Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “nonlinear sigma model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

The response of a nonlinear, time-dependent, baroclinic model of the atmosphere to tropical thermal forcing

A multi-level, sigma coordinate, primitive equation atmospheric model has been utilized to study both the tropical and extratropical response to an isolated region of steady thermal forcing in the tropics. The nonlinear response during the first 28 days of the simulation is described. The response can be generally characterized by two distinct components. The first component is a quasi-stationary disturbance which extends eastward and poleward away from the source region along a 'great circle' path. The structure of this disturbance is essentially barotropic away from the source region. The second component is a growing baroclinic wave propagating zonally at mid-latitudes. Significantly, this disturbance is apparently the result of baroclinic instability induced by the quasi-stationary wavetrain. The discussion is predominantly heuristic in form and relies heavily on graphical presentation and quasi-geostrophic theory to interpret the response and individual components of the thermodynamic energy and momentum equations.

Grose, W. L.↗

Sensitivity of an atmospheric photochemistry model to chlorine perturbations including consideration of uncertainty propagation

Models of stratospheric photochemistry are generally tested by comparing their predictions for the composition of the present atmosphere with measurements of species concentrations. These models are then used to make predictions of the atmospheric sensitivity to perturbations. Here the problem of the sensitivity of such a model to chlorine perturbations ranging from the present influx of chlorine-containing compounds to several times that influx is addressed. The effects of uncertainties in input parameters, including reaction rate coefficients, cross sections, solar fluxes, and boundary conditions, are evaluated using a Monte Carlo method in which the values of the input parameters are randomly selected. The results are probability distributions for present atmosheric concentrations and for calculated perturbations due to chlorine from fluorocarbons. For more than 300 Monte Carlo runs the calculated ozone perturbation for continued emission of fluorocarbons at today's rates had a mean value of -6.2 percent, with a 1-sigma width of 5.5 percent. Using the same runs but only allowing the cases in which the calculated present atmosphere values of NO, NO2, and ClO at 25 km altitude fell within the range of measurements yielded a mean ozone depletion of -3 percent, with a 1-sigma deviation of 2.2 percent. The model showed a nonlinear behavior as a function of added fluorocarbons. The mean of the Monte Carlo runs was less nonlinear than the model run using mean value of the input parameters.

Stolarski, R. S.↗

The influence of orography on the transport of atmospheric constituents

Given the fact that martian orography varies over a range of two scale heights (cf., about one scale height on Earth), it is thought that on Mars some aspects of the circulation should be affected to a large degree by the presence of orography. Initial results from two numerical models are presented that illustrate the effect of orography on cross-equatorial transport on Mars. On Earth, western boundary currents are found not only in the oceans as one would expect, but also in the troposphere, the most notable example being the East African Jet, which has an important effect on the monsoon circulation of the Eastern Indian Ocean. Two models were used for this investigation: a simple GCM (hereafter referred to as the SGCM); and a simple one-level barotropic model (BM). The SGCM solves the hydrostatic primitive equations on a sphere by representing model variables by spherical harmonics in the horizontal, with nonlinear terms being calculated in grid-point space. In the vertical, the model uses the sigma coordinate system in finite-difference form. The model represents the radiative processes in the atmosphere by a Newtonian relaxation to a specified zonal mean temperature state and surface drag by Rayleigh friction in the lowest model level.

Joshi, Manoj M.↗

The Aemulus Project. V. Cosmological Constraint from Small-scale Clustering of BOSS Galaxies

