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NASA NTRS2003

Development of Testing Methodologies for the Mechanical Properties of MEMS

This effort is to investigate and design testing strategies to determine the mechanical properties of MicroElectroMechanical Systems (MEMS) as well as investigate the development of a MEMS Probabilistic Design Methodology (PDM). One item of potential interest is the design of a test for the Weibull size effect in pressure membranes. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. However, the primary area of investigation will most likely be analysis and modeling of material interfaces for strength as well as developing a strategy to handle stress singularities at sharp corners, filets, and material interfaces. This will be a continuation of the previous years work. The ultimate objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads.

Ekwaro-Osire, Stephen↗
NASA NTRS2008

A Globally Optimal Particle Tracking Technique for Stereo Imaging Velocimetry Experiments

An important phase of any Stereo Imaging Velocimetry experiment is particle tracking. Particle tracking seeks to identify and characterize the motion of individual particles entrained in a fluid or air experiment. We analyze a cylindrical chamber filled with water and seeded with density-matched particles. In every four-frame sequence, we identify a particle track by assigning a unique track label for each camera image. The conventional approach to particle tracking is to use an exhaustive tree-search method utilizing greedy algorithms to reduce search times. However, these types of algorithms are not optimal due to a cascade effect of incorrect decisions upon adjacent tracks. We examine the use of a guided evolutionary neural net with simulated annealing to arrive at a globally optimal assignment of tracks. The net is guided both by the minimization of the search space through the use of prior limiting assumptions about valid tracks and by a strategy which seeks to avoid high-energy intermediate states which can trap the net in a local minimum. A stochastic search algorithm is used in place of back-propagation of error to further reduce the chance of being trapped in an energy well. Global optimization is achieved by minimizing an objective function, which includes both track smoothness and particle-image utilization parameters. In this paper we describe our model and present our experimental results. We compare our results with a nonoptimizing, predictive tracker and obtain an average increase in valid track yield of 27 percent

McDowell, Mark↗
NASA NTRS2010

Navier-Stokes Dynamics by a Discrete Boltzmann Model

This work investigates the possibility of particle-based algorithms for the Navier-Stokes equations and higher order continuum approximations of the Boltzmann equation; such algorithms would generalize the well-known Pullin scheme for the Euler equations. One such method is proposed in the context of a discrete velocity model of the Boltzmann equation. Preliminary results on shock structure are consistent with the expectation that the shock should be much broader than the near discontinuity predicted by the Pullin scheme, yet narrower than the prediction of the Boltzmann equation. We discuss the extension of this essentially deterministic method to a stochastic particle method that, like DSMC, samples the distribution function rather than resolving it completely.

Rubinstein, Robet↗
NASA NTRS2014

Wide-Field Hubble Space Telescope Observations of the Globular Cluster System in NGC 1399*

We present a comprehensive high spatial resolution imaging study of globular clusters (GCs) in NGC 1399, thecentral giant elliptical cD galaxy in the Fornax galaxy cluster, conducted with the Advanced Camera for Surveys(ACS) aboard theHubble Space Telescope(HST).Using a novel technique to construct drizzled point-spreadfunction libraries for HSTACS data, we accurately determine the fidelity of GC structural parameter measurementsfrom detailed artificial star cluster experiments and show the superior robustness of the GC half-light radius,rh,compared with other GC structural parameters, such as King core and tidal radius. The measurement ofrhfor themajor fraction of the NGC 1399 GC system reveals a trend of increasingrhversus galactocentric distance,Rgal,out to about 10 kpc and a flat relation beyond. This trend is very similar for blue and red GCs, which are found tohave a mean size ratio ofrh,redrh,blue0.820.11 at all galactocentric radii from the core regions of the galaxyout to40 kpc. This suggests that the size difference between blue and red GCs is due to internal mechanismsrelated to the evolution of their constituent stellar populations. Modeling the mass density profile of NGC 1399shows that additional external dynamical mechanisms are required to limit the GC size in the galaxy halo regionstorh2 pc. We suggest that this may be realized by an exotic GC orbit distribution function, an extended darkmatter halo, andor tidal stress induced by the increased stochasticity in the dwarf halo substructure at largergalactocentric distances. We compare our results with the GCrhdistribution functions in various galaxies and findthat the fraction of extended GCs withrh5 pc is systematically larger in late-type galaxies compared with GCsystems in early-type galaxies. This is likely due to the dynamically more violent evolution of early-type galaxies.We match our GCrhmeasurements with radial velocity data from the literature and split the resulting sample at themedianrhvalue into compact and extended GCs. We find that compact GCs show a significantly smaller line-of-sight velocity dispersion,cmp22525 km s1, than their extended counterparts,ext31721 km s1.Considering the weaker statistical correlation in the GCrhcolor and the GCrhRgalrelations, the more significantGC sizedynamics relation appears to be astrophysically more relevant and hints at the dominant influence of theGC orbit distribution function on the evolution of GC structural parameters.

