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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 181 records · Page 10

Simulation of a Wireless Authentication Protocol

Abstract—A wireless authentication protocol that employs timeslots and associated frequency-channels (APEC) is simulated using Python as the simulation environment and implemented into radio hardware as a proof of concept. The APEC protocol does not rely on the use of challenge-response, multifactor authentication schemes but relies instead on the physical properties of a wireless signal. The APEC protocol provides opportunities for real-time deployment in cell phone network infrastructure, as well as in adverse civil and military applications. Description of the APEC implementation and the corresponding results of the simulation study are presented.

42 - ENGINEERING↗

APEC Poster

A wireless authentication protocol that employs timeslots and associated frequency- channels (APEC) is simulated using Python as the simulation environment and implemented into radio hardware as a proof of concept. The APEC protocol does not rely o n the use of challenge -response, multifactor authentication schemes but relies instead on the physical properties of a wireless signal. The APEC protocol provides opportunities for real-time deployment in cell phone network infrastructure, as well as in adverse civil and military applications. Description of the APEC implementation and the corresponding results of the simulation study are presented.

42 - ENGINEERING↗

TOMCAT5G: A Configuration and Trust Analysis Tool for over-the-air Feature and Core Classification in 5G

Because surveillance and tracking are common in next generation wireless protocols, a user may want to have extra information about a cellular network before connecting to it. The thrust of this research answers the question: how much information can a user device get about a 5G cellular core network as a function of the amount of information the user device provides to the network?

42 ENGINEERING↗

ChargeX OCPI Recommendations

The Open Charge Point Interface (OCPI) is an open protocol that enables electric vehicle (EV) charging systems to work together across networks. It supports communication and data sharing between Charge Point Operators (CPOs), who manage charging stations, and e-Mobility Service Providers (eMSPs), who provide charging services to EV drivers. OCPI facilitates functions like user authorization, remote charge point control, charging session data exchange, and billing through Charge Detail Records (CDRs). This allows EV roaming, so drivers can charge at different networks without multiple accounts. As the EV market grows due to increased adoption and technological advancements, OCPI faces higher demands. This has revealed issues with CDR format consistency, timestamp standardization across regions, transmission of EV-side error codes for troubleshooting, and support for new use cases. These challenges can affect operations and user experience, particularly as the industry starts considering Vehicle-to-Grid (V2G) systems, where EVs supply energy to the grid, and Vehicle-to-Everything (V2X) technologies for broader energy interactions. Using feedback from the ChargeX Diagnostics taskforce discussions, industry 1-on-1 meetings, technical standards, and OCPI’s evolution through versions (e.g., OCPI 2.1.1, 2.2, and 2.2.1), this report identifies these issues and suggests practical recommendations. These aim to improve interoperability, streamline operations, and prepare OCPI for future trends in the EV charging ecosystem.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Degrees of Rate Control in Interconnected Reaction Networks

Overall reactions in interconnected networks exhibit net, forward, and reverse rates that are governed by both constitutive elementary steps in the pathway of interest and branching elementary steps that lead to alternative products. Accordingly, steps in branching pathways exhibit negative net, forward, and reverse degrees of rate control, as they reduce reaction flux to the desired product. We here contextualize the forward and reverse degrees of rate control in terms of kinetic resistances (inverse of rates) and leverage the additive nature of kinetic resistance to decouple kinetic driving forces contributed by constitutive elementary steps and branching points (nodal species) in interconnected networks. Regardless of the network connectivity, forward and reverse degrees of rate control are shown to converge at equilibrium. Away from equilibrium, we identify two critical features of interconnected networks: stoichiometric regularity─condition where all stoichiometric numbers are unity─and pathway symmetry around nodal species─condition where branching pathways share the same rate constants, stoichiometry, and species concentrations/activities─that result in (i) equal forward, reverse, and consequently net degrees of rate control and (ii) forward and reverse degrees of rate control that exhibit constant offsets, respectively, across all extents of reaction. Furthermore, our discourse further provides a mathematical description for the influence of stoichiometric irregularity and pathway asymmetry on forward and reverse degrees of rate control. Altogether, the presented work details the effects of network (inter)connectivity and stoichiometry on reaction kinetics and, in doing so, establishes general protocols for capturing these effects as additive terms in the formulation of forward and reverse degrees of rate control.

