On the Optimization of Mixture Resolving Signal Processing Structures
Mixture resolving signal processing optimization with optimum linear detection operators and mixture resolving estimators
OPTIMIZATION↗
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Fabrication of Thermoplastic Composite Laminates Having Film Interleaves By Automated Fiber Placement
Experiments were carried out at the NASA Langley Research Center automated Fiber placement facility to determine an optimal process for the fabrication of composite materials having polymer film interleaves. A series of experiments was conducted to determine an optimal process for the composite prior to investigation of a process to fabricate laminates with polymer films. The results of the composite tests indicated that a well-consolidated, void-free laminate could be attained. Preliminary interleaf processing trials were then conducted to establish some broad guidelines for film processing. The primary finding of these initial studies was that a two-stage process was necessary in order to process these materials adequately. A screening experiment was then performed to determine the relative influence of the process variables on the quality of the film interface as determined by the wedge peel test method. Parameters that were found to be of minor influence on specimen quality were subsequently held at fixed values enabling a more rapid determination of an optimal process. Optimization studies were then performed by varying the remaining parameters at three film melt processing rates. The resulting peel data were fitted with quadratic response surfaces. Additional specimens were fabricated at levels of high peel strength as predicted by the regression models in an attempt to gage the accuracy of the predicted response and to assess the repeatability of the process. The overall results indicate that quality laminates having film interleaves can be successfully and repeatably fabricated by automated fiber placement.
Hulcher, A. B.↗
Adjoint methods for aerodynamic wing design
A model inverse design problem is used to investigate the effect of flow discontinuities on the optimization process. The optimization involves finding the cross-sectional area distribution of a duct that produces velocities that closely match a targeted velocity distribution. Quasi-one-dimensional flow theory is used, and the target is chosen to have a shock wave in its distribution. The objective function which quantifies the difference between the targeted and calculated velocity distributions may become non-smooth due to the interaction between the shock and the discretization of the flowfield. This paper offers two techniques to resolve the resulting problems for the optimization algorithms. The first, shock-fitting, involves careful integration of the objective function through the shock wave. The second, coordinate straining with shock penalty, uses a coordinate transformation to align the calculated shock with the target and then adds a penalty proportional to the square of the distance between the shocks. The techniques are tested using several popular sensitivity and optimization methods, including finite-differences, and direct and adjoint discrete sensitivity methods. Two optimization strategies, Gauss-Newton and sequential quadratic programming (SQP), are used to drive the objective function to a minimum.
Grossman, Bernard↗
Optimal fabrication processes for unidirectional metal-matrix composites: A computational simulation
A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with non-linear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.
Saravanos, D. A.↗
Optimal fabrication processes for unidirectional metal-matrix composites - A computational simulation
A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with nonlinear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.
Saravanos, D. A.↗
Deconvoluting the Friction Stir Weld Process for Optimizing Welds
In the friction stir welding process, the rotating surfaces of the pin and shoulder contact the weld metal and force a rotational flow within the weld metal. Heat, generated by the metal deformation as well as frictional slippage with the contact surface, softens the metal and makes it easier to deform. As in any thermo-mechanical processing of metal, the flow conditions are critical to the quality of the weld. For example, extrusion of metal from under the shoulder of an excessively hot weld may relax local pressure and result in wormhole defects. The trace of the weld joint in the wake of the weld may vary geometrically depending upon the flow streamlines around the tool with some geometry more vulnerable to loss of strength from joint contamination than others. The material flow path around the tool cannot be seen in real time during the weld. By using analytical "tools" based upon the principles of mathematics and physics, a weld model can be created to compute features that can be observed. By comparing the computed observations with actual data, the weld model can be validated or adjusted to get better agreement. Inputs to the model to predict weld structures and properties include: hot working properties ofthe metal, pin tool geometry, travel rate, rotation and plunge force. Since metals record their prior hot working history, the hot working conditions imparted during FSW can be quantified by interpreting the final microstructure. Variations in texture and grain size result from variations in the strain accommodated at a given strain rate and temperature. Microstructural data from a variety of FSWs has been correlated with prior marker studies to contribute to our understanding of the FSW process. Once this stage is reached, the weld modeling process can save significant development costs by reducing costly trial-and-error approaches to obtaining quality welds.
