Aeronautical Engineering: A special bibliography with indexes, supplement 48

This special bibliography lists 291 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1974

Computing bounds for linear functionals of exact weak solutions to Poisson's equation

We present a method for Poisson’s equation that computes guaranteed upper and lower bounds for the values of piecewise-polynomial linear functional outputs of the exact weak solution of the infinite-dimensional continuum problem with piecewise-polynomial forcing. The method results from exploiting the Lagrangian saddle point property engendered by recasting the output problem as a constrained minimization problem. Localization is achieved by Lagrangian relaxation and the bounds are computed by appeal to a local dual problem. The proposed method computes approximate Lagrange multipliers using traditional finite element approximations to calculate a primal and an adjoint solution along with well known hybridization techniques to calculate interelement continuity multipliers. The computed bounds hold uniformly for any level of refinement, and in the asymptotic convergence regime of the finite element method, the bound gap decreases at twice the rate of the energy norm measure of the error in the finite element solution. Given a finite element solution and its output adjoint solution, the method can be used to provide a certificate of precision for the output with an asymptotic complexity that is linear in the number of elements in the finite element discretization. The elemental contributions to the bound gap are always positive and hence lend themselves to be used as adaptive indicators, as we demonstrate with a numerical example

New Coding/Decoding Techniques for Wireless Communication Systems

Wireless communication encompasses cellular telephony systems (mobile communication), wireless sensor networks, satellite communication systems and many other applications. Studies relevant to wireless communication deal with maintaining reliable and efficient exchange of information between the transmitter and receiver over a wireless channel. The most practical approach to facilitate reliable communication is using channel coding. In this dissertation we propose novel coding and decoding approaches for practical wireless systems. These approaches include variable-rate convolutional encoder, modified turbo decoder for local content in Single-Frequency Networks, and blind encoder parameter estimation for turbo codes. On the other hand, energy efficiency is major performance issue in wireless sensor networks. In this dissertation, we propose a novel hexagonal-tessellation based clustering and cluster-head selection scheme to maximize the lifetime of a wireless sensor network. For each proposed approach, the system performance evaluation is also provided. In this dissertation the reliability performance is expressed in terms of bit-error-rate (BER), and the energy efficiency is expressed in terms of network lifetime

Bio-signal based control in assistive robots: a survey

Recently, bio-signal based control has been gradually deployed in biomedical devices and assistive robots for improving the quality of life of disabled and elderly people, among which electromyography (EMG) and electroencephalography (EEG) bio-signals are being used widely. This paper reviews the deployment of these bio-signals in the state of art of control systems. The main aim of this paper is to describe the techniques used for (i) collecting EMG and EEG signals and diving these signals into segments (data acquisition and data segmentation stage), (ii) dividing the important data and removing redundant data from the EMG and EEG segments (feature extraction stage), and (iii) identifying categories from the relevant data obtained in the previous stage (classification stage). Furthermore, this paper presents a summary of applications controlled through these two bio-signals and some research challenges in the creation of these control systems. Finally, a brief conclusion is summarized

Applications of Finite Element Modeling for Mechanical and Mechatronic Systems

Modern engineering practice requires advanced numerical modeling because, among other things, it reduces the costs associated with prototyping or predicting the occurrence of potentially dangerous situations during operation in certain defined conditions. Thus far, different methods have been used to implement the real structure into the numerical version. The most popular uses have been variations of the finite element method (FEM). The aim of this Special Issue has been to familiarize the reader with the latest applications of the FEM for the modeling and analysis of diverse mechanical problems. Authors are encouraged to provide a concise description of the specific application or a potential application of the Special Issue