10 SYNTHETIC FUELS↗

Cybersecurity of Networked Microgrids: Challenges Potential Solutions and Future Directions

Networked microgrids are clusters of geographically-close, islanded microgrids that can function as a single, aggregate island. This flexibility enables customer-level resilience and reliability improvements during extreme event outages and also reduces utility costs during normal grid operations. To achieve this cohesive operation, microgrid controllers and external connections (including advanced communication protocols, protocol translators, and/or internet connection) are needed. However, these advancements also increase the vulnerability landscape of networked microgrids, and significant consequences could arise during networked operation, increasing cascading impact. To address these issues, this report seeks to understand the unique components, functions, and communications within networked microgrids and what cybersecurity solutions can be implemented and what solutions need to be developed. A literature review of microgrid cybersecurity research is provided and a gap analysis of what is additionally needed for securing networked microgrids is performed. Relevant cyber hygiene and best practices to implement are provided, as well as ideas on how cybersecurity can be integrated into networked microgrid design. Lastly, future directions of networked microgrid cybersecurity R&D are provided to inform next steps.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Finite-Time Termination for Consensus Algorithm in Switching Topologies

Here, in this article, we present a finite-time stopping criterion for consensus algorithms in networks with dynamic communication topology. Prior state of the art has established convergence to the consensus value; however, the asymptotic convergence of these algorithms poses a challenge in practical settings where the response from agents is required in finite time. To this end, we propose a maximum-minimum protocol that propagates the global maximum and minimum values of agent states (while running the consensus algorithm) in the network. This article focuses on establishing that the global maximum and minimum values are strictly monotonic even for a dynamic topology, and they can be used to distributively ascertain the closeness to convergence in finite time. We rigorously show that each node can have access to the global maximum and minimum by running the proposed maximum-minimum protocol to realize a finite-time stopping criterion for the otherwise asymptotic consensus algorithm. The practical utility of the algorithm is illustrated through experiments where each agent is instantiated by a NodeJS socket.io server.

24 POWER TRANSMISSION AND DISTRIBUTION↗

nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling

Time- and rate-dependent material functions in non-Newtonian fluids in response to different deformation fields pose a challenge in integrating different constitutive models into conventional computational fluid dynamic platforms. Considering their relevance in many industrial and natural settings alike, robust data-driven frameworks that enable accurate modeling of these complex fluids are of great interest. The main goal is to solve the coupled Partial Differential Equations (PDEs) consisting of the constitutive equations that relate the shear stress to the deformation and fully capture the behavior of the fluid under various flow protocols with different boundary conditions. Here, in this work, we present non-Newtonian physics-informed neural networks (nn-PINNs) for solving systems of coupled PDEs adopted for complex fluid flow modeling. The proposed nn-PINN method is employed to solve the constitutive models in conjunction with conservation of mass and momentum by benefiting from Automatic Differentiation (AD) in neural networks, hence avoiding the mesh generation step. nn-PINNs are tested for a number of different complex fluids with different constitutive models and for several flow protocols. These include a range of Generalized Newtonian Fluid (GNF) empirical constitutive models, as well as some phenomenological models with memory effects and thixotropic timescales. nn-PINNs are found to obtain the correct solution of complex fluids in spatiotemporal domains with good accuracy compared to the ground truth solution. We also present applications of nn-PINNs for complex fluid modeling problems with unknown boundary conditions on the surface, and show that our approach can successfully recover the velocity and stress fields across the domain, including the boundaries, given some sparse velocity measurements.

42 ENGINEERING↗

A Self-Synchronizing Underwater Acoustic Network for Mooring Load Monitoring of a Wave Energy Converter

This paper reports on the development of a self-synchronizing underwater acoustic network developed for remote monitoring of mooring loads in Wave Energy Converters (WECs). This network uses Time Division Multiple Access and operates self-contained with the ability for users to remotely transmit commands to the network as needed. Each node is a self-contained unit, consisting of a protocol adaptor board, an FAU-DPAM underwater acoustic modem and a battery pack. A node can be connected to a load cell, to a topside user or to the WEC. Every node is swapable. The protocol adaptor board, named Protocol Adaptor for Digital LOad Cell (PADLOC) supports a variety of digital load cell message formats (CAN, MODBUS, custom ASCII) and underwater acoustic modem serial formats. PADLOC enables topside users to connect to separate load cells through a user-specific command. This is especially important if the user is monitoring multiple load cells during deployment or maintenance, when the primary data system may be offline. Each PADLOC board handles formatting, buffering and has a one-on-one serial connection with each pair (node) of a digital load cell and acoustic modem. In addition, each PADLOC board handles the timekeeping and power saving features for each node. The only limitation is the data bit rate and delay limitations associated with the underwater acoustic modem. A four node self-synchronizing network has been developed to demonstrate the load cell monitoring capability using the PADLOC technology on the CalWave WEC.

