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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Verification of the Convection-Allowing Ensemble System over the Hindu Kush Himalaya Region During the 2018 and 2019 Pre-Monsoon Severe Thunderstorm Seasons

Some of the most intense thunderstorms on the planet occur in the Hindu Kush Himalaya (HKH) region of South-Central Asia. NASA/SERVIR Applied Sciences Team competitive project to develop capacity of severe thunderstorm monitoring and forecasting tool for HKH. Project Goal: Use [NASA] modeling and remote-sensing assets to build early warning capabilities and facilitate timely disaster response for high impact weather events in the HKH region. Specific objectives: 1. Prototype and transition High-Impact Weather Assessment Toolkit (HIWAT) 2. Jointly develop HIWAT capabilities & training with SERVIR’s hub in Kathmandu, Nepal: International Centre for Integrated Mountain Development (ICIMOD) 3. Demonstrate capacity in end-user environment 4. Transition HIWAT system to ICIMOD for future maintenance.

Case, Jonathan L.↗
DOE OSTI2020

Design, Development and Testing Plan for Energy Efficiency Algorithms Related to Building-Integrated Cooling, Heating, and Power Systems

Building-integrated cooling, heating and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. It is estimated that the total CHP technical potential in the commercial building sector is approximately 76 GW, but only a small fraction of it is actually deployed. Advanced control and monitoring systems that realize the full potential of these CHP systems can transform this capacity into an asset for both the owner and the grid and also accelerate the adoption of these systems in the building sector. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. It has been demonstrated by several studies that as much as 30% of building energy use is wasted. Much of the waste results from the inability to anticipate load variations (design day vs. non-design day operations; diurnal variation of loads), identify improper operation, and efficiently operate, control and maintain building systems. Moreover, many buildings, even those with adequate control infrastructure, lack knowledgeable staff to operate and maintain energy systems. Operators of buildings with CHP systems will constantly need to make tradeoffs (economic dispatch) between onsite power generation and purchasing power, between onsite heat production from distributed generation versus heating/cooling from conventional systems, and different passive and active load management measures. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of a clean, efficient, reliable and affordable next-generation integrated energy systems. This report lists the components for which PM, real-time CxV and AFDD algorithms will be developed, how the algorithms will be tested, and metrics that will be used to validate the algorithms and easy of deployment. Deployment of these algorithms in the field will result in savings reduction in energy consumption of between 10% and 20%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1995

Marketing Remote Sensing Data for North Pacific Fisheries Development and Management

Fish poaching, drug trafficking, ocean dumping, and other illegal activities are important problems on the high seas and in national economic zones. The primary thrust of the EOCAP II project, "Marketing Remote Sensing Data for North Pacific Fisheries Development and Management", was to use space-based sensors to improve the effectiveness of marine monitoring, control, and surveillance (MCS). Our initial objectives were to concentrate on the development of MCS tools using Advanced Very High Resolution Radiometry (AVHRR) and Synthetic Aperture Radar (SAR) data. Although we have successfully completed development of an initial version of our SAR-based monitoring tool (OmniVision), project activity has resulted in a much broader application of space-based assets to marine applications. Based in part on work commenced within EOCAP II, a new company, Ocean and Coastal Environmental Sensing, Inc. (OCENS), has been launched and the development of several new software products outside of the MCS arena initiated. One of those products, SeaStation, is near completion with a Fall, 1995 release date. Equity investment in OCENS now totals $70,000-with an additional amount being sought in the first round of financing. One of the pre-eminent objectives of EOCAP II is to make contributions to the US economy and job growth through the expansion of commercial uses of remotely sensed data. OCENS and the software products it is introducing into marine and coastal zone markets responds to this primary object*e. EOCAP II funding leveraged the market and technical know-how of OCENS founders into smart products that benefit marine and coastal zone users. Although technical difficulties and geopolitical shifts damaged the commercial feasibility of initial project objectives, the flexibility of the EOCAP II program now permits long-term business success. This in no small part stems from the fact that the EOCAP program recognizes the realities of small and start-up businesses and does not attempt to force these conditions to fit the apparent needs of big government. Instead, EOCAP works with those who know their market best in order to produce successful products and expanding businesses.

