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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 541 records · Page 30

A Novel Multi-Agent Deep Reinforcement Learning-enabled Distributed Power Allocation Scheme for mmWave Cellular Networks

We consider the power allocation problem over shared spectrum for millimeter-Wave (mmWave) cellular downlink. Existing approaches usually find sub-optimal solutions by solving a non-convex optimization which leads to scalability issues due to centralized control. Therefore, distributed and adaptive approaches are desirable. Recently, model-free Deep Reinforcement Learning (DRL) has achieved success in such wireless resource management tasks. By modeling the radio environment as a Markov Decision Process (MDP) with the base stations (BSs) being the agents, power allocation can be automated at the agent level with comparable throughput performance to conventional centralized schemes. The multi-agent setting presents new challenges as the radio environment is impacted by the joint actions of the agents and is no longer stationary from any individual agent’s perspective. Existing literature bypasses this non-stationarity violation by ignoring it which may cause performance degradation. To tackle this issue, we propose a distributed continuous power allocation scheme based on a modified version of multi-agent Deep Deterministic Policy Gradient (MADDPG) that is tailored for the distributed multiple-agent setting. The proposed scheme employs a centralized-training distributed-execution framework where Q-functions are trained over subsets of BSs while each BS determines its transmit power based only on its own local observation. It admits constant per-BS communication and computation complexity and is thus scalable to large networks. Numerical evaluation shows that the proposed scheme adapts well to a wide range of interference conditions and can achieve comparable or better performance than several state-of-the-art non-learning approaches.

99 GENERAL AND MISCELLANEOUS↗

Advanced architectures for high-performance quantum networking

As practical quantum networks prepare to serve an ever-expanding number of nodes, there has grown a need for advanced auxiliary classical systems that support the quantum protocols and maintain compatibility with the existing fiber-optic infrastructure. We propose and demonstrate a quantum local area network design that addresses current deployment limitations in timing and security in a scalable fashion using commercial off-the-shelf components. First, we employ White Rabbit switches to synchronize three remote nodes with ultra-low timing jitter, significantly increasing the fidelities of the distributed entangled states over previous work with Global Positioning System clocks. Second, using a parallel quantum key distribution channel, we secure the classical communications needed for instrument control and data management. Therefore, the conventional network that manages our entanglement network is secured using keys generated via an underlying quantum key distribution layer, preserving the integrity of the supporting systems and the relevant data in a future-proof fashion.

97 MATHEMATICS AND COMPUTING↗

Module-OT: A Hardware Security Module for Operational Technology

Increased penetration levels of renewable energy and other types of distributed energy resources (DERs) on the modern electric grid-combined with technological advancements for electric system monitoring and control-introduce new cyberattack vectors and increase the cyberattack surface of energy systems. According to the IEEE Std. 1547-2018, DERs must use Modbus, Distributed Network Protocol 3 (DNP3), or Smart Energy Profile 2.0 (SEP2) as their communication protocol. Previous research identified several vulnerabilities and security breaches in each one of these communication protocols; despite this, existing standards for DERs do not recommend cybersecurity measures. In order to reduce vulnerabilities in power distribution systems, this paper presents a novel open-source hardware security module that improves both information and operational security to better protect data and communications on the distribution grid. The security hardware is called “module for operational technology,” or simply Module-OT, and it has been validated and tested in an emulated distribution system application. Module-OT is integrated within a communication system in the transport layer of the Open Systems Interconnection (OSI) model. It improves system security through encryption, authentication, authorization, certificate management, and user access control. The main advancement of Module-OT is the addition of hardware cryptographic acceleration that improves the overall communication performance in terms of end-to-end latency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-layered Resilient Microgrid Networks

