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At least 1,675 records · Page 93

Ultrasonic characterization of material heterogeneities in stainless steel components produced by laser powder bed fusion

We introduce pulse-echo ultrasound as a method for characterizing the impact of powder bed fusion parameters on the properties of additively manufactured stainless-steel components, their material anisotropy, and location-dependent heterogeneity. Our results indicate that accurate characterization requires careful selection of ultrasonic propagation paths, which must consider the direction of additive layering, variations in processing parameters, and the component's geometry. We employed two distinct methods to estimate material properties from ultrasonic data: One assumes isotropy, while the other accounts for anisotropic interactions during the propagation of elastic waves. When applied to samples fabricated with laser energy densities ranging from 24 to 42 J/mm³ , these methods revealed transverse isotropy and weak anisotropy (quantified by small Thomsen parameters, ε = 0.0651 and γ = 0.0092) and less than a ∼6 % change in acoustic impedance. The assumption of isotropy, in this case, leads to small errors (less than 4 % or 1 % for Young's modulus in the build or transverse directions) when estimating orthotropic material properties using ultrasonic data measured along just two orthogonal directions, one of which must align with the build direction. By comparing ultrasonic measurements — which aggregate the spatial variability in material properties along the length of elastic wave propagation into a single value — with localized measurements obtained from surface nanoindentation, we uncovered and spatially profiled significant differences between the surface and interior properties. Specifically, the surface Young's modulus decreased from approximately 210 GPa to 180 GPa within a depth of about 3 mm. We attribute this surface-localized heterogeneity in PBF-fabricated components to distinct thermal histories experienced by the surface and interior regions. Collectively, the results of this study establish a framework for the ultrasonic characterization of material heterogeneity and anisotropy in material properties and demonstrate its application in additively manufactured metal components.

36 MATERIALS SCIENCE↗

The Shape and Density Evolution of Snow Aggregates

Abstract Snow aggregates evolve into a variety of observed shapes and densities. Despite this diversity, models and observational studies employ fractal or Euclidean geometric measures that are assumed universal for all aggregates. This work therefore seeks to improve understanding and representation of snow aggregate geometry and its evolution by characterizing distributions of both observed and Monte Carlo–generated aggregates. Two separate datasets of best-fit ellipsoid estimates derived from Multi-Angle Snowflake Camera (MASC) observations suggest the use of a bivariate beta distribution model for capturing aggregate shapes. Product moments of this model capture shape effects to within 4% of observations. This mathematical model is used along with Monte Carlo simulated aggregates to study how combinations of monomer properties affect aggregate shape evolution. Plate aggregates of any aspect ratio produce a consistent ellipsoid shape evolution whereas thin column aggregates evolve to become more spherical. Thin column aggregates yield fractal dimensions much less than the often-assumed value of 2.0. Ellipsoid densities and fractal analogs of density (lacunarity) are much more variable depending on combinations of monomer size and shape. Simple mathematical scaling relationships can explain the persistent triaxial ellipsoid shapes that appear in both observed and modeled aggregates. Overall, both simulations and observations prove aggregates are rarely oblate. Therefore, the use of the proposed bivariate ellipsoid distribution in models will allow for similar-sized aggregates to exhibit a realistic dispersion of masses and fall speeds.

54 ENVIRONMENTAL SCIENCES↗

Simulated 'On-Line' Wear Metal Analysis of Lubricating Oils by X-Ray Fluorescence Spectroscopy

