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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Real-Time Testbed for Smart Inverter Cyber Security Studies

Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗
DOE OSTI2011

Electric Vehicle Communication Standards Testing and Validation Phase I: SAE J2847/1

Executive Summary Vehicle to grid communication standards are critical to the charge management and interoperability among vehicles, charging stations and utility providers. Several standards initiatives by the Society of Automobile Engineers (SAE), International Standards Organization and International Electrotechnical Commission (ISO/IEC), and ZigBee / HomePlug Alliance are developing requirements for communication messages and protocols. While the standard development is in progress for more than two years, no definitive guidelines are available for the automobile manufacturers, charging station manufacturers and utility backhaul network systems. At present, there is a wide range of proprietary communication options developed and supported in the industry. Recent work by the Electric Power Research Institute (EPRI) in collaboration with SAE and automobile manufacturers has identified performance requirements and test plan based on possible communication pathways using power line communication over the control pilot and mains. Though the communication pathways and power line communication technology options are identified, much work needs to be done in developing application software and testing of communication modules before these can be deployed in production vehicles. This report presents a test plan and results from initial testing of two power line communication modules developed to meet the requirements of SAE J2847/1 standard.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Roundtable Report: Terahertz and 6G Wireless Communications in Science and Extreme Environments

The main objective of the roundtable is to bring together computer scientists and wireless communications experts from industry, academia, and government to explore the electromagnetic spectrum in the Terahertz (THz) bands for ultra-high-speed short-distance wireless communications in extreme environments. This new generation of THz wireless communications is the key to future machine-to-machine communications critical for the mass deployment of an intelligent Internet of Things (IoT). The roundtable discussion explores THz and 6G wireless technologies along with Visible Light Communications (VLC), intelligent reflection surfaces, free-space quantum and optical communications, and nano communications. The roundtable considers the suitability of these technologies for extreme environments from the nanoscale to the mesoscale for the following: scientific facilities and associated instruments, as well as industry, and manufacturing. Such use cases are not traditionally the primary customer of commercial wireless networks which are focused on personal broadband voice and data communications. Finally, the discussion identifies high-level opportunities and challenges for leveraging THz and 6G wireless communications and related Artificial Intelligence (AI) that can catalyze the advancement of the development of hyperconnected smart scientific instruments and facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Roadmap for Testing and Validation of Electric Vehicle Communication Standards

Vehicle to grid communication standards are critical to the charge management and interoperability among plug-in electric vehicles (PEVs), charging stations and utility providers. The Society of Automobile Engineers (SAE), International Organization for Standardization (ISO), International Electrotechnical Commission (IEC) and the ZigBee Alliance are developing requirements for communication messages and protocols. While interoperability standards development has been in progress for more than two years, no definitive guidelines are available for the automobile manufacturers, charging station manufacturers or utility backhaul network systems. At present, there is a wide range of proprietary communication options developed and supported in the industry. Recent work by the Electric Power Research Institute (EPRI), in collaboration with SAE and automobile manufacturers, has identified performance requirements and developed a test plan based on possible communication pathways using power line communication (PLC). Though the communication pathways and power line communication technology options are identified, much work needs to be done in developing application software and testing of communication modules before these can be deployed in production vehicles. This paper presents a roadmap and results from testing power line communication modules developed to meet the requirements of SAE J2847/1 standard.

Pratt, Richard M.↗
DOE OSTI2011

Graph anomalies in cyber communications

Enterprises monitor cyber traffic for viruses, intruders and stolen information. Detection methods look for known signatures of malicious traffic or search for anomalies with respect to a nominal reference model. Traditional anomaly detection focuses on aggregate traffic at central nodes or on user-level monitoring. More recently, however, traffic is being viewed more holistically as a dynamic communication graph. Attention to the graph nature of the traffic has expanded the types of anomalies that are being sought. We give an overview of several cyber data streams collected at Los Alamos National Laboratory and discuss current work in modeling the graph dynamics of traffic over the network. We consider global properties and local properties within the communication graph. A method for monitoring relative entropy on multiple correlated properties is discussed in detail.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Airborne wireless communication systems, airborne communication methods, and communication methods

