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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Discovery of Signatures, Anomalies, and Precursors in Synchrophasor Data with Matrix Profile and Deep Recurrent Neural Networks (Final Project Report)

The widespread deployment of phasor measurement unit (PMU) across the U.S. together with the burgeoning machine learning technology made it possible to develop data-driven PMU data analytics to improve grid security and reliability in a more insightful and effective manner. Although PMU applications have been explored for over a decade, the representative PMU usage is limited to the bulk power system monitoring mainly due to the data integrity issues associated with PMUs (typically missing, fragmented, and wrongly amplified data). To forge a breakthrough on this stalemate and embrace PMUs for power system control and protection as well, we applied various advanced machine learning and big data analysis technology to the power system event detection and classification as the first step toward the power system control and protection pertaining to grid security enhancement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Innovation in Radiological Security, Part 2 of 2 – Insights into Developing a Cloud-hosted Security Technology

A Sentry Remote Monitoring System (Sentry-RMS) is a stand-alone security system that provides detection, assessment, and communication of priority alarms as an additional means of thwarting internal and external threats to sites that maintain radiological material. The SEntry-RMS CommUnications and REsponse (Sentry-SECURE) platform is an optional feature of the Sentry-RMS that relays priority alarm information to the identified response stakeholders. Sentry-SECURE is hosted in a cloud environment that abstracts the data owner’s and data consumer’s platforms to allow for greater information sharing. This promotes situational awareness amongst authorized users and enables future innovation among modern response platforms. When securely architecting a cloud solution such as this, the use of design paradigms can be an effective tool to increase the accuracy and reliability of cyber- and information-security-related decisions made throughout the development process. This approach also supports the categorization of design considerations into three levels: industry concepts, project approaches, and data protections for digital processes. Industry concepts consist of the notional underpinnings that guide or motivate a security process, system, or design but often lack any tangible attributes. Project approaches represent decisions made during the design and development process to prioritize a solution, method, or practice above another that may provide a comparable functional output but lacks a desired security benefit. Data protections for digital processes represent the selection, integration, and implementation of specific controls for a given asset. This paper will explore specific examples of how Sentry-SECURE has been designed to account for considerations at each of these three levels, while balancing the operational intent of the platform with the security enhancements necessary to maintain data integrity, availability, and confidentiality.

assessment, RMS, security, physical, cloud, Cyber ↗
NASA NTRS2012

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

USAID↗
NASA NTRS2012

Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post ]Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post ]event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS ]capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellitederived damage track information into the SDAT for near real ]time use by forecasters and decision makers.

Jedlove, Gary J.↗
DOE OSTI2024

Emerging Technologies for Privacy Preservation in Energy Systems

This study explores the intersection of digitalization and privacy within the energy sector, focusing on the emerging challenges and opportunities presented by integrating Distributed Energy Resources (DERs) and advanced metering infrastructure. The need for robust digital privacy measures has become crucial as the energy industry evolves towards a more decentralized, digitalized, and decarbonized future. This study delves into four cutting-edge privacy-preserving technologies—Homomorphic Encryption (HE), Secure Multiparty Computation (SMPC), Differential Privacy (DP), and Federated Learning (FL)—each offering unique solutions to safeguard consumer data by increasing digital connectivity and data exchange. Through a detailed examination of these methods, the study explains how each technology operates, its applications within the energy sector, and the specific privacy challenges it addresses. Homomorphic Encryption allows for secure computations on encrypted data, enabling data analysis without compromising privacy. Secure Multiparty Computation enables collaborative data analysis across different entities while protecting the confidentiality of the inputs. Differential Privacy introduces randomness into the assembled data set, preventing the identification of individual records in statistical databases. Lastly, Federated Learning offers a paradigm shift in data analysis, where machine learning models are trained at the edge, minimizing the centralization of sensitive data. The research underscores the significance of implementing these privacy-enhancing technologies to comply with strict data protection regulations, foster consumer trust, and enhance the security of the energy infrastructure. By providing a comprehensive overview of these methodologies and their practical implications for the energy sector, this study aims to contribute to the ongoing discourse on digital privacy, offering insights into how the energy industry can navigate the complexities of data privacy in the digital age.

