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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Deep Learning for Fish Identification from Sonar Data: CRADA 481 [Abstract only]

To help solve the challenges of hydropower energy production related to the potential for eel injury and mortality from passage through hydropower turbines, we will develop a deep learning method for identifying migrating eels from imaging sonar. This project continues with a prior project conducted by the Pacific Northwest National Laboratory (PNNL) and the Electric Power Research Institute (EPRI) in FY2018-2019. The proposed method employs Convolution Neural Network (CNN), a powerful deep learning method for image classification, to distinguish between images of eels and non-eel moving objects. We propose to collect more laboratory data and add more existing field data to train a powerful deep learning model. In addition to eels and sticks as classified in previous studies, we will add images containing several non-eel fish species and macrophyte mats to the training data. A multi-class classification model will be developed to distinguish these objects. Object detection algorithm will be explored and developed to locate and identify multiple objects in each sonar frame. Motion analysis will be performed to track the movement of objects in sonar video clips. We will also improve the data conversion algorithm so that it can read in both DIDSON and ARIS (both are imaging sonars developed by Sound Metrics Corp) data files and convert them to images with comparably high resolution, regardless of the varying detection ranges in different environments. The developed algorithms will be packaged as a software with a graphic user interface. The software will be evaluated by external collaborators in the field. The developed framework can be generalized for automatic monitoring of fish passage and migration using other imaging sonars like ARIS and will benefit the design and operation of ecologically friendly hydroelectric projects. The developed wavelet and CNN model configuration parameters can potentially be transferred to lamprey detection in similar riverine environments.

13 HYDRO ENERGY↗
DOE OSTI2019

Swift-XRT Follow-up of Gravitational-wave Triggers in the Second Advanced LIGO/Virgo Observing Run

The Neil Gehrels Swift Observatory carried out prompt searches for gravitational-wave (GW) events detected by the LIGO/Virgo Collaboration (LVC) during the second observing run ("O2"). Swift performed extensive tiling of eight LVC triggers, two of which had very low false-alarm rates (GW170814 and the epochal GW170817), indicating a high confidence of being astrophysical in origin; the latter was the first GW event to have an electromagnetic counterpart detected. In this paper we describe the follow-up performed during O2 and the results of our searches. No GW electromagnetic counterparts were detected; this result is expected, as GW170817 remained the only astrophysical event containing at least one neutron star after LVC's later retraction of some events. A number of X-ray sources were detected, with the majority of identified sources being active galactic nuclei. We discuss the detection rate of transient X-ray sources and their implications in the O2 tiling searches. Finally, we describe the lessons learned during O2 and how these are being used to improve the Swift follow-up of GW events. In particular, we simulate a population of gamma-ray burst afterglows to evaluate our source ranking system's ability to differentiate them from unrelated and uncataloged X-ray sources. We find that ≈60%–70% of afterglows whose jets are oriented toward Earth will be given high rank (i.e., "interesting" designation) by the completion of our second follow-up phase (assuming that their location in the sky was observed), but that this fraction can be increased to nearly 100% by performing a third follow-up observation of sources exhibiting fading behavior.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Mini-modules made with monolithically integrated all-perovskite tandems

The objective of the project was to improve the efficiency and stability of all-perovskite tandem solar cells. Another goal was to demonstrate that a mini-module could be made using scalable methods. When the project started, there were < 10 papers on narrow band gap solar cells, so we needed to improve the chemical composition, find suitable contacts and do fundamental research to learn more about Sn-containing perovskites. We achieved > 20 % PCE and < 5 % degradation after 1000 hours under one sun illumination. We found that stability is dramatically improved by using < 50 % Sn and avoiding anything that is acidic from interacting with the Sn. For the top cell, we needed to increase the band gap and solve a problem with wrinkling due to compressive stress that arises during spin coating. We achieved > 20 % PCE and < 5 % degradation after 1000 hours under one sun illumination. It is necessary to have a recombination layer between the two solar cells. We developed an ALD process to deposit recombination layers that are excellent barriers. These barriers solved a problem associated with the first solar cell getting partially dissolved when the second solar cell is deposited. This process greatly improved the yield by reducing the density of shunts between the cells. In collaboration with other researchers at NREL, we made 25.5 % efficient tandems that maintain 80 % of their stability after 1500 hours under 0.8 sun illumination. We published manuscripts that compare options for commercializing various kinds of perovskite modules taking into account possible degradation near scribe lines, reverse bias degradation in partially shaded modules, and the ability to bin cells if singulated cells are connected by wire.

