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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

NASA Tech Briefs, June 2014

Topics include: Real-Time Minimization of Tracking Error for Aircraft Systems; Detecting an Extreme Minority Class in Hyperspectral Data Using Machine Learning; KSC Spaceport Weather Data Archive; Visualizing Acquisition, Processing, and Network Statistics Through Database Queries; Simulating Data Flow via Multiple Secure Connections; Systems and Services for Near-Real-Time Web Access to NPP Data; CCSDS Telemetry Decoder VHDL Core; Thermal Response of a High-Power Switch to Short Pulses; Solar Panel and System Design to Reduce Heating and Optimize Corridors for Lower-Risk Planetary Aerobraking; Low-Cost, Very Large Diamond-Turned Metal Mirror; Very-High-Load-Capacity Air Bearing Spindle for Large Diamond Turning Machines; Elevated-Temperature, Highly Emissive Coating for Energy Dissipation of Large Surfaces; Catalyst for Treatment and Control of Post-Combustion Emissions; Thermally Activated Crack Healing Mechanism for Metallic Materials; Subsurface Imaging of Nanocomposites; Self-Healing Glass Sealants for Solid Oxide Fuel Cells and Electrolyzer Cells; Micromachined Thermopile Arrays with Novel Thermo - electric Materials; Low-Cost, High-Performance MMOD Shielding; Head-Mounted Display Latency Measurement Rig; Workspace-Safe Operation of a Force- or Impedance-Controlled Robot; Cryogenic Mixing Pump with No Moving Parts; Seal Design Feature for Redundancy Verification; Dexterous Humanoid Robot; Tethered Vehicle Control and Tracking System; Lunar Organic Waste Reformer; Digital Laser Frequency Stabilization via Cavity Locking Employing Low-Frequency Direct Modulation; Deep UV Discharge Lamps in Capillary Quartz Tubes with Light Output Coupled to an Optical Fiber; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems, Version II; Advanced Sensor Technology for Algal Biotechnology; High-Speed Spectral Mapper; "Ascent - Commemorating Shuttle" - A NASA Film and Multimedia Project DVD; High-Pressure, Reduced-Kinetics Mechanism for N-Hexadecane Oxidation; Method of Error Floor Mitigation in Low-Density Parity-Check Codes; X-Ray Flaw Size Parameter for POD Studies; Large Eddy Simulation Composition Equations for Two-Phase Fully Multicomponent Turbulent Flows; Scheduling Targeted and Mapping Observations with State, Resource, and Timing Constraints;

Source record↗
NASA NTRS2013

System for Suppressing Vibration in Turbomachine Components

Disclosed is a system for suppressing vibration and noise mitigation in structures such as blades in turbomachinery. The system includes flexible piezoelectric patches which are secured on or imbedded in turbomachinery blades which, in one embodiment, comprises eight (8) fan blades. The system further includes a capacitor plate coupler and a power transfer apparatus, which may both be arranged into one assembly, that respectively transfer data and power. Each of the capacitive plate coupler and power transfer apparatus is configured so that one part is attached to a fixed member while another part is attached to a rotatable member with an air gap there between. The system still further includes a processor that has 16 channels, eight of which serve as sensor channels, and the remaining eight, serving as actuation channels. The processor collects and analyzes the sensor signals and, in turn, outputs corrective signals for vibration/noise suppression of the turbine blades.

Morrison, Carlos R.↗
NASA NTRS2010

Spacecraft Power Source Installation at Launch Complex

For certain space missions, an assembly must be integrated onto the spacecraft as late as possible in the launch vehicle processing flow. 12This late integration can be driven for a variety of reasons including thermal or hazardous materials constraints. This paper discusses the process of integrating an assembly onto a spacecraft as late as one week prior to the opening of the launch window. Consideration is given to achieving sufficient access for hardware integration, methods of remotely securing hardware to the spacecraft, maintaining spacecraft cleanliness throughout the integration process, and electrically integrating the component to the spacecraft. Specific examples are taken from the remote mechanical, electrical, and fluid cooling system integration of the power source onto the Mars Science Laboratory (MSL) Rover at the Atlas V Vertical Integration Facility (VIF) at Cape Canaveral Air Force Station, Florida.