The objective of this project was to assess the sensitivity of X-ray Fluorescence Spectroscopy (XFS) for quantitative evaluation of metal particle content in engine oil suspensions and the feasibility of real-time, dynamic wear metal analysis. The study was focused on iron as the majority wear metal component. Variable parameters were: particle size, particle concentration and oil velocity. A commercial XFS spectrometer equipped with interchangeable static/dynamic (flow cell) sample chambers was used. XFS spectra were recorded for solutions of Fe-organometallic standard and for a series of DTE oil suspensions of high purity spherical iron particles of 2g, 4g, and 8g diameter, at concentrations from 5 ppm to 5,000 ppm. Real contaminated oil samples from Langley Air Force Base aircraft engines and NASA Langley Research Center wind tunnels were also analyzed. The experimental data conform the reliability of XFS as the analytical method of choice for this project. Intrinsic inadequacies of the instrument for precise analytic work at low metal concentrations were identified as being related to the particular x-ray beam definition, system geometry, and flow-cell materials selection. This work supports a proposal for the design, construction and testing of a conceptually new, miniature XFS spectrometer with superior performance, dedicated to on-line, real-time monitoring of lubricating oils in operating engines. Innovative design solutions include focalization of the incident x-ray beam, non-metal sample chamber, and miniaturization of the overall assembly. The instrument would contribute to prevention of catastrophic engine failures. A proposal for two-year funding has been presented to NASA Langley Research Center Internal Operation Group (IOG) Management, to continue the effort begun by this summer's project.

Kelliher, Warren C.↗

Co-Flow Hollow Cathode Technology

Hall thrusters utilize identical hollow cathode technology as ion thrusters, yet must operate at much higher mass flow rates in order to efficiently couple to the bulk plasma discharge. Higher flow rates are necessary in order to provide enough neutral collisions to transport electrons across magnetic fields so that they can reach the discharge. This higher flow rate, however, has potential life-limiting implications for the operation of the cathode. A solution to the problem involves splitting the mass flow into the hollow cathode into two streams, the internal and external flows. The internal flow is fixed and set such that the neutral pressure in the cathode allows for a high utilization of the emitter surface area. The external flow is variable depending on the flow rate through the anode of the Hall thruster, but also has a minimum in order to suppress high-energy ion generation. In the co-flow hollow cathode, the cathode assembly is mounted on thruster centerline, inside the inner magnetic core of the thruster. An annular gas plenum is placed at the base of the cathode and propellant is fed throughout to produce an azimuthally symmetric flow of gas that evenly expands around the cathode keeper. This configuration maximizes propellant utilization and is not subject to erosion processes. External gas feeds have been considered in the past for ion thruster applications, but usually in the context of eliminating high energy ion production. This approach is adapted specifically for the Hall thruster and exploits the geometry of a Hall thruster to feed and focus the external flow without introducing significant new complexity to the thruster design.

Hofer, Richard R.↗

Variance of the Quantum Dwell Time for a Nonrelativistic Particle

Munoz, Seidel, and Muga [Phys. Rev. A 79, 012108 (2009)], following an earlier proposal by Pollak and Miller [Phys. Rev. Lett. 53, 115 (1984)] in the context of a theory of a collinear chemical reaction, showed that suitable moments of a two-flux correlation function could be manipulated to yield expressions for the mean quantum dwell time and mean square quantum dwell time for a structureless particle scattering from a time-independent potential energy field between two parallel lines in a two-dimensional spacetime. The present work proposes a generalization to a charged, nonrelativistic particle scattering from a transient, spatially confined electromagnetic vector potential in four-dimensional spacetime. The geometry of the spacetime domain is that of the slab between a pair of parallel planes, in particular those defined by constant values of the third (z) spatial coordinate. The mean Nth power, N = 1, 2, 3, . . ., of the quantum dwell time in the slab is given by an expression involving an N-flux-correlation function. All these means are shown to be nonnegative. The N = 1 formula reduces to an S-matrix result published previously [G. E. Hahne, J. Phys. A 36, 7149 (2003)]; an explicit formula for N = 2, and of the variance of the dwell time in terms of the S-matrix, is worked out. A formula representing an incommensurability principle between variances of the output-minus-input flux of a pair of dynamical variables (such as the particle s time flux and others) is derived.

