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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A purity monitor for the KEDR liquid krypton calorimeter

We present a purity monitor for the KEDR liquid krypton calorimeter. A new method is suggested based on the usage of a short pulse of a gas discharge as a source of ultraviolet radiation for the photoproduction of electrons in a drift cell of the monitor. This paper describes the design of the monitor, the results of experiments with gaseous and liquid krypton, as well as the experience of using the developed device in the process of krypton purification for the KEDR liquid krypton calorimeter.

Evtushenko, P. N.↗
DOE OSTI2022

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
DOE OSTI2022

Optimizing the Internal Cell Structure of the Radon Monitor Based on Electrostatic Collection Method

Abstract As Rn-222 decays, an alpha particle is emitted and the residual polonium nucleus recoils in the opposite direction. At the end of the recoil path, 88% of the polonium atoms have a positive charge and 12% are neutral. The electric potential distribution in the 60 ml hemispherical internal cell of the radon monitor based on electrostatic collection is studied for reducing the combined probability of the positively charged Po-218 and the OH− produced by the ionization of water vapour in the air. The COMSOL software is used to simulate the electric potential distribution in the internal cell of the radon monitor based on the electrostatic collection method at 27°C, a pressure of 0.1 Mpa. For improving the collection efficiency of Po-218 ions, the average collection time along vertical and oblique lines is calculated when the upper surface of the internal cell is plastic, uncharged metal and charged metal, respectively. Assuming that the gas in the internal cell is uniformly distributed, the results show that if the upper surface of the hemispherical internal cell is plastic or uncharged metal, the electric potential formed in the internal cell is more uniform, and it is beneficial to reduce the total collection time of the positively charged Po-218 ions, thereby improving collection efficiency. The simulation results can be used as an effective reference for optimizing the design of the internal cell structure of the radon monitor based on electrostatic collection method.

Fan, Zhongkai (ORCID:0000000181247459)↗
DOE OSTI2024

Learnability Transitions in Monitored Quantum Dynamics via Eavesdropper’s Classical Shadows

Monitored quantum dynamics—unitary evolution interspersed with measurements—has recently emerged as a rich domain for phase structure in quantum many-body systems away from equilibrium. Here we study monitored dynamics from the point of view of an eavesdropper who has access to the classical measurement outcomes, but not to the quantum many-body system. We show that a measure of information flow from the quantum system to the classical measurement record—the —undergoes a phase transition in correspondence with the measurement-induced phase transition (MIPT). This transition determines the eavesdropper’s (in)ability to learn properties of an unknown initial quantum state of the system, given a complete classical description of the monitored dynamics and arbitrary classical computational resources. We make this learnability transition concrete by defining classical shadow protocols that the eavesdropper may apply to this problem, and show that the MIPT manifests as a transition in the sample complexity of various shadow-estimation tasks, which become harder in the low-measurement phase. We focus on three applications of interest: Pauli expectation values (where we find the MIPT appears as a point of optimal learnability for typical Pauli operators), many-body fidelity, and global charge in U ( 1 ) -symmetric dynamics. Our work unifies different manifestations of the MIPT under the umbrella of and gives this notion a general operational meaning via classical shadows. Published by the American Physical Society 2024

Physics↗
DOE OSTI2017

A Distribution Level Wide Area Monitoring System for the Electric Power Grid–FNET/GridEye

The wide area monitoring system (WAMS) is considered a pivotal component of future electric power grids. As a pilot WAMS that has been operated for more than a decade, the frequency monitoring network FNET/GridEye makes use of hundreds of global positioning system-synchronized phasor measurement sensors to capture the increasingly complicated grid behaviors across the interconnected power systems. In this paper, the FNET/GridEye system is overviewed and its operation experiences in electric power grid wide area monitoring are presented. Particularly, the implementation of a number of data analytics applications will be discussed in details. FNET/GridEye lays a firm foundation for the later WAMS operation in the electric power industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Online condition monitoring based dead-time compensation for high frequency SiC voltage source inverter

Dead-time, device output capacitance, and other non-ideal characteristics cause voltage error for the midpoint PWM voltage of the semiconductor phase-leg employed in a voltage-source inverter (VSI). Voltage-second balancing is a well-known concept to mitigate this distortion and improve converter power quality. This paper proposes a unique voltage-second balancing scheme for a SiC based voltage source inverter using online condition monitoring of turn-off delay time and drain-source voltage rise/fall time. This data is sent to the micro-controller to be used in an algorithm to actively adjust the duty cycle of the input PWM gate signals to match the voltage-second of the non-ideal output voltage with an ideal output voltage-second. The monitoring system also allows for this implementation to eliminate the need for precise current sensing and allows for the implementation to be load independent. Dynamic current sensing is still a developing technology, and each load has a unique effect on the output voltage distortion. Test results for a 1 kW half-bridge inverter implementing this monitoring system and voltage-second balancing scheme show a 70% enhancement on the error against the ideal fundamental current value of the output current and a 2% THD improvement on the output current low frequency harmonics.

