107 research outputs found

    The Martian climate and energy balance models with CO2/H2O atmospheres

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    The analysis begins with a seasonal energy balance model (EBM) for Mars. This is used to compute surface temperature versus x = sin(latitude) and time over the seasonal cycle. The core model also computes the evolving boundaries of the CO2 icecaps, net sublimational/condensation rates, and the resulting seasonal pressure wave. Model results are compared with surface temperature and pressure history data at Viking lander sites, indicating fairly good agreement when meridional heat transport is represented by a thermal diffusion coefficient D approx. 0.015 W/sq. m/K. Condensational wind distributions are also computed. An analytic model of Martian wind circulation is then proposed, as an extension of the EMB, which incorporates vertical wind profiles containing an x-dependent function evaluated by substitution in the equation defining the diffusion coefficient. This leads to a parameterization of D(x) and of the meridional circulation which recovers the high surface winds predicted by dynamic Mars atmosphere models (approx. 10 m/sec). Peak diffusion coefficients, D approx. 0.6 w/sq m/K, are found over strong Hadley zones - some 40 times larger than those of high-latitude baroclinic eddies. When the wind parameterization is used to find streamline patterns over Martian seasons, the resulting picture shows overturning hemispheric Hadley cells crossing the equator during solstices, and attaining peak intensities during the south summer dust storm season, while condensational winds are most important near the polar caps

    Improving Pattern Recognition and Neural Network Algorithms With Applications to Solar Panel Energy Optimization

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    Artificial Intelligence is a big part of automation and with today\u27s technological advances, artificial intelligence has taken great strides towards positioning itself as the technology of the future to control, enhance and perfect automation. Computer vision includes pattern recognition and classification and machine learning. Computer vision is at the core of decision making and it is a vast and fruitful branch of artificial intelligence. In this work, we expose novel algorithms and techniques built upon existing technologies to improve pattern recognition and neural network training, initially motivated by a multidisciplinary effort to build a robot that helps maintain and optimize solar panel energy production. Our contributions detail an improved non-linear pre-processing technique to enhance poorly illuminated images based on modifications to the standard histogram equalization for an image. While the original motivation was to improve nocturnal navigation, the results have applications in surveillance, search and rescue, medical imaging enhancing, and many others. We created a vision system for precise camera distance positioning motivated to correctly locate the robot for capture of solar panel images for classification. The classification algorithm marks solar panels as clean or dirty for later processing. Our algorithm extends past image classification and, based on historical and experimental data, it identifies the optimal moment in which to perform maintenance on marked solar panels as to minimize the energy and profit loss. In order to improve upon the classification algorithm, we delved into feedforward neural networks because of their recent advancements, proven universal approximation and classification capabilities, and excellent recognition rates. We explore state-of-the-art neural network training techniques offering pointers and insights, culminating on the implementation of a complete library with support for modern deep learning architectures, multilayer percepterons and convolutional neural networks. Our research with neural networks has encountered a great deal of difficulties regarding hyperparameter estimation for good training convergence rate and accuracy. Most hyperparameters, including architecture, learning rate, regularization, trainable parameters (or weights) initialization, and so on, are chosen via a trial and error process with some educated guesses. However, we developed the first quantitative method to compare weight initialization strategies, a critical hyperparameter choice during training, to estimate among a group of candidate strategies which would make the network converge to the highest classification accuracy faster with high probability. Our method provides a quick, objective measure to compare initialization strategies to select the best possible among them beforehand without having to complete multiple training sessions for each candidate strategy to compare final results

    Study of flutter related computational procedures for minimum weight structural sizing of advanced aircraft

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    Results of a study of the development of flutter modules applicable to automated structural design of advanced aircraft configurations, such as a supersonic transport, are presented. Automated structural design is restricted to automated sizing of the elements of a given structural model. It includes a flutter optimization procedure; i.e., a procedure for arriving at a structure with minimum mass for satisfying flutter constraints. Methods of solving the flutter equation and computing the generalized aerodynamic force coefficients in the repetitive analysis environment of a flutter optimization procedure are studied, and recommended approaches are presented. Five approaches to flutter optimization are explained in detail and compared. An approach to flutter optimization incorporating some of the methods discussed is presented. Problems related to flutter optimization in a realistic design environment are discussed and an integrated approach to the entire flutter task is presented. Recommendations for further investigations are made. Results of numerical evaluations, applying the five methods of flutter optimization to the same design task, are presented

    Research Reports: 1983 NASA/ASEE Summer Faculty Fellowship Program

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    Thirty-five technical reports contain results of investigations in information and electronic systems; materials and processing; systems dynamics; structures and propulsion; and space sciences. Ecology at KSC, satellite de-spin, and the X-ray source monitor were also studied

    REXOR 2 rotorcraft simulation model. Volume 1: Engineering documentation

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    A rotorcraft nonlinear simulation called REXOR II, divided into three volumes, is described. The first volume is a development of rotorcraft mechanics and aerodynamics. The second is a development and explanation of the computer code required to implement the equations of motion. The third volume is a user's manual, and contains a description of code input/output as well as operating instructions

    Investigation of juncture stress fields in multicellular shell structures

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    Discontinuity stress fields in thin elastic multicellular shell structures subject to inertial, pressure, and thermal loadin

    Investigation of a bearingless helicopter rotor concept having a composite primary structure

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    Experimental and analytical investigations were conducted to evaluate a bearingless helicopter rotor concept (CBR) made possible through the use of the specialized nonisotropic properties of composite materials. The investigation was focused on four principal areas which were expected to answer important questions regarding the feasibility of this concept. First, an examination of material properties was made to establish moduli, ultimate strength, and fatigue characteristics of unidirectional graphite/epoxy, the composite material selected for this application. The results confirmed the high bending modulus and strengths and low shear modulus expected of this material, and demonstrated fatigue properties in torsion which make this material ideally suited for the CBR application. Second, a dynamically scaled model was fabricated and tested in the low speed wind tunnel to explore the aeroelastic characteristics of the CBR and to explore various concepts relative to the method of blade pitch control. Two basic control configurations were tested, one in which pitch flap coupling could occur and another which eliminated all coupling. It was found that both systems could be operated successfully at simulated speeds of 180 knots; however, the configuration with coupling present revealed a potential for undesirable aeroelastic response. The uncoupled configuration behaved generally as a conventional hingeless rotor and was stable for all conditions tested

    Development of solution techniques for nonlinear structural analysis

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    Nonlinear structural solution methods in the current research literature are classified according to order of the solution scheme, and it is shown that the analytical tools for these methods are uniformly derivable by perturbation techniques. A new perturbation formulation is developed for treating an arbitrary nonlinear material, in terms of a finite-difference generated stress-strain expansion. Nonlinear geometric effects are included in an explicit manner by appropriate definition of an applicable strain tensor. A new finite-element pilot computer program PANES (Program for Analysis of Nonlinear Equilibrium and Stability) is presented for treatment of problems involving material and geometric nonlinearities, as well as certain forms on nonconservative loading
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