Hubble↗
NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗
NASA NTRS1973

Brownian motion of electrons in time-dependent magnetic fields.

The behavior of a weakly ionized plasma in slowly varying time-dependent magnetic fields is studied through an extension of Williamson's stochastic theory. In particular, attention is focused on the properties of electron diffusion in the plane perpendicular to the direction of the magnetic field, when the field strength is large. It is shown that, in the strong field limit, the classical 1/B-squared dependence of the perpendicular diffusion coefficient is obtained for two models in which the field B(t) is monotonic in t and for two models in which B(t) possesses at least one turning point.

Iverson, G. J.↗
NASA NTRS2003

Generation and Scattering of Radiation Observed by Voyager in the Outer Heliosphere

Excellent progress was made under this grant on the generation and scattering of the 2-3 kHz radio emissions observed by the Voyager spacecraft in the outer heliosphere. These are the most powerful radio emissions produced in our solar system, surpassing even those of Jupiter and the Sun. The widely-held hypothesis pursued is that the radiation is generated near the electron plasma frequency f(sub p) or near 2f(sub p) as a shock wave traverses the heliosheath regions and/or heliopause predicted in the interaction region between the solar wind and the local interstellar medium. (Note that f (sup 2) (sub p) is proportional to the plasma density.) The traveling shock wave is plausibly associated with a global merged interaction region (GMIR). Accordingly, this so-called GMIR model is strongly analogous to the common interpretation of type II solar radio bursts and to radio emissions associated with Earth's bow shock, with coronal mass ejections (CMEs) and Earth's magnetosphere playing the role of a GMIR, respectively. Accordingly, Dr Cairns work on type II bursts, Earth's foreshock, and stochastic growth theory (not described in detail) strongly aided and complemented the research progress on the 2-3 kHz emissions described.

Spangler, Steven R.↗
NASA NTRS1991

Stochastic inflation lattice simulations - Ultra-large scale structure of the universe

Non-Gaussian fluctuations for structure formation may arise in inflation from the nonlinear interaction of long wavelength gravitational and scalar fields. Long wavelength fields have spatial gradients, a (exp -1), small compared to the Hubble radius, and they are described in terms of classical random fields that are fed by short wavelength quantum noise. Lattice Langevin calculations are given for a toy model with a scalar field interacting with an exponential potential where one can obtain exact analytic solutions of the Fokker-Planck equation. For single scalar field models that are consistent with current microwave background fluctuations, the fluctuations are Gaussian. However, for scales much larger than our observable Universe, one expects large metric fluctuations that are non-Gaussian. This example illuminates non-Gaussian models involving multiple scalar fields which are consistent with current microwave background limits.

Salopek, D. S.↗
NASA NTRS1990

A graphical language for reliability model generation

A graphical interface capability of the hybrid automated reliability predictor (HARP) is described. The graphics-oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault tree gates, including sequence dependency gates, or by a Markov chain. With this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the Graphical Kernel System (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing.

