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At least 235 records · Page 13

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗

On Heatshield Shapes for Mars Entry Capsules

The 70deg sphere-cone - the standard geometry for all US Mars entry missions - is thoroughly examined via flow field simulations at a select few peak heating points along candidate flight trajectories. Emphasis is placed on turbulent heating based on the Baldwin- Lomax turbulence model. It is shown that increased leeward turbulent heating for a 70 sphere-cone flying at angle of attack is primarily due to the discontinuity in curvature between the spherical nose cap and the conical frustum - the attachment of the sonic line at this sphere-cone junction leads to a supersonic edge Mach number over the leeward acreage. In an attempt to mitigate this problem of elevated turbulent heating, alternate geometries, without any curvature discontinuities in the acreage, are developed. Two approaches, one based on nonlinear optimization with constraints, and one based on the use of non-uniform rational B-splines, are considered. All configurations examined remain axisymmetric. The aerothermal performance of alternate geometries is shown to be superior to that of the 70 sphere-cone.

Prabhu, DInesh K.↗

Channel Measurements for Switching Strategies in Hybrid RF/Optical Communications

Free space optical (FSO) communication links increase data rate, reduce size and power, and increase security. These criteria are particularly important in space communication. Increasing mission complexity and crowding of lower frequency bands is driving the need for optical communications. This makes FSO communication technology extremely attractive, and there is significant ongoing work towards the development of FSO transceivers, ground stations, and relays. Notable projects include the Laser Communications Relay Demonstrator (LCRD), Integrated LCRD Low-Earth Orbit User Modem and Amplifier Terminal (ILLUMA-T), and CubeSat Laser Infrared Crosslink (CLICK) CubeSats. These technologies will eventually operate in unison with existing Radio Frequency (RF) systems, but there is little experimental investigation of such hybrid networks. This paper presents some experimental underpinnings of switching strategies for hybrid RF/FSO systems in various attenuation conditions. A 170 m optical path was constructed in an enclosed test chamber where atmospheric conditions can be tightly controlled. The performance of a 1550 nm infrared FSO link was evaluated in this chamber under varying conditions of turbulence and jitter. The system will eventually be used to investigate switching criteria between the FSO and RF channels. Optimizing the use of RF/FSO communication links will allow data rate, size, power, and security improvements. Therefore, this research will help to mature the network architecture and improve the performance of communication networks to be used for LEO, GEO, Lagrange, Lunar missions and beyond.

Space Networks↗

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimality with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider unmodelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Patrick, Nicholas J. M.↗

AIVT: Inference of turbulent thermal convection from measured 3D velocity data by physics-informed Kolmogorov-Arnold networks

We propose the artificial intelligence velocimetry-thermometry (AIVT) method to reconstruct a continuous and differentiable representation of the temperature and velocity in turbulent convection from measured three-dimensional (3D) velocity data. AIVT is based on physics-informed Kolmogorov-Arnold networks and trained by optimizing a loss function that minimizes residuals of the velocity data, boundary conditions, and governing equations. We apply AIVT to a set of simultaneously measured 3D temperature and velocity data of Rayleigh-Bénard convection, obtained by combining particle image thermometry and Lagrangian particle tracking. This enables us to directly compare machine learning results to true volumetric, simultaneous temperature and velocity measurements. We demonstrate that AIVT can reconstruct and infer continuous, instantaneous velocity and temperature fields and their gradients from sparse experimental data at a high resolution, providing an additional approach for understanding thermal turbulence.

Science & Technology - Other Topics↗

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance x,ary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are (1) determining, what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major U.S. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimility with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider un-modelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Patrick, Nicholas J. M.↗

The influence of jet-grid turbulence on heat transfer from the stagnation region of a cylinder in crossflow

