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At least 631 records · Page 35

Pulsatile instability in rapid directional solidification: Strongly-nonlinear analysis

In models of rapid directional solidification, non-equilibrium interfacial conditions are employed. As a result, there is an oscillatory mode of instability, as well as the steady cellular mode, found in the equilibrium model of Mullins and Sekerka. When the temperature field is decoupled from the problem, the preferred wave number for the oscillatory mode is zero, and the interface pulsates in time while remaining spatially uniform. Results from multiple scale analyses in the two limiting cases of the parameters are reported. In these limits, it is found that the instability is a bifurcation to relaxation oscillations; these nonlinear oscillations may be related to the observed microstructure that results from rapid solidification processes such as laser surface remelting.

Braun, Richard J.↗

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height anomalies. Because of its potential for large scale synoptic coverage of the deep ocean, acoustic travel time data should be a natural complement to satellite altimetry. Satellite data give us vertical integrals associated with thermodynamic and dynamic processes.

Miller, Robert N.↗

Test and Analyses of a Composite Multi-Bay Fuselage Panel Under Uni-Axial Compression

A composite panel containing three stringers and two frames cut from a vacuum-assisted resin transfer molded (VaRTM) stitched fuselage article was tested under uni-axial compression loading. The stringers and frames divided the panel into six bays with two columns of three bays each along the compressive loading direction. The two frames were supported at the ends with pins to restrict the out-of-plane translation. The free edges of the panel were constrained by knife-edges. The panel was modeled with shell finite elements and analyzed with ABAQUS nonlinear solver. The nonlinear predictions were compared with the test results in out-of-plane displacements, back-to-back surface strains on stringer flanges and back-to-back surface strains at the centers of the skin-bays. The analysis predictions were in good agreement with the test data up to post-buckling.

Li, Jian↗

Optimized Wavelength-Tuned Nonlinear Frequency Conversion Using a Liquid Crystal Clad Waveguide

An optimized wavelength-tuned nonlinear frequency conversion process using a liquid crystal clad waveguide. The process includes implanting ions on a top surface of a lithium niobate crystal to form an ion implanted lithium niobate layer. The process also includes utilizing a tunable refractive index of a liquid crystal to rapidly change an effective index of the lithium niobate crystal.

Stephen, Mark A.↗

Recommended Crew Systems Capabilities for a 30 to 90 Day Four-Crew Lunar Surface Mission

For any given surface mission duration, there exists a set of surface capabilities necessary to sustain a four-person crew for the length of time the crew is on the surface. Identifying these capabilities is important to mission planners and spacecraft design engineers responsible for lunar surface habitation elements, who need to know which systems and capabilities must be prioritized for the vehicles they are designing. However, simply identifying the surface capabilities does not necessarily equal a viable surface configuration. These capabilities may or may not satisfy stakeholder expectations or even permit completion of mission objectives. Lunar lander cargo mass constraints are a powerful forcing function that requires significant efforts to reduce the mass of all surface elements, including those supporting crew habitation. The required capabilities do increase as a function of mission duration, but it is a nonlinear growth. There are key points in mission duration, beyond which certain additional capabilities are needed. This forms bands of capability between each point. Within a given band, the same functional capabilities are needed, and the only scaling is that associated with daily consumables. The next higher band requires additional capabilities. This paper will focus on those capabilities needed for missions of 30-90 days. It should be noted that there are some uncertainties interpreting NASA requirements that require capabilities after a certain number of days, as typically this refers to number of days in space, not number of days on the lunar surface. Depending on transportation architecture, the number of days between Earth launch and lunar surface landing may vary, therefore impacting when certain required capabilities are implemented. However, activities to prepare humans for missions to Mars and commercial interest in lunar development may drive progressive increases in surface duration. Missions up to 30 days are expected to follow the initial 6.5-day surface missions and there may be commercial interest in extending to even greater durations. This paper will examine the potential case of a 30-90-day surface mission duration with respect to the systems necessary to support crew living and working on the lunar surface.

Habitat↗

Nonlinear oscillations of inviscid free drops

The present analysis of free liquid drops' inviscid oscillations proceeds through solution of Bernoulli's equation to obtain the free surface shape and of Laplace's equation for the velocity potential field. Results thus obtained encompass drop-shape sequences, pressure distributions, particle paths, and the temporal evolution of kinetic and surface energies; accuracy is verified by the near-constant drop volume and total energy, as well as the diminutiveness of mass and momentum fluxes across drop surfaces. Further insight into the nature of oscillations is provided by Fourier power spectrum analyses of mode interactions and frequency shifts.

Patzek, T. W.↗

Stiffness and Damping Coefficient Estimation of Compliant Surface Gas Bearings for Oil-Free Turbomachinery

Foil gas bearings are a key technology in many commercial and emerging oilfree turbomachinery systems. These bearings are nonlinear and have been difficult to analytically model in terms of performance characteristics such as load capacity, power loss, stiffness, and damping. Previous investigations led to an empirically derived method to estimate load capacity. This method has been a valuable tool in system development. The current work extends this tool concept to include rules for stiffness and damping coefficient estimation. It is expected that these rules will further accelerate the development and deployment of advanced oil-free machines operating on foil gas bearings.

