phase. We will also demonstrate the use of the technical framework in assessing the impact of occupancy behavior on energy saving technologies. The technical framework presented is part of our human behavior research, a 5-year program under the U.S. - China Clean Energy Research Center for Building Energy Efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Multiphysics modeling of printed surface acoustic wave thermometers

Surface acoustic wave (SAW) transducers are a class of sensors and actuators that operate on the fundamental principle of piezoelectricity. Aerosol jet printing and other additive manufacturing techniques have resulted in the low-cost fabrication of low-power and small-footprint SAW devices that are suitable for sensing in high-temperature and radioactive environments. In this work, we developed a series of temperature-dependent finite element models for a SAW transducer consisting of printed silver interdigitated transducers (IDTs) deposited onto piezoelectric lithium niobate. Modeling accuracy was evaluated experimentally from room temperature to 200 °C using an aerosol-jet-printed SAW thermometer. A time-domain study enabled visualization of the wave propagation and successfully guided the denoising of the scattering parameter measurement. Additionally, frequency-domain models using traditional modal analysis or the unique port boundary condition feature in COMSOL Multiphysics accurately predicted the temperature-driven natural frequency drift in the SAW thermometer. The finite element models developed in this study serve to facilitate the computer-aided design of future SAW transducers for applications in harsh environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Design, characterization, and fabrication of solar-retroreflective cool-wall materials

Raising urban albedo increases the fraction of incident sunlight returned to outer space, cooling cities and their buildings. We evaluated the angular distribution of solar radiation incident on exterior walls in 17 U S. climates to develop performance parameters for solar-retroreflective walls, then applied first-principle physics and ray-tracing simulations to explore designs. Our analysis indicates that retroreflective walls must function at large incidence angles to reflect a substantial portion of summer sunlight, and that this will be difficult to attain with materials that rely on total internal reflection. Gonio-spectrophotometer measurements of the solar spectral bi-directional reflectivity of a bicycle reflector showed little to no retroreflection at large incidence angles. Visual comparisons of retroreflection to specular first-surface reflection for four different retroreflective safety films using violet and green lasers suggest their retroreflection to be no greater than 0.09 at incidence angles up to 45°, and no greater than 0.30 at incidence angles of up to 70°. Attempts to produce a two-surface retroreflector with orthogonal mirror grooves by cutting and polishing an aluminum block indicate that residual surface roughness impedes retroreflection. Ongoing efforts focus on forming orthogonal surfaces with aluminized Mylar film, a material with very high specular reflectance across the solar spectrum. We investigated (1) folding or stamping a free film; (2) adhering the film to a pre-shaped substrate; or (3) attaching the film to a flat ductile substrate, then shaping. The latter two methods were more successful but yielded imperfect right angles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Structural, Electronic, and Electrostatic Determinants for Inhibitor Binding to Subsites S1 and S2 in SARS-CoV-2 Main Protease

Creating small-molecule antivirals specific for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins is crucial to battle coronavirus disease 2019 (COVID-19). SARS-CoV-2 main protease (Mpro) is an established drug target for the design of protease inhibitors. We performed a structure–activity relationship (SAR) study of noncovalent compounds that bind in the enzyme’s substrate-binding subsites S1 and S2, revealing structural, electronic, and electrostatic determinants of these sites. The study was guided by the X-ray/neutron structure of Mpro complexed with Mcule-5948770040 (compound 1), in which protonation states were directly visualized. Virtual reality-assisted structure analysis and small-molecule building were employed to generate analogues of 1. In vitro enzyme inhibition assays and room-temperature X-ray structures demonstrated the effect of chemical modifications on Mpro inhibition, showing that (1) maintaining correct geometry of an inhibitor’s P1 group is essential to preserve the hydrogen bond with the protonated His163; (2) a positively charged linker is preferred; and (3) subsite S2 prefers nonbulky modestly electronegative groups.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Hanford Tank Farms Waste Feed Flow Loop Phase VI: PulseEcho System Performance Evaluation

This document presents the visual and ultrasonic PulseEcho critical velocity test results obtained from the System Performance test campaign that was completed in September 2012 with the Remote Sampler Demonstration (RSD)/Waste Feed Flow Loop cold-test platform located at the Monarch test facility in Pasco, Washington. This report is intended to complement and accompany the report that will be developed by WRPS on the design of the System Performance simulant matrix, the analysis of the slurry test sample concentration and particle size distribution (PSD) data, and the design and construction of the RSD/Waste Feed Flow Loop cold-test platform.

