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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Final Technical Report – DOE Grant DE-SC0005904

DOE grant DE-SC0005904 was allocated to fund the faculty development, curriculum development and travel to support the four institutions of the Connecticut State University System’s (CSUS) Initiative for Nanotechnology-related Equipment, Faculty Development and Curriculum Development. DOE grant DE-SC0005072 was also awarded for this program. In 2010, CSUS had identified the establishment of nanotechnology programs and infrastructure as a priority. At that time, the system set the goal of establishing an academic initiative in nanotechnology for the CSUS, beginning with the development of a series of courses at the graduate level. Implementation was planned via a collaborative effort including faculty from all four of the CSUS campuses. The CSUS Nanotechnology Working Group [CSUS NWG] was established to accomplish this goal. A faculty member from the Physics Department at Southern Connecticut State University [SCSU] was assigned the task of organizing and coordinating the work of the CSUS NWG. Representatives from each of the four CSUS campuses were appointed to join the CSUS NWG with the following initial representation: SCSU [Physics and Biology], Western Connecticut State University (WCSU) [Chemistry], Eastern Connecticut State University (ECSU) [Chemistry] and Central Connecticut State University (CCSU) [Chemistry. As a further outcome it was determined that this collaborative effort would lead to the establishment of a formal nanotechnology center, serving as the nucleus of CSUS student and faculty learning and research. This CSUS Nanotechnology Center [CSUS-NC] was to be located at Southern Connecticut State University (SCSU). The goal of this grant was to provide funding for curriculum and faculty development necessary to facilitate the development and implementation of a collaborative Graduate Certificate in Nanotechnology for the Connecticut State University System. This outcome has been successfully achieved. The courses and structure of the Graduate Certificate program have been developed and approved and the program will be completely implemented in the fall of 2013. The Nanotechnology Center will be recognized as the CSCU Center for Nanotechnology and will thus impact both the CSUS and Connecticut Community College Systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

H-Canyon Ventilation System Exhaust Tunnel Inspection at the Savannah River Site - 18052

The Department of Energy (DOE) H-Canyon Facility at the Savannah River Site (SRS) is operated by Savannah River Nuclear Solutions (SRNS). The Facility Structural Integrity Program (SIP) performs periodic visual inspections to confirm the component is capable of performing its safety function. This Program provides the process to document the conditions of safety related structural systems and components, their damage mechanisms, and recommend repairs if required before there is impact on the safety envelope. The H-Canyon Exhaust Tunnel is part of the H-Canyon Exhaust Ventilation System and is periodically inspected under the Structural Integrity Program. The Tunnel performs a Safety Class passive design feature function that is available 100% of the time. The Tunnel directs Canyon process air from the Canyon to the Sand Filter System. The radiological and chemical airborne activity coupled with the physical configuration of the tunnel precludes a manned entry into the tunnel. Tunnel inspections have been performed using cameras on a stick, referred to as pole cameras prior to CY2003. Since CY2003, five camera equipped crawlers have been used with varying levels of inspection success. With each successive crawler inspection, expectations have increased to perform tasks beyond visual examinations. The 2017 crawler performed the visual inspection but also included improvements on crawler performance, such as testing the use of wireless capability and remediation of crawler travel route, to the addition of stationary cameras and lighting at key locations. The latest 2017 crawler successfully traveled the entire length of the tunnel between the Canyon and Sand Filter System for the second time since development, thus providing key visual data for the integrity program [2]. In addition, several access ports were installed in 2017 following the removal of concrete core samples that allow for new visual inspection of the Canyon Crossover tunnel, thus providing information for an area that was generally inaccessible for monitoring. Planning for the 2019 crawler inspection is underway with the expectations to improve upon inspection cameras and also introduce mapping technologies such as LIDAR. The challenge to obtain meaningful data from the remote inspections of a 60+ year operating Canyon Exhaust tunnel continues to be a complex endeavor requiring close coordination of multiple organizations, adherence to Conduct of Operations, Radiological Safety, Worker Safety, etc. principles as well as alignment with Facility Safety Basis requirements. This paper discusses the continuing improvements in inspection techniques and the challenges associated these inspections. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

System and method for hardware scheduling of conditional barriers and impatient barriers

A method and a system are provided for hardware scheduling of barrier instructions. Execution of a plurality of threads to process instructions of a program that includes a barrier instruction is initiated, and when each thread reaches the barrier instruction during execution of program, it is determined whether the thread participates in the barrier instruction. The threads that participate in the barrier instruction are then serially executed to process one or more instructions of the program that follow the barrier instruction. A method and system are also provided for impatient scheduling of barrier instructions. When a portion of the threads that is greater than a minimum number of threads and less than all of the threads in the plurality of threads reaches the barrier instruction each of the threads in the portion is serially executed to process one or more instructions of the program that follow the barrier instruction.