Cali, Umit↗
DOE OSTI2018

Creating an Interprocedural Analyst-Oriented Data Flow Representation for Binary Analysts (CIAO)

National security missions require understanding third-party software binaries, a key element of which is reasoning about how data flows through a program. However, vulnerability analysts protecting software lack adequate tools for understanding data flow in binaries. To reduce the human time burden for these analysts, we used human factors methods in a rolling discovery process to derive user-centric visual representation requirements. We encountered three main challenges: analysis projects span weeks, analysis goals significantly affect approaches and required knowledge, and analyst tools, techniques, conventions, and prioritization are based on personal preference. To address these challenges, we initially focused our human factors methods on an attack surface characterization task. We generalized our results using a two-stage modified sorting task, creating requirements for a data flow visualization. We implemented these requirements partially in manual static visualizations, which we informally evaluated, and partially in automatically generated interactive visualizations, which have yet to be integrated into workflows for evaluation. Our observations and results indicate that 1) this data flow visualization has the potential to enable novel code navigation, information presentation, and information sharing, and 2) it is an excellent time to pursue research applying human factors methods to binary analysis workflows.

42 ENGINEERING↗
NASA NTRS1980

Environmental control and life support system: Analysis of STS-1

The capability of the orbiter environmental control and life support system (ECLSS) to support vehicle cooling requirements in the event of cabin pressure reduction to 9 psia was evaluated, using the Orbiter versions of the shuttle environmental consumbles usage requirement evaluation (SECURE) program, and using heat load input data developed by the spacecraft electrical power simulator (SEPS) program. The SECURE model used in the analysis, the timeline and ECLSS configuration used in formulating the analysis, and the results of the analysis are presented. The conclusion which may be drawn drom these results. is summarized. There are no significant thermal problems with the proposed mission. There are, however, several procedures which could be optimized for better performance: setting the cabin HX air bypass and the interchanger water bypass to the zero flow position is of questionable efficacy; the cabin air pressure monitoring procedure should be re-evaluated; and the degree of equipment power down specified for this analysis and no problems were noted.

Steines, G.↗
NASA NTRS2005

Technologies for Networked Enabled Operations

Current point-to-point data links will not scale to support future integration of surveillance, security, and globally-distributed air traffic data, and already hinders efficiency and capacity. While the FAA and industry focus on a transition to initial system-wide information management (SWIM) capabilities, this paper describes a set of initial studies of NAS network-enabled operations technology gaps targeted for maturity in later SWIM spirals (201 5-2020 timeframe).

Glass, B.↗
DOE OSTI2025

Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

When a vulnerability is reported by the National Vulnerability Database (NVD), affected products are listed in the structured Common Platform Enumeration (CPE) format. Unfortunately, if the vulnerability is in a software library (e.g., Log4j), it will not include CPEs for each product containing that library. In these cases, security operators need to manually read the vendor's or third-party security advisories to see if their product is affected. However, these advisories do not report affected products in a structured format, which prevents automated processing, This paper makes the first effort towards automatically constructing structured CPEs for the vulnerable products in a non-NVD security advisory from the unstructured data in the advisory. Since this is a very challenging problem, this paper specifically focuses on the initial but key step of matching the un-structured vendor names in security advisories to the structured vendor representations in the standard CPE format. We explore the feasibility of using string similarity to solve the problem. The basic idea is to compare a vendor name from the non-NVD advisory with each vendor in the official CPE dictionary. The CPE vendor with the highest similarity score to the advisory's vendor will be considered as the match. We first conduct an experimental, comparative study of multiple mainstream string similarity metrics for this matching problem. To improve the performance, we then design a new string similarity metric that is adapted from an existing metric by weighing different tokens in the advisory's vendor name differently.

