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Droplet Number Concentration Value Added Product

Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloud interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).

Sivaraman, Chitra↗

QMU as an Approach to Strengthening the Predictive Capabilities of Complex Models

Complex systems are made up of multiple interdependent parts, and the behavior of the entire system cannot always be directly inferred from the behavior of the individual parts. They are nonlinear and system responses are not necessarily additive. Examples of complex systems include energy, cyber and telecommunication infrastructures, human and animal social structures, and biological structures such as cells. To meet the goals of infrastructure development, maintenance, and protection for cyber-related complex systems, novel modeling and simulation technology is needed. Sandia has shown success using M&S in the nuclear weapons (NW) program. However, complex systems represent a significant challenge and relative departure from the classical M&S exercises, and many of the scientific and mathematical M&S processes must be re-envisioned. Specifically, in the NW program, requirements and acceptable margins for performance, resilience, and security are well-defined and given quantitatively from the start. The Quantification of Margins and Uncertainties (QMU) process helps to assess whether or not these safety, reliability and performance requirements have been met after a system has been developed. In this sense, QMU is used as a sort of check that requirements have been met once the development process is completed. In contrast, performance requirements and margins may not have been defined a priori for many complex systems, (i.e. the Internet, electrical distribution grids, etc.), particularly not in quantitative terms. This project addresses this fundamental difference by investigating the use of QMU at the start of the design process for complex systems. Three major tasks were completed. First, the characteristics of the cyber infrastructure problem were collected and considered in the context of QMU-based tools. Second, UQ methodologies for the quantification of model discrepancies were considered in the context of statistical models of cyber activity. Third, Bayesian methods for optimal testing in the QMU framework were developed. This completion of this project represent an increased understanding of how to apply and use the QMU process as a means for improving model predictions of the behavior of complex systems.

Gray, Genetha Anne↗

Methods for spectral image analysis by exploiting spatial simplicity

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Keenan, Michael R↗

Droplet Number Concentration Value Added Product

Cloud droplet number concentration is an important factor in understanding aerosol-cloud interactions. As aerosol concentration increases, it is expected that droplet number concentration (Nd) will increase and droplet size will decrease, for a given liquid water path. This will greatly affect cloud albedo as smaller droplets reflect more shortwave radiation; however, the magnitude and variability of these processes under different environmental conditions is still uncertain.McComiskey et al. (2009) have implemented a method, based onBoers and Mitchell (1994), for calculating Nd from ground-based remote sensing measurements of optical depth and liquid water path. They show that the magnitude of the aerosol-cloud interactions (ACI) varies with a range of factors, including the relative value of the cloud liquid water path (LWP), the aerosol size distribution, and the cloud updraft velocity. Estimates of Nd under a range of cloud types and conditions and at a variety of sites are needed to further quantify the impacts of aerosol cloud interactions. In order to provide data sets for studying aerosol-cloud interactions, the McComiskey et al. (2009) method was implemented as the Droplet Number Concentration (NDROP) value-added product (VAP).