High-fidelity surrogate models for parametric shape design in microfluidics

Nowadays, the main computational bottleneck in computer-assisted industrial design procedures is the necessity of testing multiple parameter settings for the same problem. Material properties, boundary conditions or geometry may have a relevant influence on the solution of those problems. Consequently, the effects of changes in these quantities on the numerical solution need to be accurately estimated. That leads to significantly time-consuming multi-query procedures during decision-making processes. Microfluidics is one of the many fields affected by this issue, especially in the context of the design of robotic devices inspired by natural microswimmers. Reduced-order modelling procedures are commonly employed to reduce the computational burden of such parametric studies with multiple parameters. Moreover, highfidelity simulation techniques play a crucial role in the accurate approximation of the flow features appearing in complex geometries. This thesis proposes a coupled methodology based on the high-order hybridisable discontinuous Galerkin (HDG) method and the proper generalized decomposition (PGD) technique. Geometrically parametrised Stokes equations are solved exploiting the innovative HDG-PGD framework. On the one hand, the parameters describing the geometry of the domain act as extra-coordinates and PGD is employed to construct a separated approximation of the solution. On the other hand, HDG mixed formulation allows separating exactly the terms introduced by the parametric mapping into products of functions depending either on the spatial or on the parametric unknowns. Convergence results validate the methodology and more realistic test cases, inspired by microswimmer devices involving variable geometries, show the potential of the proposed HDG-PGD framework in parametric shape design. The PGD-based surrogate models are also utilised to construct separated response surfaces for the drag force. A comparison between response surfaces obtained through the apriori and the a posteriori PGD is exposed. A critical analysis of the two techniques is presented reporting advantages and drawbacks of both in terms of computational costs and accuracy.Actualmente, el principal obstáculo en los procesos de diseño industrial computarizado es la necesidad de examinar múltiples parámetros para el mismo problema. Las propiedades de los materiales, las condiciones de contorno o la geometría pueden tener una influencia relevante en la solución de esos problemas. Por lo tanto, es necesario estimar con precisión los efectos de las variaciones de esas cantidades en la solución numérica. Esto da origen a procedimientos de consultas múltiples que requieren considerable tiempo durante los procesos de toma de decisión. La microfluídica es uno de los varios campos afectados por esta problemática, especialmente en el contexto del diseño de dispositivos robóticos inspirados en los micronadadores naturales. Generalmente se recurre a procedimientos de reducción de orden de modelo para reducir la complejidad computacional de estos estudios paramétricos basados en múltiples parámetros. Además, los esquemas de alto orden son fundamentales para la aproximación precisa de las particularidades de los flujos que aparecen en las geometrías complejas. Esta tesis propone una metodología acoplada basada en el método de Galerkin discontinuo hibridizable de alto orden (HDG) y la técnica de descomposición propia generalizada (PGD). Las ecuaciones de Stokes geométricamente parametrizadas se resuelven empleando el innovador método HDG-PGD. Por un lado, los parámetros que describen la geometría del dominio actúan como extra-coordinadas y la PGD permite construir una aproximación separada de la solución. Por otra parte, la formulación mixta de HDG admite la separación exacta de los términos introducidos por la descripción paramétrica del dominio en productos de funciones dependientes de las incógnitas espaciales o paramétricas. Los resultados de convergencia validan la metodología y estudios de casos más realistas, inspirados en los dispositivos de micronatación con geometrías variables, muestran el potencial del marco propuesto de HDG-PGD en el diseño de formas parametrizadas. Los modelos reducidos basados en la PGD también permiten construir superficies de respuesta separadas para la fuerza de arrastre. Se realiza una comparación entre las superficies de respuesta obtenidas mediante la PGD a priori y a posteriori. Se exponen una análisis crítica de las dos técnicas reportando las ventajas y desventajas de ambas en términos de costes computacionales y precisión

Computing upper and lower bounds on linear functional outputs from linear coercive partial differential equations

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2003.Includes bibliographical references (p. 115-123).Uncertainty about the reliability of numerical approximations frequently undermines the utility of field simulations in the engineering design process: simulations are often not trusted because they lack reliable feedback on accuracy, or are more costly than needed because they are performed with greater fidelity than necessary in an attempt to bolster trust. In addition to devitalized confidence, numerical uncertainty often causes ambiguity about the source of any discrepancies when using simulation results in concert with experimental measurements. Can the discretization error account for the discrepancies, or is the underlying continuum model inadequate? This thesis presents a cost effective method for computing guaranteed upper and lower bounds on the values of linear functional outputs of the exact weak solutions to linear coercive partial differential equations with piecewise polynomial forcing posed on polygonal domains. The method results from exploiting the Lagrangian saddle point property engendered by recasting the output problem as a constrained minimization problem. Localization is achieved by Lagrangian relaxation and the bounds are computed by appeal to a local dual problem. The proposed method computes approximate Lagrange multipliers using traditional finite element discretizations to calculate a primal and an adjoint solution along with well known hybridization techniques to calculate interelement continuity multipliers. At the heart of the method lies a local dual problem by which we transform an infinite-dimensional minimization problem into a finite-dimensional feasibility problem.(cont.) The computed bounds hold uniformly for any level of refinement, and in the asymptotic convergence regime of the finite element method, the bound gap decreases at twice the rate of the H¹-norm measure of the error in the finite element solution. Given a finite element solution and its output adjoint solution, the method can be used to provide a certificate of precision for the output with an asymptotic complexity that is linear in the number of elements in the finite element discretization. The complete procedure computes approximate outputs to a given precision in polynomial time. Local information generated by the procedure can be used as an adaptive meshing indicator. We apply the method to Poisson's equation and the steady-state advection-diffusion-reaction equation.by Alexander M. Sauer-Budge.Ph.D