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At least 109 records · Page 6

Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie

Abstract Purpose The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. Methods We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Results EMI revealed high spatial heterogeneities in ECa distribution across the land-lake interfaces, with higher values in the wetland and transition zones compared to the upland zone. Soil ECa maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m). ERT and GPR showed vertical variation in soil properties with clear stratigraphic boundaries, and correlation of ERT profiles with lithologs from piezometers revealed the stratigraphic units of silt–clay and till sequence down to 3.5 m depth which are consistent with the surficial geology of the study area. Conclusions These results validate the use of multiple geophysical methods for extrapolating soil properties and mapping stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗

A fully ro-vibrationally resolved corona model for the molecular hydrogen Fulcher-𝛼 system

A ro-vibrationally resolved corona model for the molecular hydrogen Fulcher-𝛼 transition based on the Yacora solver is introduced. The model couples 1365 ro-vibrational levels of the 𝑋 1 ⁢𝛴$^+_𝑔$, 𝑑 3⁢ 𝛱 𝑢 and 𝑎 3 ⁢𝛴$^+_𝑔$ states via electron impact excitation from the ground state into the 𝑑 3⁢ 𝛱 𝑢 state and subsequent spontaneous emission into the 𝑎 3 ⁢𝛴$+_𝑔$ state. For the process of electron impact excitation a set of 45260 fully ro-vibrationally resolved cross sections calculated with the molecular convergent close-coupling (MCCC) method in the adiabatic-nuclei formulation is applied. The MCCC cross sections are compared with results of a scaling method used in other works, demonstrating the need for dedicated ro-vibrationally resolved cross sections. By post-processing the model output, entire Fulcher spectra can be simulated. These spectra are benchmarked with measurements from an inductively coupled plasma discharge at a pressure between 1.1–10 Pa and a RF power of 700 W. The model results agree very well with the experiment both in relative shape and in absolute value. A non-ro-vibrationally resolved, purely electronically resolved collisional radiative model for molecular hydrogen (including further states and reaction channels) is applied to investigate the validity of the corona approximation for the benchmark plasmas and the relevance of possible process extensions of the corona model. Furthermore, the influence of collisional quenching, autoionization and predissociation is discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗

Astrometric observations of the satellites of the outer planets. I - The Galilean satellites in 1977

Astrometric observations of the Galilean satellites of Jupiter performed around the opposition of 1977 with a 67-cm photovisual refractor are reported. The measurements are reduced to absolute and intersatellite positions by two different methods: a linear least-squares plate-constant solution to the AGK3 reference-star frame and the trail-scale method of Pascu (1977). Results of a plate-constant reduction are also presented for two observations of JV (Amalthea). Comparison of the data with Liske's (1978) theoretical predictions for the intersatellite positions indicates no systematic bias in the data; a probable scatter of about 15 arcsec in both right ascension and declination is estimated.

Ianna, P. A.↗

Satellite measurements of large-scale air pollution - Methods

A technique for deriving large-scale pollution parameters from NIR and visible satellite remote-sensing images obtained over land or water is described and demonstrated on AVHRR images. The method is based on comparison of the upward radiances on clear and hazy days and permits simultaneous determination of aerosol optical thickness with error Delta tau(a) = 0.08-0.15, particle size with error + or - 100-200 nm, and single-scattering albedo with error + or - 0.03 (for albedos near 1), all assuming accurate and stable satellite calibration and stable surface reflectance between the clear and hazy days. In the analysis of AVHRR images of smoke from a forest fire, good agreement was obtained between satellite and ground-based (sun-photometer) measurements of aerosol optical thickness, but the satellite particle sizes were systematically greater than those measured from the ground. The AVHRR single-scattering albedo agreed well with a Landsat albedo for the same smoke.