McClanahan, Kylie↗
DOE OSTI2019

PV Cyber Security Research (Final Report)

Extensive deployment of interoperable distributed energy resources (DER) on power systems is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid support functions which can drastically influence power quality, voltage, and bulk system frequency. This project was split into two phases. The first provided a survey and roadmap of the cybersecurity for the solar industry. The second investigated multiple PV cybersecurity research and development (R&D) concepts identified in the first phase. In the first year, the team created a roadmap for improving cybersecurity for distributed solar energy resources. This roadmap was intended to provide direction for the nation over the next five years and focused on the intersection of industry and government and recommends activities in four related areas: stakeholder engagement, cyber security research and development, standards development, and industry best practices. At the same time, the team produced a primer for DER vendors, aggregators, and grid operators to establish a common taxonomy and describe basic principles of cyber security, encryption, communication protocols, DER cyber security recommendations and requirements, and device-, aggregator-, and utility-level security best practices to ensure data confidentiality, integrity, and availability. This material was motivated by the need to assist the broader PV industry with cybersecurity resilience and describe the state-of-the-art for securing DER communications. Lastly, an adversary-based assessment of multiple PV devices was completed at the Distributed Energy Technologies Laboratory at Sandia National Laboratories to determine the status of industry cybersecurity practices. The team found multiple deficiencies in the security features of the assessed devices. In the second year, a set of recommendations was created for DER communication protocols— especially with respect to the state-of-the-art requirements in IEEE 2030.5. Additionally, several cybersecurity R&D technologies related to communications-enabled photovoltaic systems were studied to harden DER communication networks. Specifically, the team investigated (a) using software defined networking to create a moving target defense system for DER communications, and (b) engineering controls that prevent misprogramming or adversary action on DER devices/networks by disallowing setpoints that will generate unstable power system operations.

14 SOLAR ENERGY↗
DOE OSTI2025

Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights

GeoGov Summit Final Presentation entitled "Utilizing AI and Spatial Data to Identify & Rapidly Disseminate Energy Infrastructure Insights". Maintaining the integrity of energy infrastructure plays a critical role in ensuring energy security. Robust foundational AI models using data from federal, state, industry, and other sources can help address integrity risk management & mitigation issues as well as evaluate extended use strategies. Trusted foundational models can help with industry adoption and accelerate innovation by enhancing integrity predictions, reduce costs, and informing infrastructure build-out. Coordination, collaboration & data sharing to develop robust models to aid in: Optimizing operations; Minimizing costs; Ensuring energy security.

Advanced Infrastructure Integrity Model (AIIM)↗
DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Assuring and Securing Machine Learning

A short presentation highlighting using machine learning and topological data analysis to address the challenges of assuring and securing machine learning enabled systems.

Machine Learning↗
NASA NTRSDate not supplied

AAM National Campaign Tech Talk: Data Pipeline Familiarization

NASA's AWS-based Data Pipeline allows real-time data submission and ingestion, with immediate monitoring of data rate, coverage and ingestion quality. Problems are immediately discovered and can be corrected with agility by both Partners and NASA during the a simulation or flight event​.

Data Pipeline↗
DOE OSTI2026

A Feasibility Study on the Integration of Human Performance Data From Diverse Sources Based on the Complexity of a Proceduralized Task

Securing the safety of socio-technical systems including nuclear facilities is the upmost goal to ensure their sustainability because historical records demonstrate that the performance degradation of human operators (e.g., human errors) is one of the crucial contributors to the occurrence of unexpected events resulting in extensive casualties and financial losses. This implies that the collection of human performance data in diverse conditions with which they could be faced during the operation of nuclear facilities. As this collection requires significant resources, it is necessary to resolve how to accomplish it with limited resources. To address this challenge, as suggested in the SHEEP framework, it is indispensable to extract valuable insights after integrating various kinds of human performance data obtained from different sources. However, a practical method to soundly integrate them seems to be still incomplete. Accordingly, the applicability of TACOM (Task Complexity) measure is investigated as a tool to identify useful information based on the integration of human performance data observed from different simulation conditions. As a result, it is expected that the TACOM measure would play an important role in addressing the technical challenge in securing human performance data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Methods of Securing Chemical and Pharmaceutical Knowledge and Recommendations for International Institutions to Enhance Research Integrity