Source record↗
NASA NTRS2013

Orion Scripted Interface Generator (OrionSIG)

The Orion spacecraft undergoing development at NASA and Lockheed Martin aims to launch the first humans to set foot on asteroids and Mars.' Sensors onboard Orion must transmit back to Earth astronomical amounts of data recording almost everything in 50,231 lb. (22,784 kg)2 of spacecraft, down to the temperatures, voltages, or torsions of even the most minor components. This report introduces the new Orion Scripted Interface Generator (OrionSIG) software created by summer 2013 NASA interns Robert Dooling and Samuel Harris. OrionSIG receives a list of Orion variables and produces a script to graph these measurements regardless of their size or type. The program also accepts many other input options to manipulate displays, such as limits on the graph's range or commands to graph different values in a reverse sawtooth wave. OrionSIG paves the way for monitoring stations on Earth to process, display, and test Orion data much more efficiently, a helpful asset in preparation for Orion's first test mission in 2014. Figure I.

Dooling, Robert J.↗
DOE OSTI2021

PHYSICS-BASED AUTOMATED REASONING FOR HEALTH MONITORING: SENSOR SET SELECTION

This paper addresses the problem of how to select a sensor set for equipment health monitoring that meets the needs of advanced O&M tasks that target cost reduction. They include maintenance optimization and asset management for the existing fleet and near-autonomous operation as currently envisioned for advanced reactors. The method uses physics-based automated reasoning to provide for a more “explainable” diagnosis. The algorithm is described along with its implementation on a computational cluster. Preliminary results for application to a use case in the current fleet are described.

diagnosis↗
DOE OSTI2025

Threat Hunt Guide for BESS Environments

The rapid digitalization of the electric grid - driven by the integration of inverter-based resources (IBRs), battery energy storage systems (BESS), and advanced grid control platforms - has significantly enhanced grid efficiency, visibility, and flexibility. However, this evolution also introduces new cybersecurity risks, particularly through supply chain dependencies and operational blind spots at the grid edge. To address these challenges, Idaho National Laboratory (INL), through the Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) Rapid Risk initiative, conducted a series of rapid risk assessment engagements with energy organizations across the United States. Drawing on lessons learned from these engagements, INL developed the following threat hunting guide for asset owners and operators (AOOs) to enhance their cybersecurity visibility within BESS and IBR systems. The guide demonstrates how to use passive network monitoring to baseline device behavior, detect adversarial activity, and investigate anomalies without disrupting operations. By implementing these practices, energy sector stakeholders can improve coordination between cybersecurity and operations teams and strengthen the resilience of distributed energy resources (DERs) within the modern power grid. Prior to implementing any network monitoring, packet capture, or threat hunting activity described in this guide, AOOs are strongly advised to review applicable governance frameworks, legal requirements, and organizational policies. This guide is intended for informational and educational purposes only. It does not replace compliance with any federal, state, or local cybersecurity mandates or industry standards. Implementation of described configurations, technologies, or analytic workflows is performed at the discretion and responsibility of the asset owner and operator.

25 - ENERGY STORAGE↗
NASA NTRS2016

Initial Demonstration of the Real-Time Safety Monitoring Framework for the National Airspace System Using Flight Data

As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have an automated framework to provide an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecast, predicted health of assets in the airspace, and so on. Towards this end, as part of our earlier work, we formulated the Real-Time Safety Monitoring (RTSM) framework for monitoring and predicting the state of safety and to predict unsafe events. In our previous work, the RTSM framework was demonstrated in simulation on three different constructed scenarios. In this paper, we further develop the framework and demonstrate it on real flight data from multiple data sources. Specifically, the flight data is obtained through the Shadow Mode Assessment using Realistic Technologies for the National Airspace System (SMART-NAS) Testbed that serves as a central point of collection, integration, and access of information from these different data sources. By testing and evaluating using real-world scenarios, we may accelerate the acceptance of the RTSM framework towards deployment. In this paper we demonstrate the framework's capability to not only estimate the state of safety in the NAS, but predict the time and location of unsafe events such as a loss of separation between two aircraft, or an aircraft encountering convective weather. The experimental results highlight the capability of the approach, and the kind of information that can be provided to operators to improve their situational awareness in the context of safety.

Real-time Safety Monitoring↗
NASA NTRS2001

The Standard Autonomous File Server, a Customized, Off-the-Shelf Success Story

The Standard Autonomous File Server (SAFS), which includes both off-the-shelf hardware and software, uses an improved automated file transfer process to provide a quicker, more reliable, prioritized file distribution for customers of near real-time data without interfering with the assets involved in the acquisition and processing of the data. It operates as a stand-alone solution, monitoring itself, and providing an automated fail-over process to enhance reliability. This paper will describe the unique problems and lessons learned both during the COTS selection and integration into SAFS, and the system's first year of operation in support of NASA's satellite ground network. COTS was the key factor in allowing the two-person development team to deploy systems in less than a year, meeting the required launch schedule. The SAFS system his been so successful, it is becoming a NASA standard resource, leading to its nomination for NASA's Software or the Year Award in 1999.

