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At least 91 records · Page 5

Moments of inclination error distribution computer program

A FORTRAN coded computer program is described which calculates orbital inclination error statistics using a closed-form solution. This solution uses a data base of trajectory errors from actual flights to predict the orbital inclination error statistics. The Scott flight history data base consists of orbit insertion errors in the trajectory parameters - altitude, velocity, flight path angle, flight azimuth, latitude and longitude. The methods used to generate the error statistics are of general interest since they have other applications. Program theory, user instructions, output definitions, subroutine descriptions and detailed FORTRAN coding information are included.

Myler, T. R.↗

The forward-backward asymmetry and differences of partial moments in inclusive semileptonic $B$ decays

Global fits to moments of kinematic distributions measured in inclusive semileptonic B\rightarrow X_c l \nu_l B → X c l ν l enable the determination of the Cabibbo-Kobayashi-Maskawa matrix element \left|V_{cb}\right| | V c b | together with non-perturbative matrix elements of the heavy quark expansion. In current fits, only two distinct kinematic distributions are employed and, as a consequence, higher moments of these distributions need to be taken into account to extract the relevant non-perturbative matrix elements. The moments of a given distribution are highly correlated and experimental uncertainties increase for higher moments. To address these issues, Turczyk suggested the inclusion of the charged lepton forward-backward asymmetry \mathcal{A}_{FB} 𝒜 F B in global fits, since it provides information on non-perturbative parameters beyond the commonly used moments. It is possible to construct differences of partial moments of kinematic distributions, which can provide additional information on the non-perturbative parameters beyond \mathcal{A}_{FB} 𝒜 F B and are studied in this work for the first time. Further, experimental cuts on the four-momentum transfer square are studied and are shown to preserve the shape of the angular distribution, in contrast to commonly used cuts on the lepton energy. Finally, the impact of final-state radiation and experimental lepton identification requirements on measurements of \mathcal{A}_{FB} 𝒜 F B and differences of partial moments are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Laser Calibration of an Impact Disdrometer

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

calibration↗

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗

Prediction of wing aeroelastic effects on aircraft lift and pitching moment characteristics

The distribution of flight loads on an aircraft structure determines the lift and pitching moment characteristics of the aircraft. When the load distribution changes due to the aeroelastic response of the structure, the lift and pitching moment characteristics also change. Some estimate of the effect of aeroelasticity on stability and control characteristics, particularly lift and pitching moment, is required for use in aircraft simulation models for evaluation of flight characteristics. This presentation outlines a procedure to incorporate aeroelastic effects into lift and pitching moment data from wind tunnel tests. Results are presented which were obtained from applying this procedure to an aircraft with a very flexible transport-type research wing. The procedure described is generally applicable to all types of aircraft.

Eckstrom, C. V.↗

Prediction of wing aeroelastic effects on aircraft lift and pitching moment characteristics

The distribution of flight loads on an aircraft structure determine the lift and pitching moment characteristics of the aircraft. When the load distribution changes due to the aeroelastic response of the structure, the lift and pitching moment characteristics also change. An estimate of the effect of aeroelasticity on stability and control characteristics is often required for the development of aircraft simulation models of evaluation of flight characteristics. This presentation outlines a procedure for incorporating calculated linear aeroelastic effects into measured nonlinear lift and pitching moment data from wind tunnel tests. Results are presented which were obtained from applying this procedure to data for an aircraft with a very flexible transport type research wing. The procedure described is generally applicable to all types of aircraft.

Eckstrom, Clinton V.↗

Prediction of wing aeroelastic effects on aircraft life and pitching moment characteristics

The distribution of flight loads on an aircraft structure determine the lift and pitching moment characteristics of the aircraft. When the load distribution changes due to the aeroelastic response of the structure, the lift and pitching moment characteristics also change. An estimate of the effect of aeroelasticity on stability and control characteristics is often required for the development of aircraft simulation models of evaluation of flight characteristics. This presentation outlines a procedure for incorporating calculated linear aeroelastic effects into measured nonlinear lift and pitching moment data from wind tunnel tests. Results are presented which were obtained from applying this procedure to data for an aircraft with a very flexible transport type research wing. The procedure described is generally applicable to all types of aircraft.

Eckstrom, Clinton V.↗

Comparison of wing-span averaging effects on lift, rolling moment, and bending moment for two span load distributions and for two turbulence representations

An analytical method of computing the averaging effect of wing-span size on the loading of a wing induced by random turbulence was adapted for use on a digital electronic computer. The turbulence input was assumed to have a Dryden power spectral density. The computations were made for lift, rolling moment, and bending moment for two span load distributions, rectangular and elliptic. Data are presented to show the wing-span averaging effect for wing-span ratios encompassing current airplane sizes. The rectangular wing-span loading showed a slightly greater averaging effect than did the elliptic loading. In the frequency range most bothersome to airplane passengers, the wing-span averaging effect can reduce the normal lift load, and thus the acceleration, by about 7 percent for a typical medium-sized transport. Some calculations were made to evaluate the effect of using a Von Karman turbulence representation. These results showed that using the Von Karman representation generally resulted in a span averaging effect about 3 percent larger.