14 SOLAR ENERGY↗
DOE OSTI2022

Design, Construction, and Testing of 0.5-m, 18-mm Period Nb 3 Sn Superconducting Undulator Magnets

We report design and fabrication of a new Nb 3 Sn-based superconducting undulator (SCU) are underway at the Advanced Photon Source (APS) of Argonne National Laboratory in collaboration with Fermilab and Lawrence Berkeley National Laboratory. To develop a robust and reliable fabrication process, the magnet development consists of several steps. First, magnetic and mechanical simulations were performed to optimize the magnet design; then, the design matured further by fabricating and testing a series of very short prototypes, ~8 cm long with a period length of 18 mm. These short prototype studies were previously reported. Second, the design was scaled to an intermediate length of ~0.5 m. These two steps led to the final design of ~1.1–m-long magnets, which are currently being fabricated. The quench behavior of each 0.5-m-long undulator magnet, as well as undulator assemblies from these magnets, was studied. The first SCU magnet assembly did not meet the design specifications due to the breakdown of the insulation. With an improved design and fabrication process based on lessons learned, the second SCU assembly achieved the design undulator field of 1.2 T. The design was further optimized, and the third set of magnets was fabricated and successfully tested.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Triton Initiative: FY 2024 Communications, Outreach, and Engagement End-of-Year Report

The Department of Energy (DOE) Water Power Technologies Office (WPTO) Triton Initiative works to reduce barriers to permitting of marine energy testing and installation through environmental monitoring research that can help inform decision-makers on potential environmental effects associated with these systems. Communications, outreach, and engagement efforts are critical to Triton's success, which involves facilitating the effective communication and dissemination of environmental monitoring research information and results to end-users and fostering collaborations between researchers and industry partners to address the most pressing needs of this emerging industry. The Triton Initiative's communications, outreach, and engagement (TCOE) foundational goals are to educate and raise awareness of ME and the role of Triton's environmental monitoring research in supporting the industry, build trust with audiences through transparent communications and outreach, and evaluate and refine TCOE tactics based on feedback and metrics. The TCOE FY 2024-specific objectives were to (1) refine and grow Triton's audience network by reaching new individuals and communities within Triton's target audience base, and (2) improve the strategy and evaluation of TCOE efforts to demonstrate the value of communications and outreach for the ME community. This report presents the results and analysis of communications activities from September 1, 2023 through August 31, 2024. We assess the TCOE target audiences, highlight notable successes and lessons learned from FY2024, and identify the most effective channels and activities used to connect with those audiences to achieve the TCOE goals.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Panel Session 83: Development of the DOE Mercury Management Strategy

This panel discussion addressed the current efforts to develop an integrated strategy for managing the mercury (Hg) challenges across the DOE complex, including challenges in remediation of Hg contamination and related ongoing or planned technology development efforts across the EM complex. Panel members discussed opportunities for collaboration in defining and implementing a mercury management strategy for the various sites, national laboratories, and contractors and for all to provide technical information for DOE to develop an integrated, cost effective Hg management strategy. Emphasis of the panel was placed on challenges at the Oak Ridge Reservation and the Savannah River Site. Opening remarks were made by Ming Zhu. Ming stated that the Academy of Sciences recently released a report on the challenges of addressing Hg in the environment; the report leveraged recent remedial efforts. Presentations proposed include: 1 - Approach to Addressing Mercury at Y-12 (Brian Henry, US DOE OREM (USA)); 2 - Mercury Management Strategy (Renee Echols, FireWater Associates, LLC (USA)); 3 - Integration of Science to Address Mercury Clean-up Challenge (Eric Pierce, Oak Ridge National Laboratory (USA)); 4 - Mercury Related Research and Development by CRESP (Kevin Brown, Vanderbilt University - CRESP (USA)); 5 - Lessons Learned from D and D of West COLEX (Kent Fortenberry, UCOR (USA)); 6 - Mercury in the SRS Liquid Waste System (Richard Edwards, Savannah River Remediation (USA)); 7 - TDD Program on Mercury at Savannah River (Bill Wilmarth, Savannah River National Laboratory (USA))