Dyer, Jacob↗
DOE OSTI2026

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2026

Digital Twin Based Condition Monitoring of LCC-LCC Inductive Power Transfer Systems

Inductive power transfer (IPT) systems provide a flexible, hands-free charging opportunity to electric vehicles (EV). The resonant network components and the transmitter and receiver coils are often subjected to high voltages or currents. Component aging in the compensation network and coils of resonant IPT systems is detrimental to the reliability and power transfer efficiency of the IPT system. Monitoring the component health of such multi-element complex systems requires robust optimization algorithms. This paper discusses condition monitoring of a resonant IPT system for an EV charger using a digital twin model. A hybrid estimation algorithm based on genetic algorithms and adaptive particle swarm optimization is developed to estimate the parameters of the digital twin model. Simulation results are used to verify the monitoring capabilities of the developed algorithm under various operating conditions of the IPT system.

Weldehawaryat, Lidya Mussie [graduate research ass↗
DOE OSTI2024

PMU Data Quality and Sensor Health Monitoring

Phasor Measurement Units (PMUs) play a critical role in the evolution of the electric power industry by providing high-precision, real-time monitoring of essential power system metrics. However, effectively detecting abnormalities and critical events from PMU data is a complex task, complicated by intricate temporal patterns, a scarcity of labeled data for training algo- rithms, and constraints on online computational power. In this study, we apply TranAD, an innovative algorithm that combines transformer architectures with the refinement of adversarial learning, to both synthetic and real-world PMU datasets for developing a data quality and sensor online health monitoring platform for utilities. Our findings reveal that TranAD not only provides efficient detection and localization but also enhances the detail with which abnormalities are detected, marking a a significant step forward in the field of clean data acquisition processes for power system monitoring

deep neural network, machine learning (ML)↗
DOE OSTI2021

A Cyber Threat Mitigation Approach For Wide Area Control of SVCs using Stability Monitoring

We propose a stability monitoring approach for the mitigation of cyber threats directed at the wide area control (WAC) system used for coordinated control of Flexible AC Transmission Systems (FACTS) used for power oscillation damping (POD) of active power flow on inter-area tie lines. The approach involves monitoring the modes of the active power oscillation on an inter-area tie line using the Matrix Pencil (MP) method. We use the stability characteristics of the observed modes as a proxy for the presence of destabilizing cyber threats. We monitor the system modes to determine whether any destabilizing modes appear after the WAC system engages to control the POD. If the WAC signal exacerbates the POD performance, the FACTS falls back to POD using local measurements. The proposed approach does not require an expansive system-wide view of the network. We simulate replay, control integrity, and timing attacks for a test system and present results that demonstrate the performance of the SM approach for mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Real-Time Monitoring of Temperature Rises of Energized Transformer Cores With Distributed Optical Fiber Sensors

Real-time temperature mapping that solves local overheating problems is important for obtaining an optimized thermal design for high-efficiency power transformers. Internal temperature monitoring of operating power transformers can also be leveraged for asset monitoring applications targeting at fault detection enabling condition-based maintenance. Transformers present a variety of challenging sensing environments such as high levels of electromagnetic interference and limited space for conventional sensors to operate. Immersion of power transformers in insulation oils for thermal management during operation and the presence of relatively large and time-varying electrical and occasional magnetic fields make sensing technologies requiring electrical wires or active power at sensing locations highly undesirable. In this work, we investigate thermal response of a standard telecom fiber instrumented on compact transformer cores by using an optical frequency-domain reflectometry scheme. As a result, correlation between conventional temperature sensing methods and fiber-optic sensing results as well as tradeoffs between spatial resolution and temperature measurement accuracy is discussed and spatially resolved real-time monitoring of temperatures in energized transformers is experimentally demonstrated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

PMU-Based Monitoring and Mitigation of Delayed Voltage Recovery Using Admittances