Hahne, Gerhard↗

New Constraints on the Geometry and Kinematics of Matter Surrounding the Accretion Flow in X-Ray Binaries from Chandra High-Energy Transmission Grating X-Ray Spectroscopy

The narrow, neutral Fe Kα fluorescence emission line in X-ray binaries (XRBs) is a powerful probe of the geometry, kinematics, and Fe abundance of matter around the accretion flow. In a recent study it has been claimed, using Chandra High-Energy Transmission Grating (HETG) spectra for a sample of XRBs, that the circumnuclear material is consistent with a solar-abundance, uniform, spherical distribution. It was also claimed that the Fe Kα line was unresolved in all cases by the HETG. However, these conclusions were based on ad hoc models that did not attempt to relate the global column density to the Fe Kα line emission. We revisit the sample and test a self-consistent model of a uniform, spherical X-ray reprocessor against HETG spectra from 56 observations of 14 Galactic XRBs. We find that the model is ruled out in 13/14 sources because a variable Fe abundance is required. In two sources a spherical distribution is viable, but with nonsolar Fe abundance. We also applied a solar-abundance Compton-thick reflection model, which can account for the spectra that are inconsistent with a spherical model, but spectra with a broader bandpass are required to better constrain model parameters. We also robustly measured the velocity width of the Fe Kα line and found FWHM values of up to approx. 5000 km/s. Only in some spectra was the Fe Kα line unresolved by the HETG.

Tzanavaris, P.↗

Reduced order models for thermal radiative transfer problems based on moment equations and data-driven approximations of the Eddington tensor

Here a new group of structure and asymptotic preserving reduced-order models (ROMs) for multidimensional nonlinear thermal radiative transfer (TRT) problems is presented. They are formulated by means of the nonlinear projective approach and data compression techniques. The nonlinear projection is applied to the Boltzmann transport equation (BTE) to derive a hierarchy of low-order moment equations. Approximation of the Eddington tensor that provides exact closure for the system of moment equations is found with projection-based data-driven methodologies. These include the (i) proper orthogonal decomposition (POD), (ii) dynamic mode decomposition (DMD) and (iii) a variant of the DMD. A parameterization is derived for this ROM for the temperature of radiation incoming to the problem domain (the radiation drive temperature). This parameterization is informed from results of a dimensionless study of the TRT problem. Analysis of the ROMs is performed on the classical Fleck-Cummings TRT multigroup test problem in 2D geometry with a radiation-driven Marshak wave. Numerical results are presented to demonstrate the performance of these ROMs for the simulation of evolving radiation and heat waves. Results show these models to be sufficiently accurate for practical computations with rather low-rank representations of the Eddington tensor. As the rank of the approximation is increased, the errors of solutions generated by the ROMs gradually decreases.

42 ENGINEERING↗

Structural Rearrangements of Subnanometer Cu Oxide Clusters Govern Catalytic Oxidation

Sub-nanometer metal oxide clusters are very important materials that are widely used, for example, in catalysis or electronic devices such as sensors. Hence, it is critical to understand the atomic structures and properties of sub-nanometer metal oxide clusters under a reactive gas environment, such as O 2 . We consider here experimentally accessible precise-size Cu clusters (Cu 4 ) supported on partially hydroxylated amorphous alumina and show that such clusters can access, in catalytic conditions at high temperature under a pressure of O 2 , a large ensemble of oxidized structures, representing a large variety of oxygen content, of geometries in link with the support, and of catalytic activities for oxidation reactions, as seen from their reducibilities. A grand canonical basin hopping method based on first-principles energy reveals an ensemble of 24 configurations for the Cu 4 O x cluster of low free energy, less than 0.8 eV above the global minimum. The low free energy ensemble consists of clusters of different stoichiometries, which are mainly Cu 4 O 3 and Cu 4 O 4 in the temperature range of 200–400 °C and under a pressure of 0.5 bar of O 2 . The presence of several competitive isomers at each composition implies that cluster fluxionality impacts the phase diagram, which should be ensemble-averaged. In terms of catalytic oxidation activity, Cu 4 O 3 isomers present highly variable O abstraction energy: the most stable isomers are inactive for alkane oxidative dehydrogenation, but isomerization to metastable isomers, that proceed with low barrier, enable to create active configurations with low O abstraction energy. O atoms with the lowest anionic character, and thus of more electrophilic nature, present the best oxidation capability. In contrast, all Cu 4 O 4 isomers show a low O abstraction energy and a high potential catalytic activity. Here, this manuscript demonstrates the unique structural and electronic properties of sub-nano Cu oxide clusters and illustrates the critical roles of configuration ensembles and rearrangement to highly reactive metastable cluster isomers in nanocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Compact Augmented Spark Igniters for Liquid Rocket Engines

