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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 109 records · Page 6

Archiving Data from New Survey Technologies: Lessons Learned on Enabling Research with High-Precision Data While Preserving Participant Privacy: Preprint

During the past 15 years, increasing numbers of organizations and planning agencies have begun collecting high-resolution Global Positioning System (GPS) travel data. Despite the significant effort and expense to collect it, privacy concerns often lead to underutilization of the data. To address this dilemma of providing data access while preserving privacy, the National Renewable Energy Laboratory, with support from the U.S. Department of Transportation and U.S. Department of Energy, established the Transportation Secure Data Center (TSDC). Lessons drawn from best-practice examples from other data centers have helped shape the structure and operating procedures for the TSDC, which functions under the philosophy of first and foremost preserving privacy, but doing so in a way that balances security with accessibility and usability of the data for legitimate research. This paper provides details about the TSDC approach toward achieving these goals, which has included creating a secure enclave with no external access for backing up and processing raw data, a publicly accessible website for downloading cleansed data, and a secure portal environment through which approved users can work with detailed spatial data using a variety of tools and reference information. This paper also describes lessons learned from operating the TSDC with respect to improvements in GPS data handling, processing, and user support, along with plans for continual enhancements to better support the needs of both data providers and users and to thus advance the research value derived from such valuable data.

33 ADVANCED PROPULSION SYSTEMS↗

Universal Utility Data Exchange (UUDEX) Functional Design Requirements: Cybersecurity of Energy Delivery Systems Research and Development

This document provides a set of high-level functional design requirements for Universal Utility Data Exchange (UUDEX). These requirements include a set of use cases, data exchanges supported by UUDEX, both for grid operations and for cyber security data, functional requirements for data exchange, data models used by UUDEX, data exchange architectures, and security considerations. These functional design requirements are intended to be used in more detailed design documents.

97 MATHEMATICS AND COMPUTING↗

Universal Utility Data Exchange (UUDEX) Functional Design Requirements - Rev 1

This document provides a set of high-level functional design requirements for Universal Utility Data Exchange (UUDEX). These requirements include a set of use cases, data exchanges supported by UUDEX, both for grid operations and for cyber security data, functional requirements for data exchange, data models used by UUDEX, data exchange architectures, and security considerations. These functional design requirements are intended to be used in more detailed design documents.

97 MATHEMATICS AND COMPUTING↗

A Survey on Next-generation Power Grid Data Architecture

The operation and control of power grids will increasingly rely on data. A high-speed, reliable, flexible and secure data architecture is the prerequisite of the next-generation power grid. This paper summarizes the challenges in collecting and utilizing power grid data, and then provides reference data architecture for future power grids. Based on the data architecture deployment, related research on data architecture is reviewed and summarized in several categories including data measurement/actuation, data transmission, data service layer, data utilization, as well as two cross-cutting issues, interoperability and cyber security. Research gaps and future work are also presented.

You, Shutang↗

Valve Health Monitoring System Utilizing Smart Instrumentation

The valve monitoring system is a stand alone unit with network capabilities for integration into a higher level health management system. The system is designed for aiding in failure predictions of high-geared ball valves and linearly actuated valves. It performs data tracking and archiving for identifying degraded performance. The data collection types are cryogenic cycles, total cycles, inlet temperature, body temperature torsional strain, linear bonnet strain, preload position, total travel and total directional changes. Events are recorded and time stamped in accordance with the IRIG B True Time. The monitoring system is designed for use in a Class 1 Division II explosive environment. The basic configuration consists of several instrumentation sensor units and a base station. The sensor units are self contained microprocessor controlled and remotely mountable in three by three by two inches. Each unit is potted in a fire retardant substance without any cavities and limited to low operating power for maintaining safe operation in a hydrogen environment. The units are temperature monitored to safeguard against operation outside temperature limitations. Each contains 902-928 MHz band digital transmitters which meet Federal Communication Commission's requirements and are limited to a 35 foot transmission radius for preserving data security. The base-station controller correlates data from the sensor units and generates data event logs on a compact flash memory module for database uploading. The entries are also broadcast over an Ethernet network. Nitrogen purged National Electrical Manufactures Association (NEMA) Class 4 enclosures are used to house the base-station

