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At least 1,567 records · Page 87

Chemical Functionalization, Self-Assembly, and Applications of Nanomaterials and Nanocomposites

This special issue addresses the research studies on chemical functionalization, self-assembly, and applications of nanomaterials and nanocomposites. It contains twentyfour articles including two reviews and twenty-two research articles. It is used to create new functional nanomaterials and nanocomposites with a variety of sizes and morphologies such as Zn/Al layered double hydroxide, tin oxide nanowires, FeOOH-modified anion resin, Au nanoclusters silica composite nanospheres, Ti-doped ZnO sol-composite films, TiO2/ZnO composite, graphene oxide nanocomposites, LiFePO4/C nanocomposites, and chitosan nanoparticles. These nanomaterials and nanocomposites have widespread applications in tissue engineering, antitumor, sensors, photoluminescence, electrochemical, and catalytic properties. In addition, this themed issue includes some research articles about self-assembly systems covering organogels and Langmuir films. Furthermore, B. Blasiak et al. performed a literature survey on the recent advances in production, functionalization, toxicity reduction, and application of nanoparticles in cancer diagnosis, treatment, and treatment monitoring. P. Colson et al. performed a literature survey on the recent advances in nanosphere lithography due to its compatibility with wafer-scale processes as well as its potential to manufacture a wide variety of homogeneous one-, two-, or three-dimensional nanostructures.

Jiao, Tifeng↗

Evaluation of an oil-debris monitoring device for use in helicopter transmissions

Experimental tests were performed on an OH-58A helicopter main-rotor transmission to evaluate an oil-debris monitoring device (ODMD). The tests were performed in the NASA 500-hp Helicopter Transmission Test Stand. Five endurance tests were run as part of a U.S. Navy/NASA/Army advanced lubricants program. The tests were run at 100 percent design speed, 117-percent design torque, and 121 C (250 F) oil inlet temperature. Each test lasted between 29 and 122 hr. The oils that were used conformed to MIL-L-23699 and DOD-L-85734 specifications. One test produced a massive sun-gear fatigue failure; another test produced a small spall on one sun-gear tooth; and a third test produced a catastrophic planet-bearing cage failure. The ODMD results were compared with oil spectroscopy results. The capability of the ODMD to detect transmission component failures was not demonstrated. Two of the five tests produced large amounts of debris. For these two tests, two separate ODMD sensors failed, possibly because of prolonged exposure to relatively high oil temperatures. One test produced a small amount of debris and was not detected by the ODMD or by oil spectroscopy. In general, the ODMD results matched the oil spectroscopy results. The ODMD results were extremely sensitive to oil temperature and flow rate.

Lewicki, David G.↗

Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis

A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.

Dempsey, Paula J.↗

TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring: Supporting Data

This dataset was used to assess the performance of a compression algorithm for Soil Deformation and Temperature Monitoring data. The development of this technology is presented in the article named time division duplex (TDD) "TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring" and published in Springer's Journal on Signal Processing Systems. [Time Division Duplex (TDD); Long Range (LoRa)]Field experiment data includes: 1) soil temperature measurements, 2) snow temperature data, 3) soil temperature and deformation data. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 15 minutes. Lists included for probe, datalogger, and packaging components. The two temperature data sets were acquired at a site at the East River Watershed, Colorado, while the temperature/deformation data were collected at the Teller Road (mile 27) site near Nome, Alaska. The package includes 8 comma-separated files (.csv) and one .pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Physiological and Cognitive Factors Related to Human Performance During the Grand Canyon Rim-to-Rim Hike

Exposure to extreme environments is both mentally and physically taxing, leading to suboptimal performance and even life-threatening emergencies. Physiological and cognitive monitoring could provide the earliest indicator of performance decline and inform appropriate therapeutic intervention, yet little research has explored the relationship between these markers in strenuous settings. The Rim-to-Rim Wearables at the Canyon for Health (R2RWATCH) study is a research project at Sandia National Laboratories funded by the Defense Threat Reduction Agency to identify which physiological and cognitive phenomena collected by non-invasive wearable devices are the most related to performance in extreme environments. In a pilot study, data were collected from civilians and military warfighters hiking the Rim-to-Rim trail at the Grand Canyon. Each participant wore a set of devices collecting physiological, cognitive, and environmental data such as heart rate, memory, ambient temperature, etc. Promising preliminary results found correlates between physiological markers recorded by the wearable devices and decline in cognitive abilities, although further work is required to refine those measurements. Planned follow-up studies will validate these findings and further explore outstanding questions.

