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At least 397 records · Page 22

Constraining the Twomey effect from satellite observations: issues and perspectives

Abstract. The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd, ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd, ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, ΔNd, ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining ΔNd, ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-to-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

54 ENVIRONMENTAL SCIENCES↗

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗

Boride-based Ceramic Super-high Temperature Thermocouples in Harsh Environments (Final Scientific/Technical Report)

An electromotive force (emf) can be generated along a temperature gradient between the cold end and hot end of a thermoelectric material, termed the Seebeck effect. Based on the Seebeck effect, metallic alloys have been extensively employed to detect temperatures for centuries, named thermocouples. However, commercially available thermocouple alloys suffer from limitations, such as oxidation, chemical degradation, and poor long-term stability under high-temperature harsh environments. This DOE-funded project aimed to develop high-temperature, chemically tolerant thermocouples suitable for operation in extreme environments relevant to semiconducting thermoelectric materials. The research focused on boride-based semiconducting thermoelectric compounds as candidates for next-generation thermocouples with enhanced oxidation resistance, chemical stability, and thermal robustness under conditions representative of charcoal-fired electricity facilities. During the funded years, boride materials were synthesized using an arc-plasma technique under ambient air and argon atmospheres, enabling scalable and cost-effective production compared with conventional boride fabrication methods. The synthesized borides were processed into nanostructured powders, followed by consolidation into dense bulk materials using a spark plasma sintering (SPS) bottom-up approach. Comprehensive characterization was performed, including microstructural analysis, electrical transport measurements, and optical and thermal property evaluation. Both p-type and n-type boride electric legs were fabricated and integrated into boride-based thermocouples. The thermal and irradiation stabilities of the boride nanomaterials and bulk thermoelectric materials were systematically evaluated to assess suitability for long-term operation in harsh environments. Additionally, 12 students were broadly hands-on trained spanning the full research workflow, including word processing and technical editing (e.g., LATEX for manuscript and poster preparation), data collection and analysis (using Python and related libraries and hardware interfaces), sample preparation (including arc-plasma synthesis and spark plasma sintering), and advanced characterization techniques (such as X-ray diffraction, UV–vis spectroscopy, electron microscopy, differential thermal analysis (DTA), and Seebeck coefficient measurements, etc). Overall, this project demonstrated the feasibility of boride-based thermoelectric materials as durable high-temperature thermocouples, providing a promising pathway toward robust temperature sensing technologies aligned with DOE energy infrastructure and extreme-environment monitoring needs.

20 FOSSIL-FUELED POWER PLANTS↗

Online Monitoring of Catalytic Processes by Fiber-Enhanced Raman Spectroscopy

An innovative solution for real-time monitoring of reactions within confined spaces, optimized for Raman spectroscopy applications, is presented. This approach involves the utilization of a hollow-core waveguide configured as a compact flow cell, serving both as a conduit for Raman excitation and scattering and seamlessly integrating into the effluent stream of a cracking catalytic reactor. The analytical technique, encompassing device and optical design, ensures robustness, compactness, and cost-effectiveness for implementation into process facilities. Notably, the modularity of the approach empowers customization for diverse gas monitoring needs, as it readily adapts to the specific requirements of various sensing scenarios. As a proof of concept, the efficacy of a spectroscopic approach is shown by monitoring two catalytic processes: CO 2 methanation (CO 2 + 4H 2 → CH 4 + 2H 2 O) and ammonia cracking (2NH 3 → N 2 + 3H 2 ). Leveraging chemometric data processing techniques, spectral signatures of the individual components involved in these reactions are effectively disentangled and the results are compared to mass spectrometry data. This robust methodology underscores the versatility and reliability of this monitoring system in complex chemical environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

Expediting DECam Multimessenger Counterpart Searches with Convolutional Neural Networks

