Research achievements in optimization techniques
Optimization techniques for orbital transfer, and spacecraft trajectories
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Optimization techniques for orbital transfer, and spacecraft trajectories
Optimization techniques in computing minimum-fuel multistage trajectories for space missions
Major optimization techniques of compilers are described and grouped into three categories: machine dependent, architecture dependent, and architecture independent. Machine-dependent optimizations tend to be local and are performed upon short spans of generated code by using particular properties of an instruction set to reduce the time or space required by a program. Architecture-dependent optimizations are global and are performed while generating code. These optimizations consider the structure of a computer, but not its detailed instruction set. Architecture independent optimizations are also global but are based on analysis of the program flow graph and the dependencies among statements of source program. A conceptual review of a universal optimizer that performs architecture-independent optimizations at source-code level is also presented.
Numerical optimization techniques are playing an increasing role in curve and surface construction. Often difficult problems in curve and surface construction, especially when some aspect of shape control is involved, can be phrased as a constrained optimization problem. Four such classes of problems are explored: parametric curve fitting with non-linear shape constraints; explicit surface fitting with linear shape constraints; surface fitting to scattered data giving rise to ill-posed problems; finally, variable knot problems. In each of these problems there is a nonlinear aspect: either the shape of the curve or surface is important for manufacturing or engineering reasons or the shape affects the convergence of numerical algorithms which use the curve or surface or the placement of knots affects the accuracy of the fits. In all cases the class of functions used is that of parametric spline curves and tensor or direct product spline surfaces. The reason for choosing this class is that splines provide flexible models that are easily evaluated and stored. Furthermore, the B-spline representation of splines leads to convenient expressions for shape control over regions.
Nonlinear optimization techniques in dynamic programming and solution of ordinary nonlinear differential equations by Runge-Kutta method
Adaptive random search computing techniques and optimized solutions for unimodal function problems
Polynomial optimization techniques for activity scheduling (optimization based prototype scheduler) are presented in the form of the viewgraphs. The following subject areas are covered: agenda; need and viability of polynomial time techniques for SNC (Space Network Control); an intrinsic characteristic of SN scheduling problem; expected characteristics of the schedule; optimization based scheduling approach; single resource algorithms; decomposition of multiple resource problems; prototype capabilities, characteristics, and test results; computational characteristics; some features of prototyped algorithms; and some related GSFC references.
Optimization techniques for control of fuel valve systems for air breathing jet engines and 40-60 inlet control problems
Iterative optimization techniques for circuit design
Optimization techniques applied to passive measures for in-orbit spacecraft survivability, is a six-month study, designed to evaluate the effectiveness of the geometric programming (GP) optimization technique in determining the optimal design of a meteoroid and space debris protection system for the Space Station Core Module configuration. Geometric Programming was found to be superior to other methods in that it provided maximum protection from impact problems at the lowest weight and cost.
The work that has been done in the last decade or so in the application of optimization techniques to vehicle design is discussed. Much of the work reviewed deals with the design of body or suspension (chassis) components for reduced weight. Also reviewed are studies dealing with system optimization problems for improved functional performance, such as ride or handling. In reviewing the work on the use of optimization techniques, one notes the transition from the rare mention of the methods in the 70's to an increased effort in the early 80's. Efficient and convenient optimization and analysis tools still need to be developed so that they can be regularly applied in the early design stage of the vehicle development cycle to be most effective. Based on the reported applications, an attempt is made to assess the potential for automotive application of optimization techniques. The major issue involved remains the creation of quantifiable means of analysis to be used in vehicle design. The conventional process of vehicle design still contains much experience-based input because it has not yet proven possible to quantify all important constraints. This restraint on the part of the analysis will continue to be a major limiting factor in application of optimization to vehicle design.
This viewgraph presentation gives an overview of global optimization techniques for fluid flow and propulsion devices. Details are given on the need, characteristics, and techniques for global optimization. The techniques include response surface methodology (RSM), neural networks and back-propagation neural networks, design of experiments, face centered composite design (FCCD), orthogonal arrays, outlier analysis, and design optimization.
A multidisciplinary optimization procedure is developed for the design of high speed proprotors. The objectives are to simultaneously maximize the propulsive efficiency in high speed cruise without sacrificing the rotor figure of merit in hover. Since the problem involves multiple design objectives, multiobjective function formulation techniques are used. A derailed two-celled isotropic box beam is used to model the load carrying member within the rotor blade. Constraints are imposed on rotor blade aeroelastic stability in cruise, the first natural frequency in hover and total blade weight. Both aerodynamic and structural design variables are used. The results obtained using both techniques are compared to the reference rotor and show significant aerodynamic performance improvements without sacrificing dynamic and aeroelastic stability requirements.
The papers collected in this volume were presented at the Symposium on Mathematical Optimization Techniques held in the Santa Monica Civic Auditorium, Santa Monica, California, on October 18-20, 1960. The objective of the symposium was to bring together, for the purpose of mutual education, mathematicians, scientists, and engineers interested in modern optimization techniques. Some 250 persons attended. The techniques discussed included recent developments in linear, integer, convex, and dynamic programming as well as the variational processes surrounding optimal guidance, flight trajectories, statistical decisions, structural configurations, and adaptive control systems. The symposium was sponsored jointly by the University of California, with assistance from the National Science Foundation, the Office of Naval Research, the National Aeronautics and Space Administration, and The RAND Corporation, through Air Force Project RAND.
This paper presents the instrument offset optimization technique for the Doppler Aerosol Wind Lidar (DAWN) profiling algorithm at NASA Langley Research Center (LaRC). The 2 um Doppler wind Lidar system at LaRC has a long history of research development and airborne campaigns. The core of the wind Lidar data processing is Airborne Wind Profiling Algorithm for Doppler Wind Lidar (APOLO), which was developed at LaRC. The extraction of wind parameters from the airborne Doppler wind Lidar data is challenging due to many factors such as the speed of aircraft, and the errors in instrument installation and calibration. It is unavoidable to prevent the adverse impact of calibration error and instrument installation offset on the performance of wind parameter estimation in the algorithm. Due to the unsteady environment where the data are collected, even a small offset will result in nonsensical results in the parameter estimation process. A brief introduction of APOLO and the overview of the optimization techniques are presented in this paper.
Results of the investigation of formal nonlinear programming-based numerical optimization techniques of helicopter airframe vibration reduction are summarized. The objective and constraint function and the sensitivity expressions used in the formulation of airframe vibration optimization problems are presented and discussed. Implementation of a new computational procedure based on MSC/NASTRAN and CONMIN in a computer program system called DYNOPT for optimizing airframes subject to strength, frequency, dynamic response, and dynamic stress constraints is described. An optimization methodology is proposed which is thought to provide a new way of applying formal optimization techniques during the various phases of the airframe design process. Numerical results obtained from the application of the DYNOPT optimization code to a helicopter airframe are discussed.
Application of numerical optimization techniques to automated conceptual aircraft design is examined. These methods are shown to be a general and efficient way to obtain quantitative information for evaluating alternative new vehicle projects. Fully automated design is compared with traditional point design methods and time and resource requirements for automated design are given. The NASA Ames Research Center aircraft synthesis program (ACSYNT) is described with special attention to calculation of the weight of a vehicle to fly a specified mission. The ACSYNT procedures for automatically obtaining sensitivity of the design (aircraft weight, performance and cost) to various vehicle, mission, and material technology parameters are presented. Examples are used to demonstrate the efficient application of these techniques.