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Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites: Observed cloud variability at ARM sites
Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy’s Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness all quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the log normal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.
High-Level Reverse Intersystem Crossing and Molecular Rigidity Improve Spin Statistics for Triplet–Triplet Annihilation Upconversion
The structural factors affecting triplet−triplet annihilation (TTA) at the molecular level are not well-understood. Here, our steady-state photoluminescence and transient absorption results demonstrate that the spin statistical factor, η, decreases from 0.60 to 0.46 and 0.14 going from 9,10-diphenylanthracene (DPA) to the 1,5-DPA and 2,6-DPA isomers, respectively, during photon upconversion with a platinum octaethylporphyrin sensitizer. Density functional theory (DFT) shows that η depends on the energetics of hot triplet states and molecular rigidity. The significantly high conical intersection energy between the S 0 and T 1 states for 9,10-DPA gives its longer triplet lifetime. Time-dependent DFT calculations show that 9,10-DPA and 1,5-DPA can undergo high-level reverse intersystem crossing from their T 2 and T 3 states, respectively, to the bright S 1 state, increasing the limit of the spin statistical factor. Both factors ultimately serve to enhance the TTA efficiency. Furthermore, this work provides insight into designing molecules for efficient light-emitting and photon upconversion applications.
The statistical properties of Klein-Gordon oscillator in noncommutative space
We study the relativistic spin-zero bosons influenced by the Klein-Gordon oscillator and an external magnetic field in noncommutative formulation. The problem is considered in two dimensions and is solved in an exact analytical manner. Having found the spectrum of the system, the statistical properties of an N-boson system are reported.
High-statistics study of $K^0_S$ pair production in two-photon collisions
We report a high-statistics measurement of the differential cross section of the process $γγ → K^0_S K^0_S$ in the range 1.05 GeV $≤ W ≤$ 4.00 GeV, where $W$ is the center-of-mass energy of the colliding photons, using 972 fb -1 of data collected with the Belle detector at the $KEKB$ asymmetric-energy $e^+ e^-$ collider operated at and near the $Υ$-resonance region. The differential cross section is fitted by parameterized S-, D 0 - , D 2 - , G 0 - and G 2 -wave amplitudes. In the D 2 wave, the $f_2$(1270), $a_2$(1320) and $f^\prime_2$(1525) are dominant and a resonance, the $f_2$(2200), is also present. The $f_0$(1710) and possibly the $f_0$(2500) are seen in the $S$ wave. The mass, total width and product of the two-photon partial decay width and decay branching fraction to the $K\overline{K}$ state $Γ_{γγ}(ΒK\overline{K})$ are extracted for the $f^\prime_2$(1525), $f_0$(1710), $f_2$(2200) and $f_0$(2500). The destructive interference between the $f_2$(1270) and $a_2$(1320) is confirmed by measuring their relative phase. The parameters of the charmonium states $Χ_{c0}$ and $Χ_{c2}$ are updated. Possible contributions from the $Χ_{c0}(2P)$ and $Χ_{c2}(2P)$ states are discussed. A new upper limit for the branching fraction of the $P-$ and $CP-$violating decay channel $η_c → K^0_S K^0_S$ is reported. The detailed behavior of the cross section is updated and compared with $QCD$-based calculations.
Statistical evaluation of experimental determinations of neutrino mass hierarchy
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A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint
There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape of the load profile is the most significant predictor of the size of the battery.
Methods of statistical analysis in collider experiments by incorporating different types of systematic and statistical uncertainties
A number of statistical analysis techniques are described which meet demands arising in collider experiments in problems of processing the sampled data distributions by including systematic and statistical uncertainties of measurements.
Quantitative Evaluation of MD/HD Vehicle Electrification using Statistical Data
This paper presents a wide-ranging analysis of Class 3-8 commercial vehicle electrification by means of developing a framework tool which uses a quantitative method of estimating electric vehicle energy consumption and appropriate charging considerations. The Fleet DNA composite statistics on real-world driving behavior is used to evaluate feasible or market-ready battery electric vehicle (BEV) technologies in medium- and heavy-duty (MD/HD) applications. In the paper, ten representative Class 3-8 commercial vehicle electrifications have been evaluated as a function of various service coverages, including applications in port drayage tractors, refuse trucks, delivery trucks, buses, and bucket trucks. The results indicate significant energy savings and fuel cost savings across all MD/HD vehicle electrifications. The majority of MD BEVs, with the exception of Class 3 bucket trucks, achieve better than a 5-year payback with 50–75% service coverage. For HD BEVs, with the exception of the Class 8 port drayage tractors, the 90% service coverage results in a 10-year or longer payback time, while the 50% service coverage yields a 7–8 year payback. Class 8 port drayage tractors should achieve payback in no more than a 3.5 years with 50–75% service coverage. Thus, the analysis indicates a highly feasible potential for Class 3-6 MD vehicles to be electrified, and feasible opportunities for electrification in Class 7-8 HD short-distance applications.