We analyze clustering measurements of BOSS galaxies using a simulation-based emulator of two-point statistics. We focus on the monopole and quadrupole of the redshift-space correlation function, and the projected correlation function, at scales of 0.1 ~ 60 h -1 Mpc. Although our simulations are based on wCDM with general relativity (GR), we include a scaling parameter of the halo velocity field, γ f , defined as the amplitude of the halo velocity field relative to the GR prediction. We divide the BOSS data into three redshift bins. After marginalizing over other cosmological parameters, galaxy bias parameters, and the velocity scaling parameter, we find fσ 8 (z = 0.25) = 0.413 ± 0.031, fσ 8 (z = 0.4) = 0.470 ± 0.026, and fσ 8 (z = 0.55) = 0.396 ± 0.022. Compared with Planck observations using a flat Lambda cold dark matter model, our results are lower by 1.9σ, 0.3σ, and 3.4σ, respectively. These results are consistent with other recent simulation-based results at nonlinear scales, including weak lensing measurements of BOSS LOWZ galaxies, two-point clustering of eBOSS LRGs, and an independent clustering analysis of BOSS LOWZ. All these results are generally consistent with a combination of ${\gamma }_{f}^{1/2}{\sigma }_{8}\approx 0.75$. We note, however, that the BOSS data is well fit assuming GR, i.e., γf = 1. We cannot rule out an unknown systematic error in the galaxy bias model at nonlinear scales, but near-future data and modeling will enhance our understanding of the galaxy–halo connection, and provide a strong test of new physics beyond the standard model.

79 ASTRONOMY AND ASTROPHYSICS↗

Nonlinear consider covariance analysis using a sigma-point filter formulation

The research reported here extends the mathematical formulation of nonlinear, sigma-point estimators to enable consider covariance analysis for dynamical systems. This paper presents a novel sigma-point consider filter algorithm, for consider-parameterized nonlinear estimation, following the unscented Kalman filter (UKF) variation on the sigma-point filter formulation, which requires no partial derivatives of dynamics models or measurement models with respect to the parameter list. It is shown that, consistent with the attributes of sigma-point estimators, a consider-parameterized sigma-point estimator can be developed entirely without requiring the derivation of any partial-derivative matrices related to the dynamical system, the measurements, or the considered parameters, which appears to be an advantage over the formulation of a linear-theory sequential consider estimator. It is also demonstrated that a consider covariance analysis performed with this 'partial-derivative-free' formulation yields equivalent results to the linear-theory consider filter, for purely linear problems.

covariance↗

The error associated with use of various forms of the divergence equation to diagnose geopotential and temperature

This study utilizes a model-generated data set to evaluate the errors associated with the diagnosis of geopotential height using three approximate forms of the divergence equation (DE). The DE was solved on the original sigma-coordinate surfaces of the model to exclude any error produced in the process of interpolating the data from observation points to the coordinate surface of the DE. An inviscid, nonlinear, divergent DE produced rms geopotential height errors as large as 3 m and rms temperature errors of over 26 C in the lower planetary boundary layer (PBL), with minimal errors above 800 mb. Elimination of the isobaric divergence in the velocity field caused additional height errors of 5-6 m and temperature errors of 0.4-1.2 C in the free troposphere. Use of a further-degraded DE without nonlinear terms caused height errors of 10-15 m in the upper troposphere with modestly increased temperature errors. Error fields at all levels had synoptic-scale features, with some mesoalpha structure. No spatial noise was apparent. Use of a temporal spectral filter to eliminate high-frequency modes from the model-generated data did not significantly influence the error associated with use of various forms of the DE.

Modica, George M.↗

Calculations of microwave brightness temperature of rough soil surfaces: Bare field

A model for simulating the brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is obtained by the integration of the bistatic scattering coefficients for rough surfaces. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation sigma and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both 1.4 GHz and 5 GHz frequences. A nonlinear least-squares fitting method is used to obtain the values of delta and l that best characterize the surface roughness. The effect of shadowing is incorporated by introducing a function S(theta), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for the horizontal polarization are in excellent agreement with the data. However, for the vertical polarization, some discrepancies exist between the calculations and data, particularly at the 1.4 GHz frequency. Possible causes of the discrepancy are discussed.

Mo, T.↗

Calculations of microwave brightness temperature of rough soil surfaces

A model for simulating the brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is obtained by the integration of the bistatic scattering coefficients for rough surfaces. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation sigma and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both 1.4 GHz and 5 GHz frequencies. A nonlinear least-squares fitting method is used to obtain the values of delta and l that best characterize the surface roughness. The effect of shadowing is incorporated by introducing a function S(theta), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for the horizontal polarization are in excellent agreement with the data. However, for the vertical polarization, some discrepancies exist between the calculations and data, particularly at the 1.4 GHz frequency. Possible causes of the discrepancy are discussed.