Here, this paper examines strategies for securing chemical and pharmaceutical expertise in a globalized research environment, focusing on safeguarding intellectual property and preventing the misuse of sensitive and potentially dual-use information. The product of collective efforts between Pacific Northwest National Laboratory, Carol Davila University of Medicine and Pharmacy, and New Bulgarian University, highlights the challenges and opportunities posed by cross-border research collaborations, particularly in the context of differing regulatory frameworks and research cultures. It explores current mechanisms to prevent data loss and unauthorized access to sensitive information while assessing the effectiveness of existing security measures, frameworks, and international export control regimes. The approach examines the differing methodologies for promoting transparency, trust-building, and mutual accountability in joint research projects to cultivate secure data-sharing practices and intellectual property. It provides recommendations for international institutions to implement security guidelines in framing research priorities, encourages continual training and education programs, and the integration of processes for monitoring research compliance. This partnership aims to advance scientific innovation while maintaining global stability, ensuring compliance with international norms, and safeguarding valuable intellectual property as measures in chemical and pharmaceutical research security practices continue to expand due to international collaboration and knowledge exchange.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Nevada National Security Site 2015 Waste Management Monitoring Report Area 3 and Area 5 Radioactive Waste Management Sites

Environmental monitoring data are collected at and around the Area 3 and Area 5 Radioactive Waste Management Sites (RWMSs) within the Nevada National Security Site (NNSS). These data include direct radiation exposure, as well as radiation from the air, groundwater, meteorology, and vadose zone. This report summarizes the 2015 environmental data to provide an overall evaluation of RWMS performance and to support environmental compliance and performance assessment (PA) activities. Some of these data (e.g., radiation exposure, air, and groundwater) are presented in other reports developed by National Security Technologies, LLC. Direct radiation monitoring data indicate exposure levels at the RWMSs are within the range of background levels measured at the NNSS. Slightly elevated exposure levels outside the Area 3 RWMS are attributed to nearby historical aboveground nuclear weapons tests. Air monitoring data show that tritium concentrations in water vapor and americium and plutonium concentrations in air particles are below Derived Concentration Standards for these radionuclides. Groundwater monitoring data indicate the groundwater in the uppermost aquifer beneath the Area 5 RWMS is not impacted by RWMS operations. Results of groundwater analysis from wells around the Area 5 RWMS were all below established investigation levels. Leachate samples collected from the leachate collection system at the mixed low-level waste cell were below established contaminant regulatory limits. During 2015, precipitation at the Area 3 RWMS was 0.9% above average, and precipitation at the Area 5 RWMS was 25% above average. Water balance measurements indicate that evapotranspiration from the vegetated weighing lysimeter dries the soil and prevents downward percolation of precipitation more effectively than evaporation as measured from the bare-soil weighing lysimeter. The 1.8 inches of precipitation in September reached the lowest sensors at 180 cm on the Cell 5S and 5N covers, however the sensors on the floor do not indicate any signs of the precipitation percolating thru the waste to the floor. Moisture from precipitation did not percolate below 150 centimeters (cm) (5 feet [ft]) in the vegetated final cover on the U-3ax/bl disposal unit at the Area 3 RWMS. A second remedial revegetation trial was done on the southern portion of the North Cover. In March 2015 it was determined that germination occurred on both the mulched and non-mulched treatments that were irrigated, but that no germination occurred on the non-irrigated treatments. By June the seedlings observed in March were gone, possibly grazed by rabbits which were observed inside the rabbit-proof fence. In August the entire area was sprayed with the herbicide glyphosate in an attempt to minimize weed seed production. During 2015, there was no drainage through 2.4 meters (8 ft) of soil as indicated from the Area 3 drainage lysimeters that received only natural precipitation. Thirty-one percent of the applied precipitation and irrigation drained from the bare-soil drainage lysimeter, which received 3 times the natural precipitation. All 2015 monitoring data indicate that the Area 3 and Area 5 RWMSs are performing within expectations of the model and parameter assumptions for the facilities’ PAs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