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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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At least 1,513 records · Page 84

Cybersecurity Center for Offshore Wind Energy (Final Project Report)

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models with SCADA infrastructure, and deployed a scaled physical turbine and associated sensors. High-resolution operational and side-channel data streams were collected and used to refine machine-learning (ML)-based attack detection systems and to extend the WindCRAFT framework to multi-turbine threat scenarios. The project demonstrated a realistic, scalable environment for evaluating cyber threats, validated attack detection approaches using enriched datasets, and identified new multi-turbine and inter-turbine communication attack vectors. The resulting testbed, models, and security mechanisms provide a foundation for ongoing R&D and deployment of cyber-resilient offshore wind energy systems.

17 WIND ENERGY↗

What we were asked to do

Recommendations are made after 32 interviews, lesson identification, lesson analysis, and mission characteristics identification. The major recommendations are as follows: (1) to develop end-to-end planning and scheduling operations concepts by mission class and to ensure their consideration in system life cycle documentation; (2) to create an organizational infrastructure at the Code 500 level, supported by a Directorate level steering committee with project representation, responsible for systems engineering of end-to-end planning and scheduling systems; (3) to develop and refine mission capabilities to assess impacts of early mission design decisions on planning and scheduling; and (4) to emphasize operational flexibility in the development of the Advanced Space Network, other institutional resources, external (e.g., project) capabilities and resources, operational software and support tools.

Source record↗

Software Testing and Verification in Climate Model Development

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Clune, Thomas L.↗

Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems

The Koopman operator has recently garnered much attention for its value in dynamical systems analysis and data-driven model discovery. However, its application has been hindered by the computational complexity of extended dynamic mode decomposition; this requires a combinatorially large basis set to adequately describe many nonlinear systems of interest, e.g. cyber-physical infrastructure systems, biological networks, social systems, and fluid dynamics. Often the dictionaries generated for these problems are manually curated, requiring domain-specific knowledge and painstaking tuning. In this paper we introduce a deep learning framework for learning Koopman operators of nonlinear dynamical systems. We show that this novel method automatically selects efficient deep dictionaries, outperforming state-of-the-art methods. We benchmark this method on partially observed nonlinear systems, including the glycolytic oscillator and show it is able to predict quantitatively 100 steps into the future, using only a single timepoint, and qualitative oscillatory behavior 400 steps into the future.

koopman operators, machine learning, deep learning↗

Developing An Autonomy Infusion Infrastructure for Robotic Exploration

Future robotic exploration missions will require autonomy in order to accomplish mission goals for operational efficiency and science return. For example, it will require three communication cycles for the Mars Exploration Rovers, Spirit and Opportunity, to place an instrument on a science target. Reducing this time necessitates highly accurate navigation, obstacle avoidance, target tracking, target analysis, manipulation, and fault diagnosis. Technologies to address these and other operational elements are currently being developed at NASA and within academia. However, infusion into missions has always been a difficult task for researchers. In order to keep risk down, mission managers are reluctant to include new technologies unless they have undergone extensive testing and verification under flight-realistic conditions. Furthermore, infusion of new technologies into missions is made more difficult by the variety of software frameworks under which these technologies are developed. Missions would like to see competing solutions demonstrated on a common platform so that they can compare performance and choose the solution best suited to their application.

Bualat, Maria G.↗

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗

Seismic isolation: A pathway to standardized advanced nuclear reactors

Standardizing advanced nuclear reactors is a pathway to substantially reducing their overnight capital cost and achieving parity with other power sources, including renewables and fossil fuels. The seismic load case has thwarted standardization of nuclear power plants because site-specific seismic hazard and local near-surface geology has triggered soil-structure-interaction analysis, design, equipment qualification, regulatory review, and licensing, ensuring that each build is different. To achieve standardized or site-independent certified advanced reactor designs, the impact of the seismic load case on the engineering and construction cost and time must be substantially mitigated. Seismic isolation is a mature technology that has been used for more than 30 years in non-nuclear sectors to substantially reduce earthquake demands in buildings and other infrastructure. In this paper, seismic isolation is used to enable standardization of advanced reactor designs, aimed at the complete re-use of a site-independent, certified design and repeated procurement of safety-class equipment. A pathway to standardized designs using seismic isolation is demonstrated for two fundamentally different advanced reactors: a molten salt reactor and a high temperature gas reactor. Each reactor building is equipped with three specialized pieces of safety-class equipment, namely, a reactor vessel, a steam generator, and a control rod drive mechanism housing that is attached to the reactor head. Analysis is performed per ASCE and ASME standards to design the buildings and the equipment for two base conditions: conventional (fixed base) and base isolated. The impact of the seismic load case is characterized for the reinforced concrete walls in the buildings and for the equipment, measured using vessel wall thickness and horizontal accelerations. Here the analysis results show that the fixed-base buildings, designed for a site of low seismic hazard (peak ground acceleration, PGA = 0.15 g) could be constructed at a site of much greater seismic hazard (PGA = 0.7 g) if seismic base isolation is employed. Importantly, the scope of the site-specific analysis, design, and qualification would be limited to the seismic isolators and the isolated substructure, drastically reducing plant-specific engineering, review, and licensing, and time to construction start. Regulatory challenges and opportunities with standardized reactor designs are identified.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Data mining of plug-in electric vehicles charging behavior using supply-side data

