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At least 811 records · Page 45

5G integrated edge computing platform for efficient component monitoring in coal-fired power plants

This project developed a cutting-edge 5G-integrated edge computing framework to enhance operational efficiency and reliability in coal-fired power plants through real-time component monitoring and anomaly detection. The initiative focused on leveraging distributed machine learning, federated learning, and 5G-based dynamic network slicing to support scalable, fault-tolerant monitoring environments to meet the operational requirements in industrial control systems. With a Distributed Edge Computing Service (DECS) orchestration, this project enabled federated learning at edge for condition monitoring and introduced adaptive client selection strategies to minimize communication overhead. Scalable distributed training was achieved using the Horovod framework, thus enhancing performance across edge nodes. In the realm of 5G networking, the project designed and deployed reconfigurable, QoS-aware network slicing tailored for operational technology (OT) environments, integrating software-defined networks to bolster cyber-resilience and enabling dynamic slicing for federated learning workloads. A significant milestone was the development of a virtualized ICS environment with 5G core integration—which allowed elastic and fault tolerant distributed training on real-world datasets such as NASA Bearings, Hydraulic Systems, and TEP. To broaden the impact of the project, a TRL-3 virtualized ICS testbed for research and education was designed. This project engaged several graduate and undergraduate students to conduct research on the cutting-edge technology, and it resulted in one PhD dissertation, one MS thesis, and over 14 peer-reviewed publications. With the support of this project students also participated in national cybersecurity competitions to improve their professional development skills.

20 FOSSIL-FUELED POWER PLANTS↗

Novel Carbon Storage Monitoring Methods

Conference presentation at American Institute of Chemical Engineers (AIChE) Annual Meeting, San Diego, California, October 27–31, 2024. We presented a high-level overview of many novel and sustainable carbon storage monitoring methods that are at various stages of planning or demonstration to accelerate the deployment of CCS technologies at future CCS sites across the United States. Our work impacts the general CCS industry by providing novel and more sustainable methods for tracking CO 2 plume migration and performing assurance monitoring. Our work primarily benefits three parties: 1) CCS community members through knowledge sharing of lessons learned; 2) CCS operators through commercialization of additional methods, including improvements on workflows and simplification of fieldwork; and 3) stakeholders of CCS projects through implementation of low-impact and more autonomous monitoring solutions.

02 PETROLEUM↗

Design of an AIM Network for Monitoring Carbon Storage Projects

Conference poster presented at Carbon Capture, Utilization, and Storage (CCUS) Conference 2024, Houston, Texas, March 11–13, 2024. The Energy & Environmental Research Center (EERC) is researching novel carbon storage-monitoring techniques at an approved North Dakota geologic carbon storage site. One of the research objectives is to design an autonomous, integrated, and modular (AIM) monitoring network that is compliant with monitoring requirements across multiple carbon capture and storage (CCS) policy frameworks, such as the U.S. Environmental Protection Agency’s (EPA) underground injection control (UIC) Class VI permitting program.

02 PETROLEUM↗

Recent Collaborations and Innovations to Demonstrate Next-Generation Techniques for Monitoring Subsurface Carbon Storage

World Carbon Capture, Utilization, and Storage (CCUS) Conference, Bergen, Norway, September 1–4, 2025. This talk provides a high-level overview of many novel and sustainable carbon storage-monitoring methods to accelerate the deployment of CCUS technologies at future CCUS sites across the United States. The Energy & Environmental Research Center’s work impacts the general CCUS industry by providing novel low-impact methods for tracking the injected plume’s migration and more autonomous data collection and processing techniques for performing assurance monitoring. Specifically, the results benefit 1) CCUS community members through knowledge sharing of lessons learned; 2) CCUS operators through commercialization of additional methods, including improvements to workflows and simplification of fieldwork; and 3) CCUS project stakeholders through implementation of low-impact and more autonomous monitoring solutions.

02 PETROLEUM↗

Riverbed Temperature and 4D ERT Monitoring Reveals Heterogenous Horizontal and Vertical Groundwater-Surface Water Exchange Flows Under Dynamic Stage Conditions

Groundwater surface water exchange plays a critical role in physical, biological, and geochemical function of coastal and riverine systems. Observing exchange flow behavior in heterogeneous systems is a primary challenge, particularly when flows are governed by dynamic river stage or tidal variations. In this paper we demonstrate a novel application of time-lapse 3D electrical resistivity tomography and temperature monitoring where an array of thermistors installed beneath a riverbed double as resistivity electrodes. We use the array to monitor stage driven exchange flows over a 6-day period in a dynamic, stage-driven high order stream. We present a method for addressing the otherwise confounding effects of the moving river-surface boundary on the raw resistivity data, thereby enabling successful tomographic imaging. Temperature time-series at each thermistor location and time-lapse 3D images of changes in bulk electrical conductivity together provide a detailed description of exchange dynamics over a 10-meter by 45-meter section of the riverbed, to a depth of approximately 5 m. Results reveal highly variable flux behavior throughout the monitoring domain including both horizontal and vertical exchange flows.

