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

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DOE OSTI2014

Selling an Energy Efficiency Loan Portfolio in Oregon: Resale of the Craft3 loan portfolio to Self-Help Credit Union

Under the Clean Energy Works (CEW) program, Craft3 developed a loan product that widened access to financing for homeowners, offered long term funding, and collected repayments through the customer?s utility bill. The program?s success led Craft3 to pursue the sale of the loan portfolio to both mitigate its own risks and replenish funds for lending. This sale breaks new ground for energy efficiency finance and is notable as it was completed even with many novel program design elements. It replenished Craft3?s program capital and uncovered some valuable lessons that may facilitate future transactions. However, the lack of data history and the unproven nature of the loan portfolio meant that Craft3 had to limit the risk of losses to Self-Help, the purchaser of the portfolio. It remains to be seen whether this experience will pave the way for more sales of on-bill energy efficiency loan portfolios. This case study illustrates how certain program design decisions can sometimes both facilitate programmatic objectives and possibly present challenges for the sale of a portfolio of energy efficiency loans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Strengthening LLNL Missions through Laboratory Directed Research and Development in High Performance Computing

High performance computing (HPC) has been a defining strength of Lawrence Livermore National Laboratory (LLNL) since its founding. Livermore scientists have designed and used some of the world’s most powerful computers to drive breakthroughs in nearly every mission area. Today, the Laboratory is recognized as a world leader in the application of HPC to complex science, technology, and engineering challenges. Most importantly, HPC has been integral to the National Nuclear Security Administration’s (NNSA’s) Stockpile Stewardship Program—designed to ensure the safety, security, and reliability of our nuclear deterrent without nuclear testing. A critical factor behind Lawrence Livermore’s preeminence in HPC is the ongoing investments made by the Laboratory Directed Research and Development (LDRD) Program in cutting-edge concepts to enable efficient utilization of these powerful machines. Congress established the LDRD Program in 1991 to maintain the technical vitality of the Department of Energy (DOE) national laboratories. Since then, LDRD has been, and continues to be, an essential tool for exploring anticipated needs that lie beyond the planning horizon of our programs and for attracting the next generation of talented visionaries. Through LDRD, Livermore researchers can examine future challenges, propose and explore innovative solutions, and deliver creative approaches to support our missions. The present scientific and technical strengths of the Laboratory are, in large part, a product of past LDRD investments in HPC. Here, we provide seven examples of LDRD projects from the past decade that have played a critical role in building LLNL’s HPC, computer science, mathematics, and data science research capabilities, and describe how they have impacted LLNL’s mission.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Computationally Efficient Control Co-Design Optimization Framework with Mixed-Fidelity Fluid and Structure Analysis: OpenTurbineCoDe (OTCD) - ARPA-E ATLANTIS Phase I Project (Final Technical Report)

The goal of the Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control (ATLANTIS) Program is to develop new technologies for floating offshore wind turbines, or wind farms, using the discipline of control co-design (CCD.) In this context, our goal is to develop a computationally efficient optimization framework for design of floating offshore wind turbines. Our specific aim is to utilize high-fidelity structural, aerodynamic, aero-structural tools, and to derive control-oriented reduced- or low-order models directly from the high-fidelity tools. We proposed a mixed-fidelity modeling approach which means that we are also using low- and mid-fidelity tools when necessary. This research is conducted by a multidisciplinary team consisting of Rutgers University, University of Michigan, Brigham Young University, and the National Renewable Energy Laboratory (NREL). The computational framework, called OpenTurbineCoDe, is designed to integrate, where possible, traditional structural, aerodynamic, aeroelastic models (e.g., OpenFAST) and advanced control algorithms with higher fidelity simulation tools including Reynolds-averaged Navier–Stokes (RANS) solvers, and three-dimensional structural finite element solvers. All the high-fidelity tools used in this research provide numerically exact gradients to facilitate both efficient optimization and local linearization for control implementation.