Chitra Sivaraman, PNNL↗

Cloud properties derived from two lidars over the ARM SGP site

[1] Active remote sensors such as lidars or radars can be used with other data to quantify the cloud properties at regional scale and at global scale (Dupont et al., 2009). Relative to radar, lidar remote sensing is sensitive to very thin and high clouds but has a significant limitation due to signal attenuation in the ability to precisely quantify the properties of clouds with a 20 cloud optical thickness larger than 3. In this study, 10-years of backscatter lidar signal data are analysed by a unique algorithm called STRucture of ATmosphere (STRAT, Morille et al., 2007). We apply the STRAT algorithm to data from both the collocated Micropulse lidar (MPL) and a Raman lidar (RL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site between 1998 and 2009. Raw backscatter lidar signal is processed and 25 corrections for detector deadtime, afterpulse, and overlap are applied. (Campbell et al.) The cloud properties for all levels of clouds are derived and distributions of cloud base height (CBH), top height (CTH), physical cloud thickness (CT), and optical thickness (COT) from local statistics are compared. The goal of this study is (1) to establish a climatology of macrophysical and optical properties for all levels of clouds observed over the ARM SGP site 30 and (2) to estimate the discrepancies induced by the two remote sensing systems (pulse energy, sampling, resolution, etc.). Our first results tend to show that the MPLs, which are the primary ARM lidars, have a distinctly limited range where all of these cloud properties are detectable, especially cloud top and cloud thickness, but even actual cloud base especially during summer daytime period. According to the comparisons between RL and MPL, almost 50% of situations show a signal to noise ratio too low (smaller than 3) for the MPL in order to detect clouds higher than 7km during daytime period in summer. Consequently, the MPLderived annual cycle of cirrus cloud base (top) altitude is biased low, especially for daylight periods, compared with those derived from the RL data, which detects 5 cloud base ranging from 7.5 km in winter to 9.5 km in summer (and tops ranging from 8.6 to 10.5 km). The optically thickest cirrus clouds (COT>0.3) reach 50% of the total population for the Raman lidar and only 20% for the Micropulse lidar due to the difference of pulse energy and the effect of solar irradiance contamination. A complementary study using the cloud fraction 10 derived from the Micropulse lidar for clouds below 5 km and from the Raman lidar for cloud above 5 km allows for better estimation of the total cloud fraction between the ground and the top of the atmosphere. This study presents the diurnal cycle of cloud fraction for each season in comparisons with the Long et al. (2006) cloud fraction calculation derived from radiative flux analysis.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the Turbulent Entrainment‐Mixing Processes Based on Z ‐LWC Relationships of Cloud Droplets

Abstract Turbulent entrainment‐mixing processes profoundly influence the relationship between radar reflectivity factor and liquid water content ( Z ‐LWC) of cloud droplets. However, quantification of the entrainment‐mixing mechanisms based on the Z ‐LWC relationship is still lacking. To address this gap, 12,218 entrainment‐mixing cases are simulated using the Explicit Mixing Parcel Model. We examine the variations of the parameters in the power‐law relationship Z = a LWC b , and the relationship between parameter b and homogeneous mixing degree ( ψ ), a measure quantifying entrainment‐mixing processes. The results indicate that parameter b distributes within the range of 1–2, with a positive correlation between parameter b and ψ . The b ‐ ψ relationship is fitted, which connects the Z ‐LWC relationship for various entrainment‐mixing types. The results suggest the potential for employing a remote sensing approach to investigate the entrainment‐mixing mechanisms of non‐precipitating small cumulus/stratocumulus clouds, thereby overcoming the limitations of traditional observational studies that rely solely on aircraft observations.

54 ENVIRONMENTAL SCIENCES↗

Final Report fir DE-SC0005507 (A1618): The Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations

We proposed to analyze data collected during the Routine Aerial Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) in order to develop an integrated product of cloud microphysical properties (number concentration of drops in different size bins, total liquid drop concentration integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds, effective radius of water drops, and radar reflectivity factor) that could be used to evaluate large-eddy simulations (LES), general circulation models (GCMs) and ground-based remote sensing retrievals, and to develop cloud parameterizations with the end goal of improving the modeling of cloud processes and properties and their impact on atmospheric radiation. We have completed the development of this microphysical database. We investigated the differences in the size distributions measured by the Cloud and Aerosol Spectrometer (CAS) and the Forward Scattering Probe (FSSP), between the one dimensional cloud imaging probe (1DC) and the two-dimensional cloud imaging probe (2DC), and between the bulk LWCs measured by the Gerber probe against those derived from the size resolved probes.