54 ENVIRONMENTAL SCIENCES↗

Magnetoimpedance Biosensors and Real-Time Healthcare Monitors: Progress, Opportunities, and Challenges

A small DC magnetic field can induce an enormous response in the impedance of a soft magnetic conductor in various forms of wire, ribbon, and thin film. Also known as the giant magnetoimpedance (GMI) effect, this phenomenon forms the basis for the development of high-performance magnetic biosensors with magnetic field sensitivity down to the picoTesla regime at room temperature. Over the past decade, some state-of-the-art prototypes have become available for trial tests due to continuous efforts to improve the sensitivity of GMI biosensors for the ultrasensitive detection of biological entities and biomagnetic field detection of human activities through the use of magnetic nanoparticles as biomarkers. In this review, we highlight recent advances in the development of GMI biosensors and review medical devices for applications in biomedical diagnostics and healthcare monitoring, including real-time monitoring of respiratory motion in COVID-19 patients at various stages. We also discuss exciting research opportunities and existing challenges that will stimulate further study into ultrasensitive magnetic biosensors and healthcare monitors based on the GMI effect.

60 APPLIED LIFE SCIENCES↗

A Summary of Environmental Monitoring Recommendations for Marine Energy Development That Considers Life Cycle Sustainability

Recommendations derived from papers documenting the Triton Field Trials (TFiT) study of marine energy environmental monitoring technology and methods under the Triton Initiative (Triton), as reported in this Special Issue, are summarized here. Additionally, a brief synopsis describes how to apply the TFiT recommendations to establish an environmental monitoring campaign, and provides an overview describing the importance of identifying the optimal time to perform such campaigns. The approaches for tracking and measuring the effectiveness of recommendations produced from large environmental monitoring campaigns among the stakeholder community are discussed. The discussion extends beyond the initial scope of TFiT to encourage discussion regarding marine energy sustainability that includes life cycle assessment and other life cycle sustainability methodologies. The goal is to inspire stakeholder collaboration across topics associated with the marine energy industry, including diversity and inclusion, energy equity, and how Triton’s work connects within the context of the three pillars of energy sustainability: environment, economy, and society.

16 TIDAL AND WAVE POWER↗

Liquid Core Detection and Strand Condition Monitoring in a Continuous Caster Using Optical Fiber

Real-time monitoring of the liquid core position during the continuous casting of steel has been demonstrated using low-cost distributed optical-fiber-based strain sensors. These sensors were installed on the containment roll support structures in the segments of a production continuous caster to detect the position of the solid–liquid interface and monitor the strand condition during the continuous casting. Distributed Fiber Bragg Grating sensors (FBGs) were used in this work to monitor strain at six roll positions in the caster. The sensor performance was first validated by comparing optical strain measurements with conventional strain gauge measurements in the lab. Next, optical strain measurements were performed on an isolated caster segment in a segment maintenance facility using hydraulic jacks to simulate the presence of a liquid core under the roll. Finally, the sensors were evaluated during caster operation. The sensors successfully detected the load increase associated with the presence of a liquid core under each instrumented roll location. Incidents of bulging and roll eccentricity were also detected using frequency analysis of the optical strain signal. The liquid core position measurements were compared using predictions from computer models (digital twins) in use at the production site. The measurements were in good agreement with the model predictions, with a few exceptions. Under certain transient caster operating conditions, such as spraying practice changes and SEN exchanges, the model predictions deviated slightly from the liquid core position determined from strain measurements.

47 OTHER INSTRUMENTATION↗

Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter

The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data quality monitoring (DQM) system to promptly spot and diagnose particle data acquisition problems to avoid data quality loss. In this study, we present a semi-supervised spatio-temporal anomaly detection (AD) monitoring system for the physics particle reading channels of the Hadron Calorimeter (HCAL) of the CMS using three-dimensional digi-occupancy map data of the DQM. We propose the GraphSTAD system, which employs convolutional and graph neural networks to learn local spatial characteristics induced by particles traversing the detector and the global behavior owing to shared backend circuit connections and housing boxes of the channels, respectively. Recurrent neural networks capture the temporal evolution of the extracted spatial features. We validate the accuracy of the proposed AD system in capturing diverse channel fault types using the LHC collision data sets. The GraphSTAD system achieves production-level accuracy and is being integrated into the CMS core production system for real-time monitoring of the HCAL. We provide a quantitative performance comparison with alternative benchmark models to demonstrate the promising leverage of the presented system.