17 WIND ENERGY↗
DOE OSTI2021

Space Nuclear Thermal Propulsion Critical Assembly Boron Worth Experiments

The Space Nuclear Thermal Propulsion (SNTP) project was an attempt to create a more powerful and more efficient rocket engine utilizing nuclear technologies. As part of this project a zero-power critical assembly referred to as SNTPCX was designed and installed at Sandia National Laboratories. The SNTP-CX was a light water moderated particle bed reactor utilizing highly enriched uranium fuel in the form of UC particles. The SNTP-CX performed 142 runs covering numerous experiments from the year 1989 to 1992. The program was canceled in 1994 as the nation’s priorities shifted. Now these experiments are being evaluated for use as criticality safety benchmarks. Nineteen of the 142 reactor runs were dedicated to a series of experiments to calculate the worth of the boron used in the light water moderator. This series of experiments has been selected for further evaluation as a critical benchmark for the International Criticality Safety Benchmark Evaluation Project (ICSBEP).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Energy Efficient Clothes Dryer with IR Heating and Electrostatic Precipitator

The project goal was to develop a revolutionary energy saving technology for residential clothes drying. The team developed an IR (infrared) heating system and NESP (Nebulizer and Electro-Static Precipitator) for integration into a ventless clothes dryer. The proposed technology addresses two of the major inefficiencies in current electric vented dryers by providing effective energy transfer for the removal of the water and recapture of the vapor latent heat. The IR heaters operating in the mid wave (2.5-10um) are very efficient as they target the 3-micron peak absorption of the water molecule. This allows direct energy absorption, unlike conventional element heaters where heat is transferred by convection. The low power NESP removes water vapor from the exhausted stream and recaptures the latent heat in the ESP (Electro-Static Precipitator) exchanger section. This allows the warm dry air to be recirculated back into the drum for additional efficiency savings. The remaining majority of the dryer hardware stays the same. Summing the efficiency gain from the two subcomponents we anticipated the EF (Efficiency Factor) to exceed the goal of 4.04. EF is obtained by dividing the weight (lbs) of water removed by the energy (kWhr) used, where the test load size is 8.45 lbs of bone dry clothing wetted to 57.5% or 4.8lbs of water, and dried to a remaining moisture content of 2.5-5%. Additional benefits include not having to recondition (heat or cool) the large amounts of make-up air to replace the air exhausted by a vented dryer. It was anticipated that the NESP/heat exchanger would be the most challenging and highest risk element in the program. Therefore, the team focused their efforts during Phase 1 of the program on the design, construction, testing, and optimization of the NESP/heat exchanger. At the end Phase 1, the team compared the performance of the NESP/heat exchanger with the system level requirements and made a Go/No-Go decision on proceeding with the second portion of the program. Phase 2 of the program was structured to develop the IR heating system and then integrate it and the NESP/heat exchanger into a residential clothes dryer prototype for final testing. The proposed technology utilizes heat recovery which is known to have the biggest impact on dryer efficiency. The two current mainstream recovery approaches are air to air exchangers and heat pump condenser systems. Air to air exchanges can be very efficient but require large surface areas which are prone to fouling from uncaptured lint. Dryers based on heat pump condenser recovery systems have shown efficiency improvements of 20–60% and are commercially available. The issue with a heat pump condenser approach is the added cost, as typical prices are twice that of standard vented dryers and they are only available in small to medium capacities. The energy factor (EF) for these systems is 5.50 to 6.88 pounds/kWh compared to conventional dryers at 2.75 to 3.67 pounds/kWh. The efficiency improvements for the proposed technology come from the use of IR heating and the NESP. As the concept is in its infancy, and these improvements were difficult to predict without experimental data, assumptions were made based on available literature. IR radiant drying times, when compared to convection, are typically 30% less. This is a result of the fact that radiant energy heats directly and is absorbed at and below the surface, unlike convection heating, that must conduct the heat through the boundary film of air at the clothes surface and rely on wicking of the moisture to the surface. The second area of improvement comes from the NESP. The NESP operation is as follows: 1. Highly charged, micron sized, droplets of water are injected into the dryer exhaust by the Nebulizer. 2. These charged droplets attract water molecules and continue to grow in size, until losing their charge. During this process, latent heat is rejected back into the air stream. 3. The large droplets enter the ESP, where they are recharged and drawn to the ESP wall, to be extracted at the bottom of the ESP. The warm dry air is then recirculated back into the dryer. The proposed technology, at the time of the proposal submission was estimated to have an EF of 4.79. At program completion we have designed, built, tested, integrated and optimized the proposed technologies into a prototype “high efficiency” residential clothes dryer. Testing of the integrated prototype dryer provided insight into the technical effectiveness and economic feasibility of the proposed technologies. The program has the potential of greatly impacting energy savings. The predicted EF of the proposed technology is 4.79, yielding an energy savings of 42% when compared to conventional electric vented dryers. Given there are approximately 84 million dryers in the US consuming ~64 billion kWh per year, a net savings of 27 billion kWh per year or 0.092 quads could be realized. Since the dryer is not vented, make up air from the room is not needed, adding an additional savings of ~1kWh per load, or 23.8 billion kWh per year. In addition, it is envisioned that the proposed ESP, when successful, would potentially find applications in industrial and residential dehumidification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Survey on Efficient and Productive Use of Electricity In Women-Run Small Businesses in Uganda