This paper aims to better understand the charging patterns of plug-in electric vehicles (PEVs) and identify factors that may significantly impact PEVs’ charging behavior. We collected 189,864 supply-side charging session data over 13 months from 821 charging stations in Illinois from ChargePoint. Through descriptive and regression analyses, we characterize the distributions of key charging behavior indicators, including charging location, dwell time, and battery start state of charge (SOC), and quantify the impacts of closely related factors on these charging behaviors. In this work, we find that: (1) PEVs are more likely to charge in the morning at multifamily commercial locations with a lower start SOC compared with single family residential locations; (2) Weekday and morning sessions are more likely to utilize workplace charging and have shorter dwell time compared with weekend and afternoon sessions; (3) Single family residential area and locations with Levels 1/2 chargers have a higher start SOC and longer dwell time compared with other locations and DC fast chargers (DCFCs). These findings provide policy insights to identify potential time and locations to incentivize PEVs for grid services, as well as identify critical location categories for further charging infrastructure investment to better reduce range anxiety and promote PEV adoption.

33 ADVANCED PROPULSION SYSTEMS↗

BigPanDA monitoring system evolution in the ATLAS Experiment

Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Paths to Sustainable Distributed Generation through 2050: Matching Local Waste Biomass Resources with Grid, Industrial, and Community Needs

This project identifies and evaluates current and future organic waste fuel types and matches these wastes with local grid, industrial, building power, and thermal energy needs. The team developed data on organic waste streams and thermal energy needs, and then constructed a techno-economic analysis model that can process the data and compute viable production of electricity, waste heat, biogas, and/or biomethane for a range of energy price points. Scenarios generated by the model include allocation of local organic waste streams to existing or new conversion infrastructure and are evaluated in a life-cycle assessment model to determine local and global environmental impacts. The project’s webbased tool provides rapid evaluation of potential waste-to-energy sites, including retrofits/expansions of existing facilities or entirely new construction, on the basis of resource availability, potential for waste heat use, and economic and environmental metrics.

09 BIOMASS FUELS↗

High Efficacy Validation of Hydride Mega Tanks at the ARIES Lab (HEVHY METAL)

The High Efficacy Validation of Hydride Mega Tanks at ARIES Lab (HEVHY METAL) project will advance materials-based hydrogen storage technologies by large-scale demonstration and identification of deployment pathways. This includes demonstrating how two metal hydride HY2MEGA subsystems are installed with megawatt-scale green hydrogen infrastructure; validating its performance via rates, capacities, and efficiencies; and investigating supply and demand side techno-economics.

ARIES↗

Non-Powered Dam Hydropower Development and Ranking Opportunity Tool

In pursuit of a net-zero-carbon emissions economy in the United States, non-powered dams (NPDs) represent a large opportunity to develop hydropower while leveraging existing infrastructure. With almost 600 NPD sites in the United States identified as having over 1 megawatt (MW) of potential capacity, only a small portion of the total potential capacity at these sites has been developed in recent years. , Conventional NPD retrofit feasibility analysis primarily focuses on the developer’s perspective but fails to consider the broader impacts of developing a dam, including on the neighboring communities. This tool, the Non-Powered Dam Hydropower Development and Ranking Opportunity Tool (NPD HYDRO), allows users to prioritize or rank NPD sites for future development based on user-defined priorities. Benefits can be evaluated in several categories: the grid, community, industry, and environment (referred to as the four impact scores in the tool as discussed in Section 2.2). In addition, the tool provides the user with a qualitative measure for the feasibility of adding energy storage during NPD conversion, specifically battery, hydrogen electrolysis, and pumped-storage hydropower (PSH). By taking a holistic approach to the potential range of benefits provided by NPD conversions with results tailored to the user’s priorities, NPD HYDRO provides the opportunity for national-level screening and enables users to focus on the sites that are most closely aligned with their interests.