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Alstom’s Chemical Looping Combustion Technology for CO 2 Capture for New and Retrofit Coal-Fired Power Plants

Cold Flow Modeling (CFM) is a critical tool to understand solid transport, corresponding process stability, and the impact on the performance of the LCL-CTM technology. As such it plays a central role in the development of the LCL-CTM process and deserves a standalone report in the final reporting on Phase II of the collaboration with DOE under award DE FE0009484. The 40-Foot Cold Flow Model (CFM) was constructed before the 3 MWth Prototype. The purpose of the CFM is to: develop design and operational information to design the Prototype help resolve solids transport problems that occur with the Prototype provide Prototype operator training. This report provides a review on the use of the CFM to achieve better understanding, design, and operation of solid transport for the LCL-CTM technology. Significant progress was made by iteratively designing, operating, and testing between the CFM and the Prototype scale. Fundamental understanding of the transport of reactive solids was acquired based on the reported effort. Unfortunately, the technical gaps identified for Phase II of the LCL-CTM technology development could not all be eliminated and the transport of solids under high fuel load remained unstable at the Prototype scale. The nature of the iterative learning going back and forth between CFM and Prototype scale became cost-prohibitive and forced the project to pivot at a relatively late date in the project. The LCL-CTM process switched from a Transport reactor design to a Bubbling Fluidized Bed (BFB) design in order to successfully achieve all process criteria but at the 100-kWth scale to accommodate the residual funding. The CFM remains a very relevant tool for future LCL-CTM process development. While the LCL-CTM technology still must be demonstrated under scale up conditions (and the success of the BFB testing would push to scale up in that configuration), the CFM will remain a preferred tool for troubleshooting and reducing the technical gaps of LCL-CTM.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

An Intelligent Adaptable Monitoring Package. Final Report

The “Intelligent Adaptable Monitoring Package” project was a four-year effort that demonstrated the feasibility of integrated sensing packages at tidal and wave energy sites. Such integration is generally required by the breadth of sensors required to understand environmental effects at marine energy sites and the operational difficulty of deploying, maintaining, and recovering such sensors. Over the course of the project, the Adaptable Monitoring Package (AMP) was deployed in multiple settings, each corresponding to a project budget period: - Budget Period 1: Demonstration of cabled deployment at Pacific Northwest National Laboratory’s Marine Science Laboratory. The deployment highlighted AMP hardware endurance over a 4-month deployment in a tidally-dominated environment and laid the groundwork for machine learning algorithms to detect and classify targets present in active sonar data. - Budget Period 2: Demonstration of an autonomous deployment at PacWave South off the coast of Newport, Oregon. The deployment highlighted the stability of AMP hardware and software, with the autonomous package collecting data on a duty cycle over a 1.5-month deployment. - Budget Period 3: Demonstration of an autonomous deployment powered by a wave energy converter at the U.S. Navy’s Wave Energy Test Site. The deployment highlighted the potential of wave energy to power ocean observatories and led to the development of machine learning algorithms to detect and classify targets in optical camera data. In aggregate, this project’s greatest success was demonstrating the AMP’s flexibility in a range of deployment scenarios. Each budget period represented a “first of a kind” demonstration of integrated instrumentation – cabled AMP, autonomous AMP, wave-energy powered AMP – and each deployment helped to identify and set goals for the next. Further, despite the exploratory nature of these deployments, each one achieved high system up-time and proved that flexible integration of multiple sensors in a single package represents a viable strategy for marine energy environmental monitoring. The key lessons learned from the project are: - Without continuous power, either from a shore cable or in situ source, many of the benefits of integration are lost (If continuous power is not available, the ability to detect rare events is lost, as is the ability to minimize the risk of behavioral changes through adaptive sensing. However, even on a duty cycle, there is still value in being able to acquire synchronous data from multiple sensors.); and - Observations from a moving platform present substantially greater data processing challenges than those from stationary platforms. Finally, these deployments also demonstrate an important truth: successful integration alone does not guarantee that relevant data are collected. To grow the knowledge base about environmental interactions with marine energy converters, integrated systems, like the AMP, need to include the right sensor mix and connect the data pipelines to effective processing algorithms. These deployments establish a strong foundation for future collaborations with the environmental research community: not only to understand the environmental effects of marine energy, but also to improve our general ability to study life in the sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Overview of Hydraulic Fracturing Test Site 2 in the Permian Delaware Basin (HFTS-2)