Distribution grid resilience, especially when the grid is under high penetration of Distributed Energy Resources (DER), e.g. PV and energy storage, is essential to ensure the quality of electric power services. The resiliency aspect is particularly important for critical loads that typically include hospitals, police/fire stations, and national security facilities. Networks of multiple interconnected reconfigurable microgrids help to increase renewable energy penetration and may be used as basic building blocks for implementing future resilient power grids. However, this integration requires additional layers of communications, both horizontal and vertical, which may substantially increase the potential cyber attack surfaces as well as escalate risks for wide-spread malfunctions of automation systems. The Mulit-layered Resilient Microgrid Networks project is an industry-academic collaboration between ABB, Duke Energy and the University of Illinois at Urbana-Champaign (UIUC) that has developed and demonstrated a cyber-physical resilient control and communication architecture for deployment of multiple microgrid networks, as well as retrofitting the existing distribution grids by increasing DER penetration levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Resilient information and inference networks under mixed-trust sensing

With ubiquitous digitization, sensing, and computational intelligence deployed in increasingly more and broader domains, including critical infrastructure, potentially misleading and destabilizing effects of multimodal anomalies and adversarial behavior are growing in importance. Here, we develop randomized and reinforcement learning-based strategies for strategically recruiting and utilizing deployed (and, thus, vulnerable and potentially faulty and/or compromised) nodes from information and inference networks, while defending against adversaries that attempt to misguide assessments of inferred variables. Recognizing that, besides communication and other costs, sampling from any observable node can either provide true data or dangerously expose our inference to misinformation (without being easily distinguishable what actually happens), the proposed strategies proceed by progressively recruiting nodes and cautiously scaling their information contribution based on assumed, or, in our reinforcement learning approach, intelligently weighed trustworthiness, with the learning approach also considering network-wide, threat-inclusive risk/value tradeoffs. While avoiding the hardware, communication, analytical and computational burden of explicit redundancy, the proposed defensive schemes enable on-the-fly assessments of underlying processes, and system-wide situational awareness with demonstrable resilience against adversarial activities.

97 - MATHEMATICS AND COMPUTING↗

Masked Symbol Modeling for Demodulation of Oversampled Baseband Communication Signals in Impulsive Noise-Dominated Channels

Recent breakthroughs in natural language processing show that attention mech- anism in Transformer networks, trained via masked-token prediction, enables models to capture the semantic context of the tokens and internalize the grammar of language. While the application of Transformers to communication systems is a burgeoning field, the notion of context within physical waveforms remains under-explored. This paper addresses that gap by re-examining inter-symbol con- tribution (ISC) caused by pulse-shaping overlap. Rather than treating ISC as a nuisance, we view it as a deterministic source of contextual information embedded in oversampled complex baseband signals. We propose Masked Symbol Model- ing (MSM), a framework for the physical (PHY) layer inspired by Bidirectional Encoder Representations from Transformers methodology. In MSM, a subset of symbol-aligned samples is randomly masked, and a Transformer predicts the missing symbol identifiers using the surrounding “in-between” samples. Through this objective, the model learns the latent syntax of complex baseband waveforms. We illustrate MSM’s potential by applying it to the task of demodulating sig- nals corrupted by impulsive noise, where the model infers corrupted segments by leveraging the learned context. Our results suggest a path toward receivers that interpret, rather than merely detect communication signals, opening new avenues for context-aware PHY layer design.

Bedir, Oguz↗

CAN-D: A Modular Four-Step Pipeline for Comprehensively Decoding Controller Area Network Data