Searches for counterparts to multimessenger events with optical imagers use difference imaging to detect new transient sources. However, even with existing artifact-detection algorithms, this process simultaneously returns several classes of false positives: false detections from poor-quality image subtractions, false detections from low signal-to-noise images, and detections of preexisting variable sources. Currently, human visual inspection to remove the false positives is a central part of multimessenger follow-up observations, but when next generation gravitational wave and neutrino detectors come online and increase the rate of multimessenger events, the visual inspection process will be prohibitively expensive. We approach this problem with two convolutional neural networks operating on the difference imaging outputs. The first network focuses on removing false detections and demonstrates an accuracy of 92% on our data set. The second network focuses on sorting all real detections by the probability of being a transient source within a host galaxy and distinguishes between various classes of images that previously required additional human inspection. We find the number of images requiring human inspection will decrease by a factor of 1.5 using our approach alone and a factor of 3.6 using our approach in combination with existing algorithms, facilitating rapid multimessenger counterpart identification by the astronomical community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Method for measurement of TRISO kernel and layer volumes by X-ray computed tomography

Layer dimensions are key parameters for as-fabricated tristructural-isotropic (TRISO) particle fuel as well as for post-irradiation examination of particle performance. Layer thicknesses are typically measured by optical microscopy of the particle cross section near mid-plane, while layer volumes are estimated with serial sectioning and microscopy. This method for measuring layer volumes is limited due to the resolution limit imposed by slice thickness and the effect of the polishing process on delicate irradiated particle microstructures. In this study, image processing software has been developed to segregate the three-dimensional (3D) TRISO particle images provided by x-ray computed tomography (XCT) into high-resolution volumetric data for the kernel, all particle layers, and any internal voids introduced during irradiation. These data can be used to analyze key in-reactor behaviors of TRISO particles such as kernel swelling or buffer shrinkage, which are important inputs for fuel performance modeling.

36 MATERIALS SCIENCE↗

Line coupling and line mixing effects on calculated widths of symmetric-top molecules with the k-degeneracy: A theoretical study of N 2 -, O 2 -, and air-broadened lines of CH 3 I

Calculations of the N 2 -, O 2 -, and air-broadened widths, together with their temperature dependence exponents have been made for transitions of CH 3 I in the ν 5 and ν 6 bands. The calculations are based on a semi-classical line shape formalism developed by the current authors through modifying and refining the Robert-Bonamy formalism. In recent years, we have applied this formalism for linear molecules, symmetric-top molecules with inversion symmetry, and asymmetric-top molecules. For symmetric-top molecules with the k degeneracy such as CH 3 I, the formalism has a new feature. In this case, one should consider each of the CH 3 I transitions labeled by k i or f ≠ 0 as a doublet. Then, one needs to consider the effects of the line mixing process between these two components. Furthermore, comparisons of our theoretical predictions with some data available demonstrate a very reasonable agreement. Finally, we propose new experiments at higher perturber pressures that would enable one to check the theoretically calculated relaxation matrices and to extend the analysis to the inter-doublet mixing effects.

74 ATOMIC AND MOLECULAR PHYSICS↗

Polaron absorption in aligned conjugated polymer films: breakdown of adiabatic treatments and going beyond the conventional mid-gap state model

This study provides the first experimental polarized intermolecular and intramolecular optical absorption components of field-induced polarons in regioregular poly(3-hexylthiophene-2,5-diyl), rr-P3HT, a polymer semiconductor. Highly aligned rr-P3HT thin films were prepared by a high temperature shear-alignment process that orients polymer backbones along the shearing direction. rr-P3HT in-plane molecular orientation was measured by electron diffraction, and out-of-plane orientation was measured through series of synchrotron X-ray scattering techniques. Then, with molecular orientation quantified, polarized charge modulation spectroscopy was used to probe mid-IR polaron absorption in the ℏω = 0.075 — 0.75 eV range and unambiguously assign intermolecular and intramolecular optical absorption components of hole polarons in rr-P3HT. This data represents the first experimental quantification of these polarized components and allowed long-standing theoretical predictions to be compared to experimental results. The experimental data is discrepant with predictions of polaron absorption based on an adiabatic framework that works under the Born–Oppenheimer approximation, but the data is entirely consistent with a more recent nonadiabatic treatment of absorption based on a modified Holstein Hamiltonian. This nonadiabatic treatment was used to show that both intermolecular and intramolecular polaron coherence break down at length scales significantly smaller than estimated structural coherence in either direction. Importantly, this strongly suggests that polaron delocalization is fundamentally limited by energetic disorder in rr-P3HT.