Howell, Sandra V.↗
NASA NTRS1991

Combined energy and pitch angle diffusion of pickup ions at Comet Halley

It is well known that cometary pickup ions, e.g., H2O(+), OH(+), O(+), CO(+), H(+), initially form a ring-beam distribution in the solar wind reference frame, which is highly unstable to the growth of MHD waves (such as ion-cyclotron waves). The low-frequency magnetic fluctuations (or waves), which were observed upstream of Comet Halley, cannot only pitch-angle-scatter the pickup ions so that the distribution becomes at least partially isotropized, but also stochastically accelerate the ions, resulting in the energetic ion populations observed in the vicinity of Comet Halley. Here, numerical solutions of the quasi-linear diffusion equation were used to investigate the cometary ion pickup process at Comet Halley. Both pitch angle and energy diffusion are taken into account. Many quasi-linear models of cometary pickup ions exist which involve one type of diffusion or the other but not both types at once. It is found that the pitch angle scattering occurs faster than the energy diffusion, as expected. Moreover, the results demonstrate that the distribution of accelerated energetic ions is more isotropic than that of ions which have just been picked up. In fact, the ion distribution function on the initial pickup shell is quite anisotropic, even close to the Comet-Halley bow shock.

Ye, Gang↗
NASA NTRS2017

Data Assimilation and Uncertainties in Early Solar Cycle Predictions

Stochastic nature of solar activity variations together with our limited knowledge of the dynamo mechanism and subsurface dynamics causes uncertainty in predictions of the solar cycle. For improving the physics-­‐based predictions we can take advantage of the mathematical data assimilation approach that allows us to take into account both, observational errors and model uncertainties, and provide estimates of the next solar cycle along with prediction uncertainties. In this study we use the Parker's migratory dynamo model together with the equation of magnetic helicity balance, which reproduces main properties of the sunspot cycles and allow us to minimize discrepancies between the observed global activity variations and the model solution. The test simulation runs show that a reliable prediction can be obtained for two phases of preceding solar cycle: 1) if the polar field reversals shortly after the solar maxima (strong toroidal field and weak poloidal field), and 2) during the solar minima (strongest poloidal and weak toroidal fields). The early estimate of Cycle 25 obtained by this method shows that this cycle will start in 2019 – 2020, reach the maximum in 2023 – 2024, and that the mean sunspot number at the maximum will be about 90 (for the v2.0 sunspot number series).

Data Assimilation↗
NASA NTRS1985

Study of non-thermal photon production under different scenarios in solar flares. 2: The Compton inverse and Bremsstrahlung models and fittings

Energy spectra of photons emitted from Bremsstrahlung (BR) of energetic electrons with matter, is obtained from the deconvolution of the electron energy spectra. It can be inferred that the scenario for the production of X-rays and gamma rays in solar flares may vary from event to event. However, it is possible in many cases to associated low energy events to impulsive acceleration, and the high energy phase of some events to stochastic acceleration. In both cases, flare particles seem to be strongly modulated by local energy losses. Electric field acceleration, associated to neutral current sheets is a suitable candidate for impulsive acceleration. Finally, that the predominant radiation process of this radiation is the inverse Compton effect due to the local flare photon field.

Perez-Peraza, J.↗
NASA NTRS2010

Solar Radiation Transport in the Cloudy Atmosphere: A 3D Perspective on Observations and Climate Impacts

The interplay of sunlight with clouds is a ubiquitous and often pleasant visual experience, but it conjures up major challenges for weather, climate, environmental science and beyond. Those engaged in the characterization of clouds (and the clear air nearby) by remote sensing methods are even more confronted. The problem comes, on the one hand, from the spatial complexity of real clouds and, on the other hand, from the dominance of multiple scattering in the radiation transport. The former ingredient contrasts sharply with the still popular representation of clouds as homogeneous plane-parallel slabs for the purposes of radiative transfer computations. In typical cloud scenes the opposite asymptotic transport regimes of diffusion and ballistic propagation coexist. We survey the three-dimensional (3D) atmospheric radiative transfer literature over the past 50 years and identify three concurrent and intertwining thrusts: first, how to assess the damage (bias) caused by 3D effects in the operational 1D radiative transfer models? Second, how to mitigate this damage? Finally, can we exploit 3D radiative transfer phenomena to innovate observation methods and technologies? We quickly realize that the smallest scale resolved computationally or observationally may be artificial but is nonetheless a key quantity that separates the 3D radiative transfer solutions into two broad and complementary classes: stochastic and deterministic. Both approaches draw on classic and contemporary statistical, mathematical and computational physics.