Here, the Hydraulic Fracturing Test Site 2 (HFTS-2) is a large collaborative field-based R&D program in the Permian Delaware Basin, funded by the US Department of Energy through the National Energy Technology Laboratory (NETL) and the E&P industry, with support from academia. The projects' main objective is to improve the understating of the hydraulic fracturing process through utilization of advanced diagnostics and collection of through-fracture cores to provide undisputable evidence and attributes of the created hydraulic fractures. At the HFTS-2, in excess of $30 million was used to perform hydraulic fracturing research focusing on the Wolfcamp formation at a field site hosted and operated by Occidental. In addition to the research data collected by the project, Occidental provided a significant amount of background data for about a dozen existing wells in the test area as well as access to previously collected core. Additional technical and laboratory support was provided by the program members. Building on learnings and unanswered questions from HFTS-1 in the Permian Midland basin, the HFTS-2 used eight new producing wells and two existing (parent) wells to perform hydraulic fracturing research. Multiple science wells were drilled to sample and characterize the subsurface, including the collection of 540 feet of core in a vertical pilot hole and 948 feet of high-angle through-fracture core. The project installed permanent fiber optic cables in 3 wells to monitor near wellbore signals during fracturing and to collect cross-well strain measurements. Additional advanced diagnostics included a significant formation evaluation program on the vertical whole core, multi array moment tensor inversion capable microseismic survey, multi-well time-lapse geochemistry analysis, analysis of proppant distribution in producing child and slant core well, and others. We will provide an overview of the HFTS-2 project, including list of the consortium members, details of the test site, experiments performed, and technologies tested.

58 GEOSCIENCES↗
DOE OSTI2024

Reactor System Demonstration with Cyber-Attack Scenarios Using CrowPis and Arduino Microcontrollers

This study covers developing and simulating nuclear reactor system using CrowPis and Arduino microcontrollers for demonstrating cyber-attack scenarios. The team was tasked with implementing more sensors and cybersecurity aspects to the reactor program that was created by last year’s high school interns. The team received the opportunity to collaborate and obtain advice from multiple university interns that helped us gain a better perspective of our project. Our mentor’s background in nuclear science was pivotal to our understanding what we could add to the reactor program to make it as realistic as possible. The first week of our internship was spent reading as much material as possible to gain an understanding of and the background for cyber-attacks and nuclear science. Nuclear science was a new horizon for each of the high school interns on the team, so spending this time in the beginning of our internship was crucial to our success. For the remaining portion of our internship, the team collectively did our best to implement as many sensors and use as much hardware as we could to make an accurate representation of a nuclear reactor in the program that was created. This internship was a big learning experience for everyone on the team. We all gained so many insights into the nuclear world and how it can benefit our lives, as well as how so many moving pieces are needed for it to work properly.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

