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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO 2 experiment

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov ) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO 2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO 2 and CH 4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. In order to successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following; 1. data acquisition and control system – set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system – set of hardware and software to deliver data to a central depository for storage and further processing; and 3. data management plan – set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. Finally, the approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

Data Networks

Explore the source record for details and available documents.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

APPLICATION OF NEURAL NETWORK ALGORITHMS FOR BPM LINEARIZATION

Stripline BPM sensors contain inherent non-linearities, as a result of field distortions from the pickup elements. Many methods have been devised to facilitate corrections, often employing polynomial fitting. The cost of computation makes real-time correction difficult, particulalry when integer math is utilized. The application of neural-network technology, particularly the multi-layer perceptron algorithm, is proposed as an efficient alternative for electrode linearization. A process of supervised learning is initially used to determine the weighting coefficients, which are subsequently applied to the incoming electrode data. A non-linear layer, known as an activation layer, is responsible for the removal of saturation effects. Implementation of a perceptron in an FPGA-based software-defined radio (SDR) is presented, along with performance comparisons. In addition, efficient calculation of the sigmoidal activation function via the CORDIC algorithm is presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

The Science DMZ: A Network Design Pattern for Data-Intensive Science

The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

42 ENGINEERING↗
DOE OSTI2017

International Energy Agency Ocean Energy Systems Task 10 Wave Energy Converter Modeling Verification and Validation: Preprint

This is the first joint reference paper for the Ocean Energy Systems (OES) Task 10 Wave Energy Converter modeling verification and validation group. The group is established under the OES Energy Technology Network program under the International Energy Agency. OES was founded in 2001 and Task 10 was proposed by Bob Thresher (National Renewable Energy Laboratory) in 2015 and approved by the OES Executive Committee EXCO in 2016. The kickoff workshop took place in September 2016, wherein the initial baseline task was defined. Experience from similar offshore wind validation/verification projects (OC3-OC5 conducted within the International Energy Agency Wind Task 30) [1], [2] showed that a simple test case would help the initial cooperation to present results in a comparable way. A heaving sphere was chosen as the first test case. The team of project participants simulated different numerical experiments, such as heave decay tests and regular and irregular wave cases. The simulation results are presented and discussed in this paper.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Communications for the Future Electric Grid: Systems and Implications

As the operation of the electric grid continues to become more automated, the associated increase in sensors and systems places increasing demands for fast response, cybersecure communications. This paper presents a review of advances underway in communications and networking technologies that may be implemented to meet these future electric grid requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Informing Cybersecurity Decisions With the Value-at-Risk Framework

Security at every site is critical to making hydropower a strong contributor to the country's grid, but with ongoing development and expanding capabilities, the diversity of the existing hydropower fleet makes across-the-board investment decisions difficult. The threat of cyberattacks naturally increases as the interconnection of Information Technology and Operational Technology networks broadens. Hydropower plants require custom analyses that are specific to the unique challenges and characteristics of any given facility. Facilities, however, often do not have the necessary resources for managers to make informed decisions on investments based on assessed capabilities and risks.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2023

Informing Cybersecurity Decisions With the Value-at-Risk Framework

Security at every site is critical to making hydropower a strong contributor to the country's grid, but with ongoing development and expanding capabilities, the diversity of the existing hydropower fleet makes across-the-board investment decisions difficult. The threat of cyberattacks naturally increases as the interconnection of Information Technology and Operational Technology networks broadens. Hydropower plants require custom analyses that are specific to the unique challenges and characteristics of any given facility. Facilities, however, often do not have the necessary resources for managers to make informed decisions on investments based on assessed capabilities and risks.

cybersecurity↗
DOE OSTI2023

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because it can aid in both cybersecurity analysis and the evaluation of other cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

cyber-physical systems↗
DOE OSTI2024

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because they can aid in both cybersecurity analysis and the evaluation of cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

alfalfa↗
DOE OSTI2020

A software‐defined networks ‐based measurement method of network traffic for 6G technologies

Abstract In software‐defined networks (SDN) for 6G technologies, the controller should accurately and efficiently measure the flow traffic in switches for traffic engineering. Fine‐grained flow measurement can more accurately describe the traffic in the network, but it also consumes much more resources. To reduce the overhead incurred in the measurement process and obtain the approximate fine‐grained measurements, we propose a novel lightweight measurement scheme that runs in the controller. The novel lightweight measurement architecture consists of two parts: coarse‐grained measurement and interpolation‐optimization. In the first part, based on the SDN architecture, we use the pull‐based random sampling method to quickly obtain the coarse‐grained measurement of flow traffic through OpenFlow protocol. In the second part, we insert some discrete values into the coarse‐grained measurement with the interpolation theory, then we optimize interpolation results until finding the optimal fine‐grained flow traffic measurement by utilizing the multiconstraint method. We verified the feasibility of the proposed measurement method, and simulation results show that the measurement error of the proposed method is under 25%, but the flow measurement overhead of this method occupies only 3.3% compared with that of the fine‐grained method.

Huo, Liuwei↗
DOE OSTI2023

Integrating 5G Technology for Improved Process Monitoring and Network Slicing in ICS

Industrial Control Systems (ICS) are crucial for monitoring physical processes that support essential cyber-enabled services like power generation. The use of proprietary communication and lack of effective intrusion detection mechanisms pose constraints for efficient operation. Therefore, there is a need to modernize these systems with decentralized technologies like Edge Computing and 5G. However, integrating 5G and Edge Computing into large-scale ICS networks presents implementation and performance challenges. To address these challenges, this paper proposes an integrated ICS architecture that combines 5G and Edge Computing technologies with traditional ICS protocols. The objective is to minimize implementation and operational difficulties while improving the monitoring of physical processes and enabling robust intrusion detection. The proposed architecture outlines the necessary components, services, and communication protocols required for the integration of 5G and Edge Computing.

