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At least 145 records · Page 8

Dynamic concurrent learning method to neutralize cyber attacks and faults for industrial asset monitoring nodes

Input signals may be received from monitoring nodes of the industrial asset, each input signal comprising time series data representing current operation. A neutralization engine may transform the input signals into feature vectors in feature space, each feature vector being associated with one of a plurality of overlapping batches of received input signals. A dynamic decision boundary may be generated based on the set of feature vectors, and an abnormal state of the asset may be detected based on the set of feature vectors and a predetermined static decision boundary. An estimated neutralized value for each abnormal feature value may be calculated based on the dynamic decision boundary and the static decision boundary such that a future set of feature vectors will be moved with respect to the static decision boundary. An inverse transform of each estimated neutralized value may be performed to generate neutralized signals comprising time series data that are output.

97 MATHEMATICS AND COMPUTING↗

Enhancing the Operational Resilience of Advanced Reactors with Digital Twins by Recurrent Neural Networks

Because of a lack of operation data during abnormal and accident scenarios, along with the existence of uncertainty in the evaluation model for transient and accident analysis, the established abnormal and emergency operating procedures can be biased in characterizing the reactor states and ensuring operational resilience. To improve state awareness and ensure operational flexibility for minimizing effects on the system due to anomaly, digital twin (DT) technology is suggested to support operator's decision-making by effectively extracting and using knowledge of the current and future plant states from the knowledge base. To demonstrate DT's capability for recovering the complete states of reactors and for predicting the future reactor behaviors, this paper develops and assesses both the diagnosis and prognosis DTs in a nearly autonomous management and control system for an Experimental Breeder Reactor-II simulator during different loss-of-flow scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Dynamic, resilient virtual sensing system and shadow controller for cyber-attack neutralization

An industrial asset may have monitoring nodes (e.g., sensor or actuator nodes) that generate current monitoring node values. An abnormality detection and localization computer may receive the series of current monitoring node values and output an indication of at least one abnormal monitoring node that is currently being attacked or experiencing a fault. An actor-critic platform may tune a dynamic, resilient state estimator for a sensor node and output tuning parameters for a controller that improve operation of the industrial asset during the current attack or fault. The actor-critic platform may include, for example, a dynamic, resilient state estimator, an actor model, and a critic model. According to some embodiments, a value function of the critic model is updated for each action of the actor model and each action of the actor model is evaluated by the critic model to update a policy of the actor-critic platform.

Roychowdhury, Subhrajit↗

Developing IEEE Std 2800-Compliant Algorithms for Transmission-Connected Inverter-Based Resources

This study addresses the compliance of Inverter-based Resources (IBRs) with IEEE Standard 2800, a leading standard that defines interconnection and interoperability requirements for IBRs integrated into transmission systems. Focusing on abnormal grid scenarios, the research evaluates the specific demands on IBRs, proposing a controller development framework for abnormal grid conditions. This framework caters to maintaining ride-through operation in line with IEEE Std 2800, alongside managing currents during voltage ride-through scenarios. The effectiveness of this proposed controller framework is rigorously validated through case studies, employing a MATLAB/Simulink model of an IBR to test its performance under diverse grid fault conditions, ensuring the IBRs' alignment with standard requirements and their robust performance in enhancing grid reliability.

grid↗

Systems, methods, and devices for failure detection of one or more energy storage devices

An energy storage device management system can include a management portion for charging/discharging an energy storage device and an ultrasound interrogation portion for passing ultrasound energy through the energy storage device during charge/discharge cycles. A memory stores a stream of capture data instances derived from ultrasound energy exiting the energy storage device and baseline ultrasound data instances corresponding with the energy storage device during normal charging/discharging thereof. A processor can compare each capture data instance with the baseline ultrasound data and detect abnormal operating states of the energy storage device. A warning system can issue a notification when abnormal operating states are detected.

Kowalski, Jeffrey A.↗

Sequence-Based Anomaly Detection in Critical Infrastructure Networks

United States critical infrastructure faces new cyber threats from adversarial nation-state actors in the form of malware-free attacks. Traditional cybersecurity techniques use rules-based methods to identify indicators of compromise on networks, often missing these sophisticated attacks. Our approach leverages multiple state of the art machine learning models in a pipeline to identify abnormal network events through sequential analysis. We combine both device and packet-level information into individual events to characterize anomalous network actions. The model is trained and tested on real network traffic from the Idaho National Lab High Performance Computing (HPC) with greater than 98% precision. It is capable of flagging malicious tactics used by adversaries in malware-free attacks, severe changes to the network, and abnormal user activity by network devices.