Semancik, Susan K.↗
NASA NTRS2001

Introduction to mission data system

MDS state-based architecture. A system compromises project assets in the context of some external environments that influences them. The function of mission software is to monitor and control a system to meet operators' intents.

MDS mission data system↗
DOE OSTI2020

Verifying Deep Reductions in the Nuclear Arsenals: Development and Demonstration of a Motion-detection Subsystem for a “Buddy Tag” Using Non-export Controlled Accelerometers

Future nuclear arms-control agreements may place numerical limits on items that are difficult to monitor with national technical means, even when complemented with onsite inspections. Such items could include small objects and mobile assets, such as non-deployed nuclear warheads and mobile missile launchers. Typically, this verification task can be addressed with unique identifiers, but standard tagging techniques may be unacceptable in this case due to host concerns about safety and intrusiveness. First proposed in the late 1980s and partially developed by Sandia National Laboratories in the early 1990s, the “Proximity Tag” or “Buddy Tag” concept seeks to overcome these concerns by separating the tag from the treaty accountable item itself. A buddy tag has two key elements: a tamper-indicating enclosure and a motion-detection system designed to detect illicit movements in a stand-down period. As part of this project, we have built a buddy-tag prototype for demonstration and evaluation purposes. This paper reviews the design choices and functionalities of the tag’s motion-detection subsystem.We pursue a modular approach for the tag’s hardware, built around an Arduino-class microcontroller and a non-export-controlled low-noise accelerometer, and use open-source algorithms for the motion-detection software. Finally, we discuss the results of an extensive experimental campaign involving both indoor and outdoor measurements assessing the performance of the tag under real-world environmental conditions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach

With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Online Detection of Inter-Turn Winding Faults in Single-Phase Distribution Transformers Using Smart Meter Data

Turn-to-turn faults between primary windings due to insulation degradation are a major cause of distribution transformer failure, and occur due to high levels of stress such as overloading and overheating. An additional consequence of these faults is an increased voltage on the transformer secondary due to effective change in turns ratio. This paper develops a novel method for early detection of insulation degradation and subsequent inter-turn winding failure by monitoring the transformer secondary voltage. The algorithm is based on a cumulative sum (CUSUM) statistic and compares voltages on neighbouring transformers to flag degrading assets. Results obtained from simulation as well as experimental data show that smart meter measurements can be utilized to achieve very high detection accuracy while keeping costs low. Here, the paper also demonstrates the validity of the algorithm in the presence of measurement noise, residential solar power injection etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗
NASA NTRS2001

Using Multiple Space Assests with In-Situ Measurements to Track Flooding in Thailand

Increasing numbers of space assets can enable coordinated measurements of flooding phenomena to enhance tracking of extreme events. We describe the use of space and ground measurements to target further measurements as part of a flood monitoring system in Thailand. We utilize rapidly delivered MODIS data to detect major areas of flooding and the target the Earth Observing One Advanced Land Imager sensor to acquire higher spatial resolution data. Automatic surface water extent mapping products delivered to interested parties. We are also working to extend our network to include in-situ sensing networks and additional space assets.

flooding↗
NASA NTRS2024

Coronado National Memorial Disasters: Investigating Geohazards & Slope Failure Susceptibility Utilizing NASA Earth Observations

The Coronado National Memorial (CORO), located in Hereford, Arizona, is situated along the United States' southern border, featuring recently established but still incomplete border barrier roads. This landscape is inherently prone to geohazards, and debris flow due to the steep mountainous topography, complex terrain, monsoonal rains, and freeze/thaw action - and the new infrastructure has exhibited these processes in the form of rockfall, embankment failure, and debris flow. NASA DEVELOP partnered with CORO to conduct a feasibility assessment of Earth observations for identification of geohazards and slope failure susceptibility. Leveraging Earth observations (United States Geological Survey 3D Elevation Program Digital Elevation Model and a locally obtained Light Detection And Ranging-derived Digital Elevation Model) from 2019 to 2023, and geospatial datasets starting from 2008, the study was able to provide tools to determine the focus for damage mitigation, identify areas most susceptible to slope failures, and prioritize at risk assets through three products: change detection maps, slope failure susceptibility maps, and a slope failure prioritization model. With an emphasis on monitoring high-risk areas and prioritizing mitigation efforts, the project addresses a critical gap in remediation strategies and aims to enhance preservation and safety of the region. Results of this study found that (i) the most identifiable areas of change were the road cuts and debris directly adjacent to the roads created for border construction, (ii) areas of highest slope failure susceptibility are located in mountainous areas with erosive geology, and (iii) roads resulting from border construction have approximately twice the risk of slope failure as roads created by the national park service.