Lytal, Paul↗
DOE OSTI2023

Cyber threat assessment of machine learning driven autonomous control systems of nuclear power plants

We report advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)-based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber–physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Scalable Stochastic Transmission Expansion: A Use Case for ExaSGD

The intermittent nature of renewable energy poses new challenges for power grids due to its variable and un- certain power output. These features of renewable generation are becoming more relevant to transmission planning as grids reach higher penetration levels of renewable energy. In this paper we present an approach for transmission planning based on scalable computational approaches which enable the explicit consideration of operational uncertainties in the planning process. Using three-stage stochastic programming and the progressive hedging algorithm, we compute transmission expansion decisions on a modified RTS-GMLC test system. We augment the grid with large amounts of wind generation and consider many operational scenarios subject to wind uncertainty. This is an example of a possible use of the ExaSGD security constrained AC optimal power flow solver.

Exascale Computing Project↗
DOE OSTI2023

Cyber-Physical Power Systems Protection: The Byzantine Cybersecurity Framework

Cybersecurity of smart grids have been topic of much interest in recent years. As this critical infrastructure operation increases dependency on automated processes and controls, exposure to cyber-physical threats become inevitable. Considering cyber-physical security of the grid, much focus of attention has been made towards smart grids real-time monitoring solutions, including the state estimation process. Analyzing the relevant literature, one can note though that seldom research has been done on cyber-physical security of smart grids protection systems. Protection systems have intangible value towards grid reliability. This paper presents a cybersecurity framework for smart grids protection systems. A physics-based inspired machine learning solution is at the core process of the framework. Processed relay inputs and outputs are used by a deep predictive coding network. Formal models, a quasi-static state estimator, provides an oracle when low confidence decision is reached. Evolving knowledge is derived through reinforcement learning. Implementation aspects considering the Pacific Northwest National Laboratory Electricity Infrastructure Operations Center are presented. Built as an extra control layer to protection systems, without hard-to-derive parameters, highlights potential aspects towards real-life applications.

Bretas, Arturo Suman↗
DOE OSTI2022

Cybersecurity for Electric Vehicle Charging Infrastructure

As the U.S. electrifies the transportation sector, cyberattacks targeting vehicle charging could impact several critical infrastructure sectors including power systems, manufacturing, medical services, and agriculture. This is a growing area of concern as charging stations increase power delivery capabilities and must communicate to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid operator communication systems could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks — or public perception of such — would ripple across the industry and produce lasting effects. Unfortunately, there is currently no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured inter faces. Comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project provided the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team created a cybersecurity threat model and performed a technical risk assessment of EVSE assets across multiple manufacturers and vendors, so that automotive, charging, and utility stakeholders could better protect customers, vehicles, and power systems in the face of new cyber threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2011

Hybrid Power Management-Based Vehicle Architecture

Hybrid Power Management (HPM) is the integration of diverse, state-of-the-art power devices in an optimal configuration for space and terrestrial applications (s ee figure). The appropriate application and control of the various power devices significantly improves overall system performance and efficiency. The basic vehicle architecture consists of a primary power source, and possibly other power sources, that provides all power to a common energy storage system that is used to power the drive motors and vehicle accessory systems. This architecture also provides power as an emergency power system. Each component is independent, permitting it to be optimized for its intended purpose. The key element of HPM is the energy storage system. All generated power is sent to the energy storage system, and all loads derive their power from that system. This can significantly reduce the power requirement of the primary power source, while increasing the vehicle reliability. Ultracapacitors are ideal for an HPM-based energy storage system due to their exceptionally long cycle life, high reliability, high efficiency, high power density, and excellent low-temperature performance. Multiple power sources and multiple loads are easily incorporated into an HPM-based vehicle. A gas turbine is a good primary power source because of its high efficiency, high power density, long life, high reliability, and ability to operate on a wide range of fuels. An HPM controller maintains optimal control over each vehicle component. This flexible operating system can be applied to all vehicles to considerably improve vehicle efficiency, reliability, safety, security, and performance. The HPM-based vehicle architecture has many advantages over conventional vehicle architectures. Ultracapacitors have a much longer cycle life than batteries, which greatly improves system reliability, reduces life-of-system costs, and reduces environmental impact as ultracapacitors will probably never need to be replaced and disposed of. The environmentally safe ultracapacitor components reduce disposal concerns, and their recyclable nature reduces the environmental impact. High ultracapacitor power density provides high power during surges, and the ability to absorb high power during recharging. Ultracapacitors are extremely efficient in capturing recharging energy, are rugged, reliable, maintenance-free, have excellent lowtemperature characteristic, provide consistent performance over time, and promote safety as they can be left indefinitely in a safe, discharged state whereas batteries cannot.