43 PARTICLE ACCELERATORS↗

Development of a Nuclear Fuel Dissolution Monitor Based on Raman Spectroscopy

The processing of spent nuclear fuel and other nuclear materials is a critical component of nuclear material management with implications for global security. The first step of fuel processing is dissolution, with several charges of fuel sequentially added to a batch of solvent. The incomplete dissolution of a charge precludes the addition of the next charge. As the dissolution takes place in a heated, highly corrosive and radiological vessel, direct monitoring of the process is not possible. We discuss the use of Raman spectroscopy to indirectly monitor dissolution through an analysis of the gaseous emissions from the dissolver. Challenges associated with the implementation of Raman spectroscopy include the composition and physical characteristics of the offgas stream and the impact of operating conditions. Nonetheless, we observed that NO2 concentrations serve as a reliable indicator of process activity and correlate to the amount of fuel material that remains undissolved. These results demonstrate the promise of the method for monitoring nuclear material dissolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

NASA Discipline Cardiopulmonary↗

A multiparameter wearable physiologic monitoring system for space and terrestrial applications

A novel, unobtrusive and wearable, multiparameter ambulatory physiologic monitoring system for space and terrestrial applications, termed LifeGuard, is presented. The core element is a wearable monitor, the crew physiologic observation device (CPOD), that provides the capability to continuously record two standard electrocardiogram leads, respiration rate via impedance plethysmography, heart rate, hemoglobin oxygen saturation, ambient or body temperature, three axes of acceleration, and blood pressure. These parameters can be digitally recorded with high fidelity over a 9-h period with precise time stamps and user-defined event markers. Data can be continuously streamed to a base station using a built-in Bluetooth RF link or stored in 32 MB of on-board flash memory and downloaded to a personal computer using a serial port. The device is powered by two AAA batteries. The design, laboratory, and field testing of the wearable monitors are described.

NASA Center ARC↗

Structural Health Monitoring on Turbine Engines Using Microwave Blade Tip Clearance Sensors

The ability to monitor the structural health of the rotating components, especially in the hot sections of turbine engines, is of major interest to aero community in improving engine safety and reliability. The use of instrumentation for these applications remains very challenging. It requires sensors and techniques that are highly accurate, are able to operate in a high temperature environment, and can detect minute changes and hidden flaws before catastrophic events occur. The National Aeronautics and Space Administration (NASA) has taken a lead role in the investigation of new sensor technologies and techniques for the in situ structural health monitoring of gas turbine engines. As part of this effort, microwave sensor technology has been investigated as a means of making high temperature non-contact blade tip clearance, blade tip timing, and blade vibration measurements for use in gas turbine engines. This paper presents a summary of key results and findings obtained from the evaluation of two different types of microwave sensors that have been investigated for use possible in structural health monitoring applications. The first is a microwave blade tip clearance sensor that has been evaluated on a large scale Axial Vane Fan, a subscale Turbofan, and more recently on sub-scale turbine engine like disks. The second is a novel microwave based blade vibration sensor that was also used in parallel with the microwave blade tip clearance sensors on the experiments with the sub-scale turbine engine disks.

Gas Turbine Engines↗

The JPL Electronic Nose: Monitoring Air in the US Lab on the International Space Station

An electronic nose with a sensor array of 32 conductometric sensors has been developed at the Jet Propulsion Laboratory (JPL) to monitor breathing air in spacecraft habitat. The Third Generation ENose is designed to operate in the environment of the US Lab on the International Space Station (ISS). It detects a selected group of analytes at target concentrations in the ppm regime at an environmental temperature range of 18 - 30 oC, relative humidity from 25 - 75% and pressure from 530 to 760 torr. The monitoring targets are anomalous events such as leaks and spills of solvents, coolants or other fluids. The JPL ENose operated as a technology demonstration for seven months in the U.S. Laboratory Destiny during 2008-2009. Analysis of ENose monitoring data shows that there was regular, periodic rise and fall of humidity and occasional releases of Freon 218 (perfluoropropane), formaldehyde, methanol and ethanol. There were also several events of unknown origin, half of them from the same source. Each event lasted from 20 to 100 minutes, consistent with the air replacement time in the US Lab.

chemical sensors↗

Recovery Rate is an Improved Metric for Monitoring Bioburden in Cleanrooms

The Astromaterials Acquisition and Curation Office maintains seven cleanrooms for curating extraterrestrial samples from a variety of sample return missions. These cleanrooms are monitored for inorganic and particulate contamination and are maintained at ISO 7 to ISO 4 equivalent standards as dictated by collection requirements. As part of the advanced curation effort and to prepare for future sample collections from carbonaceous asteroids and eventually Mars we have begun monitoring the microbiology of these cleanrooms. Insights gained from monitoring these labs can be applied to improving planetary protection efforts.