Lichtenstein, J. H.↗

Viking Lander image analysis of Martian atmospheric dust

We have reanalyzed three sets of Viking Lander 1 and 2 (VL1 and VL2) images of the Martian atmosphere to better evaluate the radiative properties of the atmospheric dust particles. The properties of interest are the first two moments of the size distribution, the single-scattering albedo, the dust single-scattering phase function, and the imaginary index of refraction. These properties provide a good definition of the influence that the atmospheric dust has on heating of the atmosphere. Our analysis represents a significant improvement over past analyses (Pollack et al. 1977, 1979) by deriving more accurate brightness closer to the sun, by carrying out more precise analyses of the data to acquire the quantities of interest, and by using a better representation of scattering by nonspherical particles. The improvements allow us to better define the diffraction peak and hence the size distribution of the particles. For a lognormal particle size distribution, the first two moments of the size distribution, weighted by the geometric cross section, are found. The geometric cross-section weighted mean radius r(sub eff) is found to be 1.85 +/- 0.3 micrometers at VL2 during northern summer when dust loading was low and 1.52 +/- 0.3 micrometers at VL1 during the first dust storm. In both cases the best cross-section weighted mean variance nu(sub eff) of the size distribution is equal to 0.5 +/- 0.2 micrometers. The changes in size distribution, and thus radiative properties, do not represent a substantial change in solar energy deposition in the atmosphere over the Pollak et al. (1977, 1979) estimates.

Pollack, James B.↗

Viking Lander image analysis of Martian atmospheric dust

We have reanalyzed three sets of Viking Lander 1 and 2 (VL1 and VL2) images of the Martian atmosphere to better evaluate the radiative properties of the atmospheric dust particles. The properties of interest are the first two moments of the size distribution, the single-scattering albedo, the dust single-scattering phase function, and the imaginary index of refraction. These properties provide a good definition of the influence that the atmospheric dust has on heating of the atmosphere. Our analysis represents a significant improvement over past analyses (Pollack et al. 1977,1979) by deriving more accurate brightnesses closer to the sun, by carrying out more precise analyses of the data to acquire the quantities of interest, and by using a better representation of scattering by nonspherical particles. The improvements allow us to better define the diffraction peak and hence the size distribution of the particles. For a lognormal particle size distribution, the first two moments of the size distribution, weighted by the geometric cross section, are found. The geometric cross-section weighted mean radius (r(sub eff)) is found to be 1.85 +/- 0.3 microns at VL2 during northern summer when dust loading was low and 1.52 +/- 0.3 microns at VL1 during the first dust storm. In both cases the best cross-section weighted mean variance (nu(eff)) of the size distribution is equal to 0.5 +/- 0.2 microns. The changes in size distribution, and thus radiative properties, do not represent a substantial change in solar energy deposition in the atmosphere over the Pollack et al. (1977,1979) estimates.

Pollack, James B.↗

Retrieving DSD Moments from GPM-DPR: A Simulation Study Based on the Full DSD Spectra Characterized by the Generalized Gamma Model

Recently, a method to retrieve rain drop size distribution (DSD) moments from X-band dual polarization radar measurements has been developed using copolar reflectivity, differential reflectivity and specific attenuation. Two reference moments are retrieved first, followed by reconstructing the DSDs and calculating other moments using a generalized gamma model to represent the underlying shape, h(x), corresponding to the pair of chosen reference moments. Here we explore a similar approach but the retrieval method in this study uses dual-frequency radar measurements. In the case of GPM-DPR, the two frequencies are 13.8and 35 GHz, and their products include attenuation corrected reflecivities at both frequencies (Z and Z) and the specific attenuation (k, k, if available). Our approach is to use these products to determine two reference moments, namely M3 andM6 representing the third and the sixth moments respectively. Then, as with the polarimetric radar retrievals, we use the most probable h(x) to reconstruct the full DSD spectra, from which other moments are calculated. The best two DPR products for estimating M3 and M6 appear to be A and Z. Figure 1 shows the retrievals versus the ‘true’ moments. 2930 three-minute DSDs were used for the (T-matrix) scattering calculations at Ku and Ka bands but only cases with A > 0.5 dB/km were chosen. For the retrieved moments, the integration was performed only up to 6 mm drop diameter. The [1:1] line is included in Fig. 1. Even with just two DPR products as input the results seem promising, although the lower order moments show somewhat more scatter, especially the zeroth moment, M0. We will quantify the retrieval errors, and additionally examine the stability of h(x). For the latter, data from (i) Greeley, Colorado, (ii) Huntsville, Alabama, and (iii)Wallops, Virginia, will be used. Finally, a GPM overpass case over Huntsville, during a widespread rain event on 11 April 2016, will be considered as an initial test case.

precipitation↗