60 APPLIED LIFE SCIENCES↗

Upgrade to Fixed and Translating Scintillation-based Loss Detector System in the Fermilab Drift Tube Linac

The closed-off structure of the Fermilab Drift Tube Linac precludes a robust array of instrumentation from directly monitoring the H- beam that is accelerated from 750 keV to 116 MeV. To improve beam tuning and operational assessment of Drift Tube Linac performance, scintillator-based loss monitors were previously installed along the exterior of the first two accelerating cavities to assess low energy beam losses. Here we present a recent upgrade to the loss monitor system, including significant improvements in analog signal processing to address baseline-interfering noise; digitization of the signals to enable regular operational use and tuning; and a new remote operation upgrade of the translating loss monitor with precise positioning of the loss monitor along its nine-foot track. Data from the fixed and translating detectors collected under varying beam conditions validate the utility of the upgrade.

Chen, E. V. [Fermilab]↗

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

Nanoplasmonic molecular ruler for nuclease activity and DNA footprinting

This invention provides a nanoplasmonic molecular ruler, which can perform label-free and real-time monitoring of nucleic acid (e.g., DNA) length changes and perform nucleic acid footprinting. In various embodiments the ruler comprises a nucleic acid attached to a nanoparticle, such that changes in the nucleic acid length are detectable using surface plasmon resonance. The nanoplasmonic ruler provides a fast and convenient platform for mapping nucleic acid-protein interactions, for nuclease activity monitoring, and for other footprinting related methods.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating high-resolution forecasts of atmospheric CO and CO 2 from a global prediction system during KORUS-AQ field campaign

Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO 2 analyses as well as two higher-resolution forecasts (16 and 9km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO 2 with a mean bias against airborne CO 2 measurements of 2.2, 0.7, and 0.3ppmv for 16 and 9km CO 2 forecasts, and analyses, respectively. The positive CO 2 mean bias in the 16km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of -19.2 (16km), -16.7 (9km), and -20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO 2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO dCO 2 Combining double low line 9 ppbvppmv -1 ) compared to the West Sea (dCO dCO 2 Combining double low line 28 ppbvppmv -1 ). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8-12 ppbvppmv -1 , the West Sea: ~ 30 ppbvppmv- 1 ) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64-0.90, the West Sea: ~ 0.80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO 2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO 2 concentrations at the surface with steeper vertical gradients (~ 0.4 ppmvhPa-1 for CO 2 and 3.5 ppbvhPa -1 for CO) in the morning samples than observed (~ 0.25 ppmvhPa -1 for CO 2 and 1.7 ppbvhPa -1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9km vs. 16km) generally produces better forecasts.

54 ENVIRONMENTAL SCIENCES↗

Surface contamination monitoring by the measurement of scattering distribution functions

This paper describes the use of Bidirectional Scattering Distribution Functions (BSDF) to quantify surface degradation, thus providing an effective method for contamination monitoring. This approach to contamination monitoring is based on the use of witness surfaces (mirrors or glass slides) located next to the critical surfaces. Contaminant accretion can be monitored during all phases of spacecraft fabrication, assembly, and testing. The method can be applied in other areas of contamination control such as monitoring of clean room environments. The BSDF can also prove extremely useful in establishing contamination control requirements and acceptability criteria. This paper describes the apparatus adopted to perform BSDF measurements and discusses some practical aspects of data collection. The results obtained in contamination monitoring programs performed at the NASA Goddard Space Flight Center are presented. Some possible new applications of this monitoring technique are also addressed.