Della-Corte, Christopher↗

Fluid management technology: Liquid slosh dynamics and control

Flight experiments were defined for the Cryogenic On-Orbit Liquid Depot Storage, Acquisition and Transfer Satellite (COLD-SAT) test bed satellite and the Shuttle middeck to help establish the influence of the gravitational environment on liquid slosh dynamics and control. Several analytical and experimental studies were also conducted to support the experiments and to help understand the anticipated results. Both FLOW-3D and NASA-VOF3D computer codes were utilized to simulate low Bond number, small amplitude sloshing, for which the motions are dominated by surface forces; it was found that neither code provided a satisfactory simulation. Thus, a new analysis of low Bond number sloshing was formulated, using an integral minimization technique that will allow the assumptions made about surface physics phenomena to be modified easily when better knowledge becomes available from flight experiments. Several examples were computed by the innovative use of a finite-element structural code. An existing spherical-pendulum analogy of nonlinear, rotary sloshing was also modified for easier use and extended to low-gravity conditions. Laboratory experiments were conducted to determine the requirements for liquid-vapor interface sensors as a method of resolving liquid surface motions in flight experiments. The feasibility of measuring the small slosh forces anticipated in flight experiments was also investigated.

Dodge, Franklin T.↗

Structured Covariance Gaussian Networks for Orion Crew Module Aerodynamic Uncertainty Quantification

In this paper we propose a new approach for nonlinear regression and uncertainty quantification. The method is based on a pair of neural networks which parameterize mean and dense covariance functions of a multivariate Gaussian process, trained together to maximize the log-likelihood of observing the given data. The covariance matrix is made positive definite at every input by construction. We also propose a sampling approach that produces viable surrogate function realizations from the Gaussian process. We call the proposed model a Structured Covariance Gaussian Network (SCGN). We illustrate the use of SCGNs for learning an aerodynamic response surface with built-in uncertainty for the Orion crew module. We find that SCGN provides an efficient and systematic way to learn nonlinear functional relationships and dense covariances. We compare results to a baseline Gaussian process regressor and observe that the SCGN provides comparable uncertainty descriptions with improved scalability to dataset size. The sample functions generated by SCGN are fast to evaluate online and are therefore convenient for use in trajectory simulations. These results suggest that SCGN may be a viable computational method for aerodynamic uncertainty quantification.

machine learning↗

Structured Covariance Gaussian Networks for Orion Crew Module Aerodynamic Uncertainty Quantification

In this paper we propose a new approach for nonlinear regression and uncertainty quantification. The method is based on a pair of neural networks which parameterize mean and dense covariance functions of a multivariate Gaussian process, trained together to maximize the log-likelihood of observing the given data. The covariance matrix is made positive definite at every input by construction. We also propose a sampling approach that produces viable surrogate function realizations from the Gaussian process. We call the proposed model a Structured Covariance Gaussian Network (SCGN). We illustrate the use of SCGNs for learning an aerodynamic response surface with built-in uncertainty for the Orion crew module. We find that SCGN provides an efficient and systematic way to learn nonlinear functional relationships and dense covariances. We compare results to a baseline Gaussian process regressor and observe that the SCGN provides comparable uncertainty descriptions with improved scalability to dataset size. The sample functions generated by SCGN are fast to evaluate online and are therefore convenient for use in trajectory simulations. These results suggest that SCGN may be a viable computational method for aerodynamic uncertainty quantification.

machine learning↗

Retrieval of Surface Snow Grain Size and Melt Water from AVIRIS Spectra

The Earth's energy balance and hydrology are affected by the distribution and characteristics of snow cover on the surface. Snow grain size and snow melt influence surface albedo and hydrology. A model of snow reflectance that depends on both grain size and surface melt water was developed to derive these parameters from remote spectral measurements. This reflectance model is based on a discrete ordinate radiative transfer approach that uses Mie calculations of snow optical properties, which are based on the complex refractive index of ice and water. This snow model was linked to an atmospheric radiative transfer code and a nonlinear least squares fitting algorithm. The resulting combined algorithm was applied to an AVIRIS snow data set acquired over Mammoth Mountain, California. Maps of grain size and surface snow melt were generated that are consistent with the expected ranges and distributions for conditions at the site.