An airborne wireless communication system includes circuitry configured to access information describing a configuration of a terrestrial wireless communication base station that has become disabled. The terrestrial base station is configured to implement wireless communication between wireless devices located within a geographical area and a network when the terrestrial base station is not disabled. The circuitry is further configured, based on the information, to configure the airborne station to have the configuration of the terrestrial base station. An airborne communication method includes answering a 911 call from a terrestrial cellular wireless phone using an airborne wireless communication system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Does geography matter? A study of technological learning and innovation in the U.S. Solar photovoltaic balance-of-systems (PV BOS) industry

Different learning channels (i.e., learning from upstream actors, local network, global codified knowledge, etc.) coexist in firms’ technological innovation processes. Although firms are exposed to globalization and convenient communication and transportation tools, researchers still argue about the role of geography in technology innovation. Geographic proximity can facilitate knowledge spillover and network-building. Localized learning and the significance of geography indicate the importance of local knowledge in innovative activities. Local knowledge tends to be more closely aligned with local firms’ technological demand and easier to understand and absorb, because they are created and applied in the same context. However, following Schumpeter, innovation researchers believe that diverse knowledge, especially knowledge from external industries and geographically distant places, is a valuable source for innovation, especially disruptive innovation. Therefore, firms must balance different learning channels, especially between localized learning and global learning. However, it is still unclear about the extent to which localized learning is important for technology innovations and which factors influence the degree of localized learning. Meanwhile, most studies in the area of localized learning usually take no account of the international dimension and the interdependent of knowledge at different geographic scales. Different learning channels (i.e., learning from upstream actors, local network, global codified knowledge, etc.) coexist in firms’ technological innovation processes. Although firms are exposed to globalization and convenient communication and transportation tools, researchers still argue about the role of geography in technology innovation. Geographic proximity can facilitate knowledge spillover and network-building. Localized learning and the significance of geography indicate the importance of local knowledge in innovative activities. Local knowledge tends to be more closely aligned with local firms’ technological demand and easier to understand and absorb, because they are created and applied in the same context. However, following Schumpeter, innovation researchers believe that diverse knowledge, especially knowledge from external industries and geographically distant places, is a valuable source for innovation, especially disruptive innovation. Therefore, firms must balance different learning channels, especially between localized learning and global learning. However, it is still unclear about the extent to which localized learning is important for technology innovations and which factors influence the degree of localized learning. Meanwhile, most studies in the area of localized learning usually take no account of the international dimension and the interdependent of knowledge at different geographic scales. To address this research gap, this paper empirically investigated firms’ learning and innovation processes in relation to the geography. The aim is to answer the following three questions: 1) how does geographic distance influence knowledge spillover; 2) how technological characteristics influence knowledge acquisition choices as regards local vs. non-local knowledge? and 3) how do local and non-local knowledge affect the quality of innovation? The subject of our empirical inquiry is photovoltaic balance-of-systems (PV BOS) components. This choice is primarily motivated by two factors: (1) large-scale deployment of distributed solar PV technologies is widely considered to be an important piece in addressing the environmental impacts of the electricity sector, making PV an important technology to study; furthermore, there is a general consensus that the biggest barrier for a wider deployment of PV is the high price of non-module components, and (2) technological aspects of non-module components of PV systems make local conditions (climate, regulation, learning networks, etc.) salient, thus affording a rich empirical setting to explore the geography-innovation-economy interactions at the local level. We find that the localization effect of technological learning in the solar PV BOS industry is at state level, the number of citations-based linkages decreases with distance, and we also find that international knowledge significantly contributes to the quality of patents, which suggests that state border might be a barrier of current knowledge spillover, and only focusing on local innovation networks is not sufficient for promoting PV BOS innovation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Fast Tuning-Free Distributed Algorithm for Solving the Network-Constrained Economic Dispatch