The objective of this dissertation is to characterize augmented spark impinging (torch) igniters. Torch igniters inject propellants into a small prechamber where a spark igniter imparts the activation energy to initiate combustion. The flame stabilizes within the prechamber and exits into the main combustion chamber where it ignites the main flow directly or by mixing with a coaxial flow to create a secondary flame. The underlying phenomena that promote reliable ignition are multifaceted and required a broad scope of investigations. Initial efforts focused on spark discharges across an annular geometry. Gaseous propellent projects the electrical arc toward the prechamber, where the arc and the thermal energy is imparted to the surrounding fluid then meets with a combustible mixture. Discharges are parametrically examined against pressure, spark-gap size, and exciter types to emulate transient engine startup. The energy imparted to the flow, approximate velocity, and distance traveled by the exhaust plume are determined. Spark quenching (no energy deposition) and its effects on perceived versus actual measurements are shown. Results outline the prechamber target zone where a combustible mixture is necessary for ignition. Next, three-dimensional, time-accurate, and nonreacting computational fluid dynamics simulations assess effects of geometric and mass flow differences on the size, location, and composition of a combustible mixture. Fluid dynamic phenomena are elucidated. Correlations between nondimensional variables are found. Results are coupled with a conservation-law analysis to produce novel objective functions. Lastly, a full-scale, modular torch igniter is tested. Injector sizes, mixture ratios, and injector momentum ratios are systematically varied to map ignition probability and ignition delay. Results show the importance of local mixture ratios, provide injector momentum ratios guidelines, and demonstrate reliable ignition of core mixture ratios typically outside flammability limits. The deliverable of this project is not a torch igniter or derivative thereof. Instead, this dissertation produces novel objective-functions for igniter design. These equations are functions of variables that may be constrained by engine-level requirements, physics, and experimental results from this work. They provide a foundation for future igniter design and will minimize iterative processes from the design cycle for next-generation ignition hardware.

Torch Igniter↗

Proximal Galerkin: A Structure-Preserving Finite Element Method for Pointwise Bound Constraints

The proximal Galerkin finite element method is a high-order, low iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of pointwise bound constraints in infinite-dimensional function spaces. This paper introduces the proximal Galerkin method and applies it to solve free boundary problems, enforce discrete maximum principles, and develop a scalable, mesh-independent algorithm for optimal design with pointwise bound constraints. This paper also introduces the latent variable proximal point (LVPP) algorithm, from which the proximal Galerkin method derives. When analyzing the classical obstacle problem, we discover that the underlying variational inequality can be replaced by a sequence of second-order partial differential equations (PDEs) that are readily discretized and solved with, e.g., the proximal Galerkin method. Throughout this work, we arrive at several contributions that may be of independent interest. These include (1) a semilinear PDE we refer to as the entropic Poisson equation; (2) an algebraic/geometric connection between high-order positivity-preserving discretizations and certain infinite-dimensional Lie groups; and (3) a gradient-based, bound-preserving algorithm for two-field, density-based topology optimization. The complete proximal Galerkin methodology combines ideas from nonlinear programming, functional analysis, tropical algebra, and differential geometry and can potentially lead to new synergies among these areas as well as within variational and numerical analysis. Open-source implementations of our methods accompany this work to facilitate reproduction and broader adoption.