The effect of high-intensity turbulence on heat transfer from the stagnation region of a circular cylinder in crossflow was studied. The work was motivated by the desire to be able to more fully understand and predict the heat transfer to the leading edge of a turbine airfoil. In order to achieve high levels of turbulence with a reasonable degree of isotropy and homogeneity, a jet-injection turbulence grid was used. The jet grid provided turbulence intensities of 10 to 12 percent, measured at the test cylinder location, for downstream blowing with the blowing rate adjusted to an optimal value for flow uniformity. Heat transfer augmentation above the zeroturbulence case ranged from 37 to 53 percent for the test cylinder behind the jet grid for a cylinder Reynolds number range of 48,000 to 180,000, respectively. The level of heat transfer augmentation was found to be fairly uniform with respect to circumferential distance from the stagnation line. Stagnation point heat transfer results (expressed in terms of the Frossling number) were found to be somewhat low with respect to previous studies, when compared on the basis of equal values of the parameter Tu Re(1/2), indicating an additional Reynolds number effect as observed by previous investigators. Consequently, for a specified value of Tu Re(1/2), data obtained with a relatively high turbulence intensity will have a lower value of the Frossling number.

Obrien, J. E.↗

Semi-Supervised Learning of Lift Optimization of Multi-Element Three-Segment Variable Camber Airfoil

This chapter describes a new intelligent platform for learning optimal designs of morphing wings based on Variable Camber Continuous Trailing Edge Flaps (VCCTEF) in conjunction with a leading edge flap called the Variable Camber Krueger (VCK). The new platform consists of a Computational Fluid Dynamics (CFD) methodology coupled with a semi-supervised learning methodology. The CFD component of the intelligent platform comprises of a full Navier-Stokes solution capability (NASA OVERFLOW solver with Spalart-Allmaras turbulence model) that computes flow over a tri-element inboard NASA Generic Transport Model (GTM) wing section. Various VCCTEF/VCK settings and configurations were considered to explore optimal design for high-lift flight during take-off and landing. To determine globally optimal design of such a system, an extremely large set of CFD simulations is needed. This is not feasible to achieve in practice. To alleviate this problem, a recourse was taken to a semi-supervised learning (SSL) methodology, which is based on manifold regularization techniques. A reasonable space of CFD solutions was populated and then the SSL methodology was used to fit this manifold in its entirety, including the gaps in the manifold where there were no CFD solutions available. The SSL methodology in conjunction with an elastodynamic solver (FiDDLE) was demonstrated in an earlier study involving structural health monitoring. These CFD-SSL methodologies define the new intelligent platform that forms the basis for our search for optimal design of wings. Although the present platform can be used in various other design and operational problems in engineering, this chapter focuses on the high-lift study of the VCK-VCCTEF system. Top few candidate design configurations were identified by solving the CFD problem in a small subset of the design space. The SSL component was trained on the design space, and was then used in a predictive mode to populate a selected set of test points outside of the given design space. The new design test space thus populated was evaluated by using the CFD component by determining the error between the SSL predictions and the true (CFD) solutions, which was found to be small. This demonstrates the proposed CFD-SSL methodologies for isolating the best design of the VCK-VCCTEF system, and it holds promise for quantitatively identifying best designs of flight systems, in general.

Intelligent Systems↗

Optimization of structures undergoing harmonic or stochastic excitation

The optimal design was investigated of simple structures subjected to dynamic loads, with constraints on the structures' responses. Optimal designs were examined for one dimensional structures excited by harmonically oscillating loads, similar structures excited by white noise, and a wing in the presence of continuous atmospheric turbulence. The first has constraints on the maximum allowable stress while the last two place bounds on the probability of failure of the structure. Approximations were made to replace the time parameter with a frequency parameter. For the first problem, this involved the steady state response, and in the remaining cases, power spectral techniques were employed to find the root mean square values of the responses. Optimal solutions were found by using computer algorithms which combined finite elements methods with optimization techniques based on mathematical programming. It was found that the inertial loads for these dynamic problems result in optimal structures that are radically different from those obtained for structures loaded statically by forces of comparable magnitude.

