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Panel reports session

This section brings together the reports of the 31 panel sessions listed below: - Avoiding the Human Capital Cliff in the DOE (PS22); - Implementing Technically-Based Cleanup; US DOE Balancing Regulatory and Fiscal Complexity (PS24); - United Kingdom - Remediation of Sellafield Legacy Ponds and Silos (PS25); - Aligning Decision-Making to Deliver Timely Results in Large Clean-up Programs (PS38); - Transition to Government Owned-Contractor Operated Site at Canadian Nuclear Laboratories (PS39); - Emerging Middle East Nuclear States' Status and Plans (PS40); - NPP Panel on Waste Management (PS41); - Robotics - International Innovations in Robotic Decommissioning Technology (PS43); - Fukushima Panel (1/2): Japan Fukushima Daiichi Decommissioning Update (PS54); - Fukushima Panel (2/2): Update on the Revitalization of Fukushima and the Surrounding Area (PS55); - US DOE LLW On-Site Disposal: LLW Disposal Facility Federal Review Group Review Process (PS56); - Challenges in DOE HLW Tank Management: Facility Start-up and Waste Disposition (PS57); - Waste Management Planning for Utility Small Modular Reactors (PS58); - US Nuclear Power Plant Waste Management - LLW Disposal Issues (PS59); - DOE-EM Robotics and Emerging Technologies Road-map (4/8) (PS60); - Graduating Students and New Scientists and Engineers - Wants and Needs - Are Companies Even Listening? (PS63); - U.S. Nuclear Robotics: Yesterday, Today, Tomorrow (5/8) (PS74); - US DOE Mixed Waste: Proposals for Dealing with Problematic Waste Streams and Policy Changes (PS76); - Current and Emerging US NRC LLW Regulatory Topics (PS77); - Agency Perspectives (US and International) on the Use of Risk and Dose Assessment Tools (PS80); - Progress on Deep Repository Programs Around the World (PS81); - US DOE Procurement and Contracting Opportunities (PS82); - Collaboration across Borders to Deliver Cleanup and Decommissioning Challenges (PS93a); - DOE Mission Success through Application of Practices and Solutions (PS94); - Challenges in Cask Certification - International Perspectives (PS96); - Robotics: Leveraging Innovations in Science and Technology to Benefit Safety Performance (PS98); - DOE Panel: DOE EM Featured Office - Portsmouth/Paducah Project Office (PS109); - Robotics: Lessons Learned from Industrial Robotics Deployment that can be Applied to the Nuclear Field (PS110a); - Roundtable: DOE Radioactive Management - Energy Facility Contractors Group - Waste Management Working Group (EFCOG WMWG) (PS118); - Thursday Topical Session 'Management of Used Nuclear Fuel: Will the United States Reengage and Align with International Efforts' (PS124); - Remotely Operated Vehicles for Emergency, Disaster, and Operational Upset Response (PS125)

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Position Papers for the ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems

At the request of the Department of Energy's (DOE) Office of Advanced Scientific Computing Research (ASCR), this program committee has been tasked with organizing a workshop to identify basic research needs in cybersecurity and privacy to better support DOE's science and energy mission. As part of the process, the program committee is soliciting community input in the form of position papers to help identify significant use cases, facility issues, and other barriers to enabling verifiably trustworthy computational science while preserving data confidentiality as appropriate for scientific workflows of interest to DOE. The program committee will review these position papers and based on the fit of their area of expertise and interest, selected contributors will have the opportunity to participate in the workshop currently planned as a virtual event November 3-5th, 2021. The thrust areas that will be explored by this workshop are the following: (1) Algorithms for secure, scalable, privacy-enhancing technologies and frameworks, including: Federated AI/ML, Differential privacy, Randomized algorithms, Adversarial modeling & simulation, Graph algorithms, and Formal methods; (2) Platforms to support the entire scientific-computing ecosystem, including edge computing for large-scale experiments, focusing on heterogeneous systems and distributed systems, including: Heterogeneous computing systems, Distributed computing systems, and Secure data architectures; and (3) Data workflows to allow agile use of data while preserving integrity and privacy, making the important properties verifiable either at runtime or post-computation, including: Integrity and provenance and Data management infrastructure. Topics that are out-of-scope for the workshop include discussing specific proposed solutions or areas that are clearly out of DOE's fundamental and applied-sciences mission scope, e.g., cryptography, enterprise security, and general-operations technology.