acoustic↗

Results from an international interlaboratory study on light‐ and elevated temperature‐induced degradation in solar modules

Abstract This paper reports the results of an international interlaboratory comparison study on light‐ and elevated temperature‐induced degradation (LETID) on crystalline silicon photovoltaic (PV) modules. A large global network of PV module manufacturers and PV testing laboratories collaborated to design a protocol for LETID detection and screen a large and diverse set of prototype modules for LETID. Results across labs indicate the reproducibility of LETID testing is likely within ±1% of maximum power (P MP ). In intentionally engineered LETID‐sensitive modules, mean degradation after the prescribed detection stress is roughly 6% P MP . In other module types the LETID sensitivity is smaller, and in some we observe essentially negligible degradation attributable to LETID. In LETID‐sensitive modules, both open‐circuit voltage (V OC ) and short‐circuit current (I SC ) degrade by a roughly similar magnitude. We observe, as do previous studies, that LETID affects each cell in a module differently. An investigation of the potential mismatch losses caused by nonuniform LETID degradation found that mismatch loss is insignificant compared to the estimated loss of cell I SC , which drives loss of module I SC . Overall, this work has helped inform the creation of a forthcoming standard technical specification for LETID testing of PV modules, IEC TS 63342 ED1, and should aid in the interpretation of results from that and other LETID tests.

14 SOLAR ENERGY↗

The connected wedge theorem and its consequences

In the AdS/CFT correspondence, bulk causal structure has consequences for boundary entanglement. In quantum information science, causal structures can be replaced by distributed entanglement for the purposes of information processing. In this work, we deepen the understanding of both of these statements, and their relationship, with a number of new results. Centrally, we present and prove a new theorem, the n-to-n connected wedge theorem, which considers n input and n output locations at the boundary of an asymptotically AdS 2+1 spacetime described by AdS/CFT. When a sufficiently strong set of causal connections exists among these points in the bulk, a set of n associated regions in the boundary will have extensive-in-N mutual information across any bipartition of the regions. The proof holds in three bulk dimensions for classical spacetimes satisfying the null curvature condition and for semiclassical spacetimes satisfying standard conjectures. The n-to-n connected wedge theorem gives a precise example of how causal connections in a bulk state can emerge from large-N entanglement features of its boundary dual. It also has consequences for quantum information theory: it reveals one pattern of entanglement which is sufficient for information processing in a particular class of causal networks. We argue this pattern is also necessary, and give an AdS/CFT inspired protocol for information processing in this setting. Our theorem generalizes the 2-to-2 connected wedge theorem proven in [3]. We also correct some errors in the proof presented there, in particular a false claim that existing proof techniques work above three bulk dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Data for Autonomous Transportation Awareness: Data Exchange Use Cases, Standards, and Barriers

This report examines the critical data exchanges between automated vehicle (AV) service providers and the cities and municipalities they serve. It assists municipal authorities in navigating the often complex and real-time digital data exchanges needed to support AV mobility services, with emphasis in three areas: (1) critical safety data for broad-area situational awareness of hazards typically associated emergency dispatch or roadway work zones; (2) performance metrics of AV services that inform the quantity, quality, spatial extents, and impact on the roadway network; and (3) regulatory and policy information, particularly dynamic information that governs how AV services interact with the roadway network, with emphasis on curb space. The report reviews existing practices and emerging protocols and standards and identifies key gaps to address moving forward.

33 ADVANCED PROPULSION SYSTEMS↗

Results from an International Interlaboratory Study on Light- and Elevated Temperature-Induced Degradation (LETID) in Solar Modules

This presentation reports recently submitted results from an international interlaboratory comparison study on light- and elevated temperature-induced degradation (LETID) on crystalline silicon photovoltaic (PV) modules. A large global network of PV module manufacturers and PV testing laboratories collaborated to design a protocol for LETID detection, and screen a large and diverse set of prototype modules for LETID. We summarize the range of observed degradation and provide initial conclusions on the reproducibility of results across labs. In LETID-sensitive modules, both open-circuit voltage (VOC) and short-circuit current (ISC) degrade by a roughly similar magnitude. We observe, as do previous studies, that LETID affects each cell in a module differently. An investigation of the potential mismatch losses caused by nonuniform LETID degradation found that mismatch loss is insignificant compared to the direct LETID-related losses. We summarize the conclusions drawn from the study, provide an update on a forthcoming standard technical specification for LETID testing of PV modules (IEC TS 63342 ED1), and discuss unresolved questions and potential future work on LETID in PV modules.