Schneider, Judy↗
Constrained adaptive digital array processing
Optimal design of detector array and signal processor to maximize output signal to noise ratio based on super gain Q factor
Winkler, L. P.↗
Framework for Multidisciplinary Analysis, Design, and Optimization with High-Fidelity Analysis Tools
A plan is presented for the development of a high fidelity multidisciplinary optimization process for rotorcraft. The plan formulates individual disciplinary design problems, identifies practical high-fidelity tools and processes that can be incorporated in an automated optimization environment, and establishes statements of the multidisciplinary design problem including objectives, constraints, design variables, and cross-disciplinary dependencies. Five key disciplinary areas are selected in the development plan. These are rotor aerodynamics, rotor structures and dynamics, fuselage aerodynamics, fuselage structures, and propulsion / drive system. Flying qualities and noise are included as ancillary areas. Consistency across engineering disciplines is maintained with a central geometry engine that supports all multidisciplinary analysis. The multidisciplinary optimization process targets the preliminary design cycle where gross elements of the helicopter have been defined. These might include number of rotors and rotor configuration (tandem, coaxial, etc.). It is at this stage that sufficient configuration information is defined to perform high-fidelity analysis. At the same time there is enough design freedom to influence a design. The rotorcraft multidisciplinary optimization tool is built and substantiated throughout its development cycle in a staged approach by incorporating disciplines sequentially.
Orr, Stanley A.↗
Numerical optimization of conical flow waveriders including detailed viscous effects
A family of optimized hypersonic waveriders is generated and studied wherein detailed viscous effects are included within the optimization process itself. This is in contrast to previous optimized waverider work, wherein purely inviscid flow is used to obtain the waverider shapes. For the present waveriders, the undersurface is a streamsurface of an inviscid conical flowfield, the upper surface is a streamsurface of the inviscid flow over a tapered cylinder (calculated by the axisymmetric method of characteristics), and the viscous effects are treated by integral solutions of the boundary layer equations. Transition from laminar to turbulent flow is included within the viscous calculations. The optimization is carried out using a nonlinear simplex method. The resulting family of viscous hypersonic waveriders yields predicted high values of lift/drag, high enough to break the L/D barrier based on experience with other hypersonic configurations. Moreover, the numerical optimization process for the viscous waveriders results in distinctly different shapes compared to previous work with inviscid-designed waveriders. Also, the fine details of the viscous solution, such as how the shear stress is distributed over the surface, and the location of transition, are crucial to the details of the resulting waverider geometry. Finally, the moment coefficient variations and heat transfer distributions associated with the viscous optimized waveriders are studied.
Bowcutt, Kevin G.↗
Optimal design of solidification processes
An optimal design algorithm is presented for the analysis of general solidification processes, and is demonstrated for the growth of GaAs crystals in a Bridgman furnace. The system is optimal in the sense that the prespecified temperature distribution in the solidifying materials is obtained to maximize product quality. The optimization uses traditional numerical programming techniques which require the evaluation of cost and constraint functions and their sensitivities. The finite element method is incorporated to analyze the crystal solidification problem, evaluate the cost and constraint functions, and compute the sensitivities. These techniques are demonstrated in the crystal growth application by determining an optimal furnace wall temperature distribution to obtain the desired temperature profile in the crystal, and hence to maximize the crystal's quality. Several numerical optimization algorithms are studied to determine the proper convergence criteria, effective 1-D search strategies, appropriate forms of the cost and constraint functions, etc. In particular, we incorporate the conjugate gradient and quasi-Newton methods for unconstrained problems. The efficiency and effectiveness of each algorithm is presented in the example problem.
Dantzig, Jonathan A.↗
Design for Manufacturing of Structures with Automated Fiber Placement via Integration of Analysis and Process Planning
Under the Design for Manufacturing (DFM) task in the NASA HiCAM program, significant process has been made towards establishing a fully automated optimization process that spans the structural analysis, design, and manufacturing process planning for Automated Fiber Placement (AFP) structures. Previous efforts in this area established the data formats and mapping processes needed to exchange data between disciplines. The software tools used in the framework are HyperX (structural optimization), CAPP (process planning), and VCP (AFP path generation). The work has culminated with automation of data exchanges and an optimization process that drives the three software toward convergence. Within this framework, HyperX is used to generate mass-optimum composite designs which are iterated with VCP and CAPP to improve manufacturability of the designs. As the ply manufacturing process is adjusted by CAPP and VCP, HyperX continually re-assesses the structural integrity of the part and makes adjustments to the laminate as needed. For example, the position of fiber steering and tow overlaps/gaps can necessitate changes to the laminate design. Once the design converges, the end result is a stack of plies that meets both structural and manufacturing requirements. This paper presents the details of the framework and demonstrations the automated process on several parts with significant double-curvature.