Controller area networks (CANs) are a broadcast protocol for real-time communication of critical vehicle subsystems. Original equipment manufacturers of passenger vehicles hold secret their mappings of CAN data to vehicle signals, and these definitions vary according to make, model, and year. Without these mappings, the wealth of real-time vehicle information hidden in the CAN packets is uninterpretable, severely impeding vehicle-related research, including CAN cybersecurity and privacy studies, aftermarket tuning, efficiency and performance monitoring, and fault diagnosis to name a few. Guided by the four-part CAN signal definition, we present CAN-D (CAN-Decoder), a modular, four-step pipeline for identifying each signal's boundaries (start bit and length), endianness (byte ordering), signedness (bit-to-integer encoding), and by leveraging diagnostic standards, augmenting a subset of the extracted signals with meaningful, physical interpretation. En route to CAN-D, we provide a comprehensive review of the CAN signal reverse engineering research. All previous methods ignore endianness and signedness, rendering them incapable of decoding many standard CAN signal definitions. Incorporating endianness grows the search space from 128 to 4.72E21 signal tokenizations and introduces a web of changing dependencies. In response, we formulate, formally analyze, and provide an efficient solution to an optimization problem, allowing identification of the optimal set of signal boundaries and byte orderings. In addition, we provide two novel, state-of-the-art signal boundary classifiers—both of which are superior to previous approaches in precision and recall in three different test scenarios—and the first signedness classification algorithm, which exhibits a $>$ 97% F-score. Altogether, CAN-D is the only solution with the potential to extract any CAN signal that is also the state of the art. In evaluation on 10 vehicles of different makes, CAN-D's average $\ell ^1$ error is five times better (81% less) than all previous methods and exhibits lower average error, even when considering only signals that meet prior methods’ assumptions. Finally, CAN-D is implemented in lightweight hardware, allowing for an on-board diagnostic (OBD-II) plugin for real-time in-vehicle CAN decoding.

42 ENGINEERING↗

Programmable Quantum Networked Microgrids

Quantum key distribution (QKD) provides a potent solution to securely distribute keys for two parties. However, QKD itself is vulnerable to denial of service (DoS) attacks. A flexible and resilient QKD-enabled networked microgrids (NMs) architecture is needed but does not yet exist. In this article, we present a programmable quantum NMs (PQNMs) architecture. It is a novel framework that integrates both QKD and software-defined networking (SDN) techniques capable of enabling scalable, programmable, quantum-engineered, and ultra-resilient NMs. Equipped with a software-defined adaptive post-processing approach, a two-level key pool sharing strategy and an SDN-enabled event-triggered communication scheme, these PQNMs mitigate the impact of DoS attacks through programmable post-processing and secure key sharing among QKD links, a capability unattainable using existing technologies. Through comprehensive evaluations, we validate the benefits of PQNMs and demonstrate the efficacy of the presented strategies under various circumstances. Extensive results provide insightful resources for building QKD-enabled NMs in practice.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Companion Assisted Software Based Remote Attestation in SCADA Networks

Critical infrastructure such as power generation and water distribution systems have become a priority target in cyber warfare because of their recent computerization and introduction to the internet. As a result, Supervisory Control and Data Acquisition (SCADA) system security has become a hot topic in academic and industrial research. Among these topics, Remote Attestation is a security method intended to detect the presence of fileless malware in remote devices as they continue to operate. This allows for the detection of malware in the absence of long-term storage artifacts before symptoms of compromise begin to appear. In general, a trusted device (the verifier) makes a request for evidence of innocence from the untrusted device (the prover). In software-based schemes, the verifier can then measure the delay between its request and the prover’s response. If this delay is greater than the known computational time of the evidence gathering algorithm performed by the prover, then evidence may have been forged. Multi-hop networks often introduce too much network jitter to allow accurate measurement of prover response time, which limits the effectiveness of software based Remote Attestation in a real-world setting. In this work, we introduce a companion device that the verifier can trust to perform a subset of attestation, thereby removing any network jitter. This device is a Field Programmable Gate Array (FPGA) that is physically connected to the prover. We provide a communication protocol between the verifier, prover, and companion. To evaluate our scheme, we simulate it in a common SCADA network environment under normal and heavy traffic loads. Our simulations are performed in the discrete event network simulator NS-3, and we perform statistical analysis over our results to show that our scheme allows for tight timing constraints to be placed on the prover such that the verifier can more easily determine the validity of the evidence that it receives.

