Defense of Supervised and Unsupervised Machine Learning Models
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Neutron scattering experiments have undergone significant technological development through large area detectors with concurrent enhancements in neutron transport and electronic functionality. Data collected for neutron events include detector pixel location in 3D, time and associated metadata, such as, sample orientation, neutron wavelength, and environmental conditions. RadiaSoft and Oak Ridge National Laboratory personnel are considering single-crystal diffraction data from the TOPAZ instrument. We are leveraging a new method for rapid, interactive analysis of neutron data using NVIDIA’s IndeX 3D volumetric visualization framework. We have implemented machine learning techniques to automatically identify Bragg peaks and separate them from diffuse backgrounds and analyze the crystalline lattice parameters for further analysis. The implementation of automatic peak identification into IndeX allows scientists to visualize and analyze data in real-time. Our methods include a robust comparison with current analysis techniques which show improvement in a variety of aspects. These improvements will be incorporated into IndeX for visualization to allow scientists an interactive tool for crystal analysis.
Heliostat optical errors can account for significant losses in efficiency of power tower concentrating solar power (CSP) plants. Accurately measuring heliostat optical errors can help to improve plant performance. A Non-Intrusive Optical (NIO) method has been developed to efficiently measure heliostat optical errors from UAS collected images of the mirror surface reflection [1]–[3]. In some cases, plant data of heliostat geometry can be incomplete or contain inaccuracies, in which case field collected data can be used to detect and correct uncertainties, which is valuable information for plant operators.
Various embodiments described herein provide for a terrain-aided location determination using a range/angle radar altimetry. Range/angle radar systems use vertical synthetic aperture radar measurements which do not include any cross-track resolution, such that if a range/Doppler cloud from a single VSAR image is compared to a regular DEM, there can be ambiguity in determining the cross-track position. By modifying the DEM to inherently include additional terrain signature information that could be compared to VSAR measurement, the limitation can be overcome, and a single range/angle radar system can provide an accurate position without the additional complexity of a range/angle/angle radar system.
A surface-launched acoustic wave sensor tag system for remotely sensing and/or providing identification information using sets of surface acoustic wave (SAW) sensor tag devices is characterized by acoustic wave device embodiments that include coding and other diversity techniques to produce groups of sensors that interact minimally, reducing or alleviating code collision problems typical of prior art coded SAW sensors and tags, and specific device embodiments of said coded SAW sensor tags and systems. These sensor/tag devices operate in a system which consists of one or more uniquely identifiable sensor/tag devices and a wireless interrogator. The sensor device incorporates an antenna for receiving incident RF energy and re-radiating the tag identification information and the sensor measured parameter(s). Since there is no power source in or connected to the sensor, it is a passive sensor. The device is wirelessly interrogated by the interrogator.
The University of Bristol's South West Nuclear Hub is part of two large UK academic research collaborations aiming to reduce the costs of nuclear power by trialing innovative solutions to major decommissioning challenges. Robotics and Artificial Intelligence in Nuclear (RAIN) and the National Centre for Nuclear Robotics (NCNR) are the two collaborations tasked by the UK research councils to coordinate this activity, for the benefit of the nuclear industry. This paper presents a summary of Bristol's research aimed at generating and demonstrating a series of technologies ready for commercialization. (authors)
Various factors that support an evaluation of the relative costs, advantages and disadvantages of utilizing an onsite laboratory or an offsite laboratory for remediation of Formerly Utilized Sites Remedial Action Program (FUSRAP) sites contaminated with radionuclides and metals are presented. In terms of how much more quickly an onsite laboratory provides results versus an offsite laboratory, the results of this study provide tools for calculating the amount of cost savings per day for excavation of contaminated soils for various scenarios including: - State, municipal or local property remediation where the remediation schedule becomes time-critical due to the extra cost and inconvenience to the town or municipality caused by the need for increased security and safety personnel, possible road closures and detours, and the inconvenience to the public due to modified or decreased services of State or municipal facilities; - Residential property where the remediation schedule becomes time-critical due to the inconvenience to the homeowner as well as the importance