HiCAM↗
General shape optimization capability
A method is described for calculating shape sensitivities, within MSC/NASTRAN, in a simple manner without resort to external programs. The method uses natural design variables to define the shape changes in a given structure. Once the shape sensitivities are obtained, the shape optimization process is carried out in a manner similar to property optimization processes. The capability of this method is illustrated by two examples: the shape optimization of a cantilever beam with holes, loaded by a point load at the free end (with the shape of the holes and the thickness of the beam selected as the design variables), and the shape optimization of a connecting rod subjected to several different loading and boundary conditions.
Chargin, Mladen K.↗
Models for optimizing the learning process.
Mathematical models for optimizing learning process, showing instructional problems reformulation as theory of optimization problems
Atkinson, R. C.↗
Shape optimization for maximum stability and dynamic stiffness
Any optimization of structures for maximum stability or for maximum dynamic stiffness deals with an eigenvalue problem. The goal of this optimization is to raise the lowest eigenvalue (or eigenvalues) of the problem to its highest (optimal) level at a constant volume of the structure. Likely the lowest eigenvalue may be either inherently multi-modal or it can become multi-modal as a result of the optimization process. The multimodeness introduces some ambiguity to the eigenvalue problem and make the optimization difficult to handle. Thus far, only the simplest cases of multi-modal structures have been effectively optimized using rather elaborate analytical methods. Numerous publications report design of a minimum volume structure with different eigenvalues constraints, in which, however, the modality of the problem is assumed a priori. The method presented here utilizes a multi-modal optimality criteria and allows for inclusion of an arbitrary number of buckling or vibrations modes which might influence the optimization process. The real multi-modality of the problem, that is the number of modes participating in the final optimal design is determined iteratively. Because of a natural use of the FEM technique the method is easy to program and might be helpful in design of large flexible space structures.
Szyszkowski, W.↗
Evaluation of LANDSAT-4 Thematic Mapper Data as Applied to Geologic Exploration: Summary of Results
As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.
Dykstra, J. D.↗
An investigation of squeeze-cast alloy 718
Alloy 718 billets produced by the squeeze-cast process have been evaluated for use as potential replacements for propulsion engine components which are normally produced from forgings. Alloy 718 billets were produced using various processing conditions. Structural characterizations were performed on 'as-cast' billets. As-cast billets were then homogenized and solution treated and aged according to conventional heat-treatment practices for this alloy. Mechanical property evaluations were performed on heat-treated billets. As-cast macrostructures and microstructures varied with squeeze-cast processing parameters. Mechanical properties varied with squeeze-cast processing parameters and heat treatments. One billet exhibited a defect free, refined microstructure, with mechanical properties approaching those of wrought alloy 718 bar, confirming the feasibility of squeeze-casting alloy 718. However, further process optimization is required, and further structural and mechanical property improvements are expected with process optimization.
Gamwell, W. R.↗
Design Process for High Speed Civil Transport Aircraft Improved by Neural Network and Regression Methods
A key challenge in designing the new High Speed Civil Transport (HSCT) aircraft is determining a good match between the airframe and engine. Multidisciplinary design optimization can be used to solve the problem by adjusting parameters of both the engine and the airframe. Earlier, an example problem was presented of an HSCT aircraft with four mixed-flow turbofan engines and a baseline mission to carry 305 passengers 5000 nautical miles at a cruise speed of Mach 2.4. The problem was solved by coupling NASA Lewis Research Center's design optimization testbed (COMETBOARDS) with NASA Langley Research Center's Flight Optimization System (FLOPS). The computing time expended in solving the problem was substantial, and the instability of the FLOPS analyzer at certain design points caused difficulties. In an attempt to alleviate both of these limitations, we explored the use of two approximation concepts in the design optimization process. The two concepts, which are based on neural network and linear regression approximation, provide the reanalysis capability and design sensitivity analysis information required for the optimization process. The HSCT aircraft optimization problem was solved by using three alternate approaches; that is, the original FLOPS analyzer and two approximate (derived) analyzers. The approximate analyzers were calibrated and used in three different ranges of the design variables; narrow (interpolated), standard, and wide (extrapolated).
Hopkins, Dale A.↗
Research on instructional strategies for optimizing the learning process
Instructional strategies for optimizing learning processes and application of such principles to practical course of instruction in computer science
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