Green Robert O.↗

Transmission Measurement of the Third-Order Susceptibility of Gold

Gold nanoparticle composites are known to display large optical nonlinearities. In order to assess the validity of generalized effective medium theories (EMT's) for describing the linear and nonlinear optical properties of metal nanoparticle composites, knowledge of the linear and nonlinear susceptibilities of the constituent materials is a prerequisite. In this study the inherent nonlinearity of the metal is measured directly (rather than deduced from a suitable EMT) using a very thin gold film. Specifically, we have used the z-scan technique at a wavelength near the transmission window of bulk gold to measure the third-order susceptibility of a continuous thin gold film deposited on a quartz substrate surface-modified with a self-assembled monolayer to promote adhesion and uniformity without affecting the optical properties. We compare our results with predictions which ascribe the nonlinear response to a Fermi-smearing mechanism. Further, we note that the sign of the nonlinear susceptibility is reversed from that of gold nanoparticle composites.

Smith, David D.↗

Development of a non-linear simulation for generic hypersonic vehicles - ASUHS1

A nonlinear simulation is developed to model the longitudinal motion of a vehicle in hypersonic flight. The equations of motion pertinent to this study are presented. Analytic expressions for the aerodynamic forces acting on a hypersonic vehicle which were obtained from Newtonian Impact Theory are further developed. The control surface forces are further examined to incorporate vehicle elastic motion. The purpose is to establish feasible equations of motion which combine rigid body, elastic, and aeropropulsive dynamics for use in nonlinear simulations. The software package SIMULINK is used to implement the simulation. Also discussed are issues needing additional attention and potential problems associated with the implementation (with proposed solutions).

Salas, Juan↗

Theoretical modelling of the fine structures in sunspots

Until a decade ago most solar physicists thought of a sunspot as the upper end of a giant flux tube floating vertically. The existence of umbral dots and penumbral grains has been known for several decades. On the basis of available observations, they seem to be regions of photospheric intensity with upflowing gas motion and magnetic fields much weaker than in the surrounding sunspot surface. It has also been suggested that the differences in the appearances of umbral dots and granular cells are caused by the highly nonlinear nature of the convection problem in the presense of strong magnetic fields. The main ideas are presented here without any equations. It can be shown that a pocket of field free gas surrounded by a vertical magnetic field in the presence of gravity takes up the shape of a tapering column ending at a vertex at the top. Some convection is expected to take place in the trapped field free gas, whereas the magnetic field around it makes those regions stable against convection. Eventually the apex of the tapering column reaches the photospheric surface where the bulging of the magnetic field makes the field no longer able to close on the field free gas and trap it underneath.

Choudhuri, Arnab Rai↗

Mesoscale lake-effect snowstorms in the vicinity of Lake Michigan - Linear theory and numerical simulations

Mesoscale lake-effect snowstorms in the vicinity of Lake Michigan are studied by a linear steady-state analytic model and a nonlinear time-dependent numerical model with parameterized subgrid-scale physics. The solutions of the linear model show that the orientation of the mean wind field to the surface heating pattern is crucial to the shapes of the disturbances. The results indicate that the relative warmth of the lake surface can induce three updraft centers under a westerly wind, two updraft centers/bands under a northwesterly wind, and a convergence band under a northerly wind. Such convergences are caused by the interaction between the mean wind and the local circulations forced by the curved thermal contrasts. The numerical results from the nonlinear model not only produce convergence patterns very similar to those found in the linear theory and in other numerical studies, but also capture the transient property in some of the lake-induced disturbances. All of these results are qualitatively confirmed by satellite images.

Hsu, Hsiao-Ming↗

Quantum sensing of paramagnetic analytes by nanodiamonds in levitated microdroplets and aqueous solutions

Nanodiamonds (ND) hosting negatively charged nitrogen-vacancy (NV-) color centers have received attention for applications in magnetic field, electric field, chemical, and bio-sensing. The versatility of these probes is their excellent room-temperature optical and spin properties, along with their small size, functionalized surfaces and resistance to bleaching, making them ideal as nanoscopic sensors in picoliter volumes (e.g. single cells, but also microcompartments and aerosols). For quantitative ND-NV- sensing of paramagnetic analytes in such contexts, however, there remains an incomplete understanding of how factors related to the aqueous phase environment control detection efficiency. To address this, optically detected magnetic resonance (ODMR) is measured in bulk macroscale solutions and single levitated microdroplets as a function of Gd+3 concentration (340 nM to 1.5 mM), nanodiamond size, pH, competitor ions, and ligands. The ODMR response to [Gd+3] is found to be nonlinear, and pH, ND and sample volume dependent; indicating the detection of Gd+3 requires efficient adsorption of the analyte to the diamond surface. Langmuir adsorption isotherms embedded in a quantitative photophysical model links the ODMR response to adsorption thermodynamics of Gd+3. The equilibrium constant for Gd+3 adsorption to a carboxylated ND surface is determined to be (1 ± 0.5) x 105 M-1 corresponding to a free energy of adsorption of (-28 ± 1) kJ mol-1. These results provide general insight into how complex aqueous and microscale environments impact nanodiamond based quantum sensing modalities, and portend their application as quantitative chemical sensors in microenvironments.

Brown, Emily K↗