In Uganda, women make up a large portion of the service sector, notably in informal small and micro businesses such as retail shops, food preparation, tailoring, sewing, beer brewing, basket weaving, healthcare, and hairdressing. Lawrence Berkeley National Laboratory (LBNL), and USAID, in partnership with the Clean Energy Enthusiasts (CEE), a local implementer in Uganda, designed and conducted a participatory survey to collect baseline data and information on the current state of benefits to energy access. The study included data on the uptake of efficient and productive electric (EPUE) equipment, business skills, and financial needs among small and mid-size women-led businesses in Uganda. The objective of the survey was to build evidence and identify economic activities where access to electricity has a positive impact on women’s empowerment by helping them develop new and existing businesses, improve productivity, and increase their income. The survey included questions about the type of electric equipment used and needed, electric consumption patterns, alternative sources to electricity, and business and capital barriers related to increased access. The survey results provided the basis for designing a training program tailored to the need of women entrepreneurs in the region.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗
DOE OSTI2026

qSIEVE: Efficient qLDPC Memory via Systolic Movement in Atom Arrays

As quantum machines have scaled up in their number of qubits, significant research has turned towards increasing their fidelity with quantum error correction codes. Although promising results have been shown with the surface code, which only requires near-neighbor connections between qubits, the high qubit overhead of such local codes promises to be problematic. Consequently, recent work has explored non-local quantum LDPC (qLDPC) codes, which have good asymptotic encoding rates. Despite theoretical progress, hardware implementations of these codes have been a longstanding challenge. At the experimental level, demonstrations of movement based communication on atom arrays suggest this is a powerful new primitive to achieve non-local connectivity. Leveraging this, we present a protocol for implementing non-local qLDPC codes in hardware. Our protocol, qSIEVE, is a co-design of such codes with movement in atom arrays. qSIEVE defines a restricted family of qLDPC codes that can be implemented efficiently with systolic movement. We then quantify the utility of qSIEVE in the context of a complete fault tolerant architecture. We compare the cost of implementing benchmark programs in a standard, surface code only architecture and a mixed architecture where data is stored in qLDPC memory with qSIEVE and loaded to surface codes for computation.

Quantum error correction↗
DOE OSTI2014

NREL/SCE High Penetration PV Integration Project: FY13 Annual Report

In 2010, the National Renewable Energy Laboratory (NREL), Southern California Edison (SCE), Quanta Technology, Satcon Technology Corporation, Electrical Distribution Design (EDD), and Clean Power Research (CPR) teamed to analyze the impacts of high penetration levels of photovoltaic (PV) systems interconnected onto the SCE distribution system. This project was designed specifically to benefit from the experience that SCE and the project team would gain during the installation of 500 megawatts (MW) of utility-scale PV systems (with 1-5 MW typical ratings) starting in 2010 and completing in 2015 within SCE's service territory through a program approved by the California Public Utility Commission (CPUC). This report provides the findings of the research completed under the project to date.