97 MATHEMATICS AND COMPUTING↗

An Architectural Survey of the Pluto Test Bunker Facility, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE), in conjunction with the National Nuclear Security Administration Nevada Field Office (NNSA/NFO), proposes to reactivate Building 26-2205 as part of a project to detect foundry-type operations with remote sensing. The project is known as the Signals Exploration Testbed, or SET for short. Building 26-2205 (State Historic Preservation Office [SHPO] Resource No. B11558) is the former Compressor Building for the Pluto Program in Area 26 of the Nevada National Security Site (NNSS). Proposed actions at Building 26-2205 include removal of exterior building and site features, such as fencing, concrete pads, a large steel tank, and visible utilities, as well as interior changes to the building’s floor plan. These activities constitute an undertaking subject to review under Section 106 of the National Historic Preservation Act (NHPA) (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800.

54 ENVIRONMENTAL SCIENCES↗

Transportation Energy Analytics Dashboard (TEAD)

The investment decisions within the nation’s transportation sector have traditionally been prioritized and measured against safety and travel efficiency goals. Increasingly, federal, state, and local policies are requiring consideration of energy use and emissions in the design of our transportation infrastructure. Yet the processes, analytics, and knowledge to include these new metrics into transportation decisions are lacking. Although targeted studies and before and after analysis are performed from time to time, no comprehensive real-time monitoring systems provide energy and emissions to the same level as congestion and safety. To address this gap, the Center for Advanced Transportation Technology (CATT Lab) and the Maryland Transportation Institute (MTI) at the University of Maryland (UMD), in partnership with the National Renewable Energy Laboratory (NREL), have developed a Transportation Energy Analytics Dashboard, or TEAD, to raise awareness of the energy and emission impacts to the same level of observability as that of safety and mobility concerns. The overall goal of this project was to develop and demonstrate an online tool to monitor transportation energy use and emissions in real-time and to archive this data for retrospective analysis. By combining surface transportation energy and emissions evaluation capability with more traditional safety, mobility and reliability system evaluation, our goal is for TEAD to create a dynamic new paradigm in transportation systems management and performance analyses, for both real-time traffic operations, and longer-term planning for project and program investment decision-making.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Sandia Academic Alliance Program Collaboration Report: 2020-2021 Accomplishments

University partnerships play an essential role in sustaining Sandia’s vitality as a national laboratory. The SAA is an element of Sandia’s broader University Partnerships program, which facilitates recruiting and research collaborations with dozens of universities annually. The SAA program has two three-year goals. SAA aims to realize a step increase in hiring results, by growing the total annual inexperienced hires from each out-of-state SAA university. SAA also strives to establish and sustain strategic research partnerships by establishing several federally sponsored collaborations and multi-institutional consortiums in science & technology (S&T) priorities such as autonomy, advanced computing, hypersonics, quantum information science, and data science. The SAA program facilitates access to talent, ideas, and Research & Development facilities through strong university partnerships. Earlier this year, the SAA program and campus executives hosted John Myers, Sandia’s former Senior Director of Human Resources (HR) and Communications, and senior-level staff at Georgia Tech, U of Illinois, Purdue, UNM, and UT Austin. These campus visits provided an opportunity to share the history of the partnerships from the university leadership, tours of research facilities, and discussions of ongoing technical work and potential recruiting opportunities. These visits also provided valuable feedback to HR management that will help Sandia realize a step increase in hiring from SAA schools. The 2020-2021 Collaboration Report is a compilation of accomplishments in 2020 and 2021 from SAA and Sandia’s valued SAA university partners.

