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At least 235 records · Page 13

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗

Modeling and control of distributed structures

An inherent incongruity in the modeling of controls for structures is discussed. Structures are basically distributed-parameter systems, described by partial differential equations, and control theory is concerned almost exclusively with discrete (in space) systems, described by ordinary differential equations. The standard approach to solving this dilemma is to discretize the system in space, which precludes the use of distributed controls. A different approach, known as the independent modal-space control method, is designed to eliminate the incongruity by bringing about a closer correspondence between modeling and control theory. The independent modal-space control method can treat distributed structures as well as discretized models and it permits design of both distributed and discrete-point controls.

Meirovitch, L.↗

Analysis of Broad-Lined Type Ic Supernovae From the (Intermediate) Palomar Transient Factory

We study 34 Type Ic supernovae that have broad spectral features (SNe Ic-BL). This is the only SN type found in association with long duration gamma-ray bursts (GRBs).We obtained our photometric data with the Palomar Transient Factory (PTF) and its continuation, the intermediate PTF (iPTF). This is the first large, homogeneous sample of SNe Ic-BL from an untargeted survey. Furthermore, given the high observational cadence of iPTF, most of these SNe Ic-BL were discovered soon after explosion. We present K-corrected Bgriz light curves of these SNe, obtained through photometry on template-subtracted images. We analyzed the shape of the r-band light curves, finding a correlation between the decline parameter delta m15 and the rise parameter delta m-10. We studied the SN colors and, based on g - r, we estimated the host-galaxy extinction for each event. Peak r-band absolute magnitudes have an average of -18:6 +- 0:5 mag. We fit each r-band light curve with that of SN 1998bw (scaled and stretched) to derive the explosion epochs. We computed the bolometric light curves using bolometric corrections, r-band data, and g - r colors. Expansion velocities from Fe ii were obtained by fitting spectral templates of SNe Ic. Bolometric light curves and velocities at peak were fitted using the semianalytic Arnett model to estimate ejecta mass Mej, explosion energy EK and 56Ni mass M(56Ni) for each SN. We find average values of Mej = 4 +- 3 M sun, EK = (7 +- 6) x 1051 erg, and M(56Ni) = 0:31 +- 0:16 M . The parameter distributions were compared to those presented in the literature and are overall in agreement with them. We also estimated the degree of 56Ni mixing using scaling relations derived from hydrodynamical models and we find that all the SNe are strongly mixed. The derived explosion parameters imply that at least 21% of the progenitors of SNe Ic-BL are compatible with massive (>28 M ), possibly single stars, whereas at least 64% might come from less massive stars in close binary systems.

Supernovae↗

Flexible Models for Solar Sail Control

Solar sails employ a unique form of propulsion, gaining momentum from incident and reflected photons. However, the momentum transferred by an individual photon is extremely small. Consequently, a solar sail must have an extremely large surface area and also be extremely light. The flexibility of the sail then must be considered when designing or evaluating control laws. In this paper, solar sail flexibility and its influence on control effectiveness is considered using idealized two-dimensional models to represent physical phenomena rather than a specific design. Differential equations of motion are derived for a distributed parameter model of a flexible solar sail idealized as a rotating central hub with two opposing flexible booms. This idealization is appropriate for solar sail designs in which the vibrational modes of the sail and supporting booms move together allowing the sail mass to be distributed along the booms in the idealized model. A reduced analytical model of the flexible response is considered. Linear feedback torque control is applied at the central hub. Two translational disturbances and a torque disturbance also act at the central hub representing the equivalent effect of deflecting sail shape about a reference line. Transient simulations explore different control designs and their effectiveness for controlling orientation, for reducing flexible motion and for disturbance rejection. A second model also is developed as a two-dimensional "pathfinder" model to calculate the effect of solar sail shape on the resultant thrust, in-plane force and torque at the hub. The analysis is then extended to larger models using the finite element method. The finite element modeling approach is verified by comparing results from a two-dimensional finite element model with those from the analytical model. The utility of the finite element modeling approach for this application is then illustrated through examples based on a full finite element model.