13 HYDRO ENERGY↗

Federal Home-to-Work Electric Vehicle Program Guide

This document serves as a comprehensive resource for Federal agencies in developing their own program resources that promote the efficient and effective use of electric vehicles (EVs) for home-to-work travel while ensuring compliance with Federal regulations and sustainability objectives. One mission of the U.S. Department of Energy's Federal Energy Management Program (FEMP) Fleet program is to help federal fleet managers meet or exceed statutory requirements related to energy and environmental performance while improving overall fleet efficiency, reducing costs, and meeting mission requirements. To further this mission, FEMP provides resources to support Federal agencies with increasing alternative fuel vehicle (AFV) acquisitions and reducing petroleum use. EVs are AFVs and help agencies meet federal fleet requirements. Federal fleets include government-owned EVs used for home-to-work travel. The purpose of this document is to serve as a guide for Federal agencies in developing their own internal program documents to manage government-owned EVs used for home-to-work travel. Federal agencies should consult their counsel and consider their own policies and authorities in the implementation of any policies or best practices regarding government-owned EVs used for home-to-work travel. The guide provides key considerations for agencies, including launching a pilot program to fine-tune best practices, conducting a cost-benefit analysis to compare home versus public charging, and exploring cost-effective solutions, such as installing standard outlets instead of dedicated charging stations. The guide underscores the importance of legal and financial considerations, such as verifying agency authority to install home charging infrastructure at an employee's home, ensuring the availability and appropriateness of using agency funds for home charging infrastructure, and understanding the tax implications of reimbursements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Software agents for the dissemination of remote terrestrial sensing data

Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Toomey, Christopher N.↗

Promoting Lifelong Ocean Education: Shaping Tomorrow's Earth Stewards and the Science and Technology Workforce

The coming ocean observing systems provide an unprecedented opportunity to change both the public perception of our oceans, and to inspire, captivate and motivate our children, our young adults and even our fellow adults to pursue careers allied with the oceans and to become stewards of our Planet's last unexplored environment. Education plans for the operational component, the Integrated Ocean Observing System (IOOS), and for the research component, Ocean Research Interactive Observatory Networks (ORION), are designed to take advantage of this opportunity. In both cases, community recommendations were developed within the context of the following assumptions: 1. Utilize research on how people learn, especially the four-pronged model of simultaneous learner-centered, knowledge-center, assessment-centered and community-centered learning 2. Strive for maximum impact on national needs in science and technology learning 3. Build on the best of what is already in place 4. Pay special attention to quality, sustainability, and scalability of efforts 5. Use partnerships across federal, state and local government, academia, and industry. Community recommendations for 100s and ORION education have much in common and offer the opportunity to create a coherent education effort allied with ocean observing systems. Both efforts focus on developing the science and technology workforce of the future, and the science and technology literacy of the public within the context of the Earth system and the role of the oceans and Great Lakes in that system. Both also recognize that an organized education infrastructure that supports sustainability and scalability of education efforts is required if ocean observing education efforts are to achieve a small but measurable improvement in either of these areas. Efforts have begun to develop the education infrastructure by beginning to form a community of educators from existing ocean and aquatic education networks and by exploring needs and issues associated with using ocean observing information assets in education. Likewise efforts are underway to address workforce issues by a systematic analysis of current and future workforce and educational needs. These activities will be described as will upcoming opportunities for the community to participate in these efforts.

Meeson, Blanche↗

Future Nuisance Flooding in Norfolk, VA, From Astronomical Tides and Annual to Decadal Internal Climate Variability

Abstract Increasing sea level rise will lead to more instances of nuisance flooding along the Virginia coastline in the coming decades, causing road closures and deteriorating infrastructure. These minor flood events can be caused by astronomical tides alone, in addition to internal climate variability on annual to decadal timescales. An assessment of nuisance flooding from these two effects is presented up until the year2050 for Norfolk, Virginia. The analysis of water levels indicates that nuisance flooding from tides alone in conjunction with a medium-high sea level scenario will result in flooding beginning in 2030 with frequency increasing thereafter. The addition of climate variability, by use of an empirical mode decomposition, leads to a substantial increase of flooding relative to the tides-alone analysis and shows flood events beginning as soon as 2020. High tides in the future will produce nuisance flooding without the need of other drivers such as coastal storms.

Burgos, A. G.↗

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources. Here, a CO2-based ISRU recombinant protein producing bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Candidate organisms were selected by growth characterization on acetate and formic acid, carbon substrates that are synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Escherichia coli. Multiplex genetic modification in E. coli was facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance analysis from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA biomanufacturing in reduced-gravity environments.

biomanufacturing↗