14 SOLAR ENERGY↗
DOE OSTI2015

Preliminary Framework for Human-Automation Collaboration

The Department of Energy’s Advanced Reactor Technologies Program sponsors research, development and deployment activities through its Next Generation Nuclear Plant, Advanced Reactor Concepts, and Advanced Small Modular Reactor (aSMR) Programs to promote safety, technical, economical, and environmental advancements of innovative Generation IV nuclear energy technologies. The Human Automation Collaboration (HAC) Research Project is located under the aSMR Program, which identifies developing advanced instrumentation and controls and human-machine interfaces as one of four key research areas. It is expected that the new nuclear power plant designs will employ technology significantly more advanced than the analog systems in the existing reactor fleet as well as utilizing automation to a greater extent. Moving towards more advanced technology and more automation does not necessary imply more efficient and safer operation of the plant. Instead, a number of concerns about how these technologies will affect human performance and the overall safety of the plant need to be addressed. More specifically, it is important to investigate how the operator and the automation work as a team to ensure effective and safe plant operation, also known as the human-automation collaboration (HAC). The focus of the HAC research is to understand how various characteristics of automation (such as its reliability, processes, and modes) effect an operator’s use and awareness of plant conditions. In other words, the research team investigates how to best design the collaboration between the operators and the automated systems in a manner that has the greatest positive impact on overall plant performance and reliability. This report addresses the Department of Energy milestone M4AT-15IN2302054, Complete Preliminary Framework for Human-Automation Collaboration, by discussing the two phased development of a preliminary HAC framework. The framework developed in the first phase was used as the basis for selecting topics to be investigated in more detail. The results and insights gained from the in-depth studies conducted during the second phase were used to revise the framework. This report describes the basis for the framework developed in phase 1, the changes made to the framework in phase 2, and the basis for the changes. Additional research needs are identified and presented in the last section of the report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Reevaluating the Thermal-Spectrum Molten Salt Breeder Reactor Fuel Cycle in a Modern Context [Slides]

Thermal-Spectrum Molten-Salt Breeder Reactors (TS-MSBRs) can have highly advantageous characteristics. There is potential for excellent safety, actinide resource utilization, proliferation resistance, waste generation, and exergy characteristics. Realizing advantageous characteristics derives from a combination of proper design/engineering and inherent properties. Grossly unacceptable properties are possible with poor design choices. TS-MSBR designs and technologies remain immature. The United States has not had a focused TS-MSBR program in nearly 50 years. TS-MSBRs have progressed due to: (1) technology development in related areas (fusion, materials, instrumentation); (2) general, worldwide molten-salt reactor (MSR) development activities; (3) molten-salt property measurement and evaluation; and (4) safety evaluation methods and performance-based, technology neutral licensing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Qualification of Digitized Legacy Fast Reactor Data

The Integral Fast Reactor (IFR) fuel compatibility test program (1984-1994) included a variety of fuel pin examinations conducted at the Hot Fuel Examination Facility (HFEF) and the Alpha-Gamma Hot Cell Facility (AGHCF). Hard copy data records of these examinations have been recovered, scanned, and preserved in PDF format. Many hard copy records are now qualified in accordance with an NRC-approved Quality Assurance Program Plan (QAPP), and there is an ongoing effort to qualify additional legacy records. This legacy fuel performance data is vital to support design and licensing of fast reactors with validation of state-of-the-art codes and advanced methods for design and analysis. Stakeholders can most easily utilize this data when the PDF scans have been converted into digital data tables. However, qualification of the scanned hard copy data does not qualify the digital data file resulting from the digitization of the data contained in the record; the subject matter expert (SME) must make a review of the digitized data table as well before it can be designated as qualified. This report outlines a peer review process to qualify the digital data file(s), typically in CSV format, corresponding to hard copy records in accordance with the existing QAPP.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Status of 1eNp0π Charged-Current Electron Neutrino Cross Section on Argon in the NuMI Beam at ICARUS

The Short-Baseline Neutrino (SBN) Program is designed to probe short-baseline neutrino anomalies, including the LSND electron neutrino excess and the MiniBooNE low-energy excess. Essential to interpreting these anomalies and to the success of future experiments like DUNE, is the precise measurement of neutrino-argon interaction cross sections. The program utilizes two liquid argon time projection chamber (LArTPC) detectors: the Short-Baseline Near Detector (SBND) located 110 meters downstream from the Booster Neutrino Beam (BNB) target, and the ICARUS detector positioned 600 meters downstream. Additionally, the ICARUS detector lies off-axis to the NuMI beamline, providing a unique, high-statistics flux of electron neutrinos and sensitivity to energies that overlap with the DUNE spectrum. To analyze the data from these detectors, we have begun employing a machine-learning-based reconstruction algorithm referred to as “Scalable Particle Imaging with Neural Embeddings” (SPINE). SPINE has shown improvement in the ability to reconstruct the properties of final state particles in the detector, like the particle ID and momentum, with the potential to enhance the quality of measurements achievable within the SBN Program e.g., the resolution on kinematics used in differential cross section extraction. This poster presents progress toward measuring the electron neutrino argon interaction cross section in the 1eNp0π topology using the NuMI beam, highlighting the impact of SPINE through the ability to select signal events across a wide kinematic range without sacrificing background rejection power.