The Quantum Nature of the Neutrino

Over the last 100 years we have learned much about the neutrino, but there remain interesting questions about this weakly interacting particle. In particular, at LLNL we are developing an experiment to measure the quantum nature of the neutrino. The 2015 long range plan recom mended tonne-scale neutrinoless double beta decay experiments as the top new project priority and this experiment will target the quantum nature of the neutrino. The LLNL team is motivated and focused on developing the best technology for this experiment which is a liquid xenon time projection chamber called nEXO. Work on nEXO at LLNL started in 2015 with an LDRD and program development funds to de velop the nEXO concept, publish sensitivity predictions, explore alternatives and risks, and to build a credible project team and this effort is on going. In addition, we received research funding from DOE-SC NP and LLNL manages pre-conceptual R&D for the nEXO collaboration a portion of which is executed at LLNL. LLNL has a long history of building large projects, science projects and time projection chambers, but nEXO is in fact the first project of this scale that LLNL is prepared to lead for DOE-SC NP. We have the tools, skills, people and motivation to make nEXO a reality. The current program devel opment dollars are used to prepare the nEXO concept for down select and CD1. These internal LLNL dollars pay for a number of things including project staff to organize the nEXO collaboration for the various reviews, to develop the draft plans and structure to manage the project as well as setting up external advisory committees. The DOE-SC NP base funding is targeted at simulation and analysis of the nEXO concept in preparation for the down select and refinement of the under standing of the detector as well as scientific effort on the large xenon test stand (LXTS) that will burn down one of the largest risks to the nEXO project. Lastly, LLNL is leading the pre-conceptual R&D effort and managing the funds for the nEXO collaboration. LLNL continues to build the best scientific team for nEXO and this year that includes adding Ethan Bernard to lead the efforts on the LXTS. We will also soon add a new postoc, Samuel Hedges, in the fall to the LLNL nEXO team. The effort this year was influenced by the portfolio review, and there were a number of scientific activities led by LLNL to prepare for this review. In addition, we again took a lead role on the new sensitivity paper as well as publishing a paper based analyzing the effects of skin xenon in nEXO. LLNL leads the software and analysis for the project and we continued work in this area as well. High voltage remains a significant risk for the project and we continue to make progress on the LXTS that will mitigate this risk. Lastly we remain active in looking at how to scale the technology to larger scales, and expect to produce a paper on this topic in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

LandScan Mosaic

The LandScan program at Oak Ridge National Laboratory (ORNL), in collaboration with the National Geospatial-Intelligence Agency (NGA), continues to deliver the most accurate and up to date global, high resolution gridded population data. Additionally, the latest advancements in the LandScan HD methodology led to reduced latency in development of rapid updates for geopolitical events. With momentum towards reporting more up to date population estimates, feedback from the user community expressed interest in reporting population estimates in ranges - whether to express a level of uncertainty or confirm to leadership and stakeholders the modeled data are estimates. Building upon the need to understand uncertainty or confidence in the modeled data and report ranges at the global scale, LandScan Mosaic was developed. LandScan Mosaic represents the next generation of high-resolution population modeling, building upon the established success of previous LandScan HD iterations. While LandScan HD employed a deterministic big data fusion approach, LandScan Mosaic enhances this methodology by integrating advanced machine learning techniques to impute missing, yet crucial, population model parameters. This advancement allows for probabilistic modeling of building occupancy and population distribution, incorporating uncertainty quantification through Monte Carlo sampling methods. By combining big data fusion with machine learning-driven imputation and stochastic modeling, LandScan Mosaic provides a more comprehensive and robust representation of population dynamics. LandScan Mosaic will be following the in the footsteps of its longstanding counterpart LandScan Global and releasing a global gridded population raster, at the 3-arcsecond resolution. This technical report documents the current stage of development of LandScan Mosaic, detailing the methodologies and data sources behind the modeling. Stakeholders are encouraged to use this document as an authoritative reference for insight into Mosaic’s data development processes. However, readers should note that LandScan Mosaic remains in a late-stage research and development phase, and methodologies and data presented here are subject to refinements ahead of the anticipated global release in Summer 2025. Feedback and inquiries from users and stakeholders are welcomed as we continue to refine and enhance this important population resource.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗
DOE OSTI2025

ReVise: A Human-AI Interface for Incremental Algorithmic Recourse

The recent adoption of artificial intelligence in socio-technical systems raises concerns about the black-box nature of the resulting decisions in fields such as hiring, finance, admissions, etc. If data subjects—such as job applicants, loan applicants, and students—receive an unfavorable outcome, they may be interested in algorithmic recourse, which involves updating certain features to yield a more favorable result when re-evaluated by algorithmic decision-making. Unfortunately, when individuals do not fully understand the incremental steps needed to change their circumstances, they risk following misguided paths that can lead to significant, long-term adverse consequences. Existing recourse approaches focus exclusively on the final recourse goal but neglect the possible incremental steps to reach the goal with real-life constraints, user preferences, and model artifacts. To address this gap, we formulate a visual analytic workflow for incremental recourse planning in collaboration with AI/ML experts and contribute an interactive visualization interface that helps data subjects efficiently navigate the recourse alternatives and make an informed decision. We also present one of the many usage scenarios, developed during exploratory feedback sessions with twelve graduate students using a real-world dataset, which demonstrates that our approach can be instrumental for data subjects in choosing a suitable recourse path.