Carosso, Paola A.↗

Artificial Intelligence for Data Center Operations (AIOps): Cooperative Research and Development (Final Report)

High performance computing data centers will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence and machine learning approaches provide the means to improve HPC data center operational efficiency, by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. NREL has developed methods of real-time collection, aggregation and streaming of these data in the ESIF HPC Data Center and has collected a significant dataset of relevant metrics across computer systems, racks, environmental, building and utility sources for research into various predictive analytics problems. HPE's Advanced Technology Group (ATG) is doing comprehensive research into exascale monitoring and management for High Performance Computing (HPC) systems (hereinafter HPE's Data Monitoring/ Management Technology). NREL and HPE will collaborate to add Artificial Intelligence (AI) to NREL's real-time data collection/ aggregation/ streaming system and HPE's Data Monitoring/ Management System, with the goal of improving the operational efficiency of NREL's Energy Systems Integration Facility (ESIF) HPC Data Center through data analytics on both historical and real-time data from IT systems and facilities operations. This collaboration will consist of efforts in Data Management, Data Analytics, and AI/ML Optimization for both manual and autonomous intervention in data center operations. This will be a multi-year, multi-staged effort with a goal towards building capabilities for an Advanced Smart Facility, and demonstration of these techniques in the NREL ESIF HPC Data Center.

97 MATHEMATICS AND COMPUTING↗

Operation experience of p-Carbon polarimeter in RHIC

The spin physics program in Relativistic Heavy Ion Collider (RHIC) requires fast polarimeter to monitor the polarization evolution on the ramp and during stores. Over past decade, the polarimeter has evolved greatly to improve its performance. These include dual chamber design, monitoring camera, Si detector selection (and orientation), target quality control, and target frame modification. The preamp boards have been modified to deal with the high rate problem, too. The ultra thin carbon target lifetime is a concern. Simulations have been carried out on the target interaction with beam. Modification has also been done on the frame design. Extra caution has been put on RF shielding to deal with the pickup noises from the nearby stochastic cooling kickers. This paper summarizes the recent operation performance of this delicate device.

43 PARTICLE ACCELERATORS↗

Data analysis of photon beam position at PLS-II

In the third generation light source, photon beam position stability is critical issue on user experiment. Generally photon beam position monitors have been developed for the detection of the real photon beam position and the position is controlled by feedback system in order to keep the reference photon beam position. In the PLS-II, photon beam position stability for front end of particular beam line, in which photon beam position monitor is installed, has been obtained less than rms 1μm for user service period. Nevertheless, detail analysis for photon beam position data in order to demonstrate the performance of photon beam position monitor is necessary, since it can be suffers from various unknown noises. (for instance, a back ground contamination due to upstream or downstream dipole radiation, undulator gap dependence, etc.) In this paper, we will describe the start to end study for photon beam position stability and the Singular Value Decomposition (SVD) analysis to demonstrate the reliability on photon beam position data.

43 PARTICLE ACCELERATORS↗

Risk-based monitoring designs for detecting CO 2 leakage through abandoned wellbores: An application of NRAP’s WLAT and DREAM tools

We report that one suggested approach to managing the risk of geologic CO 2 storage projects is to perform risk-based subsurface monitoring targeting early leak detection. The challenge in risk-based monitoring is that leakage impacts are expected to be small in comparison with the footprint of the stored CO 2 plume and could be at depths ranging from the depth of storage (often ~1 km bgs) up to surficial aquifers. Addressing this challenge requires a multidisciplinary effort capable of characterizing potential subsurface leakage in terms of likelihood, location, magnitude, impacts to overlying aquifers, and uncertainty as well as innovative monitoring technology design and implementation. The National Risk Assessment Partnership (NRAP) was established to develop related risk assessment tools to provide guidance on such assessments. Here we demonstrate the application workflow of two of the NRAP computational tools, WLAT (Wellbore Leakage Analysis Tool) and DREAM (Designs for Risk Evaluation and Management), to a hypothetical CO 2 storage site based on a study area in the Midwestern United States. This workflow shows how CO 2 leakage may be estimated, evaluated, and monitored in terms of risk. Results provide guidance on monitoring configurations and technologies which minimize the time to leak detection, maximize the probability detection, and provide cost considerations.