Planetary Protection↗

Indicators and Monitoring Systems for Urban Climate Resiliency

Cities in the USA and around the world have begun to take an active role in responding to climate change. A central requirement for effective urban climate strategies is the capacity to understand and measure how the climate is changing, the physical, environmental, and social impacts of the changes, and whether adaptation and resiliency policies and programs put in place in response are working. The objective of this paper is to review and assess how urban climate change and resiliency efforts can be measured and to define what might serve as meaningful indicator and monitoring protocols. The New York City Panel on Climate Change (NPCC) is used as a case study along with a reviews of the emerging literature of urban climate change indicators to analyze the requirements and processes needed for a successful urban climate resiliency indicator and monitoring (I and M) system. In the paper, the basic requirements of a proposed Urban Climate Resilience Indicators and Monitoring System are presented. A specific illustration of an I and M system for tracking the urban heat island highlights challenges as well as potential solutions embedded within such systems. Discussions how these protocols can be translated to other locales and settings, as well as the relationship to the US National Climate Assessment indicator process, are presented.

New York City Panel on Climate Change↗

Supporting Crew Medical Decisions on Deep Space Missions: A Real-Time Performance Monitoring

Crewed missions into deep space will require astronauts to respond autonomously to safety- and time-critical anomalies. These and other potential issues will require the continuous monitoring and recognition of potentially subtle, but complex, anomalous data patterns. NASA continues to investigate real-time metrics for Extravehicular Operations1 and for providing feedback to improve performance2. Since it is unknown how long-term exposure to deep space will affect crew health, continuous monitoring of clinical and subclinical status is warranted. NASA is characterizing crew medical decision-support needs and identifying the recommended requirements of a Clinical Decision Support System (CDSS) within the Exploration Medical Capability Element (ExMC) of the Human Research Program3. Early detection, and continuous monitoring, of performance may provide an effective prognostic capability for assessing crew health state, and the identified requirements could be provided for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. There is evidence to suggest that automatic, unobtrusive collection of keystroke features, such as alphanumeric key latencies, backspaces or typing rhythm, could be a valuable performance screening tool. Keystroke features show significant differences between control subjects and patients with overt clinical illness, such as multiple sclerosis4 and Parkinson’s disease5, as well as behavioral health and performance issues, such as mild cognitive impairment6 and depression7. This work is exploring a capability for the assessment of early task performance decline in crew as they perform daily activities. Timestamped keyboard entries are continuously collected and stored. Nominal keystroke interactions are compared to those obtained after exposure to spaceflight stressors, e.g., fatigue, to determine the methods sensitivity. This work will pave the way toward an objective detection tool that may be deployed in a spaceflight setting.

clinical↗

UASs Optimization - An evaluation of multiple mode vehicles in monitoring and communication

This presentation will describe the author's experience as Co-I in the NASA/USFS Project: "Strategic Tac Radio and Tac Overwatch (STRATO): Last Mile Communications and Realtime Observation Stratospheric Platforms for wildland fire". This project utilizes an uncrewed Stratospheric (> 70Kft) lighter than air Uninhabited Aerial System (UAS), carries 50 Kg of sensor and communications equipment, and remains on station over a wildfire for up to 30 days. The air vehicle is capable of in excess of 180 days on station, but while the full duration capabilities were not utilized in this project, they could, and would, be used in monitoring a feature like a volcano. In addition to duration, the ability of these Stratospheric Platforms to persistently monitor an area, while carrying "smart" sensors - generating information products, rather than just data - is game changing. Utilizing technologies such as LoRa, the platform can now be the nexus of an ad-hoc sensor web, receiving LoRa based data from low power in-situ sensors in the area being monitored, combining it with high fidelity information gained from on-board sensors, and sending the information product to a remote research facility, using Satellite communication, in real time. The author will relate the evolution of information collection, derivation and delivery mechanisms in the entire range of NASA's UAS fleet, to today's world, where information products conventionally derived in desk top computational environments, and made available to the Science Community in weeks or months, are now being generated and delivered in near real time.

UASs↗