degradation↗

Neural refinement of sample weights

Monte Carlo simulations are an essential tool in particle physics data analysis. Events are typically generated alongside weights that redistribute the cross section of the simulated process across the phase space. These weights can be negative, and several post hoc methods have been developed to eliminate or mitigate the negative values. All of these methods share the common strategy of approximating the average weight as a function of phase space. We introduce an alternative approach, which, instead of reweighting to the average, refines the initial weights with a scaling transformation, utilizing a phase space-dependent factor. Since this new refinement method does not need to model the full weight distribution, it can be more accurate. High-dimensional and unbinned phase space is processed using neural networks for the refinement method. In addition to the refinement method, we introduce a new resampling protocol, which can be used in conjunction with any weight transformation to not only preserve the average weight but also the statistical uncertainties of the initial distribution. Using both realistic and synthetic examples, we show that the new neural refinement method is able to match or exceed the accuracy of similar weight transformations and that the new resampling protocol is simpler in implementation than previous methods while exhibiting equivalent statistical properties.

Artificial neural networks↗

Method for Assessment of Security-Relevant Settings in Anomaly-Based Intrusion Detection for Industrial Control Systems

Ensuring the integrity of Ethernet-based networks is a challenging and constantly evolving domain. This problem is exacerbated for those operational technology (OT) networks supporting industrial control systems (ICS) since much of that equipment was originally designed to be on a network that was isolated and generally considered free of malefactors. Increasing pressure to bridge these systems with traditional information technology (IT) networks has introduced a bevy of new threats. In response, both academia and industry have responded with security solutions tailored to ICS environments. Deploying these protection systems often involves several configuration choices. While some of these choices are clear (e.g., block/enable protocol X) others are far more subjective (e.g. alert threshold == 3.43). Further complicating the situation, while often similar to IT networks, OT networks have unique challenges and characteristics that make the task of protecting them simultaneously more difficult and straight forward.Extant solutions for quantifying the relative security of intrusion detection systems fail to effectively support the operators of said systems with understanding the impact of various configuration changes. Further, they assume that the attacks are static and not subject to manipulation or alteration in the face of defenses. In this paper, we present a threat-based method for quantifying the relative impact of various security settings for intrusion detection systems (IDSs) within ICS environments. This method provides operational staff with a clear understanding of the relative impact of their settings and assumes that the attacks levied against them are dynamic. The model is described in detail, we apply the model to a synthetic data set, and discuss the inferences that can be made and what types of decisions they could be used to support.

Gillen, Rob↗

Enhanced quantum state transfer by circumventing quantum chaotic behavior

The ability to realize high-fidelity quantum communication is one of the many facets required to build generic quantum computing devices. In addition to quantum processing, sensing, and storage, transferring the resulting quantum states demands a careful design that finds no parallel in classical communication. Existing experimental demonstrations of quantum information transfer in solid-state quantum systems are largely confined to small chains with few qubits, often relying upon non-generic schemes. Here, by using a superconducting quantum circuit featuring thirty-six tunable qubits, accompanied by general optimization procedures deeply rooted in overcoming quantum chaotic behavior, we demonstrate a scalable protocol for transferring few-particle quantum states in a two-dimensional quantum network. These include single-qubit excitation, two-qubit entangled states, and two excitations for which many-body effects are present. Our approach, combined with the quantum circuit’s versatility, paves the way to short-distance quantum communication for connecting distributed quantum processors or registers, even if hampered by inherent imperfections in actual quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enabling Efficient Water Splitting with Advanced Materials Designed for High pH Membrane Interface

This project was focused on developing the durable, high-performance materials and interfaces for advanced water splitting, enabling a clear pathway for achieving <$2/Kg H2 (on scale) with efficiency of 43 kWh/kg H 2 via anion exchange membrane (AEM)-based electrolysis. We aimed to advance these final goals via an improved fundamental understanding of both hydrogen and oxygen evolution reactions (HER/OER) leading to novel platinum group metal (PGM)-free catalyst materials in conjunction with critical improvements in membrane and ionomers and gas evolution electrodes with corresponding characterization and testing. Northeastern University (NU) lead this effort focusing on catalyst development and characterization (both in situ and ex situ) while project partners lead improvements in ionomer and membrane materials and will aid in the development of specialized electrode and membrane electrode assemblies. In addition, close collaboration occured with the HydroGEN Energy Materials Network (EMN) National Laboratory consortium including efforts related to use of advanced ionomers, durability protocols and validation of electrolyzer materials (e.g. NREL), multiscale modeling and computation (e.g. LBNL), and molecular dynamics (MD) simulations of the membrane catalyst interface (e.g. SNL). The interactions with HydroGEN included exchange of data and materials as needed to facilitate project success.

08 HYDROGEN↗