58 GEOSCIENCES↗

OPTIMAL CONTROL AND ENERGY-SAVING ANALYSIS OF COMMON PRESSURE RAIL ARCHITECTURES: HHEA & STEAM

In recent years several novel hydraulic architectures have been proposed with the intention of significantly increasing system efficiency. Two of these architectures, Steigerung der Energieeffizienz in der Arbeitshydraulik mobiler Arbeitsmaschinen (STEAM), and the Hybrid Hydraulic-Electric Architecture (HHEA), use a system of multiple common pressure rails (CPRs) to serve the multiple degrees-of-freedom of the machine. The key difference is that STEAM throttles hydraulic power from these rails while HHEA combines electric and hydraulic power to meet actuator demands. As a throttle-less architecture, HHEA is expected to save more energy than STEAM at the expense of added complexity. Therefore, it is useful to quantify this additional energy saving. Both systems have discrete operational choices corresponding to how the CPRs are utilized for each actuator. It is necessary to determine optimal operation for each of these architectures for analysis and fair comparison. Techniques for optimal operation of the HHEA have been developed previously from the Langrange multiplier method. Applying the same optimal control method to STEAM encountered some technical challenge leading to the optimal control algorithm not being able to satisfy certain constraints. The issue is analyzed and solved by adding noise to the optimization. Using this proposed algorithm, case studies are performed to compare the energy-saving potentials of STEAM and HHEA for two sizes of excavators and a wheel-loader performing representative duty cycles. The baseline is a standard load-sensing architecture. Results show that STEAM and HHEA can reduce energy consumption between 35-65% and 50-80% respectively

24 POWER TRANSMISSION AND DISTRIBUTION↗

SU-C-213-04: Application of Depth Sensing and 3D-Printing Technique for Total Body Irradiation (TBI) Patient Measurement and Treatment Planning

Purpose: To develop and validate an innovative method of using depth sensing cameras and 3D printing techniques for Total Body Irradiation (TBI) treatment planning and compensator fabrication. Methods: A tablet with motion tracking cameras and integrated depth sensing was used to scan a RANDOTM phantom arranged in a TBI treatment booth to detect and store the 3D surface in a point cloud (PC) format. The accuracy of the detected surface was evaluated by comparison to extracted measurements from CT scan images. The thickness, source to surface distance and off-axis distance of the phantom at different body section was measured for TBI treatment planning. A 2D map containing a detailed compensator design was calculated to achieve uniform dose distribution throughout the phantom. The compensator was fabricated using a 3D printer, silicone molding and tungsten powder. In vivo dosimetry measurements were performed using optically stimulated luminescent detectors (OSLDs). Results: The whole scan of the anthropomorphic phantom took approximately 30 seconds. The mean error for thickness measurements at each section of phantom compare to CT was 0.44 ± 0.268 cm. These errors resulted in approximately 2% dose error calculation and 0.4 mm tungsten thickness deviation for the compensator design. The accuracy of 3D compensator printing was within 0.2 mm. In vivo measurements for an end-to-end test showed the overall dose difference was within 3%. Conclusion: Motion cameras and depth sensing techniques proved to be an accurate and efficient tool for TBI patient measurement and treatment planning. 3D printing technique improved the efficiency and accuracy of the compensator production and ensured a more accurate treatment delivery.

60 APPLIED LIFE SCIENCES↗

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗

Experimental testing of additively manufactured embedded fiber optic smart devices for clean energy applications

Abstract An additively manufactured prototype smart device was created to investigate in-flow temperature distributions using embedded high-definition fiber optic sensors within a component for clean energy systems. The devices were created using Ultrasonic Additive Manufacturing to create a unique embedded pathway within a flow conditioner for the high-definition fiber optic sensors to be placed within. The fibers used allowed for temperature measurements to be taken every 0.65 mm along the fiber. The high-resolution fibers were thermally calibrated enable the 2D reconstruction of the temperature profile in the flow path of the structure. This is due to the temperature-related strain response of the material and strain measurements of the fibers. Hot airflow testing of these devices showed the ability to identify localized temperature differences in the flow. The observed strain response within the smart device had higher strain concentrations in the thicker web regions than in the thinner web regions. These higher strain regions resulted in higher uncertainties for the temperature responses. Further calibration is needed to improve the accuracy of the smart devices, specifically within the inner web structures of a flow straightening component. Further investigations of the devices within flow showed the temperature sensing to be independent of the effects of flow velocity. The devices were able to distinguish temperature differences within single and two-phase flow and showed local sensitivity to the temperature changes with the identification of hot and cold spots. The presented results showed the viability of the smart device for obtaining detailed temperature distributions using common industrial components. Eventually, the goal for these smart devices will be to withstand higher temperature and pressure environments such as those experienced in nuclear, fusion, and concentrated solar energy systems.