97 MATHEMATICS AND COMPUTING↗

ISRU Pilot Excavator: Bucket Drum Scaling Experimental Results

NASA’s Space Technology Mission Directorate (STMD) is funding the development of a robotic excavator called the “ISRU Pilot Excavator” which will be a technology demonstration of excavating and transporting 10 metric tons of lunar regolith on the surface of the moon with a 30k-class robotic excavator. ISRU Pilot Excavator will be the next generation of robotic excavator to use bucket drums as excavation tools. This is an evolution of the Regolith Advanced Surface Systems Operations Robot (RASSOR) developed at NASA’s Kennedy Space Center. Bucket drums are hollow cylinders with regularly spaced scoops around the perimeter. The drums rotate in one direction to collect regolith with the scoops. The regolith slides down an internal baffling system inside the drum which prevents the regolith from falling back out of the scoops. The captured regolith can then be transported while held in the drum and then deposited by rotating the drum in the opposite direction allowing the regolith to slide back down the baffling and out of the excavation scoops. Bucket drums were developed by Lockheed Martin in 2008 and used on multiple robotic excavator prototypes ever since. However the forces on a bucket drum and considerations for scaling have not been measured in detail. Bucket drums are challenging to model using classical blade\bucket equations because of their unique geometry. Therefore this experiment was performed to measure the forces on three bucket drums of the same geometry at different scales. Small: 9.4” (239mm) dia. x 8.1” (206mm) width, Medium: 11.6” (294mm) dia. x 10” (254mm) width, and Large: 17” (432mm) dia. x 14.1”(358mm) width. The test stand consisted of an actuated gantry with controlled motion in the vertical (Z) and horizontal (X) axes and a single rotation axis (R). The bucket drums were individually mounted to the rotary axis of the test stand and translated across a prepared bed of BP-1 lunar regolith simulant at a specified linear speed and cutting depth. The test stand was outfitted with a torque sensor in line with the rotation of the drum (R) and a 3 axis (X, Y, and Z) load cell. In addition to the three sizes of bucket drums the linear excavation speed and cutting depth were test variables. The results of these experiments show the relationship between the three scales of bucket drums for factors such as: excavation force, torque due to regolith rotation inside the drum, excavation energy, time to fill, etc. and will be discussed in detail in this paper. This fundamental data will be used in the design of the ISRU Pilot Excavator and can inform the design of future bucket drum excavators.

Jason Michael Schuler↗

ISRU Pilot Excavator: Bucket Drum Scaling Experimental Results

NASA’s Space Technology Mission Directorate (STMD) is funding the development of a robotic excavator called the “ISRU Pilot Excavator” (IPEx) which will be a technology demonstration of excavating and transporting 10 metric tons of lunar regolith on the surface of the moon with a 30kg-class robotic excavator. IPEx will be the next generation of robotic excavators to use bucket drums as excavation tools. This is an evolution of the Regolith Advanced Surface Systems Operations Robot (RASSOR) developed at NASA’s Kennedy Space Center (KSC). Bucket drums are hollow cylinders with regularly spaced scoops around the perimeter. The drums rotate in one direction to collect regolith with the scoops. The regolith slides down an internal baffling system inside the drum which prevents the regolith from falling back out of the scoops (see Figure 1). The captured regolith can then be transported while held in the drum and then deposited by rotating the drum in the opposite direction allowing the regolith to slide back down the baffling and out of the excavation scoops. Bucket drums were developed by Lockheed Martin in 2008 and used on multiple robotic excavator prototypes ever since. However, the forces on a bucket drum and considerations for scaling have not been measured in detail. Bucket drums are challenging to model using classical blade\bucket equations because of their unique geometry. Therefore, this experiment was performed to measure the forces on three bucket drums of the same geometry at different scales. Small: 9.4” (239mm) dia. x 8.1” (206mm) width, Medium: 11.6” (294mm) dia. x 10” (254mm) width, and Large: 17” (432mm) dia. x 14.1” (358mm) width. The test stand consisted of an actuated gantry with controlled motion in the vertical (Z) and horizontal (X) axes and a single rotation axis (R). The bucket drums were individually mounted to the rotary axis of the test stand and translated across a prepared bed of BP-1 lunar regolith simulant at a specified linear speed and cutting depth. The test stand was outfitted with a torque sensor in line with the rotation of the drum (R) and a 3 axis (X, Y, and Z) load cell. In addition to the three sizes of bucket drums the linear excavation speed and cutting depth were test variables. The results of these experiments show the relationship between the three scales of bucket drums for factors such as: excavation force, torque due to regolith rotation inside the drum, excavation energy, time to fill, etc. and will be discussed in detail in this paper. This fundamental data will be used in the design of IPEx and can inform the design of future bucket drum excavators.