Mo, T.↗

Decentralized adaptive control

A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

Oh, B. J.↗

Influence of Ply Waviness on Fatigue Life of Tapered Composite Flexbeam Laminates

Nonlinear tapered flexbeam laminates, with significant ply waviness, were cut from a full-size composite rotor hub flexbeam. The specimens were tested under combined axial tension and cyclic bending loads. All of the specimens had wavy plies through the center and near the surfaces (termed marcelled areas), although for some of the specimens the surface marcels were very obvious, and for others they were much smaller. The specimens failed by first developing cracks through the marcels at the surfaces, and then delaminations grew from those cracks, in both directions. Delamination failure occurred in these specimens at significantly shorter fatigue lives than similar specimens without waviness, tested in ref. 2. A 2D finite element model was developed which closely approximated the flexbeam geometry, boundary conditions, and loading. In addition, the FE model duplicated the waviness observed in one of the test specimens. The model was analyzed using a geometrically nonlinear FE code. Modifications were made to the original model to reduce the amplitude of the marcels near the surfaces. The analysis was repeated for each modification. Comparisons of the interlaminar normal stresses, sigma(sub n), in the various models showed that under combined axial-tension and cyclic-bending loading, for marcels of the same aspect ratio, sigma(sub n) stresses increased as the distance along the taper, from thick to thin end, increased. For marcels of the same aspect ratio and at the same X-location along the taper, sigma(sub n) stresses decreased as the distance from the surface into the flexbeam interior increased. A technique was presented for determining the smallest acceptable marcel aspect ratio at various locations in the flexbeam.

Murri, Gretchen B.↗

An analysis of the Kalman filter in the Gamma Ray Observatory (GRO) onboard attitude determination subsystem

The Gamma Ray Observatory (GRO) spacecraft needs a highly accurate attitude knowledge to achieve its mission objectives. Utilizing the fixed-head star trackers (FHSTs) for observations and gyroscopes for attitude propagation, the discrete Kalman Filter processes the attitude data to obtain an onboard accuracy of 86 arc seconds (3 sigma). A combination of linear analysis and simulations using the GRO Software Simulator (GROSS) are employed to investigate the Kalman filter for stability and the effects of corrupted observations (misalignment, noise), incomplete dynamic modeling, and nonlinear errors on Kalman filter. In the simulations, on-board attitude is compared with true attitude, the sensitivity of attitude error to model errors is graphed, and a statistical analysis is performed on the residuals of the Kalman Filter. In this paper, the modeling and sensor errors that degrade the Kalman filter solution beyond mission requirements are studied, and methods are offered to identify the source of these errors.

Snow, Frank↗

Use of an adjoint model for finding triggers for Alpine lee cyclogenesis

The authors propose a new procedure, designated the adjoint-based genesis diagnostic (AGD) procedure, for studying triggering mechanisms and the subsequent genesis of the synoptic phenomena of interest. This procedure makes use of a numerical model sensitivity to initial conditions and the nonlinear evolution of the initial perturbations that are designed using this sensitivity. The model sensitivity is evaluated using the associated adjoint model. This study uses the dry version of the National Center for Atmospheric Research Mesoscale Adjoint Modeling System (MAMS) for the numerical experiments. The authors apply the AGD procedure to two cases of Alpine lee cyclogenesis that were observed during the Alpine Experiment special observations period. The results show that the sensitivity fields that are produced by the adjoint model and the associated initial perturbations are readily related to the probable triggering mechanisms for these cyclones. Additionally, the nonlinear evolution of these initial perturbations points toward the physical processes involved in the lee cyclone formation. The AGD experiments for a weak cyclone case indicate that the MAMS forecast model has an underrepresented topographic forcing due to the sigma vertical coordinate and that this model error can be compensated by adjustments in the initial conditions that are related to the triggering mechanisms, which is not associated with the topographic blocking mechanism.