Johnson, E. H.↗

Probabilistic Study of Fluid Structure Interaction

Probabilistic CFD design is needed because we are asked to do more with less. To cost effectively accomplish the design task, we need to formally quantify the effect of uncertainties (variables) in the design. Probabilistic design is one effective method to formally quantify the effect of uncertainties. Our objective is to establish a revolutionary new early design process, by developing non-deterministic physics-based probabilistic design tools, which will include all the life cycle processes. Breakthroughs will be sought in speed, accuracy, intelligence, and usability of the system. This paper is concerned with the usefulness of parametric optimization method coupled with a Navier-Stokes analysis code for the aero-thermodynamic design of turbomachinery combustor liner. The interconnection between the CFD code and NESSUS codes facilitated the coupling between the thermal profiles and structural design. We have developed new concepts for reducing the computational cost of unsteady, three-dimensional, compressible aerodynamic analyses for multistage turbomachinery flows. The flow was modeled by the three-dimensional Favre-Reynolds-averaged Navier-Stokes equations using the k-epsilon turbulence closure, which was integrated using an implicit third-order upwind solver. The methodology developed in this paper is expected to lead to the design optimization of turbomachinery blades.

Gorla, Rama S. R.↗

Performance analysis of a noncoherently combined large aperture optical heterodyne receiver

The performance of a noncoherently combined, multiple-mirror heterodyne receiver is analyzed. It is shown that in the absence of atmospheric turbulence, the performance of the noncoherently combined receiver is inferior to that of a monolithic, diffraction-limited receiver with equivalent aperture area. However, when atmospheric turbulence is taken into consideration, the efficiency of a monolithic aperture heterodyne receiver is limited by the phase coherence length of the atmosphere and generally does not improve with increasing aperture size. In constrast, the performance of a noncoherently combined system improves with an increasing number of receivers. Consequently, given a fixed collecting area, the noncoherently combined system can offer superior performance. The performance of the noncoherently combined heterodyne receiver is studied by analyzing the combining loss of the receiver SNR. It is shown that, given the collecting area, the performance of the combined receiver is optimized when the diameter of each of the individual receivers is on the order of the phase coherence length gamma sub 0 of the atmospheric turbulence.

Chen, C.-C.↗

Probabilistic Unsteady Aerodynamic Analysis

Probabilistic CFD design is needed because we are asked to do more with less. To cost effectively accomplish the design task, we need to formally quantify the effect of uncertainties (variables) in the design. Probabilistic design is one effective method to formally quantify the effect of uncertainties. Our objective is to establish a revolutionary new early design process, by developing non-deterministic physics-based probabilistic design tools, which will include all the life cycle processes. This work was concerned with the usefulness of parametric optimization method coupled with a Navier-Stokes analysis code for the aero-thermodynamic design of turbomachinery combustor liner. The interconnection between the CFD code and NESSUS codes will facilitate the coupling between the thermal profiles and structural design. We have developed new concepts for reducing the computational cost of unsteady, three-dimensional, compressible aerodynamic analyses for multistage turbomachinery flows. The flow was modeled by the three-dimensional Favre-Reynolds-averaged Navier-Stokes equations using the k-E turbulence closure, which was integrated using an implicit third-order upwind solver. The methodology developed in this work is expected to lead to the design optimization of turbomachinery blades.

Gorla, Rama S. R.↗

The incremental unknowns-a multilevel scheme for the simulation of turbulent channel flows

In numerical simulation of complex flows, it is important to identify different length scales of the flow and treat them differently. In this report, we introduce a new multilevel scheme for simulating turbulent channel flows. Two different versions of the scheme, namely the spectral and finite difference versions, are presented. The spectral version of the scheme is based on a spectral-Galerkin formulation which provides a natural decomposition of the flow into small and large wavelength parts, and which leads to linear systems that can be solved with quasi-optimal computational complexity. In the finite difference version, the Incremental Unknown (IU) is used to separate the length scales. Preliminary numerical results indicate that the scheme is well suited for turbulence computations and provides results which are comparable to that by Direct Numerical Simulation (DNS) but with significantly less CPU time.