Johnson, William A.↗

Distributed Small-Signal Stability Conditions for Inverter-Based Unbalanced Microgrids

The proliferation of inverter-based generation and advanced sensing, controls, and communication infrastructure have facilitated accelerated deployment of microgrids. A coordinated network of microgrids can maintain reliable power delivery to critical facilities during extreme events. Low-inertia offered by the power-electronics–interfaced energy resources, however, can present significant challenges to ensuring stable operation of the microgrids. In this work, distributed small-signal stability conditions for inverter-based microgrids are developed that involve the droop-controller parameters and the network parameters (e.g. line impedances, loads). The distributed closed-form parametric stability conditions derived in this paper can be verified in a computationally efficient manner, facilitating reliable design and operations of networks of microgrids. Dynamic phasor models have been used to capture the effects of electromagnetic transients. Furthermore, numerical results are presented, along with PSCAD simulations, to validate the analytical stability conditions. Effects of design choices, such as the conductor types, and inverter sizes, on the small-signal stability of inverter-based microgrids are investigated to derive useful engineering insights.

24 POWER TRANSMISSION AND DISTRIBUTION↗

WiP Abstract: Edge-Based Privacy of Naturalistic Driving Data Collection

Collecting large driving datasets is important for data-driven transportation research and studied in naturalistic driving [3]. Due to the standard implementation of a Controller Area Network (CAN) bus for a vehicle’s inter-module communication, many off-the-shelf devices can easily transform a vehicle into a rich data collection utility [2]. Vehicles with Adaptive Cruise Control (ACC) are an example of a feature resulting in emergent traffic behavior when scaled [4]. While these utilities were designed with particular data use cases, data may be publicly shared to benefit other researchers through online tools like CyVerse [1]. However, such data should only be shared when any private information is removed. This private information may exist as a set of GPS coordinates, since the start and end points of a trip may designate a driver’s place of residence or work. When considering larger continuously-collected data sets with a focus on naturalistic driving, many drivers are needed to make data collection feasible. Removal of private information becomes much more of a challenge since every driver may uniquely define their geographic privacy. This project aims to build upon the foundation of libpanda [2] by adding features of edge-based data privacy enforcement. In it’s current form, libpanda uses a GPS in conjunction with a CAN interface to record data. Libpanda feature s a set of startup and shutdown scripts to perform automatic data collection and upload. With additional support hardware on a Raspberry Pi, the Pi can maintain power on vehicle shutdown to automatically upload data before shutdown.

Bunting, Matt↗

Continuous Improvement Workshops: Stakeholder Ideas for Improving the Weatherization Assistance Program

Through a series of Continuous Improvement Workshops in 2019, network stakeholders identified opportunities for improved coordination, training, procedures and communication across all levels of the Weatherization Assistance Program. Actionable ideas generated through the Continuous Improvement Workshops were synthesized by the National Renewable Energy Laboratory and are presented in this report for DOE's consideration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Viability of S3 Object Storage for the ASC Program at Sandia

Recent efforts at Sandia such as DataSEA are creating search engines that enable analysts to query the institution’s massive archive of simulation and experiment data. The benefit of this work is that analysts will be able to retrieve all historical information about a system component that the institution has amassed over the years and make better-informed decisions in current work. As DataSEA gains momentum, it faces multiple technical challenges relating to capacity storage. From a raw capacity perspective, data producers will rapidly overwhelm the system with massive amounts of data. From an accessibility perspective, analysts will expect to be able to retrieve any portion of the bulk data, from any system on the enterprise network. Sandia’s Institutional Computing is mitigating storage problems at the enterprise level by procuring new capacity storage systems that can be accessed from anywhere on the enterprise network. These systems use the simple storage service, or S3, API for data transfers. While S3 uses objects instead of files, users can access it from their desktops or Sandia’s high-performance computing (HPC) platforms. S3 is particularly well suited for bulk storage in DataSEA, as datasets can be decomposed into object that can be referenced and retrieved individually, as needed by an analyst. In this report we describe our experiences working with S3 storage and provide information about how developers can leverage Sandia’s current systems. We present performance results from two sets of experiments. First, we measure S3 throughput when exchanging data between four different HPC platforms and two different enterprise S3 storage systems on the Sandia Restricted Network (SRN). Second, we measure the performance of S3 when communicating with a custom-built Ceph storage system that was constructed from HPC components. Overall, while S3 storage is significantly slower than traditional HPC storage, it provides significant accessibility benefits that will be valuable for archiving and exploiting historical data. There are multiple opportunities that arise from this work, including enhancing DataSEA to leverage S3 for bulk storage and adding native S3 support to Sandia’s IOSS library.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Communication systems and methods