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The Next Generation System Analysis Model: Capabilities for Simulating a Waste Management System - 19131

The U.S. Department of Energy (DOE) Office of Nuclear Energy Office of Spent Fuel and Waste Disposition's Integrated Waste Management System (IWMS) program is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWMS are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The system architecture analyses consider alternative disposition pathways for commercial spent nuclear fuel (SNF) being stored dry in at-reactor Independent Spent Fuel Storage Installations (ISFSIs) or wet in spent-fuel pools. One method for evaluating these alternatives is simulating the movement of SNF throughout the system components. Successfully simulating a system on the scale of a national waste management system requires - accurate baseline information (e.g., historic fuel discharges from reactors and dry storage loadings at reactor sites), - modeling all logistic interactions between components of the proposed system, and - tracking and reporting all relevant details regarding the simulation's execution. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWMS. It is based on the Performance Analysis Tool, a simulation platform that has been used to model logistics for the Department of Defense and the Federal Emergency Management Agency. Using existing, government-owned software allows NGSAM developers to modify the software at the level of source code and to develop flexible usability and modeling solutions for developing and running simulations of the IWMS. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. NGSAM is designed with the flexibility to model and track the behavior of virtually any IWMS architecture assumptions or design considerations. For example, NGSAM can model multiple interim storage facilities or repositories or none at all. Similarly, all assumptions regarding shipment schedules, operating schedules, and reactor operation assumptions can be modeled and adjusted in NGSAM with relative ease. The development of NGSAM was targeted to waste management system analysts as the primary users. With that in mind, analysts from ORNL, Sandia National Laboratories (SNL), and Argonne National Laboratory (ANL) were intimately involved in the development process. That involvement extended beyond merely defining requirements. System analysts have been involved with design decisions and software benchmarking and tests, and they have provided subject-matter expertise where necessary. The result is a high degree of interaction between professional software developers and system analysts, with a multitude of benefits to both groups. This paper explores some of the underlying methodology of the agile software development process used in the creation of NGSAM. It illustrates the capabilities of NGSAM. Some example use cases are discussed as well, with relevant results providing context for how NGSAM is used by system analysts to gain a greater understanding of alternative waste management system architectures. This is a technical paper that does not take into account the contractual limitations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). Under the provisions of the Standard Contract, DOE does not consider spent nuclear fuel in multi-assembly canisters to be an acceptable waste form, absent a mutually agreed-to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract provisions prevail. (authors)

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2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗

Achieving the Vision: An Update on Cleanup, Closure, and Reindustrialization of the East Tennessee Technology Park - 18401

URS-CH2M Oak Ridge LLC (UCOR) is responsible for cleanup of the U.S. Department of Energy's (DOE) East Tennessee Technology Park (ETTP) in Oak Ridge, Tennessee. Formerly known as the K-25 site, the facility enriched uranium for major defense nd energy programs for more than 40 years. The site's industrial processes - largely the gaseous diffusion method used for enriching uranium - left behind radioactive, chemical and industrial contaminants in soils and structures. Cleanup of the environmental legacies enables DOE's goal for converting ETTP into a private sector industrial park. Return of the restored site to the community will attract new industries to the region, creating jobs and growing the economy. The central elements to achieve DOE's vision for the site are 1) Cleanup, 2) Closure, and 3) Reindustrialization. Cleanup entails completion of all demolition activities and remedial actions consistent with the Comprehensive Environmental Response, Compensation and Liability Act of 1980 (CERCLA) agreements. Closure leaves facilities and infrastructure in a condition that enables transfer of the site to non-federal entities and reduces DOE's long-term stewardship costs. Closure activities include: - Infrastructure stabilization (site utilities, roads, stormwater, etc.); - Disposal or transfer of government property; - Relocation of most DOE contractors and support functions offsite; - Transfer of the majority of the site property to non-federal entities for redevelopment. Reindustrialization enables DOE's vision for the site as a multi-use private sector industrial park, reducing DOE's costs and enhancing the local economy. Transfer to the private sector will be accomplished through the Community Reuse Organization of East Tennessee (CROET), which will serve as the Park Manager. (author)

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Leveraging State Clean Water Revolving Funds to Expand Clean Energy Financing

