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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Path Finding for Maximum Value of Information in Multi-Modal Underwater Wireless Sensor Networks

Here, we consider underwater multi-modal wireless sensor networks (UWSNs) suitable for applications on submarine surveillance and monitoring, where nodes offload data to a mobile autonomous underwater vehicle (AUV) via optical technology, and coordinate using acoustic communication. Sensed data are associated with a value, decaying in time. In this scenario, we address the problem of finding the path of the AUV so that the Value of Information (VoI) of the data delivered to a sink on the surface is maximized. We define a Greedy and Adaptive AUV Path-finding (GAAP) heuristic that drives the AUV to collect data from nodes depending on the VoI of their data. For benchmarking the performance of AUV path-finding heuristics, we define an integer linear programming (ILP) formulation that accurately models the considered scenario, deriving a path that drives the AUV to collect and deliver data with the maximum VoI. In our experiments GAAP consistently delivers more than 80 percent of the theoretical maximum VoI determined by the ILP model. We also compare the performance of GAAP with that of other strategies for driving the AUV among sensing nodes, namely, random paths, TSP-based paths and a “lawn mower”-like strategy. Our results show that GAAP always outperforms every other heuristic in terms of delivered VoI, also obtaining higher energy efficiency.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Best Practices for Grid Communications

As the grid evolves, the communications architecture will need to evolve with it. That architecture affords a structured means by which the evolving complexities of the modern electric grid can be managed. This document provides best practices that can be implemented in the grid of today and evolve towards the grid and grid architecture of the future. The evolving grid and its control communications increasingly rely on commercial communications providers and a variety of technologies, from wireless (e.g., 5G, microwave, Wi-Fi) to wireline (fiber, copper) to radio communications (P25, other repeater-based systems), and all these communications systems rely on electric power. A reliable and resilient grid must account for this complex set of interdependencies in its planning activities, especially those involving restoration and recovery. The participation of all relevant parties in both planning and exercising of plans can prevent unexpected conditions that impede the reliable operation and recovery of the grid. Best practices for grid communications include using a Network Management System to document the operational state, define and monitor baselines, detect changes, and accelerate response to abnormalities. If transitioning from SONET to IP/packet-based systems, translating grid requirements into communications requirements for latency, bandwidth and throughput, IP packet delay variation, packet loss, and availability should inform and drive technology planning and selection as well as that communication system’s Quality of Service (QoS) policies and Service Level Agreements (SLAs). Secure and reliable timing is another key component of a reliable and resilient grid that can operate through adverse events. A trusted internal NTP configuration, an integrated and diverse timing delivery system, optimizing the timing architecture based on the transport technologies of the communications system, and using established standards can deliver the level of timing accuracy required by a range of time-sensitive power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Universal Common Communication Substrate (UCCS) Specification; Universal Common Communication Substrate (UCCS) Implementation

Universal Common Communication Substrate (UCCS) is a low-level communication substrate that exposes high-performance communication primitives, while providing network interoperability. It is intended to support multiple upper layer protocol (ULPs) or programming models including SHMEM,UPC,Titanium,Co-Array Fortran,Global Arrays,MPI,GASNet, and File I/O. it provides various communication operations including one-sided and two-sided point-to-point, collectives, and remote atomic operations. In addition to operations for ULPs, it provides an out-of-band communication channel required typically required to wire-up communication libraries.

Source record↗
DOE OSTI2022

Micro Baselines for Operational Technology Environments

Critical infrastructure stakeholders need to baseline their networks to understand expected communications. Top-down approaches to baselining rely on observables that are generally available but lack properties upon which traditional statistical tools depend. We propose to construct micro-baselines: signatures within operational networks based on observables associated with specific events. Such observables are informed by precursor analysis reports of historical cyber attacks on operational environments developed by Cybersecurity for Operational Technology Environments (CyOTE). Baseline measurements depend upon context beyond the cyber domain. An energy plant's baseline running in the summer may statistically differ from a similar facility in a colder region. Domain knowledge must be integrated to apply general micro-baselining algorithms to a facility-specific context. Therefore, we propose to explore the feasibility of transferring micro baselining algorithms across different facilities. Facilities that implement the same processes in different geographic locations will be compared relative to observable measurements used in micro-baselining for comparable events. One evaluation approach would condition or augment dynamic observables measured within a facility network testbed with additional observables derived from geographic context or infrastructure dependencies such as those provided by the All-Hazards Analysis tool.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Energy Systems Integration Facility (ESIF): World-Class Systems Integration Capabilities and Research