Weaver Smith, Suzanne↗

TPSAS-NF1676L-20108-DND

This presentation describes several enhancements planned for the version 4 aerosol subtyping and lidar ratio selection algorithms of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The CALIOP subtyping algorithm determines the most likely aerosol type from CALIOP measurements (attenuated backscatter, estimated particulate depolarization ratios de, layer altitude), and surface type. The aerosol type, so determined, is associated with a lidar ratio (LR) from a discrete set of values. In the version 3 algorithms, there are 6 pairs of 532 and 1064 nm lidar ratios. Some of these lidar ratios will be updated in the version 4 algorithms. In particular, the dust and polluted dust will be adjusted to reflect the latest measurements and model studies of these types. The algorithms are being updated to eliminate the occasional confusion between smoke and clean marine aerosols seen in version 3 by modifications to the elevated layer flag definitions that are used to determine the presence of smoke aerosols over the ocean. In the subtyping algorithms pure dust is determined by high estimated particulate depolarization ratios [de > 0.20]. Mixtures of dust and other aerosol types are determined by intermediate values of the estimated depolarization ratio [0.075< de <0.2]. The version 3 algorithms are limited to mixtures of dust and smoke, the so-called polluted dust aerosol type. To differentiate between mixtures of dust and smoke, and dust and marine aerosols, a new aerosol type will be added in the version 4 data products. In the revised classification algorithms, polluted dust will still defined as dust + smoke/pollution but in the marine boundary layer instances of moderate depolarization will be typed as dusty marine aerosols with a lower lidar ratio [LR = 35 sr] than polluted dust [currently LR = 55 sr]. The dusty marine type introduced in version 4 is modeled as a mixture of dust + marine aerosol. In the v3 algorithms the frequency of dust and polluted dust aerosols at daytime is higher than at nighttime. We present possible reasons for this and present the v4 distributions resulting from both improved background slope corrections of the daytime depolarization ratios and changes to the daytime thresholds for the polluted dust and dusty marine types of version 4. To gauge the impact of the enhancements, we contrast the following between versions 3 and 4: aerosol type, parameter distributions of each type, layer heights of maximum frequency, and distributions of smoke in biomass burning regions. To illustrate specific impacts the presentation shows case studies of version 3 and version 4 vertical feature masks of the aerosol subtypes, where appropriate, for the above enhancements.

A Omar↗

Comparison of distributed reacceleration and leaky-box models of cosmic-ray abundances (Z = 3-28)

A large collection of elemental and isotopic cosmic-ray data has been analyzed using the leaky-box transport model with and without reacceleration in the interstellar medium. Abundances of isotopes and elements with charges Z = 3-28 and energies E = 10 MeV/nucleon-1 TeV/nucleon were explored. Our results demonstrate that reacceleration models make detailed and accurate predictions with the same number of parameters or fewer as standard leaky-box models. Ad hoc fitting parameters in the standard model are replaced by astrophysically significant reacceleration parameters. Distributed reacceleration models explain the peak in secondary-to-primary ratios around 1 GeV/nucleon. They diminish the discrepancy between rigidity-dependent leakage and energy-independent anisotropy. They also offer the possibility of understanding isotopic anomalies at low energy.

Letaw, John R.↗

Five-Parameter Bivariate Probability Distribution

NASA technical memorandum presents four papers about five-parameter bivariate gamma class of probability distributions. With some overlap of subject matter, papers address different aspects of theories of these distributions and use in forming statistical models of such phenomena as wind gusts. Provides acceptable results for defining constraints in problems designing aircraft and spacecraft to withstand large wind-gust loads.

Tubbs, J.↗

Optimal control of first order distributed systems

The problem of characterizing optimal controls for a class of distributed-parameter systems is considered. The system dynamics are characterized mathematically by a finite number of coupled partial differential equations involving first-order time and space derivatives of the state variables, which are constrained at the boundary by a finite number of algebraic relations. Multiple control inputs, extending over the entire spatial region occupied by the system ("distributed controls') are to be designed so that the response of the system is optimal. A major example involving boundary control of an unstable low-density plasma is developed from physical laws.

Johnson, T. L.↗

Galerkin approximation for inverse problems for nonautonomous nonlinear distributed systems

An abstract framework and convergence theory is developed for Galerkin approximation for inverse problems involving the identification of nonautonomous nonlinear distributed parameter systems. A set of relatively easily verified conditions is provided which are sufficient to guarantee the existence of optimal solutions and their approximation by a sequence of solutions to a sequence of approximating finite dimensional identification problems. The approach is based on the theory of monotone operators in Banach spaces and is applicable to a reasonably broad class of nonlinear distributed systems. Operator theoretic and variational techniques are used to establish a fundamental convergence result. An example involving evolution systems with dynamics described by nonstationary quasilinear elliptic operators along with some applications are presented and discussed.

Banks, H. T.↗

A note on the regularity of solutions of infinite dimensional Riccati equations

This note is concerned with the regularity of solutions of algebraic Riccati equations arising from infinite dimensional LQR and LQG control problems. We show that distributed parameter systems described by certain parabolic partial differential equations often have a special structure that smoothes solutions of the corresponding Riccati equation. This analysis is motivated by the need to find specific representations for Riccati operators that can be used in the development of computational schemes for problems where the input and output operators are not Hilbert-Schmidt. This situation occurs in many boundary control problems and in certain distributed control problems associated with optimal sensor/actuator placement.

