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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 163 records · Page 9

Experimental Evidence on Latency in a Fleet of Controllable Water Heaters

Demand response is an important emerging part of smart grids with wide coverage in theoretical and modeling research. However, experimental evidence on the real-life behavior of controllable loads is still limited. We present observations regarding latency and communication aspects of the operation on a fleet of residential water heaters in a smart neighborhood in Atlanta, GA. Our analysis shows that latency in water heaters is not constant and does not follow a Gaussian distribution. We also find that there is a systematic relationship between latency and hour of the day. Latency was found to increase during morning and evening hours compared to the afternoon. These findings could help better plan deployment of control for demand response programs. Understanding delays associated with controlling smart devices is crucial for proper design and algorithm development for optimization, frequency of dispatch, and override detection.

communication delay↗

Estimating Critical Customer Outages Resulting from Extreme Hurricanes

US power outage data has been collected by organizations such as Oak Ridge National Laboratory (ORNL) through Environment for Analysis Geo-Located Energy Infrastructure (EAGLE-I: freely available) and poweroutage.us (commercial data: available to purchase). However, these sources do not provide information specific to outages of critical customers. Critical customers include entities, facilities, and individuals whose continuous access to electricity is essential for public safety, emergency response, disaster recovery, the well-being of vulnerable populations, public safety and order, and public utilities such as natural gas, communications, water and sanitation. Identification and geolocation of critical customers is crucial for understanding and addressing the effects of power outages on essential services and ensuring that necessary measures are taken to maintain their operations during power disruptions. This work is a first step towards estimating the occurrences of critical customer outages and developing a critical customer power outage data repository. This work estimates outage incidents of critical customers through spatiotemporal mapping of power outage data, weather data, building data, and critical infrastructure network data. Our results show that critical customer effects vary across different counties. We provide appropriate mathematical explanations and simplifications to define and systematize the proposed approach.

Bhusal, Narayan [ORNL] (ORCID:0000000222752145)↗

Refueling water storage tank (RWST) with tailored passive emergency core cooling (ECC) flow

A nuclear reactor comprises a pressure vessel containing a nuclear reactor core. A reactor core cooling system comprises a standpipe including a plurality of orifices in fluid communication with a refueling water storage tank (RWST) to drain water from the RWST into the standpipe, and an injection line configured to drain water from the standpipe to the pressure vessel. In some embodiments the standpipe is disposed in the RWST, while in other embodiments the standpipe is disposed outside of the RWST and cross-connection pipes connect the plurality of orifices with the RWST. The reactor core cooling system may further comprise a valve configured to control flow through one orifice of the plurality of orifices in fluid communication with the RWST based on water level in the standpipe. The valve may comprise a float valve having its float disposed in the standpipe.

Watson, Ronald C.↗

Network traffic control for multi-homed end-hosts via SDN

Software-defined networking (SDN) is an emerging technology of efficiently controlling and managing computer networks, such as in data centres, wide-area networks, as well as in ubiquitous communication. In this study, the authors explore the idea of embedding the SDN components, represented by SDN controller and virtual switch, in end-hosts to improve network performance. In particular, the authors consider load balancing across multiple network interfaces on end-hosts with different link capacity scenarios. The authors have explored and implemented different SDN-based load-balancing approaches based on OpenFlow software switches, and have demonstrated the feasibility and the potential of this approach. The proposed system has been evaluated with MultiPath transmission control protocol (MPTCP). Furthermore, the proposed results demonstrated the potential of applying the SDN concepts on multi-homed devices resulting in an increase in achieved throughput of 55% compared to the legacy single network approach and 10% compared to the MPTCP.

97 MATHEMATICS AND COMPUTING↗

Energy-Efficient Self-Organization and Swarm Behavior in Active Matter

Living systems have the unique ability to form hierarchical assemblies, in which individual constituents can perform tasks cooperatively and emergently. Harnessing such properties is a long-standing challenge for the rational design of dynamic materials, that can respond to their environment, communicate with one another, and undergo a rapid, reversible, assembly through the transduction of energy. Recent developments in the design of smart and active colloidal building blocks have led to tremendous breakthroughs, with, for instance, the onset of synthetic photoactivated active assemblies. In this project, we develop a combined experimental, computational, theoretical and Machine Learning framework to shed light on the physical underpinnings of such assembly processes and program the assembly of smart active materials.