36 MATERIALS SCIENCE↗

Integrated Monitoring of Macroalgae Farms Using Acoustics and UUV Sensing

The vision of this project was to develop an integrated system for autonomous underwater vehicle (AUV) monitoring of offshore kelp farms using acoustic, environmental, and optical sensors. This project supports the overall MARINER goals of developing an offshore kelp aquaculture industry to produce low-carbon or carbon-neutral biofuels. The project commenced in the spring of 2018 and used laboratory experiments to test the efficacy of acoustic sensors for monitoring kelp farm lines and growing kelp biomass. Sensors were then integrated onto two AUVs as well as an autonomous surface vehicle in order to establish the optimal type, price point, and vehicle to most efficiently monitor kelp farm structures, kelp biomass, and the surrounding environment. Multiple field deployments of these vehicles and sensors in Massachusetts, New Hampshire, and Maine confirmed that farm lines and kelp could be visualized and that monitoring the spatial patterns of environmental variables was possible. The COVID-19 pandemic severely limited fieldwork activities and laboratory testing, with deployments around kelp farms not occurring again until January 2021. Time spent away from the field focused on data visualization and the development of a low-cost, vessel-based sensor system. Unfortunately, the low-cost system experienced a disk failure during its first deployment and due to multiple resignations from the project team further engineering and development was not possible. Additionally, final results from acoustic sensor testing in 2021 were also not able to be completed due to the resignation of the postdoc leading the analysis. Despite these setbacks, multiple avenues for further development of optical imagery processing from the 360-degree Kelpcam camera and testing of the low-cost sensor system may be possible.

09 BIOMASS FUELS↗

Editorial: Applications of spectroscopy and chemometrics in nuclear materials analysis

Optical analysis techniques, including spectroscopy and image analysis, have many advantages when applied to the study of nuclear materials. They require small sample sizes, can be performed remotely, and can be proceduralized through consistent practice. Most importantly, they provide a wealth of information by generating multivariate data. For example, ultraviolet–visible–near-infrared absorbance spectroscopy of actinides in aqueous and organic solutions is dependent on the oxidation state, anionic complexation, and temperature. These variables are important for solution-based separation processes, and sensitivity to these factors, combined with online monitoring, can drive the efficiency and control of these processes. The morphology and chemical composition of actinide particles can also provide a vital clue to the mechanisms by which the particles were formed, providing forensic information on the origins of the particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

X-ray Computed Tomography of Irradiated and Unirradiated AGR-3/4 Compacts

X-ray Computed Tomography (XCT) has been utilized to image and characterize compacts from the combined third and fourth irradiation of the Advanced Gas Reactor (AGR) Program, AGR-3/4, fuel. The experiment contained tristructural isotropic (TRISO)-coated fuel particles as well as designed-to-fail (DTF) fuel particles. Two irradiated compacts, representing the lower and higher range of AGR-3/4 burnup (4.85% and 14.92% fissions per initial heavy metal atom FIMA) were examined. These represent the first known highly irradiated TRISO fuel compacts to be examined via X-ray CT. Additionally, two unirradiated compacts from the same production batch as the examined irradiation compacts were also imaged for a baseline comparison. As XCT of irradiated TRISO compacts is not a commonly implemented characterization technique, a significant portion of the report focuses on developed methodology and imaging conditions. A specialized sample shielding device was developed and fabricated specifically to limit received dose to staff during sample preparation for XCT and to minimize excess gamma radiation dose to sensitive electronic components with the utilized X-ray system. Significant penetration through the uranium oxycarbide fuel kernels by significantly hardening the X-ray beam with specialized proprietary filters acquired from Carl Zeiss NTS Ltd. The filter utilized resulted in an average X ray photon energy of ~110 keV which approaches uranium’s K-edge (~115 keV), maximizing penetration for a microfocus X-ray source. The gamma-radiation emitted from the irradiated AGR-3/4 TRISO compacts, has the same properties and mechanisms for interaction with matter as X-rays, thus the detection of gamma-radiation by the utilized X-ray detectors was initially a concern. However, although ?-rays did produce an observable signal on the X-ray detector, its contribution to the overall imaging results appeared negligible upon 3D reconstruction. The neglibile impact on the resulting 3D reconstructed volumes were likely the result of: (1) a significantly lower detection efficiency for ?-rays relative to X-rays; (2) An X-ray flux at the detector several orders of magnitude higher than that of the impinging ?-rays from the irradiated compacts. These results suggest that irradiated compacts with significantly higher radiation fields can be examined in the future if an acceptable route for sample handling and preparation can be determined. Additionally, the 3D imaging results of XCT can provide a valuable means of assessing compacts. While in many ways complimentary to traditional post irradiation examination techniques such as optical ceramography, XCT can provide additional insight into compact features traditionally difficult to discern directly from cross-sectional imaging alone. Preliminary analyses on kernel size, morphology (aspect ratio and sphericity), and kernel orientation were presented. Sphericity, a simple morphological shape descriptor, was utilized to screen for kernel extrusions within the high burnup compact. The number of kernel extrusions identified via XCT represented an approximate two-fold increase from the quantity of extruded particles observed (via optical ceramography) in adjacent compacts from the same irradiation capsule. While numerical analysis of the compact datasets was highly preliminary, initial results show promise for providing complimentary metrics to current AGR-3/4 PIE and potentially additional insight into the processes driving TRISO fuel degradation during reactor operation. Additional analyses to be performed at a later date include a more detailed examination of kernel size, kernel sphericity (and observed kernel extrusions), and sphericity. Given all particles can be observed in a single data volume possible correlation of spatial position with observed kernel features will also be made at a later date.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Joint Search for the Electromagnetic Counterpart to the Gravitational-Wave Binary Black-Hole Merger Candidate S250328ae with the Dark Energy Camera and the Prime Focus Spectrograph