Burns, John A.↗

Nickel cadmium cell composite reliability model

Ni-Cd battery reliability has become a critical design parameter with the increasing need for longer life and optimally designed secondary battery power systems in space as well as in more mundane applications. It is the purpose of this paper to present a state-of-the-art Ni-Cd cell reliability model as a function of cumulative cyclic operation, cell temperature and cyclic depth-of-discharge. In addition, a simple and convenient cell failure analysis technique will be presented in which the reliability, the distribution, and the distribution parameters can be determined by visual inspection.

Kirsch, W. W.↗

Multiple scattering of electromagnetic waves by rain

As the operating frequencies of communications systems move higher into the millimeter wave region, the effects of multiple scattering in precipitation media become more significant. In this paper, general formulations are presented for single, first-order multiple, and complete multiple scattering. Included specifically are distributions of particle size, shape, and orientation angle, as well as variation in the medium density along the direction of wave propagation. Calculations are performed for rain. It is shown that the effects of higher-order scattering are not noticeable in either attenuation or channel isolation on a dual-polarized system until frequencies of about 30 GHz are reached. The complete multiple-scattering formulation presented gives accurate results at high millimeter wave frequencies as well as including realistic medium parameter distributions. Furthermore, it is numerically efficient.

Tsolakis, A.↗

An efficient algorithm for estimating noise covariances in distributed systems

An efficient computational algorithm for estimating the noise covariance matrices of large linear discrete stochatic-dynamic systems is presented. Such systems arise typically by discretizing distributed-parameter systems, and their size renders computational efficiency a major consideration. The proposed adaptive filtering algorithm is based on the ideas of Belanger, and is algebraically equivalent to his algorithm. The earlier algorithm, however, has computational complexity proportional to p to the 6th, where p is the number of observations of the system state, while the new algorithm has complexity proportional to only p-cubed. Further, the formulation of noise covariance estimation as a secondary filter, analogous to state estimation as a primary filter, suggests several generalizations of the earlier algorithm. The performance of the proposed algorithm is demonstrated for a distributed system arising in numerical weather prediction.

Dee, D. P.↗

Controls for space structures

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control. A theory for disturbance accommodating controllers based on reduced order models of structures was developed, and stability results for these controllers in closed-loop with large-scale finite element models of structures were obtained.

Balas, Mark↗

A Probabilistic Design Method Applied to Smart Composite Structures

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Shiao, Michael C.↗

An Approach to Shape Parameterization Using Laboratory Hypervelocity Impact Experiments

NASA’s Orbital Debris Program Office relies on laboratory-based impact tests to supplement the measurement data of on-orbit events that defines the orbital debris environment. These experiments provide information that is essential to interpreting the radar and optical measurements of orbital fragmentation events into useful metrics, such as characteristic size of the debris, and to providing a better understanding of the distributions of fragment populations in terms of their masses, material constituents, fragment densities, cross-sectional areas, area-to-mass ratios, shapes, etc. The Satellite Orbital Debris Characterization Impact Test (SOCIT) was a notable laboratory impact experiment conducted in 1992 using a surplus U.S. Navy Transit navigation satellite of the 1960s. The data from this ground-based experiment were combined with on-orbit measurements to develop the NASA Standard Satellite Breakup Model (SSBM). To account for advancements in satellite design and construction since, a new impact test series – DebriSat – was conducted in 2014. This test utilized a high-fidelity mock-up spacecraft that better represents the materials and construction techniques used to design and manufacture modern spacecraft. Together, these tests offer valuable data to model an orbital debris environment composed of legacy and modern spacecraft. This paper presents an overview of the two laboratory impact tests, comparing their fragment parameter distributions with each other and with relevant distributions from the NASA SSBM. The categorization and descriptions of fragment shapes are of significant interest for future work, yet there are marked differences in the definitions of shape categories between each dataset. The categorizations of constituent materials, and the measurement techniques employed to populate these two datasets, are also different. New rubrics simplify and equate the categorizations between datasets to aid comparative analyses and to facilitate the potential use of both datasets in tandem with future environmental debris models. A preferred approach to classifying shape across disparate datasets uses the characteristic-length dimensions, and a simplified shape classification based on physical, solid-body dimensions, to mathematically construct an encapsulating right-circular cylinder that represents the fragment. The ratio of cylinder length-to-diameter (L:D) then provides a single continuum value for shape that is strongly correlated with its designated shape and size. This metric can then be used to further assess the distribution of shape with populations of other fragment characteristics within these datasets. The shape parameterization using the L:D ratios of right-circular cylinders is discussed.

John H. Seago↗