Lindholm, John Erik↗
DOE OSTI2014

Bootstrapping mixed correlators in the 3D Ising model

We study the conformal bootstrap for systems of correlators involving nonidentical operators. The constraints of crossing symmetry and unitarity for such mixed correlators can be phrased in the language of semidefinite programming. We apply this formalism to the simplest system of mixed correlators in 3D CFTs with a Z 2 global symmetry. For the leading Z 2 -odd operator σ and Z 2 -even operator ϵ, we obtain numerical constraints on the allowed dimensions (Δ σ , Δ ϵ ) assuming that σ and ϵ are the only relevant scalars in the theory. These constraints yield a small closed region in (Δ σ , Δ ϵ ) space compatible with the known values in the 3D Ising CFT.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗
DOE OSTI2024

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

American Recovery and Reinvestment Act of 2009: Final Report on Customer Acceptance, Retention, and Response to Time-Based Rates from Consumer Behavior Studies

Time-based rate programs, enabled by utility investments in advanced metering infrastructure (AMI), are increasingly being considered by utilities as tools to reduce peak demand and enable customers to better manage consumption and costs. Under the Smart Grid Investment Grant Program (SGIG), the U.S. Department of Energy (DOE) partnered with several electric utilities to conduct consumer behavior studies (CBS). The goals involved applying randomized and controlled experimental designs for estimating customer responses more precisely and credibly to advance understanding of time-based rates and customer systems, and provide new information for improving program designs, implementation strategies, and evaluations. The intent was to produce more robust and credible analysis of impacts, costs, benefits, and lessons learned and assist utility and regulatory decision makers in evaluating investment opportunities involving time-based rates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions

Energy efficiency (EE) and demand response (DR) resources provide important utility system and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures and technologies (as well as other distributed energy resources) as a strategic approach to improve their collective cost-effectiveness and performance. However, the specific EE and DR features that may be best integrated, the interplay between changing EE and DR resource potential, and the resulting utility system impacts, are not well understood. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics (e.g., presence of controls, building type, and targeted end use) in the context of different system conditions (e.g., peak demand, load-building periods during high renewable generation output). Ultimately, the framework defines EE and DR interactions not only by the change in discretionary load (i.e., DR potential) but also by the change in likelihood of participation in EE and DR programs—as well as the change in system need for, and the overall availability of, EE and DR resources. The framework is intended to improve the integration of EE and DR in utility operational and planning activities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Extraction of Uranium from Seawater: Design and Testing of a Symbiotic System (Final Report)

The U.S. Department of Energy in October 2014 awarded the Massachusetts Institute of Technology (MIT) a Nuclear Energy University Program grant (DE-NE0008268) to investigate the design and testing of a symbiotic system to harvest uranium from seawater. As defined in the proposal, the goals for the project are: 1. Address the design of machines for seawater uranium mining. 2. Develop design rules for a uranium harvesting system that would be integrated into an offshore wind power tower. 3. Fabricate a 1/50th size scale prototype for bench and pool-testing to verify initial analysis and theory. 4. Design, build, and test a second 1/10th size scale prototype in the ocean for more comprehensive testing and validation. This report describes work done as part of DE-NE0008268 from 10/01/2014 to 11/30/2017 entitled, “Extraction of Uranium from Seawater: Design and Testing of a Symbiotic System.” This effort is part of the Seawater Uranium Recovery Program. This report details the publications and presentations to date on the project, an introduction to the project’s goals and background research into previous work done to achieve these goals thus far. From there, the report describes an algorithm developed during the project used to optimize the adsorption of uranium by changing mechanical parameters such as immersion time and adsorbent reuses is described. Next, a design tool developed as part of the project to determine the global feasibility of symbiotic uranium harvesting systems. Additionally, the report details work done on shell enclosures for uranium adsorption. Moving on, the results from the design, building, and testing of a 1/50th physical scale prototype of a highly feasible symbiotic uranium harvester is described. Then, the report describes the results from flume experiment used to determine the affect of enclosure shells on the uptake of uranium by the adsorbent they enclose. From there the report details the design of a Symbiotic Machine for Ocean uRanium Extraction (SMORE). Next, the results of the 1/10th scale physical scale prototype of a highly feasible symbiotic uranium harvester are presented. The report then details the design and results of an experiment to examine the hydrodynamic effects of a uranium harvester on the offshore wind turbine it is attached to using a 1/150th Froude scale tow tank test. Finally, the report details the results of an initial cost-analysis for the production of uranium from seawater from such a symbiotic device.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