algorithmic recourse↗
DOE OSTI2019

Defending our public biological databases as a global critical infrastructure

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world’s primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly “retrofitted” mitigations. Furthermore this Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Heliostat Consortium: Update on Resource, Training, and Education Development and Women+ in Concentrating Solar

One of the major barriers to Concentrating Solar Power (CSP) industry growth in the U.S. is the lack of accessibility of expert knowledge, a lack of a stable workforce pipeline, and little public awareness of the technology area. Improved Resource, Training, and Education (RTE) is needed to address these gaps, to draw workers into the field from diverse technology areas and backgrounds, and to reduce the learning curves of newcomers into the industry. As part of the RTE topic under the NREL-led Heliostat Consortium (HelioCon), a public online resource database has been created to support information sharing across the heliostat and CSP community. Here, information will be presented on the existing and planned database resources, including introductory information about CSP and heliostats, a reference library of texts and publications, educational videos, a CSP power tower plant database and case studies, a contact list of component suppliers and developers, and a list of available software/metrology tools. Women+ in Concentrating Solar is a newly created organization to promote the education, professional development, and advancement of underrepresented genders in the Concentrating Solar Power (CSP) community in a way that includes diverse backgrounds, attitudes, and perspectives. The main objectives of the groups are to provide the following opportunities for underrepresented genders: 1) organize events to provide networking opportunities and community building, 2) boost partnerships and scientific collaboration, 3) create resources to facilitate knowledge and experience sharing, 4) provide mentorship programs to support those new to the industry, 5) bring visibility to underrepresented genders and attract more to the field, and 6) promote Diversity, Equity, and Inclusion (DEI) and engage minorities and underrepresented groups. Initial activities being pursued by the group include creating an expert database to support event organizers in recruiting speakers with representation of all gender identities, hosting online networking and webinar events, organizing conference events including seminars and networking/social events, and establishing a mentorship program to connect members in the CSP community across the globe. The group is open to all genders and has grown to over 60 members in its first few months.

concentrating solar↗
DOE OSTI2016

SU-F-E-14: Global Radiation Oncology Education and Training in Medical Physics Powered by Information and Communication Technologies

Purpose: Recent publications have highlighted the potential of Information and Communication Technologies (ICTs) to catalyze collaborations in cancer care, research and education in global radiation oncology. This work reports on the use of ICTs for global Medical Physics education and training across three countries: USA, Tanzania and Kuwait Methods: An online education platform was established by Radiation Oncology Faculty from Harvard Medical School, and the University of Pennsylvania with integrated Medical Physics Course modules accessible to trainees in Tanzania via partnership with the Muhimbili University of Health and Allied Sciences, and the Ocean Road Cancer Institute. The course modules incorporated lectures covering Radiation Therapy Physics with videos, discussion board, assessments and grade center. Faculty at Harvard Medical School and the University of Massachusetts Lowell also employed weekly Skype meetings to train/mentor three graduate students, living out-of-state and in Kuwait for up to 9 research credits per semester for over two semesters towards obtaining their graduate degrees Results: Students were able to successfully access the Medical Physics course modules and participate in learning activities, online discussion boards, and assessments. Other instructors could also access/co-teach the course modules from USA and Tanzania. Meanwhile all three graduate students with remote training via Skype and email made major progress in their graduate training with each one of them submitting their research results as abstracts to be presented at the 2016 AAPM conference. One student has also published her work already and all three are developing these abstracts for publication in peer-reviewed journals. Conclusion: Altogether, this work highlights concrete examples/model on how ICTs can be used for capacity building in Medical Physics across continents, for both education and research training needed for Masters/PhD degrees. The developed modules and model will be scaled to benefit many more trainees and other developing countries.

60 APPLIED LIFE SCIENCES↗