The Energy Systems Integration Facility (ESIF), located at the National Renewable Energy Laboratory (NREL) South Table Mountain campus, is a world-renowned user facility for research and development of modern, advanced, and clean energy technologies. ESIF is distinguished by its continuously evolving, highly integrated systems that span throughout the building, connecting research capabilities across multiple laboratories and test areas. The primary ESIF research systems include: [1] data, cyber, and control networks, [2] research electrical distribution buses (REDB), [3] thermal integration infrastructure, and [4] hydrogen systems. The data, cyber, and control networks provide monitoring, control, communication, automation, visualization, and time series data storage and tagging capabilities for research projects and ESIF systems, including facility safety functions. The REDB system consists of four dedicated AC and DC electrical power networks that can connect devices located across the facility through versatile, automatic circuit configuration to support complex power electronics experiments up to the megawatt-scale. The thermal integration infrastructure consists of three temperature-conditioned water loops that provide heating and cooling interfaces and capabilities for thermal energy research. The hydrogen systems provide megawatt-scale hydrogen production, drying, compression, high-pressure storage, and delivery to laboratory end uses, including hydrogen fuel cell vehicle fueling. The ESIF research systems interconnect and extend throughout the various lab areas of the facility to create elaborate networks composed of diverse technologies for cutting-edge research. The ESIF capabilities are operated and stewarded by the ESIF Research Operations group, who also actively upgrade and advance the systems to ensure they remain ahead of anticipated research - enabling the success of many pioneering energy integration projects. The poster, created by members of the ESIF Research Operations team, highlights and summarizes the four core integrated systems at ESIF. The poster was first presented at the internal NREL Energize Forum on May 13th, 2024, and received the "Best Poster" award.

capabilities↗
DOE OSTI2024

Assessing electrogenetic activation via a network model of biological signal propagation

Introduction: Molecular communication is the transfer of information encoded by molecular structure and activity. We examine molecular communication within bacterial consortia as cells with diverse biosynthetic capabilities can be assembled for enhanced function. Their coordination, both in terms of engineered genetic circuits within individual cells as well as their population-scale functions, is needed to ensure robust performance. We have suggested that “electrogenetics,” the use of electronics to activate specific genetic circuits, is a means by which electronic devices can mediate molecular communication, ultimately enabling programmable control. Methods: Here, we have developed a graphical network model for dynamically assessing electronic and molecular signal propagation schemes wherein nodes represent individual cells, and their edges represent communication channels by which signaling molecules are transferred. We utilize graph properties such as edge dynamics and graph topology to interrogate the signaling dynamics of specific engineered bacterial consortia. Results: We were able to recapitulate previous experimental systems with our model. In addition, we found that networks with more distinct subpopulations (high network modularity) propagated signals more slowly than randomized networks, while strategic arrangement of subpopulations with respect to the inducer source (an electrode) can increase signal output and outperform otherwise homogeneous networks. Discussion: We developed this model to better understand our previous experimental results, but also to enable future designs wherein subpopulation composition, genetic circuits, and spatial configurations can be varied to tune performance. We suggest that this work may provide insight into the signaling which occurs in synthetically assembled systems as well as native microbial communities.