LLNL SFA OBER FY23 Program Management and Performance Report: BioGeoChemistry at Interfaces

The focus of the BioGeoChemistry at Interfaces SFA has been to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach has included: (1) Field Studies that capture actinide behavior on the timescale of decades (Research Thrust 1), and (2) Fundamental Laboratory Studies that isolate specific biogeochemical processes observed in the field (Research Thrust 2). These Research Thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory, allowing the BioGeoChemistry at Interfaces SFA to advance our understanding of actinide migration behavior in the environment, and serve as a resource for environmental radiochemistry research internationally (Figure 1). In FY23, our SFA research focused on transient redox gradients across stratified waters, sediment-water interfaces, and mineral-water interfaces to address processes controlling cycling of redox-sensitive metals. Nevertheless, Research Thrusts 1 and 2 are guided by the following broad central hypotheses that were developed during our last program review held at the end of FY18: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limits their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides and other radionuclides (e.g. Cs) and provide DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites. More broadly, we are improving our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. While we retained some of our historical focus on actinide biogeochemistry this past fiscal year, biogeochemical processes occurring at unique Test Bed locations associated with this SFA provide fundamental information on abiotic and biotic redox processes that control the cycling of redox sensitive metals under dynamic and transient conditions. Furthermore, in collaboration with SFA teams at Argonne National Laboratory, our SFA has begun to transition away from the current research focus and develop a new research program in terrestrial wetland systems. The Terrestrial Wetland Function and Resilience SFA program plan will be delivered to the Environmental System Science (ESS) program within BER at the end of FY23.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Assessment of Condition Monitoring Methods and Technologies for Inservice Inspection and Testing of Nuclear Power Plant Components

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to explore the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components. The advanced technologies considered in this work are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), physics-based models, and digital twins (DT). The interest in the application of advanced technologies for condition monitoring in nuclear power plants continues to grow, and current and future licensees are expected to implement advanced technologies as part of their inservice inspection (ISI) and inservice testing (IST) programs. This report delineates the outcomes of an exploratory investigation into the implementation of advanced condition monitoring technologies to address ISI and IST requirements. A thorough review was conducted of the existing regulatory requirements for ISI and IST, along with an analysis of associated industry practices. Additionally, a state-of-the-art assessment was performed on advanced condition monitoring technologies frequently employed in non-nuclear sectors. This research incorporated two nuclear-specific case studies to illustrate the application of these technologies within the current nuclear fleet. The report provides an exhaustive discussion on the technical challenges, considerations, and opportunities associated with the deployment of advanced condition monitoring technologies. The following are key considerations in the application of advanced technologies for the ISI and IST of nuclear power plant components: • Developing adequate verification and validation procedures to confirm the functional and non-functional requirements, • Developing technical capabilities to conduct real-time asset condition monitoring, • Establishing guidance and protocol for modeling and simulation tools to continuously meet regulatory requirements, • Addressing trustworthiness, explainability, and interpretability of ML/AI methods, • Evaluating maintenance activities to maintain an adequate safety margin and avoid undesirable conditions, • Establishing cybersecure condition monitoring programs associated with a computer-based software system, and • Establishing standardized evaluation metrics for advanced condition monitoring programs. Interest in the use of advanced technologies for condition monitoring in ISI and IST programs continues to grow, and the technology is expected to experience rapid and wide industry adoption in the near future. Adoption of advanced technologies for condition monitoring could have novel and unique impacts on regulatory activities associated with ISI and IST programs. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of ISI and IST programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

A Full Demand Response Model in Co-Optimized Energy and

It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

bidding mechanism↗
DOE OSTI2025

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗
DOE OSTI2016

Electric Grid Expansion Planning with High Levels of Variable Generation

Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind power across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long distance in the EI system. Incorporating more details of renewables in expansion planning will inevitably increase the computational burden. Therefore, high performance computing (HPC) techniques are urgently needed for power system operation and planning optimization. As a scoping study task, this project tested some preliminary parallel computation techniques such as breaking down the simulation task into several sub-tasks based on chronology splitting or sample splitting, and then assigning these sub-tasks to different cores. Testing results show significant time reduction when a simulation task is split into several sub-tasks for parallel execution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Energy Efficiency and Conservation Block Grant (EECBG)- Better Buildings Neighborhood Program Final Report