A communication system is provided that include one or more processors that are configured to instruct computing devices that communicate messages with each other via a time-sensitive network to securely exchange the messages using secret information, ad direct the computing devices to exchange the secret information via a dedicated quantum channel in the time-sensitive network. The one or more processors are also configured to determine a quantum channel synchronization time associated with the secret information exchanged via the dedicated quantum channel, and modify a local classical oscillator based on the quantum channel synchronization time, the local classical oscillator configured to provide a current time.

Bush, Stephen Francis↗

Sub-nanosecond RF synchronization for MIMO software defined radio sensor networks

This disclosure presents distributed and decentralized synchronization for wireless transceivers. The disclosed system, device, and method achieve sub-nanosecond synchronization using low-cost commercial off the shelf software defined radios. By providing a decentralized mechanism that does not rely on a hierarchical master-slave structure, networks constructed as disclosed are robust to sensor drop-out in contested or harsh environments. Such networks may be used to create phased array radars and communication systems without requiring wired connections to distribute a common clock or local oscillator reference.

Moghaddam, Mahta↗

Securing Grid Communications Infrastructure: Addressing Gaps Beyond NERC CIP Facility Perimeters

The North American electric grid relies on a complex communications infrastructure that extends beyond facility perimeters traditionally covered by NERC Critical Infrastructure Protection (CIP) standards. While CIP requirements have significantly strengthened cybersecurity within Electronic Security Perimeters, many operational communications—such as those between control centers, substations, and third-party networks—fall outside current regulatory scope. As grid modernization introduces new technologies and connectivity models, these external pathways present evolving security challenges. This brief explores the nature of these challenges, including emerging attack vectors and supply chain considerations, and highlights how ongoing grid transformation increases exposure to sophisticated threats. It outlines practical strategies and policy options to complement existing standards, such as expanding secure communications practices, enhancing supply chain transparency, and fostering collaboration among federal, state, and industry stakeholders. Near-term actions like encryption, authentication, and contractual safeguards can help reduce risk while longer-term frameworks are developed to ensure resilient and secure grid operations.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Feedback Power Cost Optimization in Power Distribution Networks with Prosumers

Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Critical values of cyber parameters in a dynamic microgrid system

An islanded microgrid can be used to serve critcal load as a resiliency source when a severe outage occurs. In an islanded mode, control of a microgrid relies on the communication system significantly. Hence, microgrids are cyberphysical systems and, therefore, the cyber system plays a crucial role in the performance of the cyber-power system. A microgrid control scheme is proposed for power dispatch and regulation based on the droop and proportional-integral (PI) feedback control. The proposed control strategy is validated for transient stability following dynamic events. To evaluate the impact of a networked control system on control performance, a cyber model is developed to represent data acquisition periods and communication delays. An analytical method is proposed to determine the critical values for the data reporting periods and communication delays. The analytical method based on a state space model of a networked control system is applicable for large-scale systems. A 2-dimensional stability region of a microgrid in the space of cyber parameters can be obtained by the proposed method, and the critical values of cyber parameters are determined based on the stability region. Simulation results validate that the design of a microgrid as a cyber-physical system needs to be guided by critical values for the data reporting period and communication delay to prevent system instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