36 MATERIALS SCIENCE↗

Emergency Radiation Dose Rate Monitoring During Prolonged Armed Conflict

The 2022 Russian full-scale invasion of Ukraine has introduced unprecedented challenges for the nuclear power generation and radiological safety communities, including occupation and disturbance of highly-contaminated areas, occupation of a nuclear power plant, and strikes near and within boundaries of nuclear sites. The war has necessitated the implementation of a supplementary dose rate sensor network to provide resilient measurement data for public protection and leadership awareness. This paper discusses the implementation of such a system, the factors determining what equipment is best suited for the purpose, and practical factors regarding deployment of the system and data management. The crucial factors for operating a supplementary dose rate sensing network are backup power and communications options for dose rate sensors to make the network resilient to the effects of military operations. The most important implementation factor is to plan for extended operations beyond those typically considered for emergency response given the unpredictable nature of warfare.

resilience↗

Strong spin–orbit quenching via the product Jahn–Teller effect in neutral group IV qubits in diamond

Abstract Artificial atom qubits in diamond have emerged as leading candidates for a range of solid-state quantum systems, from quantum sensors to repeater nodes in memory-enhanced quantum communication. Inversion-symmetric group IV vacancy centers, comprised of Si, Ge, Sn, and Pb dopants, hold particular promise as their neutrally charged electronic configuration results in a ground-state spin triplet, enabling long spin coherence above cryogenic temperatures. However, despite the tremendous interest in these defects, a theoretical understanding of the electronic and spin structure of these centers remains elusive. In this context, we predict the ground-state and excited-state properties of the neutral group IV color centers from first principles. We capture the product Jahn–Teller effect found in the excited state manifold to second order in electron–phonon coupling, and present a nonperturbative treatment of the effect of spin–orbit coupling. Importantly, we find that spin–orbit splitting is strongly quenched due to the dominant Jahn–Teller effect, with the lowest optically-active 3 E u state weakly split into m s -resolved states. The predicted complex vibronic spectra of the neutral group IV color centers are essential for their experimental identification and have key implications for use of these systems in quantum information science.

Materials Science↗

Advanced Research on Integrated Energy Systems Cyber Range

As digital technologies expand to meet the needs of a more autonomous, interconnected, and advanced power system, new cybersecurity complexities and vulnerabilities arise. The ARIES Cyber Range enables the energy sector to evaluate these evolutions and validate cybersecurity solutions without impacting live systems. Combining power grid-scale hardware with emulation and simulation approaches, the ARIES Cyber Range can faithfully replicate modern energy systems - from grid physics to communication networks, and everything in between - with real-world fidelity. At NLR, researchers and partners are answering complex power system cybersecurity questions, examining emerging threats to the electric sector, and de risking new security technologies, all at a mission-relevant speed that keeps pace with rapidly evolving systems and hazards.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Cyber Labeling for Energy Industrial IoT

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security and Emergency Response (CESER), at the request of the Deputy National Security Advisor for Cyber and Emerging Technologies, Anne Neuberger, initiated research in 2023 to develop a cybersecurity labeling proof-of-concept for energy products to expand on the Federal Communications Commission’s (FCC) proposed U.S. Cyber Trust Mark program. DOE mobilized researchers from six National Laboratories to develop and gather feedback on a proof-of concept label for solar inverters and smart meters, which serve as representative products for market-facing energy sector Industrial Internet of Things (IIoT). This report details the research team’s process across two phases and the resulting findings, which include challenges facing cyber labeling programs and recommendations to implement an expanded IIoT cyber labeling program in the U.S.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Emergency Voltage Regulation in Power Systems via Ripple-Type Control

With increasing penetrations of volatile renewable generation and cyber-physical disruptions, ensuring the safe operation of bulk power systems has become unprecedentedly challenging. Because communication and computational costs restrict centralized system dispatch to being called upon every few minutes, and because purely local schemes are shown to be insufficient, distributed controls have been advocated for handling unanticipated system conditions in real time. The applicability of distributed control schemes, however, is fundamentally limited by their need for widespread communication and model cognizance. In this context, we put forth a hybrid, low-communication, saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a "hotline" communication network. Under this protocol, when agents observe a constraint violation based on local measurements, they respond locally until their control resources saturate, in which case they send a beacon for assistance to peer agents. The scheme ensures that minor violations are efficiently mitigated via fast local controls, whereas severe violations can be handled by collaboration among a relatively small set of agents. We evaluate the performance of this scheme via numerical tests on the IEEE 14-bus test feeder, where agents act upon noisy measurements under diverse scenarios of load variations and severe low-/high-voltage events.