99 - GENERAL AND MISCELLANEOUS↗

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring significant upgrades to the Compact Muon Solenoid (CMS) to handle the increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.; Fermilab] (ORCID:↗

Proactive Intrusion Detection and Mitigation System

SAND2023-05661O The proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. The PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. This hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for: • Distributed, real-time cyber-physical detection and mitigation analysis • Cybersecurity defense for grid-edge systems • Analysis framework that can provide situational awareness across the transmission, distribution, and DER systems The PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. With these goals, the main functional PIDMS objectives are: • Capability to collect cyber-physical data • Onboard storage of cyber-physical data • Peer-to-peer communication • Computationally efficient machine-learning algorithms • Online cyber-physical data analysis • Alerting/visualization capabilities • Mitigation deployment capability with bump-in-the-wire (BITW) implementation Each of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Jones, Christian↗

Deep learning model to detect various synchrophasor data anomalies

High-density synchrophasors provide valuable information for power grid situational awareness, operation and control. Unfortunately, due to factors including communication instability and hardware failure, their data quality can be greatly deteriorated by anomalies. Since the anomalies can impact the performance of the synchrophasor applications, it is of paramount significance to propose a model to detect anomalies in synchrophasor. In this study, a convolutional neural network model is established to detect and classify the anomalies in the synchrophasor measurements. Additionally, four types of anomalies observed in actual synchrophasors including erroneous patterns, random spikes, missing points and high-frequency interferences are considered in this study. The proposed model is extensively evaluated via field-collected measurements from the synchrophasor network in Jiangsu grid, China. The superior performance of the proposed model indicates the great potential of using deep learning for the detection of abnormal synchrophasor measurements.

42 ENGINEERING↗

Direct Imaging of Antiferromagnet-Ferromagnet Phase Transition in van der Waals Antiferromagnet CrSBr

The advent of van der Waals (vdW) ferromagnetic (FM) and antiferromagnetic (AFM) materials offers unprecedented opportunities for spintronics and magneto-optic devices. Combining magnetic Kerr microscopy and density functional theory calculations, the AFM-FM transition is investigated and a surprising abnormal magneto-optic anisotropy in vdW CrSBr associated with different magnetic phases (FM, AFM, or paramagnetic state) is discovered. This unique magneto-optic property leads to different anisotropic optical reflectivity from different magnetic states, permitting direct imaging of the AFM Néel vector orientation and the dynamic process of the AFM-FM transition within a magnetic field. Using Kerr microscopy, not only the domain nucleation and propagation process is imaged but also the intermediate spin-flop state in the AFM-FM transition is identified. In conclusion, the unique magneto-optic property and clear identification of the dynamics process of the AFM-FM phase transition in CrSBr demonstrate the promise of vdW magnetic materials for future spintronic technology.

36 MATERIALS SCIENCE↗

Controlled Growth of Single‐Crystal Graphene Wafers on Twin‐Boundary‐Free Cu(111) Substrates

Single-crystal graphene (SCG) wafers are needed to enable mass-electronics and optoelectronics owing to their excellent properties and compatibility with silicon-based technology. Controlled synthesis of high-quality SCG wafers can be done exploiting single-crystal Cu(111) substrates as epitaxial growth substrates recently. However, current Cu(111) films prepared by magnetron sputtering on single-crystal sapphire wafers still suffer from in-plane twin boundaries, which degrade the SCG chemical vapor deposition. Here, in this study, it is shown how to eliminate twin boundaries on Cu and achieve 4 in. Cu(111) wafers with ≈95% crystallinity. The introduction of a temperature gradient on Cu films with designed texture during annealing drives abnormal grain growth across the whole Cu wafer. In-plane twin boundaries are eliminated via migration of out-of-plane grain boundaries. SCG wafers grown on the resulting single-crystal Cu(111) substrates exhibit improved crystallinity with >97% aligned graphene domains. As-synthesized SCG wafers exhibit an average carrier mobility up to 7284 cm 2 V −1 s −1 at room temperature from 103 devices and a uniform sheet resistance with only 5% deviation in 4 in. region.