Donlan, Connor F. (ORCID:0000000223317882)↗

Performance of a Dynamically Controlled Inverter in a Photovoltaic System Interconnected with a Secondary Network Distribution System

In 2008, a 300 kW{sub peak} photovoltaic (PV) system was installed on the rooftop of the Colorado Convention Center (CCC). The installation was unique for the electric utility, Xcel Energy, as it had not previously permitted a PV system to be interconnected on a building served by the local secondary network distribution system (network). The PV system was installed with several provisions; one to prevent reverse power flow, another called a dynamically controlled inverter (DCI), that curtails the output of the PV inverters to maintain an amount of load supplied by Xcel Energy at the CCC. The DCI system utilizes current transformers (CTs) to sense power flow to insure that a minimum threshold is maintained from Xcel Energy through the network transformers. The inverters are set to track the load on each of the three phases and curtail power from the PV system when the generated PV system current reaches 95% of the current on any phase. This is achieved by the DCI, which gathers inputs from current transformers measuring the current from the PV array, Xcel, and the spot network load. Preventing reverse power flow is a critical technical requirement for the spot network which serve this part of the CCC. The PV system was designed with the expectation that the DCI system would not curtail the PV system, as the expected minimum load consumption was historically higher than the designed PV system size. However, the DCI system has operated many days during the course of a year, and the performance has been excellent. The DCI system at the CCC was installed as a secondary measure to insure that a minimum level of power flows to the CCC from the Xcel Energy network. While this DCI system was intended for localized control, the system could also reduce output percent if an external smart grid control signal was employed. This paper specifically focuses on the performance of the innovative design at this installation; however, the DCI system could also be used for new s- art grid-enabled distribution systems where renewables power contributions at certain conditions or times may need to be curtailed.

14 SOLAR ENERGY↗

Tallo: A global tree allometry and crown architecture database

Abstract Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non‐forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC‐BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599 . To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

Jucker, Tommaso↗

Final Scientific/Technical Report, Multi-Sensor Inspection and Robotic Systems for Dry Storage Casks

Once removed from service, fuel rod assemblies are cooled in a pool and then placed in dry storage until they can be transported to a repository for disposal. The extended duration that used nuclear fuel spends in dry storage makes it prudent to be able to nondestructively inspect the dry storage casks. The degradation mechanisms of most concern are chloride-induced stress corrosion cracking of the stainless steel canister that confines the spent fuel and distributed cracking of the concrete in the overpack structure. Multi-sensor inspection and robotic systems were researched, developed, built, and tested. One system operates completely outside the cask to inspect the concrete. The other system, known as the PRINSE system, for Proactive Robotic Inspection of Nuclear Storage Enclosures, enters the cask through an outlet vent and navigates around the outer surface of the stainless steel canister. The PRINSE system delivers sensors for: (i) real-time characterization of the canister surface in order to assess whether chlorides are present, (ii) detecting the presence of cracks using shear-horizontal ultrasonic guided waves, (iii) measuring the temperature of the canister surface, and (iv) a gamma radiation counter. The four sensing modalities are applicable to any cask containing a stainless steel canister, however the robotic delivery system is designed specifically for Holtec’s HI-STORM family of casks. Horizontal axis casks have exposed concrete surfaces. A fully contactless air-coupled scanning ultrasonic test platform and a frequency-wavenumber domain data analysis method are used for these concrete structures. Analysis, numerical simulation and experimental results demonstrate that distributed cracks in concrete can be detected and cracked regions localized within a scanned region of concrete. Vertical axis casks (like the HI-STORM family) have steel-clad concrete overpacks. In a separate effort, a semi-coupled test platform and a guided wave attenuation-based data analysis method are used for disbond detection. Analysis, numerical simulation and experimental results show that the bonding conditions of steel-concrete interfaces can be quantitatively characterized using the guided wave signal analysis scheme. The PRINSE system is designed for vertical axis dry storage casks, specifically the HI-STORM family. The double pulse laser-induced breakdown spectroscopy (LIBS) system takes advantage of an optical fiber to deliver intense light to the canister surface that enables surface composition characterization in-situ in real time. Chlorine concentrations as low as 10 mg/m2 were detected on stainless steel. Additionally, a simpler laser setup was created to detect sodium as a surrogate for chlorine, and sodium was detectable when the chlorine concentration was as low as 0.5 mg/m2. The electromagnetic acoustic transducers (EMATs) enable detection of stress corrosion cracks. The EMATs generate shear-horizontal waves that propagate around the canister and are reflected by cracks enabling 100% of the canister weld lines to be inspected. The EMAT-based crack detection system was tested at the Pacific Northwest National Laboratory on a canister containing blind defects and was shown to detect the crack sizes it was designed to detect. The PRINSE system is a novel marsupial robot. The command center and winch outside the cask control the delivery arm and train of cars that traverse the outside of the canister from the cask ventilation system. The sensors are housed in the cargo bays of three cars that comprise the train, which is lowered to the bottom of the canister by the winch. Encoders on the winch enable the sensors to be delivered to a prescribed location, e.g., for re-inspection of a problem area. The PRINSE system does not mar the canister surface, can be extracted manually in the case of a power failure, and is designed for an elevated temperature and gamma radiation environment, although not all components of the prototype are made from the final materials. The PRINSE system was tested on a full canister that was placed inside a HI-STORM cask at the Holtec Manufacturing Division. It was also demonstrated on a full-height mockup at Penn State to a live audience.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Remote Sensing of Sea Salt Aerosol below Trade Wind Clouds