Vukicevic, Tomislava↗

Voids and constraints on nonlinear clustering of galaxies

Void statistics of the galaxy distribution in the Center for Astrophysics Redshift Survey provide strong constraints on galaxy clustering in the nonlinear regime, i.e., on scales R equal to or less than 10/h Mpc. Computation of high-order moments of the galaxy distribution requires a sample that (1) densely traces the large-scale structure and (2) covers sufficient volume to obtain good statistics. The CfA redshift survey densely samples structure on scales equal to or less than 10/h Mpc and has sufficient depth and angular coverage to approach a fair sample on these scales. In the nonlinear regime, the void probability function (VPF) for CfA samples exhibits apparent agreement with hierarchical scaling (such scaling implies that the N-point correlation functions for N greater than 2 depend only on pairwise products of the two-point function xi(r)) However, simulations of cosmological models show that this scaling in redshift space does not necessarily imply such scaling in real space, even in the nonlinear regime; peculiar velocities cause distortions which can yield erroneous agreement with hierarchical scaling. The underdensity probability measures the frequency of 'voids' with density rho less than 0.2 -/rho. This statistic reveals a paucity of very bright galaxies (L greater than L asterisk) in the 'voids.' Underdensities are equal to or greater than 2 sigma more frequent in bright galaxy samples than in samples that include fainter galaxies. Comparison of void statistics of CfA samples with simulations of a range of cosmological models favors models with Gaussian primordial fluctuations and Cold Dark Matter (CDM)-like initial power spectra. Biased models tend to produce voids that are too empty. We also compare these data with three specific models of the Cold Dark Matter cosmogony: an unbiased, open universe CDM model (omega = 0.4, h = 0.5) provides a good match to the VPF of the CfA samples. Biasing of the galaxy distribution in the 'standard' CDM model (omega = 1, b = 1.5; see below for definitions) and nonzero cosmological constant CDM model (omega = 0.4, h = 0.6 lambda(sub 0) = 0.6, b = 1.3) produce voids that are too empty. All three simulations match the observed VPF and underdensity probability for samples of very bright (M less than M asterisk = -19.2) galaxies, but produce voids that are too empty when compared with samples that include fainter galaxies.

Vogeley, Michael S.↗

Atmospheric model development in support of SEASAT. Volume 3: Prediction models

As part of the SEASAT program of NASA, a set of four hemispheric, atmospheric models are developed. The four models use a polar stereographic grid in the horizontal and a sigma coordinate in the vertical. Conservation forms of the difference equations are integrated using either a fifteen or four minute time step on a 381 km or 127 km grid (at 60 deg N) for the 63 x 63 or 187 x 187 models respectively. A nonlinear pressure smoother is used along with momentum and temperature diffusion to help control computational noise. The horizontal boundary conditions are insulated slippery walls. Centered time differencing with time averaging of the pressure gradient force term in the momentum equations is used. Robert time filtering on of the temperature and moisture solutions is used for computational stability. The moisture and heat source/sink terms are modeled. Terms representing evaporation and large scale condensation, sensible heat exchange, parameterized cumulus convection and precipitation, and solar and terrestrial radiation are included. Initialization of the models is based on a pattern conservation technique to obtain objective analysis of the state parameter structure from the surface to 50 mb.

Wellck, R. E.↗

Secular evolution of the vertical column abundances of CHClF2 (HCFC-22) in the Earth's atmosphere inferred from ground-based IR solar observations at the Jungfraujoch and at Kitt Peak, and comparison with model calculations

Series of high-resolution infrared solar spectra recorded at the International Scientific Station of the Jungfraujoch, Switzerland, between 06/1986 and 11/1992, and at Kitt Peak National Observatory, Tucson, Arizona (U.S.A.), from 12/1980 to 04/1992, have been analyzed to provide a comprehensive ensemble of vertical column abundances of CHClF2 (HCFC-22; Freon-22) above the European and the North American continents. The columns were derived from nonlinear least-squares curve fittings between synthetic spectra and the observations containing the unresolved 2 nu(sub 6) Q-branch absorption of CHClF2 at 829.05/cm. The changes versus time observed in these columns were modeled assuming both an exponential and a linear increase with time. The exponential rates of increase at one-sigma uncertainties were found equal to (7.0 +/- 0.35)%/yr for the Junfraujoch data and (7.0 +/- 0.23)%/yr for the Kitt Peak data. The exponential trend of 7.0%/yr found at both stations widely separated in location can be considered as representative of the global increase of the CHClF2 burden in the Earth's atmosphere during the period 1980 to 1992. When assuming two realistic vertical volume mixing ratio profiles for CHClF2 in the troposphere, one quasi constant and the other decreasing by about 13% from the ground to the tropopause, the concentrations for mid-1990 were found to lie between 97 and 111 pptv (parts per trillion by volume) at the 3.58 km altitude of the Jungfraujoch and between 97 and 103 pptv at Kitt Peak, 2.09 km above sea level. Corresponding values derived from calculations using a high vertical resolution-2D model and recently compiled HCFC-22 releases to the atmosphere, were equal to 107 and 105 pptv, respectively, in excellent agreement with the measurements. The model calculated lifetime of CHClF2 was found equal to 15.6 years. The present results are compared critically with similar data found in the literature. On average, the concentrations found here are lower by 15-20% than those derived from in situ investigations; this difference cannot be explained by the absolute uncertainty of +/- 11% assigned presently to the infrared remote measurements.