36 MATERIALS SCIENCE↗

Mechanical Resonant Sensing of Spin Texture Dynamics in a 2D Antiferromagnet

Abstract The coupling between the spin degrees of freedom and macroscopic mechanical motions, including striction, shearing, and rotation, has attracted wide interest with applications in actuation, transduction, and information processing. Experiments so far have established the mechanical responses to the long‐range ordered or isolated single spin states. However, it remains elusive whether mechanical motions can couple to a different type of magnetic structure, the non‐collinear spin textures, which exhibit nanoscale spatial variations of spin (domain walls, skyrmions,etc.) and are promising candidates to realize high‐speed computing devices. Here, collective spin texture dynamics is detected with nanoelectromechanical resonators fabricated from 2D antiferromagnetic (AFM) MnPS 3 with 10 −9 strain sensitivity. By examining radio frequency mechanical oscillations under magnetic fields, new magnetic transitions are identified with sharp dips in resonant frequency. They are attributed to collective AFM domain wall motions as supported by the analytical modeling of magnetostriction and large‐scale spin‐dynamics simulations. Additionally, an abnormally large modulation in the mechanical nonlinearity at the transition field infers a fluid‐like response due to ultrafast domain motion. The work establishes a strong coupling between spin texture and mechanical dynamics, laying the foundation for electromechanical manipulation of spin texture and developing quantum hybrid devices.

Chemistry↗

Giant Orbital Anisotropy with Strong Spin–Orbit Coupling Established at the Pseudomorphic Interface of the Co/Pd Superlattice

Orbital anisotropy at interfaces in magnetic heterostructures has been key to pioneering spin–orbit-related phenomena. However, modulating the interface’s electronic structure to make it abnormally asymmetric has been challenging because of lack of appropriate methods. Here, the authors report that low-energy proton irradiation achieves a strong level of inversion asymmetry and unusual strain at interfaces in [Co/Pd] superlattices through nondestructive, selective removal of oxygen from Co3O4/Pd superlattices during irradiation. Structural investigations corroborate that progressive reduction of Co3O4into Co establishes pseudomorphic growth with sharp interfaces and atypically large tensile stress. The normal component of orbital to spin magnetic moment at the interface is the largest among those observed in layered Co systems, which is associated with giant orbital anisotropy theoretically confirmed, and resulting very large interfacial magnetic anisotropy is observed. All results attribute not only to giant orbital anisotropy but to enhanced interfacial spin–orbit coupling owing to the pseudomorphic nature at the interface. They are strongly supported by the observation of reversal of polarity of temperature-dependent Anomalous Hall signal, a signature of Berry phase. This work suggests that establishing both giant orbital anisotropy and strong spin–orbit coupling at the interface is key to exploring spintronic devices with new functionalities.

42 ENGINEERING↗

Individuals with Alzheimer's disease and low tau burden: Characteristics and implications

Abnormal amyloid-beta (Aβ) and tau deposition define Alzheimer's Disease (AD), but non-elevated tau is relatively frequent in patients on the AD pathway. We examined characteristics and regional patterns of 397 Aβ+ unimpaired and impaired individuals with low tau (A+T-) in relation to their higher tau counterparts (A+T+). Seventy-one percent of Aβ+ unimpaired and 42% of impaired Aβ+ individuals were categorized as A+T- based on global tau. In impaired individuals only, A+T- status was associated with older age, male sex, and greater cardiovascular risk. α-synuclein was linked to poorer cognition, particularly when tau was low. Tau burden was most frequently elevated in a common set of temporal regions regardless of T+/T- status. Low tau is relatively common in patients on the AD pathway and is linked to comorbidities that contribute to impairment. These findings have implications for the selection of individuals for Aβ- and tau-modifying therapies.

60 APPLIED LIFE SCIENCES↗

The POINTER Imaging baseline cohort: Associations between multimodal neuroimaging biomarkers, cardiovascular health, and cognition

Abstract INTRODUCTION The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is evaluating lifestyle interventions in older adults at risk for cognitive decline and dementia. Here we characterize the baseline data set of the POINTER Imaging ancillary study. METHODS Participants underwent health and cognitive assessments and neuroimaging with multimodal positron emission tomography (PET) (beta‐amyloid [Aβ] and tau) and magnetic resonance imaging (MRI). Framingham risk score (FRS) was used to quantify cardiovascular disease (CVD) risk. RESULTS A total of 1052 participants (31% from underrepresented ethnoracial groups) were enrolled. Compared to Aβ−, Aβ+ (29%) participants were older, had higher apolipoprotein E (APOE) ε4 carriage rate and white matter hyperintensity volume, and greater temporal tau. FRS was related to MRI measures, but not AD biomarkers. FRS and tau had independent effects on cognition. DISCUSSION In this heterogenous, at‐risk cohort, CVD risk was related to more abnormal brain structure and poorer cognition, representing a putative non‐AD (Alzheimer's disease) pathway to brain injury and cognitive decline. Highlights The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) cohort is enriched for cardiovascular disease (CVD) and poor lifestyle POINTER Imaging collected multimodal neuroimaging data in this unique, at‐risk cohort Amyloid burden was related to age, apolipoprotein E (APOE) ε4 carriage, and measures of disease progression Associations between amyloid and tau, and tau and cognition, were relatively weak CVD risk and tau pathology were independently related to memory