Jensen, Scott L.↗

Getting Data Out of the Ground: Modern Data Challenges Facing EGS Collab, the DOE Geothermal Data Repository, and the Geothermal Industry

The amount of data being generated by the geothermal industry is increasing exponentially. Advanced tools, higher resolution sensors, and digitally integrated equipment are providing valuable insight into geothermal exploration and operational efficiencies, but the volumes of data they generate and the unique properties of Enhanced Geothermal System (EGS) projects are creating challenges of their own. This paper explores those challenges and the steps the U.S. Department of Energy (DOE) is taking to address them through comprehensive data management strategies, improvements to DOE's Geothermal Data Repository (GDR), and the development of a secure data collaboration tool for DOE's Frontier Observatory for Research in Geothermal Energy (FORGE) and EGS Collab projects.

15 GEOTHERMAL ENERGY↗

Secure, Mobile, Wireless Network Technology Designed, Developed, and Demonstrated

The inability to seamlessly disseminate data securely over a high-integrity, wireless broadband network has been identified as a primary technical barrier to providing an order-of-magnitude increase in aviation capacity and safety. Secure, autonomous communications to and from aircraft will enable advanced, automated, data-intensive air traffic management concepts, increase National Air Space (NAS) capacity, and potentially reduce the overall cost of air travel operations. For the first time ever, secure, mobile, network technology was designed, developed, and demonstrated with state-ofthe- art protocols and applications by a diverse, cooperative Government-industry team led by the NASA Glenn Research Center. This revolutionary technology solution will make fundamentally new airplane system capabilities possible by enabling secure, seamless network connections from platforms in motion (e.g., cars, ships, aircraft, and satellites) to existing terrestrial systems without the need for manual reconfiguration. Called Mobile Router, the new technology autonomously connects and configures networks as they traverse from one operating theater to another. The Mobile Router demonstration aboard the Neah Bay, a U.S. Coast Guard vessel stationed in Cleveland, Ohio, accomplished secure, seamless interoperability of mobile network systems across multiple domains without manual system reconfiguration. The Neah Bay was chosen because of its low cost and communications mission similarity to low-Earth-orbiting satellite platforms. This technology was successfully advanced from technology readiness level (TRL) 2 (concept and/or application formation) to TRL 6 (system model or prototype demonstration in a relevant environment). The secure, seamless interoperability offered by the Mobile Router and encryption device will enable several new, vehicle-specific and systemwide technologies to perform such things as remote, autonomous aircraft performance monitoring and early detection and mitigation of potential equipment malfunctions. As an additional benefit, team advancements were incorporated into open standards, ensuring technology transfer. Low-cost, commercial products incorporating the new technology are already available. Furthermore, these products are fully interoperable with legacy network technology equipment currently being used throughout the world.

Ivancic, William D.↗

Remote sensing and geographically based information systems

A structure is proposed for a geographically-oriented computer-based information system applicable to the analysis of remote sensing digital data. The structure, intended to answer a wide variety of user needs, would permit multiple views of the data, provide independent management of data security, quality and integrity, and rely on automatic data filing. Problems in geographically-oriented data systems, including those related to line encoding and cell encoding, are considered.

Cicone, R. C.↗

Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles

There is a need to transfer knowledge among institutions and organizations to save effort in annotation and labeling or in enhancing task performance. However, knowledge transfer is difficult because of restrictions that are in place to ensure data security and privacy. Institutions are not allowed to exchange data or perform any activity that may expose personal information. With the leverage of a differential privacy algorithm in a high-performance computing environment, we propose a new training protocol, Bootstrap Aggregation of Teacher Ensembles (BATE), which is applicable to various types of machine learning models. The BATE algorithm is based on and provides enhancements to the PATE algorithm, maintaining competitive task performance scores on complex datasets with underrepresented class labels.We conducted a proof-of-the-concept study of the information extraction from cancer pathology report data from four cancer registries and performed comparisons between four scenarios: no collaboration, no privacy-preserving collaboration, the PATE algorithm, and the proposed BATE algorithm. The results showed that the BATE algorithm maintained competitive macro-averaged F1 scores, demonstrating that the suggested algorithm is an effective yet privacy-preserving method for machine learning and deep learning solutions.