Abstract Sea salt aerosol in the boundary layer below shallow cumulus clouds is remotely observed with a Ka-band cloud radar at the Barbados Cloud Observatory and is detected in 76% of the measurements over 1 year. Carried by convection, sea salt particles with a diameter larger than 500 nm show an upward motion of 0.2 m s−1 below shallow cumulus clouds for a 2-day case study. Caused by an increasing relative humidity with increasing altitude, the sea salt particles become larger as they move closer to the cloud base. By using combined measurements of a Ka-band cloud radar and a Raman lidar, the retrieved equivolumetric diameter of the hygroscopically grown sea salt particles is found to be between 6 and 11 μm with a total number concentration of 20 cm−3 near cloud base. Assuming a fixed shape parameter, a size distribution of sea salt particles under high-relative-humidity conditions below cloud base is estimated and agrees with measurements taken by a dry-deposition sampler and online aerosol observations. The methods outlined in this paper can be used in future studies to get a better understanding of the vertical and temporal sea salt distribution in the boundary layer and sea salt aerosol–cloud interaction processes.

54 ENVIRONMENTAL SCIENCES↗

Quantifying the Role of Snowmelt in Stream Discharge in an Alaskan Watershed: An Analysis Using a Spatially Distributed Surface Hydrology Model

Here, this study uses a spatially distributed surface hydrology model to investigate the role of snowmelt in stream discharge for the Tanana Flats Basin in interior Alaska. The Parameter ESTimation code is used to calibrate the model with observed stream discharge data. The model was further evaluated using remote sensing-based snow cover product and in situ snowpack water equivalent (SWE) observations. A 36 year (1980–2015) U.S. Geological Survey Precipitation-Runoff Modeling System simulation shows (1) the monthly stream discharge from the Tanana Flats Basin in April decreased by 44%; (2) snow cover area at high altitudes (above 2000 m) decreased in summer, both SWE and snowmelt also decreased significantly, especially in spring; (3) the timings of snowmelt onset and ending shifted by 2 (earlier) and 5 (later) days per decade, respectively; and (4) snowmelt accounts for 40% of the annual stream discharge. This study provides a quantitative tool to investigating hydrological systems considering the impacts of snow dynamics in cold regions. Additionally, this study suggests that future warming will further decrease snow coverage, advance snow melting time, and hereafter change the stream discharge dynamics in the Arctic.

58 GEOSCIENCES↗

MAPPING EARTH ANALOGS FROM PHOTOMETRIC VARIABILITY: SPIN-ORBIT TOMOGRAPHY FOR PLANETS IN INCLINED ORBITS

Aiming at obtaining detailed information on the surface environment of Earth analogs, Kawahara and Fujii proposed an inversion technique of annual scattered light curves named spin-orbit tomography (SOT), which enables us to sketch a two-dimensional albedo map from annual variation of the disk-integrated scattered light, and demonstrated the method with a planet in a face-on orbit. We extend it to be applicable to general geometric configurations, including low-obliquity planets like the Earth in inclined orbits. We simulate light curves of the Earth in an inclined orbit in three photometric bands (0.4-0.5 {mu}m, 0.6-0.7 {mu}m, and 0.8-0.9 {mu}m) and show that the distribution of clouds, snow, and continents is retrieved with the aid of the SOT. We also demonstrate the SOT by applying it to an upright Earth, a tidally locked Earth, and Earth analogs with ancient continental configurations. The inversion is model independent in the sense that we do not assume specific albedo models when mapping the surface, and hence applicable in principle to any kind of inhomogeneity. This method can potentially serve as a unique tool to investigate the exohabitats/exoclimes of Earth analogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Purpose-Built UAVs for Physical Sampling of Trace Contamination at the Portsmouth Gaseous Diffusion Plant - 17331