To meet clean energy goals, states will need significant capital. Federal funding from the Inflation Reduction Act and the Infrastructure Investment and Jobs Act will help, including by capitalizing clean energy state revolving loan funds (RLFs). States can leverage state clean water revolving funds to finance even more clean energy improvements. New York and Pennsylvania have used this innovative mechanism to extend the impact of their clean energy loan programs. For states looking to extend the reach of their clean energy financing programs, the brief: -Explains how each state leveraged their state revolving funds, -Identifies critical success factors for doing so, and -Offers key elements for replicating this model In New York, New York State Energy Research and Development Authority structured a sale of bonds secured by the repayments from a portfolio of residential energy efficiency loans from its Green Jobs – Green New York Program, with the additional support of a guarantee from the state’s clean water revolving fund. The Pennsylvania Treasury Department received a direct investment of funds from Pennsylvania’s clean water revolving fund to support the relaunch of the Keystone Home Energy Loan Program (HELP), which had previously been shuttered due to lack of support funding. From our review of these two case studies, when facilitating state clean water revolving fund transactions to support clean energy lending, the following critical success factors emerged: -Reference to preventing atmospheric deposition resulting from the combustion of fossil fuels in the state’s Clean Water Act Section 319 Nonpoint Source Pollution Management Plan, which sets out that state’s strategy for reducing pollution into state waterways. -Strong relationships and trust between the clean water revolving fund administrator and the state agency administering the clean energy loan program. -Limited funding exposure for the clean water revolving funds—which are generally large and well capitalized—to ensure that any losses experienced by clean water revolving funds would have a negligible impact on the fund’s ability to support core water and wastewater projects. -Willingness, on the part of the clean water revolving fund administrator, to innovate and engage in careful analysis to support transaction structuring, and support from state energy partner organizations. The brief provides case studies of these states’ experiences, critical success factors, and key elements for replicating the model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of the Waste Acceptance Criteria for the Idaho National Laboratory Remote-Handled Low-Level Waste Disposal Facility - 19143

The Idaho National Laboratory (INL) Remote-Handled Low-Level Waste (RH LLW) Disposal Facility has been constructed, has received operational approval from the Department of Energy (DOE), and is expected to receive its first waste shipment in FY 2019. The RH LLW Disposal Facility will support the needs of INL and the Naval Reactors Facility (NRF). RH LLW destined for the facility includes waste currently in storage from previous programs and projects conducted at INL; newly generated waste from programs and projects conducted at INL; and waste from NRF spent fuel processing activities. This new facility supports RH LLW disposal needs for the ongoing mission of INL and NRF. Waste to be disposed of at the RH LLW Disposal Facility may exhibit dose rates that range from 0.002 Sv/hr to 600 Sv/hr. Waste types include resins and activated metals as well as surface-contaminated debris generated from existing and new missions. The total number of canisters currently planned for disposal at the RH LLW Disposal Facility is 939 with the possibility of future expansion. The projected waste volume to be disposed of is 3,100 m{sup 3}. The RH LLW Disposal Facility will receive a wide variety of RH LLW and is in preparations to receive its first canisters in FY 2019. Waste acceptance criteria (WAC) and the radioactive waste management basis have been developed and implemented in accordance with the applicable DOE Order. In order to ensure that DOE requirements and guidance were appropriately implemented in the RH LLW Disposal Facility WAC, the project worked closely with the DOE Low Level Waste Disposal Facility Federal Review Group (LFRG) representatives and followed the applicable DOE standard. This paper provides an overview of the development of the WAC, including waste and waste generator certification requirements, for the RH LLW Disposal Facility. The paper illustrates the importance of maintaining strong ties to the development and revision of the RH LLW Disposal Facility Performance Assessment (PA), Documented Safety Analysis, Facility Procedures, Readiness Reviews, DOE Order, and applicable Technical Standards. The paper also provides an overview of the RH LLW Disposal Facility, WAC generator certification requirements, distinctive challenges to acceptance of legacy waste, and the unique approach the RH LLW Disposal Facility has taken to ensure compliance with PA driven limits. (authors)