Davis, Anthony B.↗
NASA NTRS1985

Structure of nonevaporating sprays. I - Initial conditions and mean properties

Structure measurements were completed within the dilute portion of axisymmetric nonevaporating sprays. Measurements included: mean velocities, velocity fluctuations, and Reynolds stress of the gas phase; and mean velocities, fluctuating velocities, mass flux, and diameter distributions of the drop phase. The measurements were used to evaluate three typical methods of analyzing sprays: (1) a locally homogeneous flow (LHF) analysis, where slip between the phases is neglected; (2) a deterministic separated flow (DSF) analysis, where slip is considered but effects of drop interactions with turbulence are ignored; and (3) a stochastic separated flow (SSF) analysis, where effects of both slip and turbulence are considered using random-walk computations for drop motion. Measurements of initial conditions of both phases near the injector, mean gas-phase properties, and liquid flux distributions are described herein. Best agreement between predictions and measurements was obtained with the SSF model, which provided a reasonable representation of turbulent dispersion of drops. A companion paper presents additional measurements of drop continuous phase properties.

Solomon, A. S. P.↗
NASA NTRS1984

Tradeoff methods in multiobjective insensitive design of airplane control systems

The latest results of an ongoing study of computer-aided design of airplane control systems are given. Constrained minimization algorithms are used, with the design objectives in the constraint vector. The concept of Pareto optimiality is briefly reviewed. It is shown how an experienced designer can use it to find designs which are well-balanced in all objectives. Then the problem of finding designs which are insensitive to uncertainty in system parameters are discussed, introducing a probabilistic vector definition of sensitivity which is consistent with the deterministic Pareto optimal problem. Insensitivity is important in any practical design, but it is particularly important in the design of feedback control systems, since it is considered to be the most important distinctive property of feedback control. Methods of tradeoff between deterministic and stochastic-insensitive (SI) design are described, and tradeoff design results are presented for the example of the a Shuttle lateral stability augmentation system. This example is used because careful studies have been made of the uncertainty in Shuttle aerodynamics. Finally, since accurate statistics of uncertain parameters are usually not available, the effects of crude statistical models on SI designs are examined.

Schy, A. A.↗
NASA NTRS1991

Simulation of probabilistic wind loads and building analysis

Probabilistic wind loads likely to occur on a structure during its design life are predicted. Described here is a suitable multifactor interactive equation (MFIE) model and its use in the Composite Load Spectra (CLS) computer program to simulate the wind pressure cumulative distribution functions on four sides of a building. The simulated probabilistic wind pressure load was applied to a building frame, and cumulative distribution functions of sway displacements and reliability against overturning were obtained using NESSUS (Numerical Evaluation of Stochastic Structure Under Stress), a stochastic finite element computer code. The geometry of the building and the properties of building members were also considered as random in the NESSUS analysis. The uncertainties of wind pressure, building geometry, and member section property were qualified in terms of their respective sensitivities on the structural response.

Shah, Ashwin R.↗
NASA NTRS1992

Graphical workstation capability for reliability modeling

In addition to computational capabilities, software tools for estimating the reliability of fault-tolerant digital computer systems must also provide a means of interfacing with the user. Described here is the new graphical interface capability of the hybrid automated reliability predictor (HARP), a software package that implements advanced reliability modeling techniques. The graphics oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault-tree gates, including sequence-dependency gates, or by a Markov chain. By using this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain, which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the graphical kernal system (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing stages.

Bavuso, Salvatore J.↗
NASA NTRS2014

Anomalous Transport of High Energy Cosmic Rays in Galactic Superbubbles

High-energy cosmic rays may exhibit anomalous transport as they traverse and are accelerated by a collection of supernovae explosions in a galactic superbubble. Signatures of this anomalous transport can show up in the particles' evolution and their spectra. In a continuous-time-random- walk (CTRW) model assuming standard diffusive shock acceleration theory (DSA) for each shock encounter, and where the superbubble (an OB stars association) is idealized as a heterogeneous region of particle sources and sinks, acceleration and transport in the superbubble can be shown to be sub-diffusive. While the sub-diffusive transport can be attributed to the stochastic nature of the acceleration time according to DSA theory, the spectral break appears to be an artifact of transport in a finite medium. These CTRW simulations point to a new and intriguing phenomenon associated with the statistical nature of collective acceleration of high energy cosmic rays in galactic superbubbles.

Barghouty, Nasser F.↗