54 ENVIRONMENTAL SCIENCES↗

Survey of Aging and Monitoring Concerns for Cables and Splices Due to Cable Repair and Replacement

The purpose of this report is to survey aging and monitoring concerns for electrical cable splices in nuclear power plants (NPPs) in long term operation. As portions of existing electrical cable runs in nuclear are replaced over time due to localized events, the total number of splices in NPPs is expected to increase. Relative to cables, the body of knowledge regarding aging of splices and splices in combination with aging cables in nuclear service environments in long-term operations is low. A few reports have considered the aging of cable system components other than cables (Jacobus 1990; Nelson 1998; Villaran and Lofaro 2002), but the nuclear industry has two decades of operating experience since these were published to further enlighten this issue. Herein we discuss electrical cables and splices commonly found in U.S. nuclear power plants, their qualification in safety-related application, and methods for monitoring their health condition. Common environmental stresses that can give rise to cable and splice failure are discussed. The Nuclear Regulatory Commission (NRC) Licensee Event Reports (LER) database was used to identify documented issues of cable and splice failure. The trend in the resultant data over time is considered to see if failures are increasing as plants age. Observations and conclusions of this work include: 1. Cables and splices are highly reliable components. Occurrence rates for events of interest were low and nearly constant over the last 20 years. 2. Common-cause failure for evaluated cable events of interest was observed to primarily be associated with loose connections, which may manifest associated with workmanship issues, thermal cycling, and/or vibration. 3. Replacement of cables is more common than repair, leading to an increase in proportion of new generation cables in the plant over time. 4. Splices on degraded cables have been observed to be problematic. Due to aging NPP infrastructure, including electrical cables, it is expected that such issues will continue to increase. 5. Condition monitoring approaches, while shown to be fruitful for cables, have been shown to be insensitive to degradation of splice sleeves, which are critical to the continued performance of splices. Additional condition monitoring (CM) work is needed to evaluate methods which are sensitive to the degradation of splice components. 6. Extended Material Degradation Assessment (EMDA) knowledge gaps for electrical cables (Bernstein et al. 2014) have not been investigated for splices but may represent similar concerns such as for the accelerated aging process historically used in environmental qualification.

42 ENGINEERING↗

Upgrade to Fixed and Translating Scintillation-Based Loss Detector System in the Fermilab Drift Tube Linac

The closed-off structure of the Fermilab Drift Tube Linac precludes a robust array of instrumentation from directly monitoring the H- beam that is accelerated from 750 keV to 116 MeV. To improve beam tuning and op-erational assessment of Drift Tube Linac performance, scintillator-based loss monitors were previously installed along the exterior of the first two accelerating cavities to assess low energy beam losses. Here we present a recent upgrade to the loss monitor system, including significant improvements in analog signal processing to address baseline-interfering noise; digitization of the signals to enable regular operational use and tuning; and a new remote operation upgrade of the translating loss monitor with precise positioning of the loss monitor along its nine-foot track. Data from the fixed and translating de-tectors collected under varying beam conditions validate the utility of the upgrade.

Chen, Erin V. [Fermilab] (ORCID:0000000215467899)↗

An optimization approach to design monitoring schemes for CO 2 leakage detection

This paper demonstrates an approach to identify optimal monitoring designs that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. This research is part of the National Risk Assessment Partnership (NRAP), a DOE project tasked with conducting risk and uncertainty analysis in the areas of reservoir performance, natural leakage pathways, wellbore integrity, groundwater protection, monitoring, and systems level modeling. Our approach applies a simulated annealing algorithm that searches the solution space by iteratively mutating potential monitoring designs. An example application is provided to demonstrate the effectiveness and efficiency of this method compared to an exhaustive search of the entire solution space. We took into account uncertainty by evaluating the performance of potential monitoring designs across a set of simulated leakage realization. A flexible two-tiered signature was implemented to infer that CO 2 leakage had occurred. This approach was ~50 times faster than an exhaustive search. A user-friendly tool, MDLD, is being developed for use on personal computers to make this method available to stakeholders, regulators, and researchers.

03 NATURAL GAS↗

Pressurized Gas Beam Monitor for Extremely High Intensities

The performance of a gas-filled RF resonator will be numerically simulated to evaluate the sensitivity of permittivity measurements and the effectiveness of calibration strategies. An entire resonator-hodoscope system will be designed and a demonstration test prepared.

43 PARTICLE ACCELERATORS↗