Kaufman, Yoram J.↗

Liquefaction of pelleted corn cobs

Liquid slurries at high loadings (pumpable slurries) are critical to handle the streams between the unit operations in a biorefinery. Their liquefaction potential was initially tested with a small-scale method using 3FPU Ctec-2 /g dry biomass, and results were confirmed in 1L bioreactors experiments. Liquid slurries of cobs were observed in small scale tests (based on visual appearance, and reducing sugars released). Results were confirmed in 1L bioreactors under similar experimental conditions. Yield stress value in bioreactor was 34 ± 6Pa at 96 h, and glucan and xylan conversion to glucose and xylose, respectively, were 41 and 21%. In addition, work has been initiated with liquefaction of other pelleted corn stover fractions: Husk/Leaf (A),Husk (B), Stems (D) and controls (whole corn stover; F and G). Compositional analysis of the pellets showed glucan content (%) in the samples ranged from 31.9 to 36.1, xylan from 19.1 to 20.9, total lignin 13.1 to 18.8,and total ash 1.73 to 10.19. The moisture content ranged from 6.21 to 11.66%. Given these similar characteristics, we also examined liquefaction of these other samples, and they also showed that liquid slurries are possible. Work is continuing to define favourable conditions for liquid slurries formation.

Cruz, Antonio↗

Scaling Evaluation of Ice-Crystal Icing on a Modern Turbofan Engine in PSL Using the COMDES-MELT Code

This paper presents preliminary ice-crystal icing (ICI) altitude scaling evaluation results of a Honeywell Uncertified Research Engine (HURE) that was tested in the NASA Glenn Research Center Propulsion Systems Laboratory (PSL) during January of 2018. This engine geometry features a hidden core design to keep the core less exposed. The engine was fitted with internal video cameras to observe various ice buildup processes at multiple selected locations within the engine core flow path covering the fan stator, the splitter-lip/shroud/strut, and the high pressure compressor (HPC) variable inlet guide vane (IGV) regions. The potential ice accretion risk was pre-determined to occur by using NASA’s in-house 1D Engine Icing Risk assessment code, COMDES-MELT. The code was successful in predicting the risk of ice accretion in adiabatic regions like the fan-stator of the HURE at specific engine operating points. However at several operating points during the test, liquid water was observed running along the shroud toward the variable IGV of the HPC regions with an air temperature well below freezing, thus no particle melting could have occurred due to heating from the air alone. It was reasoned that other sources of heat were present in that region. To account for these heat sources the inlet total temperature was adjusted to give a wet bulb temperature of 24 F below the standard minimum wet bulb temperature of 492 R to allow ice to accrete in the splitter-lip/shroud/strut region, which was determined from a reference case where hard ice was observed in that region. With that adjustment the COMDES-MELT code was successful in providing operating points where there was a risk of ice accretion during the test campaign. In addition to calculating possible conditions at different selected lower altitudes, simulations were run to determine potential inlet conditions that could lead to ice-crystal accretion along the prescribed stations where the cameras were available. From there, scaled test conditions were determined by best matching the following three icing related parameters of the reference condition: (1) the local air total wet bulb temperature, (2) the local ice crystal cloud melt ratio and (3) the engine fan face ice/water to air mass flux ratio of the ice crystal cloud. Instantaneous images taken from the time-lapsed movies of ice buildup were used along with the relevant thermodynamic data of air, water vapor and local icing condition to help evaluate how closely the proposed altitude scaling method could be used in ground based test facility to duplicate selected reference ICI features observed at specific location inside this engine at different scale altitudes. Discussions on observed limitation for engine icing scaling application from this test campaign and needed improvement are provided. A scaling test procedure to help identify potential ICI risk conditions and possible ice accretion locations of a new turbofan engine is evaluated in PSL.

Engine Testing in PSL↗

Systems and methods for scale-up synthesis multi-layered Pt-skin nanoparticle catalysts

A method for scaled-up synthesis of PtNi nanoparticles. Synthesizing a Pt nanoparticle catalyst comprises the steps of: synthesizing PtNi nanoparticles, isolating PtNi/substrate nanoparticles, acid leaching the PtNi/substrate, and annealing the leached PtNi/substrate nanoparticles, and forming a Pt-skin on the PtNi/substrate nanoparticles.