Denslow, Kayte M.↗
DOE OSTI2018

The Case for Artificial Intelligence

The emerging era of artificial intelligence will be beneficial to society and is worth embracing, says Argonne’s Marius Stan, Program Lead for Intelligent Materials Design. Artificial intelligence is playing a significant role in defining new research methods that bring us to resolution or discovery more quickly than ever before. Argonne is using or developing many of these technologies as AI extends to new branches of science and technology, sprouting new buds that represent various facets of human function and cognition — from learning to language processing to visual recognition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Streamlining analysis capabilities for SNF management - 15490

A comprehensive, integrated data and analysis tool-the Used Nuclear Fuel-Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST and DARDS) -is being developed for the US DOE Office of Nuclear Energy (DOE-NE) Nuclear Fuels Storage and Transportation Planning Project (NFST). The overarching goal of UNF-ST and DARDS is to provide a comprehensive controlled source of technical data integrated with key analysis capabilities to characterize inputs to the overall US waste management system from reactor power production through ultimate disposition. UNF-ST and DARDS seamlessly integrates a unified SNF system relational database and key analysis capabilities to simplify and automate the performance of accurate and efficient SNF related analyses to support numerous DOE waste management and fuel cycle activities. Hence, UNF-ST and DARDS enables decision making relative to design, safety, and licensing of SNF systems and facilities by providing the best information available. Automated analysis sequences have been deployed to characterize the discharge inventory and perform criticality, thermal, and dose analyses using time-dependent data. UNF-ST and DARDS provides cask-specific as-loaded safety analysis including criticality, thermal and dose evaluations, as well as results visualization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

A histidine-rich elastin-like polypeptide functions as a quickly detectable and easily purifiable protein fusion tag

Highlights: • A HRELP fusion tag is designed and highly expressed in E. coli. • HRELP fusion tag can be specifically and quickly stained with Pauly's reagent. • HRELP fusion protein can be detected in both cell lysate and SDS-PAGE. • HRELP fusion protein can be purified by pH-triggered ITC. Although many protein fusion tags have been developed for recombinant protein production to improve protein yields or facilitate purification, determining the expression and purification of the fusion protein still remain to be a time-consuming and laborious procedure. In this work, we designed a histidine-rich elastin-like polypeptide (HRELP) fusion tag and found that it could be efficiently expressed in E. coli cells and specifically stained with Pauly's reagent in a couple of minutes post SDS-PAGE analysis. Moreover, in Pauly's reagent-stained polyacrylamide gels, only the bands of HRELP fusion proteins were yellow and could be clearly visualized with little background. Furthermore, both HRELPs and HRELP20-BMP2 fusion protein could be purified by a method of pH shift-mediated inverse transition cycling (ITC). In our opinion, the HRELP established in this study may be considered as a multifunctional protein tag which could make its fusion proteins being quickly detected by Pauly staining and simply purified by pH-triggered ITC in addition to having the potential to sustained release its fusion proteins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

Abstract Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon‐storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R‐shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision‐making.

Holmquist, James R.↗
DOE OSTI2016

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deep modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

AEGIS (Air Emissions Grouped by Industrial Sectors) [SWR-24-49]

AEGIS is a robust framework designed to build and compile emissions inventories for various industrial sectors. It integrates multiple emissions databases provided by the USEPA – including GHGRP, NEI, and TRI – and leverages the STEWI and STEWICOMBO tools to retrieve, merge, and process data. The framework produces facility- and process-level inventories, identifies discrepancies (e.g., NAICS or FRS mismatches), and performs exploratory analysis including emission concentration calculations and visualization.

Atnoorkar, Swaroop↗