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Field Validation of a Grid-Interactive Efficient Building Software Solution

The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

AMES: MS and MENG in Advanced Manufacturing for Energy at the University of Connecticut (Final Technical Report)

The objective of the project is to develop and implement an advanced degree program (MS and MENG in Advanced Manufacturing for Energy Systems, AMES) responding to the long-term workforce and technology requirements of the nation’s advanced energy products manufacturing industry. The program provided an industry relevant research experience by leveraging existing energy (e.g. fuels, power electronics, electrochemical power sources) and advanced manufacturing (e.g. additive manufacturing, composites, sensing) research at UConn funded by federal and state agencies, and industry, as well as through our industry partnerships. The trainees have joined research teams, advised by faculty with relevant research interests and expertise and were co-advised by industrial mentors. The AMES program have developed a truly interdisciplinary curriculum, first graduate degree program at UConn School (now College) of Engineering not housed in an academic department, with concentrations focusing on various challenges in advanced manufacturing for energy systems, e.g. advanced materials and processing. The project also developed new courses focusing on common technical and professional skills, and integrated various components for an industry relevant training. The program has admitted 29 Master of Science (MS) students since inception in January 2019. Twenty six of these students were AMES fellows, who have received partial funding from DoE through this project. The program far exceeded the goal of admitting at least five new MS (with thesis) students. All students were required to complete a thesis (M.S.) or a capstone (M.Eng.) project that are defined in collaboration with industry partners to ensure industrial relevancy, addressing a current industrial challenges. Industrial mentors also participated in advising the students in their research. AMES fellows, in addition were also required to complete an industrial internship for further industrial experience.

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Predicting and Managing Risk to Bats at Commercial Wind Farms using Acoustics

Bat populations in North America face novel threats from white-nose syndrome and widespread turbine-related mortality related to the rapidly expanding wind power industry in addition to long-standing pressures from habitat loss and degradation. Bats, unlike most small mammals, are long-lived and slow to reproduce, highlighting the importance of understanding and managing anthropogenic sources of mortality. My dissertation research used acoustic bat detectors to measure bat activity at commercial wind projects, predict patterns in risk, and design strategic measures to reduce fatality rates by curtailing turbine operation during periods when bats are most active. Bats collide with wind turbines only when their rotors are spinning, and risk of turbine-related fatality is therefore a dynamic factor that can be manipulated by curtailing turbine operation when bats are active. We first measured inter-detector variation in metrics of acoustic bat activity to understand how the acoustic detection process may affect inferences related to spatial and temporal variation in bat activity. Using acoustic detectors mounted on top of wind turbines at two commercial wind farms in West Virginia, we then demonstrated that the amount of bat activity recorded when turbines were operating aligned closely with bat fatality rates on multiple scales. Accordingly, the metric of bat activity exposed to turbine operation provides a meaningful, quantitative indicator of turbine-related bat fatality risk. Further, bats responded consistently to changing wind speed and temperature at turbines in both wind farms across multiple years, enabling exposed bat activity to be predicted accurately among turbines and years. Building on these results, we simulated exposure of bats to turbine operation and energy loss for curtailment strategies recommended by state and federal agencies in the United States and Canada. By adjusting parameters such as cut-in wind speeds and temperature thresholds, we demonstrated the ability to design strategic curtailment programs that achieve equivalent or greater predicted reductions in bat activity exposure for substantially less energy-production loss. Characterizing fatality risk on a finer scale using acoustics will help regulatory agencies and the wind industry alike reduce risks of population-level impacts to vulnerable bat species while continuing to expand large-scale renewable energy generation.