With the increasing penetration of distributed energy resources (DERs) and their participation in the electricity market, it becomes more desirable to apply distributed algorithms for resource allocation in order to address the resulting computational and communicational challenges. Most of the existing distributed algorithms for solving the network-constrained economic dispatch (NCED) problem require the tuning of certain auxiliary parameters. As a result, the robustness of these algorithms against the varieties in DERs is greatly undermined. In this paper, a new distributed algorithm, optimality condition consensus (OCC), is proposed to solve the NCED problem by using distributed power flow (DPF) and ratio consensus as fundamental tools. It inherits the advantages of existing distributed algorithms for the NCED problem but removes the need for parameter tuning to improve performance in practice. In conclusion, the effectiveness of the proposed distributed algorithm in terms of efficiency, scalability, and robustness is demonstrated through detailed case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Resonant metasurface‐enabled quantum light sources for single‐photon emission and entangled photon‐pair generation

Light encodes information in multiple degrees of freedom (e.g., frequency, amplitude, and phase), enabling high‐speed, high‐bandwidth communication through fiber optics. Unlike classical light, quantum light (single or entangled photons) can transmit quantum states over long distances without loss of coherence, thereby coherently interconnecting quantum nodes for distributed quantum entanglement. Quantum light sources are critical for developing scalable quantum networks aimed at distributed quantum computing, quantum teleportation, and secure quantum communications. However, existing quantum light sources suffer from limited integrability, insufficient spectral and spatial tunability, and inefficiencies in achieving mass‐produced, deterministic, on‐demand quantum light generation. These limitations significantly hinder progress toward direct, on‐chip integration with quantum processing units and detectors – an essential step toward scalable quantum networks. Resonant metasurfaces that leverage photonic modes – such as Mie resonances, guided‐mode resonances, or symmetry‐protected bound states in the continuum – offer strong spatial and temporal confinement of electromagnetic fields, characterized by high quality factors and small mode volumes. These metasurfaces greatly enhance linear and nonlinear light‐matter interactions, making them ideal for efficient on‐chip quantum light generation and manipulation. Here, we describe recent advances in nanoscale quantum light sources and quantum photonic state manipulation enabled by resonant metasurfaces. We also provide an outlook on next‐generation miniaturized quantum light sources achievable through materials innovations in quantum emitters, the co‐design of resonant metasurfaces, and ultimately, the heterogeneous integration of emerging layered van der Waals materials with resonant metasurfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

FedCSpc: A Cross-Silo Federated Learning System With Error-Bounded Lossy Parameter Compression

Cross-Silo federated learning is widely used for scaling deep neural network (DNN) training over data silos from different locations worldwide while guaranteeing data privacy. Communication has been identified as the main bottleneck when training large-scale models due to large-volume model parameters and gradient transmission across public networks with limited bandwidth. Most previous works focus on gradient compression, while limited work tries to compress parameters that can not be ignored and extremely affect communication performance during the training. Here, to bridge this gap, we propose FedCSpc: an efficient cross-silo federated learning system with an XAI-driven adaptive parameter compression strategy for large-scale model training. Our work substantially differs from existing gradient compression techniques due to the distinct data features of gradient and parameter. The key contributions of this paper are fourfold. (1) Our designed FedCSpc proposes to compress the parameter during the training using the state-of-the-art error-bounded lossy compressor – SZ3. (2) We develop an adaptive compression error bound adjustment algorithm to guarantee the model accuracy effectively. (3) We exploit an efficient approach to utilize the idle CPU resources of clients to compress the parameters. (4) We perform a comprehensive evaluation with a wide range of models and benchmarks on a GPU cluster with 65 GPUs. Results show that FedCSpc can achieve the same model accuracy as FedAvg while reducing the data volume of parameters and gradients in communication by up to 7.39× and 288×, respectively. With 32 clients on a 4 Gb size model, FedCSpc significantly outperforms FedAvg in wall-clock time in the emulated WAN environment (at the bandwidth of 1 Gbps or lower without loss of generality).

SZ3↗
DOE OSTI2011

Solving the software protection problem with intrinsic personal physical unclonable functions.