Zander, R.↗

Comparing Consider-Covariance Analysis with Sigma-Point Consider Filter and Linear-Theory Consider Filter Formulations

Recent literature in applied estimation theory reflects growing interest in the sigma-point (also called unscented ) formulation for optimal sequential state estimation, often describing performance comparisons with extended Kalman filters as applied to specific dynamical problems [c.f. 1, 2, 3]. Favorable attributes of sigma-point filters are described as including a lower expected error for nonlinear even non-differentiable dynamical systems, and a straightforward formulation not requiring derivation or implementation of any partial derivative Jacobian matrices. These attributes are particularly attractive, e.g. in terms of enabling simplified code architecture and streamlined testing, in the formulation of estimators for nonlinear spaceflight mechanics systems, such as filter software onboard deep-space robotic spacecraft. As presented in [4], the Sigma-Point Consider Filter (SPCF) algorithm extends the sigma-point filter algorithm to the problem of consider covariance analysis. Considering parameters in a dynamical system, while estimating its state, provides an upper bound on the estimated state covariance, which is viewed as a conservative approach to designing estimators for problems of general guidance, navigation and control. This is because, whether a parameter in the system model is observable or not, error in the knowledge of the value of a non-estimated parameter will increase the actual uncertainty of the estimated state of the system beyond the level formally indicated by the covariance of an estimator that neglects errors or uncertainty in that parameter. The equations for SPCF covariance evolution are obtained in a fashion similar to the derivation approach taken with standard (i.e. linearized or extended) consider parameterized Kalman filters (c.f. [5]). While in [4] the SPCF and linear-theory consider filter (LTCF) were applied to an illustrative linear dynamics/linear measurement problem, in the present work examines the SPCF as applied to nonlinear sequential consider covariance analysis, i.e. in the presence of nonlinear dynamics and nonlinear measurements. A simple SPCF for orbit determination, exemplifying an algorithm hosted in the guidance, navigation and control (GN&C) computer processor of a hypothetical robotic spacecraft, was implemented, and compared with an identically-parameterized (standard) extended, consider-parameterized Kalman filter. The onboard filtering scenario examined is a hypothetical spacecraft orbit about a small natural body with imperfectly-known mass. The formulations, relative complexities, and performances of the filters are compared and discussed.

Lisano, Michael E.↗

A Comparison of the Bounded Derivative and the Normal Mode Initialization Methods Using Real Data

Browning et al. (1980) proposed an initialization method called the bounded derivative method (BDI). They used analytical data to test the new method. Kasahara (1982) theoretically demonstrated the equivalence between BDI and the well known nonlinear normal mode initialization method (NMI). The purposes of this study are the extension of the application of BDI to real data and comparison with NMI. The unbalanced initial state (UBD) is data of January, 1979 OOZ which were interpolated from the adjacent sigma levels of the GLAS GCM to the 300 mb surface. The global barotropic model described by Takacs and Balgovind (1983) is used. Orographic forcing is explicitly included in the model. Many comparisons are performed between various quantities. However, we only present a comparison of the time evolution at two grid points A(50 S, 90 E) and B(10 S, 20 E) which represent low and middle latitude locations. To facilitate a more complete comparison an initialization experiment based on the classical balance equation (CBE) was also included.

Semazzi, F. H. M.↗

Nonlinear Attitude Filtering Methods

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

F Landis Markley↗