Carber, Dan [Colorado State U.] (ORCID:00090006451↗
DOE OSTI2021

Integrated Energy Systems Program Management Plan

In 2012, the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) initiated the Nuclear Energy Enabling Technology Program, which includes the Crosscutting Technology Development (CTD) portfolio of subprograms, to conduct research, development, and demonstration (RD&D) to support existing, new and advanced reactor designs and fuel cycle technologies. This program plan describes the Integrated Energy Systems (IES) Program, an element of the CTD portfolio since 2016 that seeks to improve the economic competitiveness, efficiency and environmental performance of nuclear energy systems by expanding their potential application space beyond electricity and optimizing their utilization in the context of the larger U.S. electric and non-electric energy system.

08 HYDROGEN↗
DOE OSTI2016

Assessing Government and Industry Roles to Accelerate Commercialization of Advanced Reactors and Supporting Fuel Cycles

Recent growth in private sector interest and investment in advanced reactor designs signals a new period in the greater than six decade pursuit of commercial nuclear technology. This nuclear entrepreneurship is primarily centered in the North America; meanwhile, national programs in China, France, India, Russia, and South Korea also feature active efforts to design, construct, operate and export advanced reactors .The business case for most private ventures calls for an aggressive commercialization timeline-tied to expectations for returns on investment. Finally, strategic energy portfolio projections and utility resource planning point to the 2030 - 2050 window as the period of greatest need for dispatchable, energy intensive, low-carbon generation options to address retirement of baseload capacity, increased penetration of renewables and economy-scale decarbonization. However, lead times for commercialization range from 30 to 50 years based on more traditional government-centric timelines. Fuel development and fuel cycle infrastructure deployment represent parallel timelines that directly influence the timeline for commercialization of many advanced reactor concepts. While multi-decade development periods appear to be commonplace for new nuclear projects, such timelines were not always the norm-three separate countries set out to develop civilian commercial power from fundamental nuclear principles, in just over a decade, on average. The US led light-water reactor (LWR) development in the 1950's, the UK pioneered a gas-cooled reactor (GCR) concept in the same time period, and Canada forged the path to commercializing the heavy-water reactor (HWR) starting in the mid-1950's and into the mid-1960's. The necessary fuel cycle facilities to support the commercial reactor design also did not appear suddenly, but were a collaborative effort between government and private partners. In this paper, the efforts of these three governments and their private industry partnerships in reactor and fuel cycle development are explored, and a select sample of representative milestones for each is presented, with the roles that each group played. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Precursor Analysis Report: Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022

The Industroyer2 and Wiper Malware Targeting Ukrainian Energy Provider 2022 Precursor Analysis Report leverages publicly available information about the Industroyer2 cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. An adversary attempted to cause a blackout in Ukraine in April 2022 by using the Industroyer2 malware against a regional Ukrainian energy provider. The adversary targeted eight high-voltage electrical substations and utilized the malware in tandem with disk wipers for Windows, Linux, and Solaris operating systems in an attempt to make response and recovery efforts more difficult. The adversary reused a piece of the original Industroyer malware designed to open circuit breakers and de-energize target substations. The adversary gained initial access to the victim’s enterprise network through unknown means in February 2022 and was able to perform reconnaissance, pivot to the operations network, and reside in the system for at least 51 days. This gave the adversary a detailed understanding of the environment and allowed them to customize the Industroyer2 malware to the victim’s operations network. However, defenders detected and stopped the attack before the adversary could achieve their intended impact. Had the Industroyer2 attack been successful, it could have caused a blackout for more than two million people during the early stages of Russia’s invasion of Ukraine. Researchers and analysts identified 22 unique techniques (used in a sequence of 31 steps) utilized during the attack with a total of 297 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-three of the identified techniques used during the Industroyer2 cyber attack were precursors to the triggering event. Analysis identified 224 observables associated with these precursor techniques, 122 of which were assessed to have an increased likelihood of being perceived in the 51 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