RASSOR↗

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗

Single-Use Destructive Assay for Uranium Hexafluoride Sampling

Sampling uranium hexafluoride (UF6) for the determination of enrichments by destructive analysis (DA) is a critical component in the International Atomic Energy Agency’s layered safeguards approach for uranium processing facilities. Typically, gram-quantity UF6 samples are collected during inspections and stored under tag-and-seal until transportation to an off-site analytical laboratory. The shipping times can be long, and evolving restrictions on radioactive/corrosive materials shipments may increasingly limit the IAEA’s ability to transport UF6 samples easily. Pacific Northwest National Laboratory has developed a low-cost UF6 sampling technology called Single-Use Destructive Assay (SUDA) that addresses these challenges, as well as provides DA sample geometries that can be tailored for different analytical methods, including potential on-site analyses. The SUDA samplers, along with a unique holder, are designed for direct attachment to existing taps at uranium processing facilities, allowing gaseous UF6 to come into direct contact with a zeolite film. The SUDA technology features the ability to capture uranium in a more easily shipped and handled form as the solid, more stable, and relatively less hazardous hydrated uranyl fluoride (UO2F2•nH2O), which is formed through the controlled hydrolysis of UF6. We have recently simulated uranium collection under enrichment plant sampling conditions to further improve our understanding of SUDA sampling. Presented here is our recent work on measuring the relationship between sampling conditions and uranium collection, which includes control of the uranium-mass-to-zeolite ratio and assessing variable UF6 gas and sampling parameters that can affect collection using the SUDA sampler.

Pope, Timothy R.↗

Effect of Variable Gravity on Evaporation of Binary Fluids in a Capillary Pore Evaporator

The research project focuses on experimental investigation of the capillary-pumped evaporative heat transfer phenomenon. The objective is to examine whether the heat transfer and stability of a heated meniscus in a capillary pore can be enhanced by adding trace amounts of a non-volatile solute to a solvent and to understand the changes that occur. The experimental setup consists of a single pore evaporator connected to a reservoir which supplies liquid to the evaporator. In addition to the experiments of capillary-pumped evaporation, a parallel experimental study has been conducted to systematically investigate the effects of gravity as well as the effects of bulk composition on the heat transfer characteristics of evaporating binary thin films near the contact line region along an inclined heated surface. To investigate the buoyancy effects on evaporation along an inclined heated surface, the angle of inclination from a horizontal plane was varied fro 15 C to 90 C. An optimum concentration between 0.5% and 1% decane in pentane/decane solutions has been demonstrated at different angles of inclination. Improved heat transfer was found for the geometry with the smallest angle of inclination of 15 degrees. In addition, flow visualization has revealed that at low inclination angles effective heat transfer takes place primarily due to an extension of the thin film near the contact line. At these low inclination angles, the optimum concentration is associated with enhanced wetting characteristics and reduced thermocapillary stresses along the interface.

Girgis, Morris M.↗

Scale Mixtures of Frechet Distributions as Asymptotic Approximations of Extreme Precipitation

This paper is a further development of the results of [20] where, based on the negative binomial model for the duration of wet periods measured in days [16], an asymptotic approximation was proposed for the distribution of the maximum daily precipitation volume within a wet period. This approximation has the form of a scale mixture of the Fr´echet distribution with the gamma mixing distribution and coincides with the distribution of a positive power of a random variable having the Snedecor–Fisher distribution. Here we extend this result to the mth extremes, m ∈ ℕ, and sample quantiles. The proof of this result is based on the representation of the negative binomial distribution as a mixed geometric (and hence, mixed Poisson) distribution [17] and limit theorems for extreme order statistics in samples with random sizes having mixed Poisson distributions [10]. Some analytic properties of the obtained limit distribution are described. In particular, it is demonstrated that under certain conditions the limit distribution of the maximum precipitation is mixed exponential and hence, is infinitely divisible. It is shown that under the same conditions this limit distribution can be represented as a scale mixture of stable or Weibull or Pareto or folded normal laws. The corresponding product representations for the limit random variable can be used for its computer simulation. The results of fitting this distribution to real data are presented illustrating high adequacy of the proposed model. It is also shown that the limit distribution of sample quantiles is the well-known Student distribution. Several methods are proposed for the estimation of the parameters of the asymptotic distributions. The obtained mixture representations for the limit laws and the corresponding asymptotic approximations provide better insight into the nature of mixed probability (“Bayesian”) models.