Yoon, Hong-Jun↗

Chance-Constrained Optimization for Critical Infrastructure Protection

Stochastic optimization deals with making highly reliable decisions under uncertainty. Chance constraints are a crucial tool of stochastic optimization to develop mathematical optimization models; they form the backbone of many important national security data science applications. These include critical infrastructure resiliency, cyber security, power system operations, and disaster relief management. However, existing algorithms to solve chance-constrained optimization models are severely limited by problem size and structure. In this investigative study, we (i) develop new algorithms to approximate chance-constrained optimization models, (ii) demonstrate the application of chance-constraints to a national security problem, and (iii) investigate related stochastic optimization problems. We believe our work will pave way for new research is stochastic optimization as well as secure national infrastructures against unforeseen attacks.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

A robust wireless communication system for electromagnetically harsh environments of nuclear facilities - 155

Wireless sensors could play a significant role in safety, efficiency, and reliability of instrumentation and control process in current and next generation nuclear power reactors. While conventional narrowband wireless sensors have successfully been used in numerous industrial applications, the RF propagation challenges posed by the heavy metallic and cluttered environment of Nuclear Power Plants (NPPs) has prevented their use in such operations. These challenges include: RF propagation in harsh (reflective, absorptive, cluttered) environments, data security issues, and RF interference to and from other devices in a nuclear reactor. In this introductory paper, first we address how Ultra-wideband (UWB) technology can provide a viable solution for the signal propagation issues in such electromagnetically harsh environments. Second, we present a novel UWB remote powering scheme that allows for battery-free operation of sensors to increase their lifetime. We finalize the paper by presenting the experimental results of using UWB signaling in a representative harsh environment conducted at MIT research reactor. We plan to address the security issues through an innovative UWB communications scheme for sensor data communications in a subsequent paper. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Some aspects of adaptive transform coding of multispectral data

This paper concerns a data compression study pertaining to multi-spectral scanner (MSS) data. The motivation for this undertaking is the need for securing data compression of images obtained in connection with the Landsat Follow-On Mission, where a compression of at least 6:1 is required. The MSS data used in this study consisted of four scenes: Tristate, consisting of 256 pels per row and a total of 512 rows - i.e., (256x512), (2) Sacramento (256x512), (3) Portland (256x512), and (4) Bald Knob (200x256). All these scenes were on digital tape at 6 bits/pel. The corresponding reconstructed scenes of 1 bit/pel (i.e., a 6:1 compression) are included.

Ahmed, N.↗

Data Confidentiality Challenges in Big Data Applications

In this paper, we address the problem of data confidentiality in big data analytics. In many fields, much useful patterns can be extracted by applying machine learning techniques to big data. However, data confidentiality must be protected. In many scenarios, data confidentiality could well be a prerequisite for data to be shared. We present a scheme to provide provable secure data confidentiality and discuss various techniques to optimize performance of such a system.

data confidentiality↗

Secure and Privacy Aware Data Sharing Approach for Smart Electric Vehicles

The integration of smart electric vehicles (SEVs) into smart cities marks a significant step toward creating efficient, sustainable, and connected urban spaces. However, secure and private data sharing is a major challenge as SEVs connect with smart city systems. The interaction between SEVs and consumer electronic devices (CEDs) raises serious concerns about data security and privacy. Here, to address these challenges, this article presents how blockchain technology and federated learning (FL) can address these issues. The proposed approach provides a secure and privacy-aware framework for data exchange between SEVs and CEDs in smart cities. The experiment results demonstrate the effectiveness of the proposed framework for secure data sharing and maintaining system reliability in smart city environments. It also enables trust and promotes the widespread adoption of interconnected urban technologies.