The first detection of an optical counterpart to a gravitational wave signal revealed that collaborative efforts between instruments with different specializations provide a unique opportunity to acquire impactful multi-messenger data. We present results of such a joint search with the Dark Energy Camera (DECam) and Prime Focus Spectrograph (PFS) for the optical counterpart of the LIGO-Virgo-KAGRA event S250328ae, a binary black hole merger candidate of high significance detected at a distance of 511$\pm$82 Mpc and localized within an area of 3 (15) square degrees at 50% (90%) confidence. We observed the 90% confidence area with DECam and identified 36 high-confidence transient candidates after image processing, candidate selection, and candidate vetting. We observed with PFS to obtain optical spectra of DECam candidates, Swift-XRT candidates, and potential host galaxies of S250328ae. In total, 3897 targets were observed by seven pointings covering ~50% of the 90% confidence area. After template fitting and visual inspection, we identified 12 SNe, 159 QSOs, 2975 galaxies, and 131 stars. With the joint observations of DECam and PFS, we found variability in 12 SNe, 139 QSOs, 37 galaxies, and 2 stars. We do not identify any confident optical counterparts, though the association is not ruled out for three variable candidates that are not observed by PFS and 6 QSO candidates without clear variability if the optical counterpart of S250328ae is faint. Despite the lack of confident optical counterparts, this paper serves as a framework for future collaborations between wide-field imagers and multi-object spectrographs to maximize multi-messenger analyses.

Zhang, Haibin [Natl. Astron. Observ. of Japan] (OR↗

Continuous optical in-situ pH monitoring during early hydration of cementitious materials

A luminescent sensor technique for pH analyses has been tested in cementitious media. The optical sensors monitor in-situ pH every 5 s during early hydration reactions over a period of 100 h from initial fluid up to consolidated stage. The pH development was analysed in calcium aluminate, calcium sulfoaluminate and OPC/slag cements up to a pH level of 13.3 and directly correlated with the heat of hydration. Thus tracing the dissolution and formation processes of solid phases via pH sensor monitoring is possible. This measurement technique enables the recording of continuous and highly reproducible pH data sets from slurries, pastes, and hardening materials leading to new vistas for individual (trans)formation pathways of solids, hydration and consolidation reactions in high alkaline cementitious systems.

36 MATERIALS SCIENCE↗

Drone flight visible images, digital elevation maps, and geotiffs, Council, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Council Road Site near mile marker 71 in the Seward Peninsula, Alaska in July 2017. Derived image products for each flight include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.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↗

Drone flight visible images, digital elevation maps, and geotiffs, Teller, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along the flight path. This package includes data from a flight path over the NGEE Arctic Teller Site, west of mile marker 27 Bob Blodgett Highway in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.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↗

Drone flight visible images, digital elevation maps, and geotiffs, Kougarok, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Kougarok Site, west of mile marker 64 on Kuzitrin Road in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.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↗

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