Chen, M.↗

Development of a Comprehensive Two-Phase Flow Database for the Validation of NEK-2P

Three-dimensional (3-D) two-phase Computational Fluid Dynamics (CFD) codes are emerging as a powerful and potentially practical tool for applications in which detailed local flow information is needed. However, two-phase flow models and associated closure relations are not well established for CFD applications, which is partly due to the lack of high-quality validation data. The main objective of this work is to develop a comprehensive database of two-phase flows that can be used to validate two-phase CFD codes such as NEK-2P. In this project, four advanced local measurement systems, including Particle Image Velocimetry and Planar Laser-Induced Fluorescence (PIV-PLIF), high-speed imaging, x-ray densitometry, and multi-sensor conductivity probe are employed to measure the local two-phase flow parameters of both gas and liquid phases. By combining these techniques, the local void fraction, bubble velocity, interfacial area concentration, bubble frequency, liquid velocity, turbulence intensity, etc., in various two-phase flow regimes can be obtained. These local measurement techniques are first used in a 25.4 mm circular pipe test section. Seven air-water two-phase flow conditions spanning the bubbly, slug, churn-turbulent, and annular flow regimes are measured in this facility. The obtained database contains the radial profiles of both gas- and liquid-phase parameters at three axial locations along the test section. The second facility used in this work contains a 30 mm × 10 mm rectangular test section, in which three two-phase flow and two single-phase flow conditions are measured. Two-dimensional distributions of local two-phase flow parameters in the cross-sectional plane are measured in this facility at three axial locations as well. A facility featuring a 3×3 electrically heated rod bundle is also designed and being constructed in this project. This facility is specially designed for optical measurements and is expected to provide high-quality boiling data in the future. Preliminary analyses have been performed for the data taken in the 25.4 mm circular pipe. Both center-peaked and wall-peaked void fraction profiles have been observed in the data depending on the two-phase flow conditions and/or developing lengths. The 1-D drift-flux model was evaluated with the newly obtained datasets, in which both gas- and liquid-phases data were directly measured. The distribution parameter model has been optimized based on a new void-profile classification method proposed in this study. The optimized drift-flux model shows a significant improvement in predicting both gas velocity and void fraction. The measured liquid-phase turbulence was used to benchmark Sato’s turbulence model considering the bubble-induced shear stress for the three tested bubbly flows. The benchmark results showed good agreement between the PIV measurements and model predictions. In the bubbly flows tested that have low void fractions less than 3%, the effect of the bubble-induced turbulence was found not significant. However, the bubble-induced shear stress becomes important with the increase of the void fraction. The Conjugate Heat Transfer (CHT) model was developed and implemented in NEK-2P. This model allows the coupled simulation of the solid domain and two-phase fluid domain, allowing the specification of realistic boundary conditions. The CHT implementation was verified first with non-boiling simulations. The predicted temperatures in the fluid domain were shown to be identical in simulations with or without the CHT model. The CHT model was then validated through simulations of three Becker benchmark CHF tests performed under both Dryout (DO) and Departure from Nucleate Boiling (DNB) conditions. Reasonably good agreement was obtained between calculated wall temperatures and corresponding experimental data.

42 ENGINEERING↗

Measurement of helicon waves with phase contrast imaging on DIII-D – A theoretical feasibility study

A DIII-D high-beta H-mode discharge, with I p = 850 kA, B t = 2.1 T n e = 4 10 19 m –3 , has been designed to validate full wave modeling of helicon waves by optimizing the expected response of the Phase Contrast Imaging diagnostic. Helicon waves have been predicted to have high current drive efficiency off-axis without facing the accessibility issues of lower-hybrid waves. To test these predictions experimentally, DIII-D has recently commissioned a high-power helicon antenna. To confidently predict the behavior of helicon waves in future devices, measurements of their fundamental properties and validation against models will be essential. Phase contrast imaging (PCI) is an absolutely calibrated internal reference interferometer able to measure density fluctuations with radial wavenumbers k R between 1.5 cm –1 and 20 cm –1 . For helicon waves 2 cm –1 < k R < 10 cm –1 is expected, allowing PCI to measure their envelope and wavenumber spectrum. This makes PCI a powerful tool for the validation of state-of-the-art models, like the AORSA full wave code. AORSA is used to compute the density perturbations measured by the PCI with 2D calculations corresponding to 11 different toroidal mode numbers combined to resolve the trajectory of the helicon wave in 3D. This is necessary because the waves travel 120 degrees toroidally from the antenna to the PCI. Here, a cold plasma finite element model (CPFEM) [4] is used to predict propagation through the scrape-off layer. The result of the CPFEM model is connected to AORSA by creating an artificial Gaussian antenna on the last closed flux surface. PCI shows best results for waves with small vertical wavenumbers k z . Modeling the helicon waves for several past DIII-D experiments shows that k z is minimized if the intersection of the helicon and the PCI laser beams occurs in the midplane. For such an optimized scenario the predicted signal level is two orders of magnitude larger than the background density fluctuations arising from broadband turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical analysis of flow through scramjet engine inlets