Stamenkovic, Vojislav↗

Latest Developments in SLD Scaling

Scaling methods have been shown previously to work well for super cooled large droplet (SLD) main ice shapes. However, feather sizes for some conditions have not been well represented by scale tests. To determine if there are fundamental differences between the development of feathers for appendix C and SLD conditions, this study used time-sequenced photographs, viewing along the span of the model during icing sprays. An airspeed of 100 kt, cloud water drop MVDs of 30 and 140 microns, and stagnation freezing fractions of 0.30 and 0.50 were tested in the NASA Glenn Icing Research Tunnel using an unswept 91-cm-chord NACA0012 airfoil model mounted at 0deg AOA. The photos indicated that the feathers that developed in a distinct region downstream of the leading-edge ice determined the horn location and angle. The angle at which feathers grew from the surface were also measured; results are shown for an airspeed of 150 kt, an MVD of 30 microns, and stagnation freezing fractions of 0.30 to 0.60. Feather angles were found to depend strongly on the stagnation freezing fraction, and were independent of either chordwise position on the model or time into the spray. Feather angles also correlated well with horn angles. For these tests, there did not appear to be fundamental differences between the physics of SLD and appendix C icing; therefore, for these conditions similarity parameters used for appendix C scaling appear to be valid for SLD scaling as well. Further investigation into the cause for the large feather structures observed for some SLD conditions will continue.

Tsao, Jen-Ching↗

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

pattern recognition↗

Improved Solid-State Reaction Method for Scaled-Up Synthesis of Ceramic Proton-Conducting Electrolyte Materials

Protonic ceramic electrochemical cells (PCECs) represent promising technologies in the production of clean electricity, decarbonized hydrogen, chemicals, and fuels at intermediate temperatures. One of the challenges in commercializing PCECs is to produce the electrolyte materials on a large scale. The conventional solid-state reaction (SSR) method suffers from tedious synthesis procedures and low phase purity of the products due to the formation of unwanted secondary phases. Herein, we report an improved SSR (i-SSR) method for kilogram-scale production of high phase-purity electrolyte material BaZr 0.4 Ce 0.4 Y 0.1 Yb 0.1 O 3–δ (BZCYYb4411). In this method, the ball-milled precursor powders are pelletized prior to calcination, which effectively reduces the length of the diffusion paths between the components during perovskite phase formation. In this study, the synthesis procedure and calcination temperature are carefully optimized for efficient and repeatable production based on the powder crystallization behavior. A combined technoeconomic analysis and life cycle assessment modeling suggest that the i-SSR method could reduce the total production cost and greenhouse gas emissions by up to 19% and 39%, respectively, compared to the conventional SSR method. The high quality of the synthesized electrolyte material is corroborated by the excellent electrical conductivity and electrochemical performance of the fabricated PCEC cells.

36 MATERIALS SCIENCE↗

Small-correlated-against-large estimator for the lensing of the cosmic microwave background

Weak gravitational lensing of the cosmic microwave background (CMB) carries imprints of the physics operating at redshifts much lower than that of recombination and serves as an important probe of cosmological structure formation, dark matter physics, and the mass of neutrinos. Reconstruction of the CMB lensing deflection field through use of quadratic estimators has proven successful with existing data but is known to be sub-optimal on small angular scales ($\ell > 3000$) for experiments with low noise levels. Future experiments will provide better observations in this regime, but these techniques will remain statistically limited by their approximations. We show that correlations between fluctuations of the large-scale temperature gradient power of the CMB sourced by $\ell < 2000$, and fluctuations of the local small-scale temperature power reveal a lensing signal which is prominent in even the real-space pixel statistics across a CMB temperature map. We present the development of the Small Correlated Against Large Estimator (SCALE), a novel estimator for the CMB lensing spectrum which offers promising complementary analysis alongside other reconstruction techniques in this regime. The SCALE method computes correlations between both the large/small-scale temperature gradient power in harmonic space, and it is able to quantitatively recover unbiased statistics of the CMB lensing field without the need for map-level reconstruction. SCALE can outperform quadratic estimator signal-to-noise by a factor of up to 1.5 in current and upcoming experiments for CMB lensing power spectra $C_{6000 < L < 8000}^{\phi\phi}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sparsity Applications for Gradient‐Based Optimization of Wind Farms