Das, Debashis [Meharry Medical College, Nashville,↗

Cryptonite: A Secure and Performant Data Repository on Public Clouds

Cloud storage has become immensely popular for maintaining synchronized copies of files and for sharing documents with collaborators. However, there is heightened concern about the security and privacy of Cloud-hosted data due to the shared infrastructure model and an implicit trust in the service providers. Emerging needs of secure data storage and sharing for domains like Smart Power Grids, which deal with sensitive consumer data, require the persistence and availability of Cloud storage but with client-controlled security and encryption, low key management overhead, and minimal performance costs. Cryptonite is a secure Cloud storage repository that addresses these requirements using a StrongBox model for shared key management.We describe the Cryptonite service and desktop client, discuss performance optimizations, and provide an empirical analysis of the improvements. Our experiments shows that Cryptonite clients achieve a 40% improvement in file upload bandwidth over plaintext storage using the Azure Storage Client API despite the added security benefits, while our file download performance is 5 times faster than the baseline for files greater than 100MB.

Cloud data storage↗

Livewire Data Platform - A Solution for EEMS Data Sharing

To bring about fundamental changes in our transportation system, data sharing must be endemic. The Livewire Data Platform is a user-friendly, searchable platform allowing easy and secure data sharing and discovery for DOE's Energy Efficient Mobility Systems (EEMS) researchers. The platform was funded by the DOE Vehicle Technologies Office (VTO) to enable a research community that builds partnerships and collaboration around data in order to find answers to today's biggest mobility challenges.

33 ADVANCED PROPULSION SYSTEMS↗

Securing Environmental IoT Data Using Masked Authentication Messaging Protocol in a DAG-Based Blockchain: IOTA Tangle

The demand for the digital monitoring of environmental ecosystems is high and growing rapidly as a means of protecting the public and managing the environment. However, before data, algorithms, and models can be mobilized at scale, there are considerable concerns associated with privacy and security that can negatively affect the adoption of technology within this domain. In this paper, we propose the advancement of electronic environmental monitoring through the capability provided by the blockchain. The blockchain’s use of a distributed ledger as its underlying infrastructure is an attractive approach to counter these privacy and security issues, although its performance and ability to manage sensor data must be assessed. We focus on a new distributed ledger technology for the IoT, called IOTA, that is based on a directed acyclic graph. IOTA overcomes the current limitations of the blockchain and offers a data communication protocol called masked authenticated messaging for secure data sharing among Internet of Things (IoT) devices. We show how the application layer employing the data communication protocol, MAM, can support the secure transmission, storage, and retrieval of encrypted environmental sensor data by using an immutable distributed ledger such as that shown in IOTA. Finally, we evaluate, compare, and analyze the performance of the MAM protocol against a non-protocol approach.

Gangwani, Pranav (ORCID:0000000159226002)↗

The EGS Data Collaboration Platform: Enabling Scientific Discovery

Collaboration in the digital age has been stifled in recent years. Reasonable responses to legitimate security concerns have created a virtual landscape of silos and fortified castles incapable of sharing information efficiently. This trend is unfortunately opposed to the geothermal scientific community's migration toward larger, more collaborative projects. To facilitate efficient sharing of information between team members from multiple national labs, universities, and private organizations, the 'EGS Collab' team has developed a universally accessible, secure data collaboration platform and has fully integrated it with the U.S. Department of Energy's (DOE) Geothermal Data Repository (GDR) and the National Geothermal Data System (NGDS). This paper will explore some of the challenges of collaboration in the modern digital age, highlight strategies for active data management, and discuss the integration of the EGS Collab data management platform with the GDR to enable scientific discovery through the timely dissemination of information.

97 MATHEMATICS AND COMPUTING↗