Statistical mechanics and pressure of composite multimoded weakly nonlinear optical systems
Statistical mechanics can provide a versatile theoretical framework for investigating the collective dynamics of weakly nonlinear-wave settings that can be utterly complex to describe otherwise. In optics, composite systems arise due to interactions between different frequencies and polarizations. The purpose of this work is to develop a thermodynamic theory that takes into account the synergistic action of multiple components. We find that the type of the nonlinearity involved can have important implications in the thermalization process and, hence, can lead to different thermal equilibrium conditions. Importantly, we derive closed-form expressions for the actual optomechanical pressure that is exerted on the system. In particular, the total optomechanical pressure is the sum of the partial pressures due to each component. Our results can be applied to a variety of weakly nonlinear optical settings such as multimode fibers, bulk waveguides, photonic lattices, and coupled microresonators. We present two specific examples, where two colors interact in a one-waveguide array with either a cubic or quadratic nonlinearity.
Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations
Since turbulence measurements from Doppler lidars are being increasingly used within wind energy and boundary-layer meteorology, it is important to assess and improve the accuracy of these observations. While turbulent quantities are measured by Doppler lidars in several different ways, the simplest and most frequently used statistic is vertical velocity variance ( w ' 2 ) from zenith stares. But, the competing effects of signal noise and resolution volume limitations, which respectively increase and decrease w ' 2 , reduce the accuracy of these measurements. Herein, an established method that utilises the autocovariance of the signal to remove noise is evaluated and its skill in correcting for volume-averaging effects in the calculation of w ' 2 is also assessed. In addition, this autocovariance technique is further refined by defining the amount of lag time to use for the most accurate estimates of w ' 2 . And through comparison of observations from two Doppler lidars and sonic anemometers on a 300 m tower, the autocovariance technique is shown to generally improve estimates of w ' 2 . After the autocovariance technique is applied, values of w ' 2 from the Doppler lidars are generally in close agreement ( R 2 ≈ 0.95 -0.98) with those calculated from sonic anemometer measurements.
Some new results on the statistics of radio wave scintillation. I - Empirical evidence for Gaussian statistics
This paper presents an analysis of ionospheric scintillation data which shows that the underlying statistical structure of the signal can be accurately modeled by the additive complex Gaussian perturbation predicted by the Born approximation in conjunction with an application of the central limit theorem. By making use of this fact, it is possible to estimate the in-phase, phase quadrature, and cophased scattered power by curve fitting to measured intensity histograms. By using this procedure, it is found that typically more than 80% of the scattered power is in phase quadrature with the undeviated signal component. Thus, the signal is modeled by a Gaussian, but highly non-Rician process. From simultaneous UHF and VHF data, only a weak dependence of this statistical structure on changes in the Fresnel radius is deduced. The signal variance is found to have a nonquadratic wavelength dependence. It is hypothesized that this latter effect is a subtle manifestation of locally homogeneous irregularity structures, a mathematical model proposed by Kolmogorov (1941) in his early studies of incompressible fluid turbulence.
Median statistics estimate of the galactic rotational velocity
We compile a complete collection of 18 recent (from 2000 to 2017) measurements of Θ 0 , the rotational velocity of the Milky Way at R 0 (the radial distance of the Sun from the Galactic center). These measurements use tracers that are believed to more accurately reflect the systematic rotation of the Milky Way. Unlike other recent compilations of Θ 0 , our collection includes only independent measurements. We find that these 18 measurements are distributed in a mildly non-Gaussian fashion and a median statistics estimate indicates Θ 0 = 220 ± 10 kms –1 (2σ error) as the most reliable summary, at R 0 = 8.0 ± 0.3 kpc (2σ error).
Quantifying the heterogeneity of shale through statistical combination of imaging across scales
Shale is a highly heterogeneous material across multiple scales. A typical shale consists of nanometer-scale pores and minerals mixed with macro-scale fractures and particles of varying size. High-resolution imaging is crucial for characterizing the composition and microstructure of this rock. Yet, it is generally not feasible to image a large sample of shale at a high resolution over a large field of view (FOV), thus limiting a full characterization of the microstructure of this material. We present a stochastic framework based on multiple-point statistics that uses high-resolution training images to enhance low-resolution images obtained over a large FOV. Here, we demonstrate the approach using X-ray micro-tomography images of organic-rich Woodford shale obtained at two different resolutions and FOV. Results show that the proposed technique can generate realistic high-resolution images of the microstructure of shale over a large FOV.
Experiments, Statistical Analysis, and Modeling to Evaluate the Porosity Influence in SPS Coatings
Suspension plasma spray (SPS) is far more complicated than conventional plasma spray and requires a deep knowledge about the influence of process parameters and their correlations. In this study, YSZ coatings were manufactured by SPS with six different process parameters such as plasma power, suspension mass load, original powder size, substrate surface topology, spray distance, and spray step. Then, the porosity of as-prepared coatings was investigated by image method and X-ray transmission technique. A multivariate analysis on the collected experimental data was carried out by employing mathematical statistics methods. The results showed that: 1) Coating porosity has a negative correlation with plasma power and suspension mass load and a positive correlation with the original powder size, spray distance, spray step, and substrate roughness; 2) Spraying distance is the main factor affecting to coating porosity, followed by suspension mass load and substrate surface roughness, respectively. A linear model for porosity prediction was developed and was verified by experiments. Furthermore, the mechanism by which process parameters influence coating porosity is additionally discussed.
Microstructural characterization of dendritic evolution using two-point statistics
Characterizing large four-dimensional materials datasets is difficult due to the presence of complex mi- crostructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evo- lution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into compet- itive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap.
Scale effects in convoluted thermal/spatial statistics of plasticity initiation in small stressed volumes during nanoindentation
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