Aguayo, Jared M.↗
DOE OSTI2025

Identifying Adversarial Cyber-Activity in Operational Technology Environments Using Bayesian Networks

Critical infrastructure and other operational technology (OT) environments face increasing cybersecurity risks from adversarial behavior. This paper describes the development of a risk model using a Bayesian network to enhance the comprehension of observable cyber events caused by malicious activity in OT environments. The core of the Bayesian network is a process model that describes the stages of adversary behavior. The remainder of the model is based on the MITRE ATT&CK® for Industrial Control Systems (ICS) taxonomy, which includes tactics and techniques that may be used by the adversary. The observables provide evidence for adversary behavior through the intermediary technique and tactic nodes. One challenge in constructing this model is a lack of open-source data from cyber-attacks on OT systems. This paper discusses learning from limited data, the elicitation of expert opinion to construct the conditional probability tables when data is scarce, and the refinement of the most difficult conditional probabilities tables using several forms of sensitivity analyses. Finally, the Bayesian network is demonstrated using two historical case studies: the DarkSide ransomware attack on the Colonial Pipeline and the destructive cyberattack targeting the ThyssenKrupp blast furnace. Index Terms—Cybersecurity, industrial control systems, operational technology

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Self-organized topology of recurrence-based complex networks

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

User Access to Scientific Facilities via 5G: A Cyber Security Thought Experiment

5G is more than an over-the-air radio technology upgrade. It is a strategy to extend Mobile Network Operator service offerings beyond traditional voice, instant messaging and Internet access. 5G Mobile Network Operators will offer new telecommunication services that include enhanced guarantees of confidentiality, integrity and availability. How could such services change the way Science collaborations connect scientists to supercomputers and other scientific facilities? Current scientific collaborations implicitly trust cloud service providers to securely store and process data. The perceived risks of outsourcing Science data security are counterbalanced by assurances that cloud providers operate at a scale that allows them to implement security measures impractical for Science collaborations (e.g. continuous system administrator behavioral monitoring and strict individual separation of duties). If that is true for a cloud service provider like Amazon Web Services (2018 revenue: $25.7 billion), could it also be true for Mobile Network Operators like Verizon Wireless (2018 revenue: $91.7 billion) or AT&T Mobility (2018 revenue: $71.3 billion)? DOE Leadership Class supercomputer facility users currently access them from the public Internet via Secure Shell. The sponsors and operators of the supercomputer facilities have determined that the public Internet path between the Scientist’s Device and the Login Node does not natively provide enough confidentiality or integrity to protect those communications. Therefore, the facilities achieve additional confidentiality and integrity by requiring Secure Shell encryption across those untrusted network paths. Using 5G Network Slice technology, a Mobile Network Operator may offer communication services between supercomputer users and facilities that natively provide confidentiality and integrity guarantees. Sponsors and operators of supercomputer facilities may determine that these guarantees provide enough confidentiality and integrity to protect those communications. If so, a 5G Network Slice could replace an SSH session running over the public Internet. Finally, this use case could be extended to other Office of Science user facility access requirements. Consider microscopy instruments at (e.g.) the Center for Nanoscale Materials or the Environmental Molecular Sciences Laboratory. The embedded systems controlling such instruments may not always support encrypted network access technologies like SSH. 5G Network Slices may offer an alternative to current VPN or SSH tunneling techniques, with additional benefits like guaranteed minimum bandwidth.

5G↗
DOE OSTI2021

Spin waves in YIG based magnonic networks: Design and technological aspects

Microwaveguides for spin waves based on yttrium iron garnet films and cross-like structures built on such waveguides are experimentally studied. Additionally, effects of the waveguides geometry, location of the microantennas for excitation and detection of the spin waves, and geometry of the waveguides junctions on the spin wave excitation and propagation efficiency are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Editorial: Edge computation and digital distribution networks

The development of digital technologies is penetrating all areas of energy revolution. Based on the in-depth integration of advanced digital technologies, distribution networks are gradually transforming into digital distribution networks (DDNs) with tremendous changes from the structure to the operation mode. DDNs is the digitalized appearance of the physical distribution network, in which ubiquitous connections and massive data are the basic characteristics (Huo et al., 2022). It is an important task to utilize the massive data and propose novel operation modes to construct more efficient and intelligent distribution networks (Jian et al., 2022). Among the advanced digital technologies in DDNs, edge computing has received wide attention (Zhao et al., 2022). It has superior performance in local sensing and intelligent computation, which can effectively relieve huge communication pressure. However, the limited computing resources and the complex computing tasks at the edge side significantly challenge the collaboration of distribution network regulation and advanced digital technologies (Hu et al., 2022). It is necessary to find out proper methods to utilize advanced digital technology to construct DDNs. This Research Topic is organized to introduce the recent progress in the construction, operation and advanced computational methods for DDNs. Finally, seven papers have been accepted, which can be sorted into the following three categories: 1) Evolution and technical features of DDNs, 2) Intelligent operation control of DDNs, 3) Advanced simulation for large-scale DDNs. The three sections below respectively introduce the major research and contributions of the papers covered in each category.

24 POWER TRANSMISSION AND DISTRIBUTION↗