This project analyzes the delayed voltage recovery phenomenon by simplifying the Western Electricity Coordinating Council (WECC) composite load model using the load admittance and the thermal relay dynamics. From this analysis, a closed form expression approximating the recovery time is derived and the key load parameters impacting the behavior of voltage recovery are identified. A monitoring scheme based on the measured load admittance is then proposed to detect the onset of stalling, even in the presence of voltage oscillations, and estimate the duration of the delayed voltage recovery. A mitigation scheme utilizing smart thermostats and offline learning is also derived to ensure that the voltage recovers to the pre-contingency voltage within a specified time. Both the monitoring and mitigation schemes only need local measurements at a substation making them promising for online applications. Results for the monitoring and mitigation schemes are described in detail for the IEEE 162 bus system validating the various assumptions used for the analysis and establishing the connection between the delayed voltage recovery phenomenon and load admittance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Fast Parallel Stochastic Subspace Algorithms for Large-Scale Ambient Oscillation Monitoring

With the installation of synchrophasors widely across the power grid, measurement-based oscillation monitoring algorithms are becoming increasingly useful in identifying the real-time oscillatory modal properties in power systems. When the number of phasor measurement unit (PMU) channels grows, the computational time of many PMU data based algorithms is dominated by the computational burden in processing large-scale dense matrices. In order to overcome this limitation, this paper presents new formulations and computational strategies for speeding up an ambient oscillation monitoring algorithm, namely, stochastic subspace identification (SSI). Based on previous work, two fast singular value decomposition (SVD) approaches are first applied to the SVD evaluation within the SSI algorithm. Next, block structures are exploited so that the large-scale dense matrix computations can be processed in parallel. This helps in memory savings as well as in overall computational time. Experimental results from three sets of archived data of the western interconnection demonstrate that the new approaches can provide significant speedups while retaining modal estimation accuracy. With proposed fast parallel algorithms, the real-time oscillation monitoring of the large-scale system using hundreds of PMU measurements becomes feasible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Feasibility Assessment of Long-Term Electrical Resistivity Monitoring of a Nitrate Plume

Long-term monitoring solutions at contaminated sites are necessary to track plume migration and evaluate the performance of remediation efforts. Electrical resistivity imaging (ERI) can potentially provide information about plume dynamics; however, the feasibility and likelihood of success is seldom evaluated before conducting a field study. Coupling flow and transport models with geoelectrical models provides a powerful way to assess the potential effectiveness of an actual ERI field campaign. in this paper, we present a coupled approach for evaluating the feasibility of monitoring nitrate migration and remediation using 4D time-lapse ERI at a legacy nuclear waste facility. This kilometer-scale study focuses on depths below the water table (~70 m). A flow and transport model is developed to perform simulations of nitrate migration and removal via a hypothetical pump-and-treat system. A tracer injection is also simulated at the leading edge of the nitrate plume to enhance the conductivity contrast between the native subsurface and the groundwater fluids. Images of bulk conductivity provide limited information concerning plume migration while time-lapse difference images, which remove the static effects of geology, provide more useful information concerning plume dynamics over time. A spatial moment analysis performed on flow and transport and ERI models matches well during the tracer injection; however, inversion regularization smoothing otherwise limits the value in terms of locating the center of mass. We find that the addition of a tracer enables ERI to characterize plume dynamics during pump-and-treat operations, and late-time ERI monitoring provides a conservative estimate of nitrate plume boundaries in this synthetic study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-D-17A-07: Development and Evaluation of a Prototype Ultrasonography Respiratory Monitoring System for 4DCT Reconstruction