of maintaining good community relations; - Commercial property where the remediation schedule becomes time-critical due to the hardship and potential loss of revenue endured by the property owner; - Open area where treatment of excavation water is required, and - Open area where treatment of excavation water is not required. For every scenario, the number of matrices, radionuclide and metal contaminants of concern and the project duration are important factors. The costs for the onsite laboratory included the capital costs associated with setting up the lab such as trailer(s) or building(s), power and water hookup, analytical testing equipment, balances, computers, desks and bookcases; support equipment such as hot plates, filtration assemblies, safety equipment, ovens, etc.; and supplies such as glassware, pipettes, filters, etc. and ongoing costs such as labor, chemicals and reagents, standards, cost of the laboratory obtaining certification and maintenance. Offsite laboratory sample testing costs are generally very competitive and typically substantially lower than onsite laboratory costs if only the sample testing costs are considered. The great disadvantage of using an offsite laboratory is that they often cannot guarantee rapid turnaround times for results which creates project delays associated with the remediation process including delays determining the completeness of the characterization and remediation processes, delays in backfilling a property and additional costs for treating wastewater (excavation water, stormwater or both). These costs will vary greatly depending upon the area of the country in which the project is located due to the wide range of labor costs for the onsite laboratory and field workers, as well as the contaminants of interest, matrices and most importantly the size of the impacted area and the number of properties located in that area. This paper provides guidelines for calculating the cost savings that may be realized if an onsite laboratory can generate results more quickly than an offsite laboratory by estimating the costs associated with the remediation process for the various scenarios noted above such as work crew labor costs, excavator and dump truck equipment rentals, wastewater treatment costs (if applicable) and the additional costs incurred by homeowners, commercial property owners and towns/municipalities that are reimbursed by the potentially responsible parties. Key assumptions involve the typical quickest turnaround time provided by the onsite and offsite laboratories. Costs for the operation of a wastewater treatment system and the remediation of a site area or property were provided by personnel who have been involved in the operation of a large FUSRAP site in New Jersey for many years. This study provides valuable information for determining the most cost-effective approach for analysis of project samples and therefore may be used on upcoming FUSRAP projects. (authors)
Synchrophasor technology is widely deployed in the energy management system to monitor the grid health at micro level and perform necessary corrective actions in real time; however, integrated phasor devices and data aggregators are exposed to several cybersecurity threats. This paper proposes a federated ML(FML)-based ADS to detect several data integrity attacks in the synchrophasor network. The proposed approach integrates the horizontal FML technique and consists of substation-based local models and a control center-based global model. The proposed methodology includes training local models using heterogeneous data sets that include network and grid information and updating the global model through multiple iterations by sharing model gradients. Finally, the trained global model is applied to identify cyberattacks, normal operation, and physical events. To validate the proof of concept, we used synthetic data sets generated by Mississippi State University and Oak Ridge National Laboratory for training and testing the classification models using the National Renewable Energy Laboratory's high performance computing resources. Our experimental results, computed through several performance measures, reveal that the proposed approach shows consistent performance during the binary, three-class, and multiclass classifications while ensuring privacy of synchrophasor data.
Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the Pennsylvania-New Jersey-Maryland Interconnection (PJM), in a competitive electricity market. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure and vulnerable communication networks to a multitude of cybersecurity threats. These evolving threats not only endanger grid operations but also have the potential to trigger cascading disruptions across the broader grid network and influence regulation markets. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events and provide a comprehensive situation awareness to grid operators. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a fully active BESS topology using the slow regulation signal (Reg A) coming from the PJM market. Our simulation results reveal that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's instability and economic loss during the participation of hydropower and BESS in the regulation market.