A set of computer programs was developed to analyze flow through supersonic combustion ramjet (scramjet) inlets. These programs solve either the two or three dimensional Euler/Navier-Stokes equations in full conservation form by MacCormack's explicit or explicit-implicit method. An algebraic two-layer eddy viscosity model is used for turbulent flow calculations. The programs are operational in Control Data CYBER-200 series vector-processing computer system and were optimized to take maximum advantage of the vector processing capability of the system. Since their development, the programs were extensively verified and used to analyze a number of very complex inlet configurations. Results are presented from two-dimensional, quasi-three-dimensional, and three-dimensional analyses of the inlet flow field to illustrate the use of the program.

Kumar, Ajay↗

Supersonic Inlet with Pylons Set and Star-Shaped Forebody for Mixing, Combustion and Thrust Enhancement

Two new approaches are discussed in this paper for application in the Scramjet inlet of an air-breathing propulsion system: 1) In the first approach, the pylon set is installed in the rectangular inlet near the cowl front edge. For a quasi-axisymmetric inlet, a similar set is installed along the Star-shaped forebody axis. This set contains 3 - 4 airfoil-shaped strips or cross-sectional rings depending on the type of inlet. The inlets: rectangular, axisymmetric or star-shaped, are located at different distances from the forebody. Fuel injection takes place through these pylons, which provides for uniform mixing downstream. The locations, sizes and angles of these pylons are very important for efficient application. Optimal values of geometrical parameters were determined from multi-parametric NSE-based numerical simulations of the laminar and turbulent external/internal flows. These simulations have shown significant benefits for mixing, combustion and thrust of the proposed approach by comparison with traditional well-known designs. Experimental tests will be conducted soon at the NASA LaRC and Institute of Mechanics at Moscow State University. Preliminary estimates are very promising.

Gilinsky, M.↗

NASA Tech Briefs, March 2004

Topics covered include: 1) Advanced Signal Conditioners for Data-Acquisition Systems; 2) Downlink Data Multiplexer; 3) Viewing ISS Data in Real Time via the Internet; 4) Autonomous Environment-Monitoring Networks; 5) Readout of DSN Monitor Data; 6) Parallel-Processing Equalizers for Multi-Gbps Communications; 7) AIN-Based Packaging for SiC High-Temperature Electronics; 8) Software for Optimizing Quality Assurance of Other Software; 9) The TechSat 21 Autonomous Sciencecraft Experiment; 10) Software for Analyzing Laminar-to-Turbulent Flow Transitions; 11) Elastomer Filled With Single-Wall Carbon Nanotubes; 12) Modifying Ship Air-Wake Vortices for Aircraft Operations; 13) Strain-Gauge Measurement of Weight of Fluid in a Tank; 14) Advanced Docking System With Magnetic Initial Capture; 15) Blade-Pitch Control for Quieting Tilt-Rotor Aircraft; 16) Solar Array Panels With Dust-Removal Capability; 17) Aligning Arrays of Lenses and Single-Mode Optical Fibers; 18) Automatic Control of Arc Process for Making Carbon Nanotubes; 19) Curved-Focal-Plane Arrays Using Deformed-Membrane Photodetectors; 20) Role of Meteorology in Flights of a Solar-Powered Airplane; 21) Model of Mixing Layer With Multicomponent Evaporating Drops; 22) Solution-Assisted Optical Contacting; 23) Improved Discrete Approximation of Laplacian of Gaussian; 24) Utilizing Expert Knowledge in Estimating Future STS Costs; 25) Study of Rapid-Regression Liquefying Hybrid Rocket Fuels; and 26) More About the Phase-Synchronized Enhancement Method.

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