Purpose: Respiratory motion artifacts are commonly seen in the abdominal and thoracic CT images. A Real-time Position Management (RPM) system is integrated with CT simulator using abdominal surface as a surrogate for tracking the patient respiratory motion. The respiratory-correlated four-dimensional computed tomography (4DCT) is then reconstructed by GE advantage software. However, there are still artifacts due to inaccurate respiratory motion detecting and sorting methods. We developed an Ultrasonography Respiration Monitoring (URM) system which can directly monitor diaphragm motion to detect respiratory cycles. We also developed a new 4DCT sorting and motion estimation method to reduce the respiratory motion artifacts. The new 4DCT system was compared with RPM and the GE 4DCT system. Methods: Imaging from a GE CT scanner was simultaneously correlated with both the RPM and URM to detect respiratory motion. A radiation detector, Blackcat GM-10, recorded the X-ray on/off and synchronized with URM. The diaphragm images were acquired with Ultrasonix RP system. The respiratory wave was derived from diaphragm images and synchronized with CT scanner. A more precise peaks and valleys detection tool was developed and compared with RPM. The motion is estimated for the slices which are not in the predefined respiratory phases by using block matching and optical flow method. The CT slices were then sorted into different phases and reconstructed, compared with the images reconstructed from GE Advantage software using respiratory wave produced from RPM system. Results: The 4DCT images were reconstructed for eight patients. The discontinuity at the diaphragm level due to an inaccurate identification of phases by the RPM was significantly improved by URM system. Conclusion: Our URM 4DCT system was evaluated and compared with RPM and GE 4DCT system. The new system is user friendly and able to reduce motion artifacts. It also has the potential to monitor organ motion during therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-D-210-06: Feasibility for Monitoring the Head of the Pancreas Motion Through a Surrogate Using Ultrasound During Radiation Therapy Delivery

Purpose: Substantial target motion during the delivery of radiation therapy (RT) for pancreatic cancer is well recognized as a major limiting factor on RT effectiveness. The aim of this work is to monitor intra-fractional motion of the pancreas using ultrasound during RT delivery. Methods: Transabdominal Ultrasound B-mode images were collected from 5 volunteers using a research version of the Clarity Autoscan System (Elekta). The autoscan transducer with center frequency of 5 MHz was utilized for the scans. Imaging parameters were adjusted to acquire images at the desired depth with good contrast and a wide sweep angle. Since well-defined boundaries of the pancreas can be difficult to find on ultrasound B-mode images, the portal vein was selected as a surrogate for motion estimation of the head of the pancreas. The selection was due to its anatomical location posterior to the neck of the pancreas and close proximity to the pancreas head. The portal vein was contoured on the ultrasound images acquired during simulation using the Clarity Research AFC Workstation software. Volunteers were set up in a similar manner to the simulation for their monitoring session and the ultrasound transducer was mounted on an arm fixed to the couch. A video segment of the portal vein motion was captured. Results: The portal vein was visualized and segmented. Successful monitoring sessions of the portal vein were observed. In addition, our results showed that the ultrasound transducer itself reduces breathing related motion. This is analogous to the use of a compression plate to suppress respiration motion during thorax or abdominal irradiation. Conclusion: We demonstrate the feasibility of tracking the pancreas through the localization of the portal vein using abdominal ultrasound. This will allow for real-time tracking of the intra-fractional motion to justify PTV-margin and to account for unusual motions, thus, improving normal tissue sparing. This research was funding in part by Elekta Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-194: Continuous Patient Surface Monitoring and Motion Analysis During Lung SBRT

Purpose: Continuous monitoring of the SBRT lung patient motion during delivery is critical for ensuring adequate target volume margins in stereotactic body radiotherapy (SBRT). This work assesses the deviation of the patient surface motion using a real-time surface tracking system throughout treatment delivery. Methods: Our SBRT protocol employs abdominal compression to reduce the diaphragm movement to within 1 cm, and this is confirmed daily with fluoroscopy. Most patients are prescribed 3–5 fractions, and on treatment day a repeat motion analysis with fluoroscopy is performed, followed by a kV CBCT is aligned with the original planning CT image for 3D setup confirmation. During this entire process a patient surface data restricted to whole chest or the sternum at the middle of the breathing cycle was captured using AlignRT optical surface tracking system and defined as a reference surface. For 10 patients, the deviation of the patient position from the reference surface was recorded during the SBRT delivery in the anterior-posterior (AP) direction at 3–6 measurements per second. Results: On average, the patient position deviated from the reference surface more than 4 mm, 3 mm and 2 mm in the AP direction for 0.95%, 3.7% and 11.1% of the total treatment time, respectively. Only one of the 10 patients showed that the maximum deviation of the patient surface during the SBRT delivery was greater than 1 cm. The average deviation of the patient surface from the reference surface during the SBRT delivery was not greater than 1.6 mm for any patient. Conclusion: This investigation indicates that AP motion can be significant even though the frequency is low. Continuous monitoring during SBRT has demonstrated value in monitoring patient motion ensuring that margins selected for SBRT are appropriate, and the use of non-ionizing and high-frequency imaging can provide useful indicators of motion during treatment.

60 APPLIED LIFE SCIENCES↗