Physical Unclonable Functions (PUFs) or Physical One Way Functions (P-OWFs) are physical systems whose responses to input stimuli (i.e., challenges) are easy to measure (within reasonable error bounds) but hard to clone. The unclonability property comes from the accepted hardness of replicating the multitude of characteristics introduced during the manufacturing process. This makes PUFs useful for solving problems such as device authentication, software protection, licensing, and certified execution. In this paper, we focus on the effectiveness of PUFs for software protection in offline settings. We first argue that traditional (black-box) PUFs are not useful for protecting software in settings where communication with a vendor's server or third party network device is infeasible or impossible. Instead, we argue that Intrinsic PUFs are needed to solve the above mentioned problems because they are intrinsically involved in processing the information that is to be protected. Finally, we describe how sources of randomness in any computing device can be used for creating intrinsic-personal-PUFs (IP-PUF) and present experimental results in using standard off-the-shelf computers as IP-PUFs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2010

Quantum superadditivity in linear optics networks: Sending bits via multiple-access Gaussian channels

Superadditivity effects of communication capacities are known in the case of discrete variable quantum channels. We describe the continuous variable analog of one of these effects in the framework of Gaussian multiple access channels (MACs). Classically, superadditivity-type effects are strongly restricted: For example, adding resources to one sender is never advantageous to other senders in sending their respective information to the receiver. We show that this rule can be surpassed using quantum resources, giving rise to a type of truly quantum superadditivity. This is illustrated here for two examples of experimentally feasible Gaussian MACs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Near Optimality of Matched Filter Detection for Cyclic Prefix Direct Sequence Spread Spectrum

Abstract—Cyclic Prefix Direct Sequence Spread Spectrum -DSSS) has been presented as a potential solution for ultrareliable low latency communications (URLLC) and massive machine type communication (mMTC), where the CP-DSSS waveform would operate as a secondary network at the same frequencies as the primary network but at much lower SNR. In this paper, we show that when operating in the low SNR regime, CP-DSSS achieves near optimum performance when using a matched filter (MF) detector at the receiver. Time reversal (TR) precoding at the transmitter is also analyzed. These results also carry forward into multi-antenna scenarios where array gain is preserved. With nearly optimal performance of MF detection, CP-DSSS can be implemented with simple device transceiver structures, reducing per-unit cost for massively deployed networks.

5G and Beyond Communications↗
DOE OSTI2011

Network Upgrade for the SLC: PEP II Network

The PEP-II control system required a new network to support the system functions. This network, called CTLnet, is an FDDI/Ethernet based network using only TCP/IP protocols. An upgrade of the SLC Control System micro communications to use TCP/IP and SLCNET would allow all PEP-II control system nodes to use TCP/IP. CTLnet is private and separate from the SLAC public network. Access to nodes and control system functions is provided by multi-homed application servers with connections to both the private CTLnet and the SLAC public network. Monitoring and diagnostics are provided using a dedicated system. Future plans and current status information is included.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Networked HIL Simulation System for Modeling Large-scale Power Systems

This paper presents a networked hardware-in-the-loop (HIL) simulation system for modeling large-scale power systems. Researchers have developed many HIL test systems for power systems in recent years. Those test systems can model both microsecond-level dynamic responses of power electronic systems and millisecond-level transients of transmission and distribution grids. By integrating individual HIL test systems into a network of HIL test systems, we can create large-scale power grid digital twins with flexible structures at required modeling resolution that fits for a wide range of system operating conditions. This will not only significantly reduce the need for field tests when developing new technologies but also greatly shorten the model development cycle. In this paper, we present a networked OPAL-RT based HIL test system for developing transmission-distribution coordinative Volt-VAr regulation technologies as an example to illustrate system setups, communication requirements among different HIL simulation systems, and system connection mechanisms. Impacts of communication delays, information exchange cycles, and computing delays are illustrated. Simulation results show that the performance of a networked HIL test system is satisfactory.

Xie, Fuhong↗