Optimizing wind farms is essential for designing efficient energy systems, especially as farms grow larger and span multiple sites. However, this optimization becomes increasingly challenging due to the rising computational cost associated with more turbines. Gradient‐based optimization methods scale better than gradient‐free approaches for large problems, but the most computationally expensive component remains the calculation of gradients for the objective function and constraint Jacobians. To address this, we propose leveraging sparsity to accelerate gradient evaluations and reduce the size of the constraint Jacobian. Wind farms naturally exhibit sparsity—many turbines do not influence each other under certain wind directions. However, unlike traditional sparse problems with fixed patterns, wind farm sparsity is dynamic, requiring new strategies to handle changing interactions efficiently. This paper presents a study of sparsity in wind farm optimization and introduces several methods to exploit it. These strategies are tested on multiple farms using the analytic Cumulative Curl model, with gradients computed via automatic differentiation (AD). The same sparsity‐aware techniques are also applicable to finite difference (FD) methods, where they can yield even greater speedups due to the high cost of directional evaluations. Results show that sparse methods achieve up to a 10x speedup with less than ± 5% variance in optimized wake losses compared to traditional methods. These findings suggest that sparsity‐aware optimization not only maintains solution quality but also scales efficiently with farm size, enabling more comprehensive design exploration at reduced computational cost.

17 WIND ENERGY↗

Efficient Four-Component Dirac–Coulomb–Gaunt Hartree–Fock in the Pauli Spinor Representation

Four-component Dirac Hartree--Fock is an accurate mean-field method for treating molecular systems where relativistic effects are important. However, the computational cost and complexity of the two-electron interaction makes this method less common, even though we can consider the Dirac Hartree--Fock Hamiltonian the ``ground truth" of electronic structure, barring explicit quantum-electrodynamical effects. Being able to calculate these effects is then vital to the design of lower scaling methods for accurate predictions in computational spectroscopy and properties of heavy element complexes that must include relativistic effects for even qualitative accuracy. In this work, we present a Pauli quaternion formalism of maximal component- and spin-separation for computing the Dirac-Coulomb-Gaunt Hartree-Fock ground state, with a minimal floating-point-operation count algorithm. Furthermore, this approach also allows one to explicitly separate different spin physics from the two-body interactions, such as spin-free, spin-orbit, and the spin-spin contributions. Additionally, we use this formalism to examine relativistic trends in the periodic table, and analyze the basis set dependence of atomic gold and gold dimer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. Here, to elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

autoregressive distributed lag analysis↗

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗

A Fast, Two-dimensional Gaussian Process Method Based on Celerite: Applications to Transiting Exoplanet Discovery and Characterization

Gaussian processes (GPs) are commonly used as a model of stochastic variability in astrophysical time series. In particular, GPs are frequently employed to account for correlated stellar variability in planetary transit light curves. The efficient application of GPs to light curves containing thousands to tens of thousands of data points has been made possible by recent advances in GP methods, including the celerite method. Here we present an extension of the celerite method to two input dimensions where, typically, the second dimension is small. This method scales linearly with the total number of data points when the noise in each large dimension is proportional to the same celerite kernel and only the amplitude of the correlated noise varies in the second dimension. We demonstrate the application of this method to the problem of measuring precise transit parameters from multiwavelength light curves and show that it has the potential to improve transit parameters measurements by orders of magnitude. Applications of this method include transit spectroscopy and exomoon detection, as well a broader set of astronomical problems.

79 ASTRONOMY AND ASTROPHYSICS↗