Eichenberg, Dennis J.↗
DOE OSTI2023

Dynamic probabilistic risk assessment for electric grid cybersecurity

Electric grid cybersecurity risk has become a significant concern of industries and governments. This paper proposes a dynamic probabilistic risk assessment method for electric grid cybersecurity risk analysis. The proposed method helps reduce the reliance on expert judgment, capture a broad range of components and system dynamics, and model the interactions between various contributing entities (e.g., attacker, operator). In addition, the scenarios with multiple events, such as the occurrence of both cyberattacks and failures of physical components, the occurrence of both cyberattacks and operators’ (in)correct reactions, are considered and analyzed. Further, for each cyberattack scenario, Monte Carlo simulations are used to obtain possible sequences of the system's evolution under study and then derive risk estimates. As an application of the proposed method, the risk assessment method serves as the basis of risk-informed defense resource allocation to improve electric grid cybersecurity. The proposed method is verified using the IEEE 14-bus system by evaluating different security resource allocations for selected cyberattack scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Magnetostrictive materials for enhanced sensors and electronic components

Magnetostriction is a property of magnetic materials that causes them to change their shape or dimensions proportional to their magnetization. Low-cost, mechanically robust magnetostrictive sensors would be valuable for a wide range of applications across the DOE and national security mission space, such as monitoring the internal conditions of pipelines, rapidly detecting high-impedance faults in power lines (e.g. trees touching power lines), or enhancing implantable systems for the human body. Dilute doping (<1 at.%) of rare earth elements (REE) has been shown to amplify the magnetostriction. Furthermore, alloy processing by rapid cooling from high temperature tends to result in texturing and therefore greater magnetostriction values, which bodes well for developing advanced manufacturing approaches significantly less expensive than single crystal growth. The goal of this effort was to develop robust, low-cost magnetostrictive materials compatible with advanced manufacturing techniques to exploit the rapid cooling of these approaches while retaining the ability to produce fully dense structures. To be useful as a sensor or actuator the coercivity of the material needs to be minimized so that there is minimal magnetic hysteresis. Employing a small scale laser powder bed fusion (L-PBF) system, specimens of Fe-Ga-Ce were built from alloy powder which had a magnetostriction of 289 ppm along the build direction and 197 ppm perpendicular to the build direction. These values are not far from the 310-350 ppm observed in single crystals of Fe-Ga. The results of the series of samples run suggest this is a very promising route for REE doping to higher levels, especially if the powders can be produced using far from equilibrium approaches such as ultrasonic atomization. The promising results from applying additive manufacturing techniques to these materials, particularly the inexpensive Fe-Al system, has potential for inexpensive high-performing magnetostrictive parts producible at large scales for low-cost sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Hydropower Supply Chain Gap Analysis

In 2022, DOE conducted supply chain "deep dives" for renewable energy technologies, including hydropower (Uria-Martinez, Hydropower Industry Supply Chain Deep Dive Assessment 2022). The deep dive identified several challenges in the current hydropower supply chain. In addition, Nguyen et. al (2022) conducted an analogous deep-dive assessment on large (> 100-MW) power transformers (LPTs), a critical component of hydropower installations, and concluded that the LPTs as well as several upstream components and materials also have domestic supply chain challenges. These deep dives were the initial high-level assessments of these supply chains and were focused on identifying the biggest issues. Both recommended further investigation. In the two years since the deep dives were published, the Water Power Technologies Office (WPTO) has focused on improving our understanding of the hydropower supply chain and developing strategies for addressing these challenges. Because the challenges outlined above are most acute for large hydropower systems, most of the report and specifically, this report concentrates on the larger > 100-MW hydropower systems. Early in 2023, DOE's Secretary of Energy asked the Water Power Technologies Office (WPTO) to engage the hydropower community and seek input on strategies to secure and encourage domestic manufacturing. WPTO has established three focus areas for engagement: 1) Define the market for planned rehabilitations and new construction of the domestic fleet, 2) Provide insights for policies, incentives, loan programs, and technology investments to encourage domestic content, and 3) Define the existing and required domestic hydropower manufacturing capabilities and workforce. This report summarizes these efforts and complements the earlier work by further exploring the identified challenges and identifying potential actions to address these challenges. Furthermore, we conducted a detailed gap analysis of the domestic hydropower supply chain, down to the component level. From this analysis, we then make specific, actionable recommendations for closing these gaps. Section 2 of the report summarizes recent (i.e., since 2021) legislation impacting hydropower deployment and/or its supply chain. It then describes the efforts of WPTO to assess and improve the hydropower supply chain since the publication of the deep-dive assessments. In Section 3, the report updates the earlier supply chain and market studies, identifying specific capabilities by company and location. Section 4 outlines the hydropower demand signal for both new builds due to clean energy goals as well as refurbishments and upgrading of the current domestic fleet. Section 5 is a detailed gap analysis while Section 6 provides actionable recommendations for closing the gaps. Section 7 concludes the report by linking the recommendations to the identified gaps and discusses future efforts.