Geohazard↗
DOE OSTI2024

Trends in Cybersecurity Threats to Clean Energy

As deployments of clean energy generation and storage assets continue to grow, the increased attack surface creates a greater risk for cyber threats, but is clean energy truly a target for cyber adversaries? This poster will present research on the trends in cyber incidents that have affected clean energy companies and assets as well as the trends in disclosed and exploited vulnerabilities. From a series of ransomware attacks on European wind manufacturers, to vulnerabilities exploited in solar assets to turn controllers into botnets, to attacks on communication infrastructure that have resulted in extended outages of remote control and monitoring, we explore the techniques used and the impacts to the clean energy sector. Key takeaways include understanding of how OT-focused malware is becoming more flexible and more destructive, how known vulnerabilities are being exploited, the growing number of IT and OT attacks that use built in tools and functionalities. Additionally, we highlight the presumed motivations and targeted sectors for various identified cyber adversaries. Viewers will leave with an understanding of how recent headlines fit into the development of cyberattack trends and what preventions they may need to take to protect against increasingly popular tactics.

14 SOLAR ENERGY↗
NASA NTRS2011

Thermal Properties of Microstrain Gauges Used for Protection of Lithium-Ion Cells of Different Designs

The purpose of this innovation is to use microstrain gauges to monitor minute changes in temperature along with material properties of the metal cans and pouches used in the construction of lithium-ion cells. The sensitivity of the microstrain gauges to extremely small changes in temperatures internal to the cells makes them a valuable asset in controlling the hazards in lithium-ion cells. The test program on lithium-ion cells included various cell configurations, including the pouch type configurations. The thermal properties of microstrain gauges have been found to contribute significantly as safety monitors in lithium-ion cells that are designed even with hard metal cases. Although the metal cans do not undergo changes in material property, even under worst-case unsafe conditions, the small changes in thermal properties observed during charge and discharge of the cell provide an observable change in resistance of the strain gauge. Under abusive or unsafe conditions, the change in the resistance is large. This large change is observed as a significant change in slope, and this can be used to prevent cells from going into a thermal runaway condition. For flexible metal cans or pouch-type lithium-ion cells, combinations of changes in material properties along with thermal changes can be used as an indication for the initiation of an unsafe condition. Lithium-ion cells have a very high energy density, no memory effect, and almost 100-percent efficiency of charge and discharge. However, due to the presence of a flammable electrolyte, along with the very high energy density and the capability of releasing oxygen from the cathode, these cells can go into a hazardous condition of venting, fire, and thermal runaway. Commercial lithium-ion cells have current and voltage monitoring devices that are used to control the charge and discharge of the batteries. Some lithium-ion cells have internal protective devices, but when used in multi-cell configurations, these protective devices either do not protect or are themselves a hazard to the cell due to their limitations. These devices do not help in cases where the cells develop high impedance that suddenly causes them to go into a thermal runaway condition. Temperature monitoring typically helps with tracking the performance of a battery. But normal thermistors or thermal sensors do not provide the accuracy needed for this and cannot track a change in internal cell temperatures until it is too late to stop a thermal runaway.

Jeevarajan, Judith↗
DOE OSTI2025

GridSTIX

SF-25-112 Grid-STIX is a comprehensive extension of the STIX (Structured Threat Information Expression) 2.1 ontology specifically designed for electrical grid cybersecurity applications. This ontology provides a standardized, machine-readable framework for modeling grid assets, operational technology devices, threats, vulnerabilities, supply chain risks, and security relationships in electrical power systems. ## Key Features - **Comprehensive Grid Coverage**: Physical assets, OT devices, grid components, sensors, and energy storage systems - **Zero Trust Architecture**: Policy decision points, enforcement points, trust brokers, and continuous monitoring - **AMI Infrastructure**: Advanced metering networks, head-end systems, mesh gateways, and MDM systems - **Advanced Security Modeling**: Attack patterns, vulnerabilities, mitigations, and supply chain risks - **Critical Grid Relationships**: Power flow, protection, control, and synchronization relationships - **Supply Chain Security**: Supplier modeling, country of origin tracking, and risk assessment - **Protocol Support**: DNP3, Modbus, IEC 61850, IEC 60870-5-104, OPC-UA, and IEEE standards - **Python Code Generation**: Automated STIX-compliant Python class generation from ontologies - **Interactive Visualization**: Enhanced HTML network graphs with grid-specific categorization - **STIX 2.1 Compliance**: Full compatibility with STIX threat intelligence ecosystem

Blakely, Benjamin [Argonne National Laboratory (AN↗