collaboration↗

Emergency Voltage Regulation in Power Systems via Ripple-Type Control: Preprint

With increasing penetration of volatile renewable generation and cyber-physical disruptions, ensuring safe operation of bulk power systems has become unprecedentedly challenging. Since communication and computational costs restrict centralized system dispatch to be called upon every few minutes; and purely local schemes are shown to be insufficient, distributed controls have been advocated for handling unanticipated system conditions in real time. However, the applicability of distributed control schemes is fundamentally limited by their need for widespread communication and model cognizance. In this con-text, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a ‘hotline’ communication network. Under this protocol, when agents observe a constraint violation based on local measurements, they respond locally until their control resources saturate, in which case they send a beacon for assistance to peer agents. The scheme ensures that minor violations are efficiently mitigated via fast local controls, while severe violations may be handled by a collaboration of a relatively small set of agents. We evaluate the performance of this scheme via extensive numerical tests on the IEEE 14-bus test feeder, where agents act upon noisy measurements under diverse scenarios of random load variations and severe low/high voltage events.

distributed control↗

Emerging Threats in Transportation Security Related to Intelligent Transportation Systems (ITS)

Transport of high-consequence shipments requires a resilient and robust systems of systems to guarantee cargo arrival. Furthermore, rising adoption of technologies such as connected and automated vehicles (CAVs), intelligent infrastructure, and vehicle-to-everything (V2X) communication presents unique challenges for securing transportation systems. Within these Intelligent Transportation Systems (ITS), several additional vulnerabilities exist that create pathways for adversarial attacks and cargo interception. For example, connectivity provides cyber pathways directly into vehicle systems and infrastructure for malicious actors. Furthermore, advanced vehicle automation exposes additional vehicle control necessary for shipment interception otherwise unavailable to adversaries. Within this paper, we will discuss the specific threats introduced by ITS-enabled technologies currently deployed and in development. These include those mentioned related to connectivity and automation, but will be expanded into grid, infrastructure, and vehicle specific threats. In addition, we will discuss how to potentially mitigate these emerging challenges as well as how to safeguard transportation systems from next generation attacks.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗

Towards scaling community detection on distributed-memory heterogeneous systems

Distributed multi-GPU systems pose significant challenges and opportunities for efficient execution of parallel applications. Graph algorithms are generally characterized by irregular memory accesses, low computation to communication ratios, and load balancing problems that are especially hard to address on multi-GPU systems. Graph community detection is an important problem in the emerging domain of graph analytics with numerous applications. In this paper, we present our ongoing work on distributed-memory multi-GPU implementation for graph community detection. Our work parallelizes the widely used (albeit serial) Louvain method on distributed multi-GPU platforms. Supported by an extensive set of experiments on a multi-GPU enabled supercomputer (OLCF Summit) and a single compute node (Nvidia DGX-2®), we demonstrate competitive performance to existing distributed-memory CPU-based implementation, and up to 6.5 better results than Nvidia RAPIDS® CUGRAPH. To the best of our knowledge, this work represents the first effort for community detection on distributed multi-GPU systems. Our approach and related findings can be extended to numerous other iterative graph algorithms on multi-GPU systems.

97 MATHEMATICS AND COMPUTING↗

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs

Coarse-grained reconfigurable arrays (CGRAs) provide higher flexibility than application-specific integrated circuits (ASICs) and higher efficiency than fine-grained reconfigurable devices such as Field Programmable Gate Arrays (FPGAs). However, CGRAs are generally designed to support offloading of a single kernel. While their design, based on communicating functional units, appears to naturally suit data streaming applications composed of multiple cooperating kernels, current approaches only statically partition the resources across application kernels. However, emerging streaming applications at the edge (scientific instruments, sensor networks, network processing) perform much more than digital signal processing and often are data and input dependent. This leads to extremely variable kernel execution times, severely impacting the throughput of the entire pipeline if resources are only statically allocated. Therefore, in this paper, we propose DRIPS — a coarse-grained, dynamically, and partially reconfigurable array for data-dependent streaming applications. We present a unified compiler framework to facilitate the mapping of a given streaming application onto the DRIPS CGRA architecture. The experimental results show that DRIPS achieves an average throughput improvement of 1.46$\times$ across a set of representative applications over a statically partitioned solution. The additional area overhead to enable dynamic rebalancing consumes 16.34% of the entire area for a 5x5 CGRA prototype.