17 WIND ENERGY↗

A New Look For Greenbelt

Greenbelt, Maryland, 12 miles from the nation's capital, is an efficiently planned model town and most of its 1600 homes are almost identical in appearance. Four of them, however, stand out from their neighbors; they have distinctive blue glass rooftop superstructures made up of a series of solar collectors. They are part of a NASA community aid program, a joint energy research project involving the Greenbelt housing cooperative and NASA's Goddard Space Flight Center, located near the community. Built in 1935, Greenbelt is one of three government-planned communities of President Franklin D. Roosevelt's first administration; the others are Greendale, Wisconsin and Greenhills, Ohio. The government built the towns to make available low-cost housing, provide employment for workers on relief in the Great Depression era, and to establish models designed to encourage construction of similar developments by private industry. In 1952, the residents of Greenbelt formed a nonprofit cooperative called Greenbelt Homes, Inc., which bought the dwellings, facilities and a large part of the land from the government. The homes are individually owned but collectively maintained by the co-op, with each owner paying a prorated share of utility and maintenance costs. Greenbelt residents are mostly in the low and medium income brackets, and one of every three families lives on a fixed retirement income. For that reason, the sharp escalation of fuel oil prices that began in 1973 imposed particular hardship on the co-op community. So Greenbelt Homes' management asked its NASA neighbor, Goddard Space Flight Center, for assistance in setting up a solar energy research project. The idea was to conduct a small scale demonstration to show what savings could be realized by solar heating Greenbelt homes, with an eye toward possible future expansion of solar energy systems as a means of combating rising fuel costs. Goddard undertook the project as part of the federal government's effort to research and demonstrate ways of conserving energy. The Center was well qualified for the assignment, having acquired extensive expertise in designing thermal control systems for satellites, which must maintain stable temperatures for successful operation.

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2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

Los Alamos National Laboratory Hazardous Waste Facility Permit Community Relations Plan

The requirements of the Hazardous Waste Facility Permit are fulfilled through execution of LANL's fourth strategic goal: “Enabling mission delivery through next-generation facility, infrastructure, and operational excellence.” With input from our stakeholders, we will continue to fulfill those requirements and to improve our waste operations. In 2015, the Laboratory purpose statement focused waste management efforts by directing delivery of mission success through operational effectiveness and scientific excellence. This Plan advances that purpose through community involvement. In the process of achieving our national security mission, Los Alamos National Laboratory generates some hazardous and mixed waste. Hazardous waste is solid waste that is dangerous or potentially harmful to human health or the environment. Hazardous wastes can be liquids, solids, gases, or sludges. They can be discarded as commercial products, such as cleaning fluids or pesticides, or as the byproducts of operations. Specific substances are listed in 40 Code of Federal Regulations (CFR), Part 261: 40 CFR Part 261. Hazardous waste management activities are regulated by the U. S. Environmental Protection Agency and the New Mexico Environment Department (NMED) pursuant to New Mexico Hazardous Waste Act (HWA; Chapter 74, Article 4 NMSA 1978) and regulations under the Act. In 1989, NMED issued the Hazardous Waste Facility Permit (EPA ID Number NM0890010515-1) that established standards for the Laboratory to manage, store, and treat hazardous wastes on-site and to undertake the closure, post closure care, and cleanup as necessary, of permitted waste management units. On November 30, 2010, NMED renewed the Hazardous Waste Facility Permit (the Permit). In June 2020 the Permittees submitted a permit renewal application to the NMED for their review and approval. The Hazardous Waste Facility Permit Community Relations Plan (CRP) describes the scope of public involvement in the activities of the Permit. The CRP is specifically designed to facilitate the community outreach, engagement, and relations activities concerning the Laboratory’s Hazardous Waste Facility Permit and coordinates with but does not include public involvement for other Laboratory programs, initiatives, or environmental activities.

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Department of Energy Office of Legacy Management Progress on Defense-Related Uranium Mines Program - 18119