Headstarting efforts are thought to be critical in supplementing populations of the at-risk Gopher Frog (Rana capito); however, recent efforts have occasionally resulted in juveniles with developmental abnormalities. In response, we developed a scoring system to collect quantitative data on the presence and severity of these developmental abnormalities. Our objective was to describe and validate the abnormality scoring system so that it can be used by all Gopher Frog headstarting facilities. The scoring system covers five primary conditions encompassing commonly observed abnormalities. Two groups of participants with different levels of prior experience working with Gopher Frogs assigned scores to a set of images presented to them for each condition. We used intra-class correlation coefficients (ICC) to test the scoring system for inter- and intra-rater agreement as well as agreement with the benchmark standard (established by the authors). We found high ICC values for inter-rater agreement, intra-rater agreement, and agreement to the benchmark standard indicating either excellent or good reliability for all five conditions and for all raters when grouped together. These findings support the reliability and validity of the proposed developmental abnormality scoring system. Gopher Frog headstarting facilities can implement this scoring system to assist in tracking the frequency and severity of abnormalities observed in future headstarting efforts. We hope that by creating a reliable scoring system for Gopher Frogs, it can provide an overall framework and serve as a valuable resource to evaluate abnormalities across any amphibian species.
The Neutronics Group of the Second Target Station project at Oak Ridge National Laboratory is responsible for all neutronics analyses related to design and construction. This paper provides an overview of four neutronics analyses performed for the Second Target Station project, which is representative of all the ongoing work but especially tasks related to shielding. These analyses extend from the proton accelerator through the target monolith and bunker to the end of a neutron beamline. Each example highlights the tools and methods the Neutronics Group uses for analysis. The primary tool is the Monte Carlo radiation transport code MCNP 6.2, but this is augmented by other codes that supplement the input of MCNP. The other codes specifically highlighted in this paper include Attila4MC, ADVANTG, and AARE.
Stainless steels are widely used as primary piping material in PWR’s because of their high corrosion resistance largely due to the formation of a passive film of metal oxides, such as chromium (e.g., Cr2O3). However, upon exposure to aggressive ions like chlorides (Cl-), stainless steel becomes susceptible to localized corrosion due to the breakdown of the passive film. It is therefore essential to gain fundamental insights into the mechanism of the passive film breakdown (depassivation) to develop a tailored design to minimize localized corrosion. This project investigates the initial stages of the depassivation of the Cr passive film using density functional theory (DFT), a quantum based computational method.
In this poster the Rubin Observatory's Community Science team (CST) presents its current suite of tutorials, which are designed to help people make use of simulated data sets in preparation for the upcoming Legacy Survey of Space and Time (LSST). We will show examples of the tutorial contents, provide custom learning modules for different astronomical fields, and describe the online environment for data analysis (the Rubin Science Platform; RSP). We will also supply a checklist for how to obtain an RSP account and access the tutorials. All are welcome to drop by the poster or the Rubin booth in the exhibit hall with questions.
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Electric-field assisted sintering (EFAS) manufacturing techniques reduce energy usage requirements, fabricate near-net-shape parts, and produce bulk nanostructured materials through rapid heating and cooling rates achievable through Joule heating. Process parameters of pulsed DC voltage and constant pressure are applied through stainless steel rams and graphite tooling to the ceramic yttrium oxide powder to be sintered. Our high-fidelity modeling code application advances manufacturing for extreme environments by enabling process-informed design and improving microstructure consistency through multiphysics multiscale process-structure-property-performance correlation simulations.
Since 2021, NREL has been developing a system to measure heliostats by measuring the deflection of printed computer vision targets, called the Reflected Target Non-intrusive Assessment (ReTNA) [6], [7]. While this system will have lower resolution than a fringe deflectometry system, it has several important advantages that make it a complimentary technology: 2D surface slope measurement can be generated from a single image, it can operate in ambient lighting, target points can be directly located in 3D space with photogrammetry allowing for a non-flat target, and it's well suited to using a smaller target, and multiple images to measure larger optical surfaces. ReTNA has undergone several significant changes and improvements, described below. This talk will summarize new system layouts designed for commercial use, new computer vision algorithms used to automate the analysis process and validation campaigns for the ReTNA software.
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A powered building system that includes an electric power distribution system configured to distribute electrical power to a plurality of receptacles; one or more load sources; and one or more battery systems associated with: a respective receptacle of the plurality of receptacles and a respective load source of the one or more load sources.