Tan, Cheng↗

Landau-phonon polaritons in Dirac heterostructures

Polaritons are light-matter quasiparticles that govern the optical response of quantum materials at the nanoscale, enabling on-chip communication and local sensing. Here, we report Landau-phonon polaritons (LPPs) in magnetized charge-neutral graphene encapsulated in hexagonal boron nitride (hBN). These quasiparticles emerge from the interaction of Dirac magnetoexciton modes in graphene with the hyperbolic phonon polariton modes in hBN. Using infrared magneto-nanoscopy, we reveal the ability to completely halt the LPP propagation in real space at quantized magnetic fields, defying the conventional optical selection rules. The LPP-based nanoscopy also tells apart two fundamental many-body phenomena: the Fermi velocity renormalization and field-dependent magnetoexciton binding energies. Our results highlight the potential of magnetically tuned Dirac heterostructures for precise nanoscale control and sensing of light-matter interaction.

36 MATERIALS SCIENCE↗

Hierarchical Model-Free Transactive Control of Building Loads to Support Grid Services

Residential buildings consume 4.4 quads of electricity annually, approximately 37% of the total electricity consumption in the United States. This represents a vast resource that can be used for demand management and other ancillary services. This project aims to develop a robust, scalable hierarchical transactional control mechanism incorporating elements of model-free control (MFC) and game theory to harness buildings to provide ancillary services to the grid. This approach is being taken to address the challenges of incorporating traditional transactional control schemes into existing buildings. The challenges include small individual building sizes requiring aggregation of many buildings, unpredictable energy usage that makes model identification difficult, and satisfying the sensitive occupant comfort constraints. In the proposed approach, by separating the control mechanism into two layers above and below the load aggregator, MFC can be used below the aggregator to modulate flexible building loads in response to pricing signals with guaranteed performance. This allows the burden of identifying an accurate model of the system to be shifted to the above-aggregator layer, where fluctuations in individual building usage have less impact on predicted building system behavior. Game theory concepts can then be used to determine pricing curves and control signals among regional aggregators. Managing this control in a game-theoretic approach will allow us to build in financial incentives that increase customer engagement. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable on small, embedded devices. In a broader sense, developing a strategy capable of effectively incorporating residential and small commercial buildings will allow greater throughput of existing and emerging grid services in addition to future transactive energy grid management methods. Using MFC within a hierarchical control architecture will allow the shifting of existing forecasting challenges to an aggregate level, where dynamics are slower and more predictable. This will enable a smooth interface between the grid services requests of utilities and the reliable control required by participating buildings. MFC, which supports distributed control architecture, permits a scalable solution that can be deployed to neighborhood-size systems as well as individual buildings. This project focuses on three objectives: (1) developing the mathematical framework, algorithm toolkit, and software toolset of the two-layer transactive control testbed; (2) developing a scalable solution for application over many residential and small-size commercial buildings with sparse distributed communication; and (3) field testing and implementation on hardware of the control strategies developed in the previous two objectives. The research and development activities are focused and designed to be impactful within the relevant 2025 targets timeframe. An open-source control framework for exploiting variability and dispatchability of building loads will be delivered as the outcome of the project. This capability enables greater participation of loads in electricity markets and ancillary services that are both useful for the utility and financially beneficial for building owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Networked Microgrid Ownership, Data, and Control Implications: Challenges and Open Questions

Microgrid deployments increasingly favor the potential to form networks for greater benefits to resilience, reliability, and energy sovereignty. Both independent and networked micro-grids predominantly have a single-entity-ownership and control, where the associations from ownership to data requirements to control functions to microgrid objectives is linear. The emerging model, however, is cyclical, with bidirectional causal impacts between each of the 4 pillars: there are more complex mixed ownership models across the physical, electrical, data, communications, protection, and control boundaries that impact the data requirements for meeting control functions that help realize the use-cases or objectives. This paper is the first to delineate the pillars for effective ownership and controllability of both independent as well as networked microgrids through the cyclical model, and present barriers to the adoption of such a model.

Sundararajan, Aditya↗