The Defense-Related Uranium Mines (DRUM) Program provides the structure and basis for the US Department of Energy Office of Legacy Management (LM) to manage the verification and validation (V and V) of defense-related uranium mines (mines) that provided ore to the Atomic Energy Commission from 1947 to 1970. V and V activities are conducted to fully understand the scope of potential problems posed by these mines by determining their location, reclamation or remediation status, and potential impacts to public safety, human health, and the environment. Land management agencies have limited resources and have generally not conducted comprehensive inventories of abandoned uranium mines, thus adding to the need to undertake this program. LM has entered into memoranda of understanding (MOUs) with the US Bureau of Land Management (BLM) and US Forest Service (USFS) to facilitate a better understanding of the scope of the problem posed by these mines. Currently, LM has executed MOUs with the BLM state offices in Colorado, New Mexico, Utah, and Wyoming and the USFS Rocky Mountain Region, which includes the national forests in Colorado, Wyoming, and South Dakota. This collaborative effort with partner agencies has led LM to develop a V and V Work Plan that describes the numerous activities and types of data to be collected at the mines. V and V activities verify actual mine location, collect coordinates of mining-related features, collect radiological data and soil samples, identify potential physical safety hazards, prioritize mines using a risk-based screening approach, and report the information to partner agencies. The partner agencies may use the reports to assess priorities and determine if any further action is warranted. The DRUM Program goals are to: - Improve data quality and content in the LM national inventory of abandoned uranium mines; - Conduct site-specific reconnaissance at mines for data verification and validation; - Exchange mine information with other federal agencies and state governments to help address mines presenting the greatest risks; - Develop reports for each mine that will contain a risk scoring assessment to help each agency develop priorities. The preliminary risk screening methodology was based on a joint effort between LM and BLM to develop factors that would be based on field observations, field data, and laboratory data using a multiple-lines-of-evidence approach. The multiple-lines-of-evidence assessment allows land managers the opportunity and flexibility to query specific criteria and make rankings based on specific priorities. The risk screening for each mine is based on evaluating the primary hazards of physical safety and risks to human health and several modifying factors that include accessibility and ecological/environmental risks. Gamma radiation scans are performed across the disturbed area of the mine, and soil samples are taken from waste rock piles and drainages, when applicable. This paper presents the results of performing inventory, environmental sampling, and risk ranking along with other accomplishments and lessons learned during the initial year of V and V activities and reporting. (authors)

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Pacific Northwest National Laboratory Facility Radionuclide Emission Points and Sampling Systems

Battelle–Pacific Northwest Division operates numerous research and development laboratories in Washington State. The U.S. Department of Energy (DOE) contracts to Battelle at Richland facilities on both the DOE Hanford Site and the Pacific Northwest National Laboratory (PNNL) Richland campus. These facilities have the potential for radionuclide air emissions. The PNNL contract with DOE also includes operations at the PNNL-Sequim campus in Sequim, where there is also the potential for radionuclide air emissions. This document is a periodic update that describes current PNNL facility emission units and sampling systems. The National Emission Standard for Hazardous Air Pollutants (NESHAP [40 Code of Federal Regulations 61, Subpart H]) requires an assessment of all emission units that have the potential for radionuclide air emissions. Emission units are registered with the State of Washington. Potential emissions from emission units are assessed annually by PNNL staff. Sampling, monitoring, and other regulatory compliance requirements are designated based on the potential to-emit dose criteria, a graded approach to facility-identified potential impact categories, and regulatory requirements. The purpose of this document is to describe the facility radionuclide air emission sampling program and provide current and historical facility emission unit system performance, operation, and design information. For sampled emission units, the building, exhaust unit, control technologies, and sample extraction details are provided. Additionally, applicable configuration drawings, figures, and photographs are included. For non-sampled emission units, emission estimation and radionuclide source details are provided. Site-wide permits for the lowest potential impact category are described. Deregistered/transitioned emission unit details are also provided as necessary for at least 5 years post-closure/transition. Currently, five emission units are sampled continuously for particulate radionuclides at PNNL managed facilities on the PNNL-Richland campus (3 of the 5) and on the Hanford Site (2 of the 5). Four of these units have sampling systems that comply with the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1–2011 standard for sampling from stacks and ducts of nuclear facilities, and the fifth is grandfathered and compliant with the older ANSI N13.1–1969 standard. In addition, the PNNL-managed Hanford Site 325 Building EP 325-01-S stack is sampled continuously for emissions of tritium. No emissions sampling is required for the single licensed emission unit on the PNNL-Sequim campus.

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