Chun, Kayla↗
DOE OSTI2024

Field test of continuous-variable quantum key distribution with a true local oscillator

A continuous-variable quantum key distribution (CV QKD) using a true local (located at the receiver) oscillator (LO) has been proposed to remove any possibility of side-channel attacks associated with transmission of the LO as well as reduce the cross-pulse contamination. Here we report an implementation of true LO-CV QKD using “off-the-shelf” components and conduct QKD experiments using the fiber optical network at Oak Ridge National Laboratory. A phase reference and quantum signal are time multiplexed and then wavelength division multiplexed with the classical communications that “coexist” with each other on a single optical network fiber. Importantly, this is the first demonstration of CV QKD with a receiver-based true LO over a deployed fiber network, a crucial step for its application in real-world situations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Communication: Separable potential energy surfaces from multiplicative artificial neural networks

We present a potential energy surface fitting scheme based on multiplicative artificial neural networks. It has the sum of products form required for efficient computation of the dynamics of multidimensional quantum systems with the multi configuration time dependent Hartree method. Moreover, it results in analytic potential energy matrix elements when combined with quantum dynamics methods using Gaussian basis functions, eliminating the need for a local harmonic approximation. Scaling behavior with respect to the complexity of the potential as well as the requested accuracy is discussed.

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

Communication: Fitting potential energy surfaces with fundamental invariant neural network

A more flexible neural network (NN) method using the fundamental invariants (FIs) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. Mathematically, FIs finitely generate the permutation invariant polynomial (PIP) ring. In combination with NN, fundamental invariant neural network (FI-NN) can approximate any function to arbitrary accuracy. Because FI-NN minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. In this work, we provide the FIs for all possible molecular systems up to five atoms. Potential energy surfaces for OH{sub 3} and CH{sub 4} were constructed with FI-NN, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enabling Real-Time Communication in Multi-Agent Systems: A Graph Neural Network Based Approach

Global connectivity enables effective coordination in Multi-Agent Systems (MAS). Solving these connection problems under hardware constraints is an NP-hard non-Euclidean Degree Constrained Minimum Spanning Tree (DCMST) problem. Prior MAS controllers coordinate team movement for task completion and collision avoidance; some considering Line-of-Sight (LOS) maintenance but prioritizing flexibility over guarantees. Evolutionary Algorithms (EA) have been shown to find good solutions for DCMST, but their performance degrades with larger populations required to support a large MAS. We present a method based on edge graph attention networks, trained offline to reduce online computation times. Empirical comparisons with greedy polynomial-time solvers and EA show that our method leverages latent graph information to consistently find constraint-satisfying solutions in less time.

connectivity maintenance↗
DOE OSTI2016

Cybersecurity Intrusion Detection and Monitoring for Field Area Network: Final Report

This report summarizes the key technical accomplishments, industry impact and performance of the I2-CEDS grant entitled “Cybersecurity Intrusion Detection and Monitoring for Field Area Network”. Led by Applied Communication Sciences (ACS/Vencore Labs) in conjunction with its utility partner Sacramento Municipal Utility District (SMUD), the project accelerated research on a first-of-its-kind cybersecurity monitoring solution for Advanced Meter Infrastructure and Distribution Automation field networks. It advanced the technology to a validated, full-scale solution that detects anomalies, intrusion events and improves utility situational awareness and visibility. The solution was successfully transitioned and commercialized for production use as SecureSmart™ Continuous Monitoring. Discoveries made with SecureSmart™ Continuous Monitoring led to tangible and demonstrable improvements in the security posture of the US national electric infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗
DOE OSTI2021

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

Stalzer, Mark A.↗
DOE OSTI2013

Ultra-wideband radar sensors and networks

Ultra wideband radar motion sensors strategically placed in an area of interest communicate with a wireless ad hoc network to provide remote area surveillance. Swept range impulse radar and a heart and respiration monitor combined with the motion sensor further improves discrimination.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Dynamic defense and network randomization for computer systems

The various technologies presented herein relate to determining a network attack is taking place, and further to adjust one or more network parameters such that the network becomes dynamically configured. A plurality of machine learning algorithms are configured to recognize an active attack pattern. Notification of the attack can be generated, and knowledge gained from the detected attack pattern can be utilized to improve the knowledge of the algorithms to detect a subsequent attack vector(s). Further, network settings and application communications can be dynamically randomized, wherein artificial diversity converts control systems into moving targets that help mitigate the early reconnaissance stages of an attack. An attack(s) based upon a known static address(es) of a critical infrastructure network device(s) can be mitigated by the dynamic randomization. Network parameters that can be randomized include IP addresses, application port numbers, paths data packets navigate through the network, application randomization, etc.

97 MATHEMATICS AND COMPUTING↗