13 HYDRO ENERGY↗
DOE OSTI2022

Integrating Cybersecurity with System Operations and Restoration

This presentation covers the interaction of the discipline of system operations with the discipline of cybersecurity. First, a common mental model for risk - both cybersecurity and all-hazards - is presented, followed by a discussion of high-level management strategies for different kinds of cyber harm facing system operators, based on the consequences and frequencies of the harm. The next section covers the importance of cybersecurity for a system operator organization and explains some general concepts to understand the relationships. Finally the role of system operators in the security of the grid as a larger system of systems is discussed over the framework of a resilience event.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Unleashing the Frequency: Multi-Megawatt Demonstration of 100% Renewable Power Systems with Decentralized Communication-Less Control Scheme

Power systems, which range in size from small microgrids to island systems to large regional grids, are typically managed by a central controller that requires complex communication methods and can be unreliable and pose cyber security risks in certain applications, especially when controlling a larger number of nodes. We propose an inherently robust, scalable method of integration using multiple energy storage systems and distributed energy resources, which does not require any means of dedicated communication. This method moves beyond the paradigm of controlling grid frequency at a fixed value (e.g., 60 Hz), instead allowing the frequency to fluctuate within certain limits (e.g., 59.6-60.4 Hz). With a greater operating range, the frequency can carry necessary information from energy storage systems to highly variable distributed energy resources like photovoltaics, wind, hydro, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Power System Waveform Datasets for Machine Learning

The desire for increased visibility across the electricity grid will necessarily increase the deployment of sensing and measurement devices and associated data management needs to unprecedented levels. For the existing sensing and measurement infrastructure, there remains a great amount of “value” yet to be extracted through advanced data management and analytics. Availability of more data will not, by itself, lead to changes in grid visibility, security, and resiliency. To create the predictive and prescriptive environment required to enable new markets and transactions for customer revenue and a reliable grid, the data must be collected, organized, evaluated, and analyzed using sophisticated algorithms to provide actionable information allowing operators and customers to reliably manage an increasingly complex grid. Progress in artificial intelligence (AI) has been largely driven by large, publicly available datasets that can be used to train AI algorithms such as MNIST, a database of handwritten images of digits, and ImageNet, an image database of everyday objects. These types of publicly available databases of real-world training datasets have been largely credited for advancement of image processing, computer vision, and deep learning algorithms that these use cases deploy. However, in the power systems industry to date, there are few databases with proper event labeling, and data access to a publicly available collection of power system event waveforms that will allow users to interact with grid signature data. Publicly available datasets of power system event waveforms, such as the DOE/EPRI dataset, often lack critical metadata or contain limited examples of each event type, and data formats vary widely across these datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Grid-Scale Electricity Storage at Lowest Possible Cost Enabled by Pumped Heat Electricity Storage (Final Report)

Grid-scale energy storage technologies that can provide greater than 10 hours of electricity at full power address a critical need for full penetration of renewables on electricity grids worldwide, minimize renewable curtailment, and maximize grid security and reliability. Pumped Heat Energy Storage (PHES) systems can store energy thermally in any location at the low costs necessary for displacing fossil fuels, reducing foreign fuel imports, and reducing emissions to maintain the energy security of the United States. The award allowed Southwest Research Institute® (SwRI®) and Malta, Inc. (Malta) to advance the PHES concept to a proof-of-concept demonstration for a kW-scale system. The project focused on system operation and integration. The main project objectives were: 1. Address first implementation challenges 2. Explore system control strategies and operation 3. Translate lessons learned to the full-scale system Through these objectives the project completes a first demonstration of this technology and reduces the technical risk associated with a full-scale system.

25 ENERGY STORAGE↗