The sampling of trace amounts of contamination, particularly of low-energy byproducts such as americium, presents a challenge for non-contact sensing. In many cases, such as determining the need for cleaning inside the exhaust shaft of the Waste Isolation Pilot Plant or sampling the walls of the enormous Gaseous Diffusion Plant at Portsmouth, it may be desirable to take physical swab samples at carefully distributed sample locations for analysis by mass spectrometry. Because of the danger posed to human workers in such scenarios, including risk of falls from lethal heights and exposure to low levels of radiation and the hassle of donning and doffing PPE, a low-cost robotic solution is desired. The inaccessibility of the heights involved suggest Unmanned Aerial Vehicle (UAV) solutions, rather than Unmanned Ground Vehicle (UGV) solutions, but conventional quadrotor UAVs are ill-suited to precise physical interaction with their surroundings. Quadrotors are under-actuated, rendering them non-holonomic and preventing the dexterous application of arbitrary generalized force/torques in interaction with the environment. At Purdue University, the authors have developed a number of novel UAV platforms suitable for dexterous interaction with the environment, making them ideal for such applications. These platforms can independently control forces in all directions, allowing for controlled application of the swab to the surface. Because of the scale of these structures (over 2 km in the case of the Gaseous Diffusion Plant), flight efficiency is of supreme importance. The Purdue team is took a variety of vehicles to the Gaseous Diffusion Plant for field trials on site in August, 2016. (With results available prior to the meeting.) The Purdue Dexterous Hexrotor is a fully-actuated Hexrotor capable of exerting forces in all six directions of force and torque. Operating alone or in swarms, the Dexterous Hexrotor can fly in free space, transition to contact through impact control, and sample the surface through force control. The Purdue I-BoomCopter is a tri-copter with an extra horizontal propeller that enables long-distance flight without pitching and the ability to apply closed-loop forces horizontally. Finally, the Purdue Tiltrotor VTOL is an under-actuated hybrid UAV that combines tilting rotors for vertical takeoff and landing, with a fixed-wing, flying-body design that is ultra-efficient for long-distance flight. The Dexterous Hexrotor provided two demonstrations of physical sampling of walls and crane rails. In sampling the large open sections of the inside of the plant, a small swarm of three UAVs is commanded to sample three distinct points on an internal map of the building. Human-supervised autonomy permits the UAVs to take off by themselves, find a clear elevation at which to fly through uncluttered space, navigate to their designated sampling points, and pause for confirmation by the human supervisor. The supervisor is presented with a video image of the intended sampling spot, which, if confirmed, the UAV will automatically approach and sample. The UAVs then autonomously return to the take-off spot. The second demo involved a single UAV searching upwards, then transitioning into 3-D SLAM mode to wait for a safe sampling spot on the 3-D scan to acquire the sample from the crane rail. The human supervisor, in this case, is responsible for ensuring the absence of cables and other obstacles. I-BoomCopter demonstrated its high-speed, long-distance coverage ability by making a few fast passes before homing in on a mock-up electrical panel with door, which it opened and closed. The dexterity of the I-BoomCopter results from its large propellers, which allow for controlled hovering and the horizontal thruster for applying forces of significant magnitude. Finally, the Tiltrotor VTOL is highly efficient in fixed-wing mode, but the tilt-rotor is under-actuated in hover. The tilt-rotor will take off vertically, then transition to high-speed, long-distance flight to make a number of passes inside the facility. The significance of these demos is the low-cost implementation of physical sampling over prescribable locations in difficult-to-reach areas of potentially contaminate facilities. To make this tractable over very large facilities, the demonstration of combinations of dexterous hovering ability and long-distance/high-speed flight is also in evidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