Neurosciences & Neurology↗

Global functional connectivity density alterations in patients with bipolar disorder with auditory verbal hallucinations and modest short‐term effects of transcranial direct current stimulation augmentation treatment—Baseline and follow‐up study

Abstract Objectives To investigate the neuroimaging characteristics of auditory verbal hallucinations (AVHs) in patients with bipolar disorder (BP) experiencing depressive episodes with and without AVHs, and alterations in those characteristics after transcranial direct current stimulation (tDCS). Methods For a baseline pilot study, we recruited 80 patients with BP and depressive status (40 with and 40 without AVHs), and 40 healthy controls (HCs). Their global functional connectivity density (gFCD) was screened by functional magnetic resonance imaging (fMRI). Voxel‐wise one‐way analysis of covariance (ANCOVA) was conducted to detect intergroup differences in gFCD. In a follow‐up study, the effects of 5 weeks of tDCS augmentation treatment on clinical symptoms and gFCD were assessed in the 40 BP patients with AVHs. Results Compared to HCs, BP patients with and without AVHs exhibited increased gFCD in the central parietal lobe, insular lobe, and middle cingulate cortex, with decreased gFCD in the posterior parietal cortex, lateral prefrontal cortex, and occipital lobe (all bilateral). Only patients with AVHs showed increased gFCD in the Broca and Wernicke regions, and decreased gFCD in the hippocampus (all bilateral). After 5 weeks of tDCS, AVHs were slightly alleviated and gFCD abnormalities in the hippocampus were mildly attenuated. Conclusions Patients with BP and AVHs showed disturbances in the brain's communication capacity mainly in the left frontoparietal network, control network, and memory circuitry. Five weeks of tDCS alleviated AVHs slightly, without improving depressive symptoms, and attenuated hippocampal gFCD alterations in these patients.

Zhuo, Chuanjun↗

Probing of Local Structure in Laves Compound TbFe 2

Abstract The Laves compounds Tb 1‐x Dy x Fe 2 have attracted much interest due to the giant magnetostriction effect appearing at their morphotropic phase boundary compositions. Although previous studies have established the relationship between the average structure and magnetostrictive properties in these compounds, there is a lack of characterization of their local structures. In this paper, as a first step toward this goal, the evolution of the local structure of the terminal compound (TbFe 2 ) of this system is reported, in an attempt to provide useful information about interatomic bonding in this system. The pair distribution function (PDF) results suggest that the compound presents the rhombohedral local crystal symmetry. The lattice at the local scale shows abnormal thermal expansion which is different from the long scale structure. The different role of the Tb─Fe bond and Fe─Fe bond in affecting the crystal lattice is revealed. These findings highlight the important role of local structure in determining the magnetostrictive properties of the Laves compounds.

Kou, Ronghui↗

Transient Copper Exposure During Embryogenesis and Temperature Affect Developmental Rate, Survival, and Fin Regeneration in Japanese Medaka ( Oryzias latipes )

Combined environmental stressors that an organism experiences can have both immediate and lasting consequences. In this paper we exposed medaka (Oryzias latipes) embryos to sublethal copper sulfate (CuSO 4 ) (0, 10, and 100 ppb) in combination with different rearing temperatures (27, 30, and 33°C) to assess acute and latent effects on development, growth, and regenerative capacity. Embryos exposed to CuSO 4 and/or higher temperatures hatched significantly earlier. At 4 months post-exposure, fish exposed to low levels of CuSO 4 during development had higher survival, while fish exposed to both 100 ppb CuSO 4 and 33°C temperatures had significantly lower survival. Additionally, a sex-specific effect of embryonic CuSO 4 exposure was observed as female mass decreased with increasing copper dose. We also assessed caudal fin regenerative capabilities in both embryo-exposed fish at 4 months of age and adult medaka that were exposed to 0, 10, and 100 ppb CuSO 4 at room temperature during a 14- day trial. Whereas fin regeneration was unaffected by adult exposure to copper, fish transiently exposed during embryogenesis displayed an initial increase in fin growth rate and an increased incidence of abnormal fin morphology following regrowth. Collectively, these data suggest that developmental copper exposure has the potential to exert long lasting impacts to organismal growth, survival, and function.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