The original BetterBuildings for Greensboro grant program included an outreach campaign to inform 100% of the Greensboro community about the benefits of reducing energy use; a plan to reduce energy consumption in at least 34% of the homes and 10% of the other buildings in the east Greensboro target area; and a plan to create and retain jobs in the energy conservation industry. Under the original program structure the City of Greensboro planned to partner with local and regional lenders to create a diversified portfolio of loan products to meet the needs of various income levels and building types. All participants would participate in the loan programs as a method of meeting the program’s 5 to1 private capital match/leverage requirements. In June 2011 the program was restructured to include partnerships with large commercial and multifamily projects, with these partners providing the greater portion of the required match/leverage. The geographic focus was revised to include reducing energy consumption across the entire City of Greensboro, targeting neighborhoods with high concentrations of low-moderate income households and aged housing stock. The community outreach component used a neighborhood-based approach to train community residents and volunteers to conduct door-to-door neighborhood sweeps; delivered high quality information on available program resources; helped residents to evaluate alternative energy efficiency measures and alternative financing sources; assisted with contractor selections and monitoring/evaluation of work; coordinated activities with BetterBuildings program partners; and collected data required by the Department of Energy. Additionally, HERO (Home Energy Response Officers) delivered intro packages (energy efficiency information and products) to thousands of households at the initial point of contact. A pilot program (Early Adopters) was offered from March 1, 2011 through June 30, 2011. The Early Adopters program was designed to offer immediate assistance to property owners ready and able to make their homes more energy efficient, by offering a rebate on their energy assessment and on the cost of upgrades installed. Eligible energy efficient upgrades were inclusive of basic level insulating and weather-stripping, HVAC system and water heater upgrades, to whole home upgrades that include the replacement of windows, doors and appliances. Renewable energy systems such as solar hot water systems were also eligible for the rebate program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Extensions to the SENSEI In situ Framework for Heterogeneous Architectures

The proliferation of GPUs and accelerators in recent supercomputing systems, so called heterogeneous architectures, has led to increased complexity in execution environments and programming models as well as to deeper memory hierarchies on these systems. In this work, we discuss challenges that arise in in situ code coupling on these heterogeneous architectures. In particular, we present data and execution model extensions to the SENSEI in situ framework that are targeted at the effective use of systems with heterogeneous architectures. We then use these new data and execution model extensions to investigate several in situ placement and execution configurations and to analyze the impact these choices have on overall performance.

Loring, Burlen↗
DOE OSTI2023

Environmental Protection Coating System for Refractory Metal Alloys (EPCS for RMAs)

As part of ARPA-E’s Ultra High Temperature Impervious Materials Advancing Turbine Efficiency (UITIMATE) program, this project aims to develop an environmental protection coating system (EPCS) for refractory metal alloys (RMAs) – which will provide radical improvement in long term protection for ultra-high temperature refractory metal components in harsh gas-turbine environments. The drive for higher fuel efficiency and higher core power of gas turbines used in electric power generation and in aircraft propulsion requires higher peak operation temperatures. The temperature capability of state-of-the-art materials cannot meet the new requirements. Refractory metal alloys have desirable capabilities for achieving the required peak temperatures, but most of them are subject to oxidation in the gas turbine environment. Thus, there is a strong need to develop novel environmental protective coatings that enable the refractory metals to operate in an ultra-high temperature engine environment. This project is composed of four major technical innovations that can provide a potentially transformational solution in providing environmental protection for refractory metal alloys over a wide range of temperature. 1) Multi-layer self-healing environmental barrier coating (EBC) that provides protection against combustion gas environment. 2) Oxidation resistant diffusion barrier (DB) on the alloy surface to enhance coating stability. 3) Synergistic integration of the multi-layer self-healing EBC with the diffusion barrier to extend coating life. 4) Guidance of physics-based modeling to accelerate coating development and optimization. Our team has successfully developed a multi-layer self-healing environmental protection coating system (EPCS) that can provide oxidation protection for commercially available molybdenum based refractory metal alloys over a wide temperature range of up to 1600 °C for fuel-efficient gas turbine applications. The team also developed a multi-layer high temperature coating design tool to accelerate coating development and optimization based on physics-based modeling. The team also engaged RTX business unite, notable Pratt and Whitney, for future commercialization of this technology. The successful completion of this Phase I effort led to the selection of performing Phase II of the program. In Phase II, the team plans to apply the EPCS in the protection of a newly discovered molybdenum-based metal alloy which has the potential of superior high temperature properties to the commercial products. Th coating will be evaluated under test conditions and environment that mimic gas turbine operation.

36 MATERIALS SCIENCE↗