97 MATHEMATICS AND COMPUTING↗

Development of the GeoNEX Level 2G Products: Exploiting the Diurnal Variability of TOA Reflectance in Atmospheric Correction

This study develops a new atmospheric correction algorithm to generate the Level 2G products, in particular the gap-filled Surface Reflectance at 10-minute time steps, for the Geostationary-NASA Earth Exchange (GeoNEX) project. The algorithm is based on the MODIS MAIAC (Multi-Angle Implementation of Atmospheric Correction) framework but with significant modifications to exploit angular/temporal information from the diurnal variability of the GeoNEX L1G TOA (Top-of-Atmosphere) reflectance. The algorithm starts by evaluating the roughness/smoothness of the diurnal time series of the TOA reflectance. Because rapid changes in TOA reflectance are generally caused by passing clouds or shadows, rough segments of the time series are automatically filtered out while the smooth segments are further tested for brightness and temperature to identify clear-sky and snow-free observations. Next the algorithm runs the MAIAC RTM (Radiative Transfer Model) to retrieve the Ross-Thick-Li-Sparse (RTLS) BRDF model parameters and the daily-mean atmospheric optical depth (AOD) that allow the RTM to optimally simulate the observed diurnal variability of clear-sky TOA reflectance. Once the initial RTLS parameters are retrieved after the algorithm’s burn-in period, they are used as the prior information to predict the AOD level for the next days, while the subsequent clear-sky observations are used to make necessary adjustments to the RTLS parameters in an continuous fashion. This “prediction-analysis” cycle is then iterated to process the full time series of the L1G data, skipping only total-cloudy days or when surface snow is detected. We tested the algorithm over a list of selected AERONET sites. The retrieved results (the daily mean AOD and the RTLS parameters) reasonably agree with the ground-based measurements. Importantly, the results indicate that the diurnal cycles of surface reflectance are continuous functions of the illumination-view geometry. Thus we can use the retrieved RTLS model to accurately fill in data gaps on partial cloudy days. Also, our algorithm is totally independent from the traditional approaches based on the use of spectral band ratios between the shortwave infrared (e.g., 2.2µm) and the visible (e.g., 0.47µm and 0.64µm) bands. Our results thus demonstrate that the high-frequent diurnal geostationary observations contain unique information that helps us improve atmospheric correction of remote sensing data.

GeoNEX↗

Quantification of spatial and seasonal trends in the atmosphere and construction of statistical models for infrasonic propagation

SUMMARY Infrasonic waves are influenced by variations in the density, pressure and temperature as well as the ambient winds. Modelling infrasonic propagation can be challenging due to the dynamic nature of the atmosphere as well as the sparseness of measurements which result in variability and notable uncertainty. A framework is presented to quantify spatial and seasonal trends in atmospheric structure via analysis of the effective sound speed profile and identification of temporal trends in the middle atmospheric waveguide produced by the circumpolar vortex winds. Seasonal definitions identifying typical atmospheric structures during the summer, winter and spring/fall transition periods are identified using atmospheric data from 2010 through 2020. Seasonal trend analysis is conducted for a number of locations across the contiguous United States to quantify spatial variations in atmospheric structure that impact infrasonic propagation. For each season and location, empirical orthogonal function analysis is used to reduce the historical archive of atmospheric data into a smaller representative set that can be analysed using numerical tools more efficiently. Infrasonic ray tracing and finite-frequency modal propagation analyses are applied to construct propagation path geometry and transmission loss statistics which are useful in localization and yield estimation for infrasonic sources, respectively. An example application is detailed in which transmission loss statistics are combined with an explosive source model and noise statistics to quantify the capability of a network to detect nearby sources.

58 GEOSCIENCES↗