Browsing by Author "Giunta, Anthony A."
Now showing 1 - 9 of 9
Results Per Page
Sort Options
- Aircraft Multidisciplinary Design Optimization using Design of Experiments Theory and Response Surface Modeling MethodsGiunta, Anthony A. (Virginia Tech, 1997-05-01)Design engineers often employ numerical optimization techniques to assist in the evaluation and comparison of new aircraft configurations. While the use of numerical optimization methods is largely successful, the presence of numerical noise in realistic engineering optimization problems often inhibits the use of many gradient-based optimization techniques. Numerical noise causes inaccurate gradient calculations which in turn slows or prevents convergence during optimization. The problems created by numerical noise are particularly acute in aircraft design applications where a single aerodynamic or structural analysis of a realistic aircraft configuration may require tens of CPU hours on a supercomputer. The computational expense of the analyses coupled with the convergence difficulties created by numerical noise are significant obstacles to performing aircraft multidisciplinary design optimization. To address these issues, a procedure has been developed to create two types of noise-free mathematical models for use in aircraft optimization studies. These two methods use elements of statistical analysis and the overall procedure for using the methods is made computationally affordable by the application of parallel computing techniques. The first modeling method, which has been the primary focus of this work, employs classical statistical techniques in response surface modeling and least squares surface fitting to yield polynomial approximation models. The second method, in which only a preliminary investigation has been performed, uses Bayesian statistics and an adaptation of the Kriging process in Geostatistics to create exponential function-based interpolating models. The particular application of this research involves modeling the subsonic and supersonic aerodynamic performance of high-speed civil transport (HSCT) aircraft configurations. The aerodynamic models created using the two methods outlined above are employed in HSCT optimization studies so that the detrimental effects of numerical noise are reduced or eliminated during optimization. Results from sample HSCT optimization studies involving five and ten variables are presented here to demonstrate the utility of the two modeling methods.
- A Coarse Grained Parallel Variable-Complexity Multidisciplinary Optimization ParadigmBurgee, Susan L.; Giunta, Anthony A.; Balabanov, Vladimir; Grossman, Bernard M.; Mason, William H.; Narducci, Robert; Haftka, Raphael T.; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1995-10-01)Modern aerospace vehicle design requires the interaction of multiple discipines, traditionally processed in a sequential order. Multidisciplinary optimization (MDO), a formal methodology for the integration of these disciplines, is evolving towards methods capable of replacing the traditional sequential methodology of aerospace vehicle design by concurrent algorithms, with both an overall gain in product performance and a decrease in design time. A parallel MDO paradigm using variable-complexity modeling and multipoint response surface approximations is presented here for the particular instance of the design of a high speed civil transport (HSCT). This paradigm interleaves the disciplines at one level of complexity, and processes them hierarchically at another level of complexity, achieving parallelism within disciplines, rather than across disciplines. A master-slave paradigm manages a coarse grained parallelism of the analysis and optimization codes required by the disciplines showing reasonable speedups and efficiencies on an Intel Paragon.
- Multidisciplinary Optimization of a Supersonic Transport Using Design of Experiments Theory and Response Surface ModelingGiunta, Anthony A.; Balabanov, Vladimir; Haim, Dan; Grossman, Bernard M.; Mason, William H.; Watson, Layne T.; Haftka, Raphael T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1997-07-01)The presence of numerical noise in engineering design optimization problems inhibits the use of many gradient-based optimization methods. This numerical noise may result in the inaccurate calculation of gradients which in turn slows or prevents convergence during optimization, or it may promote convergence to spurious local optima. The problems created by numerical noise are particularly acute in aircraft design applications where a single aerodynamic or structural analysis of a realistic aircraft configuration may require tens of CPU hours on a supercomputer. The computational expenses of the analyses coupled with the convergence difficulties created by numerical noise are significant obstacles to performing aircraft multidisciplinary design optimization. To address these issues, a procedure has been developed to create noise-free algebraic models of subsonic and supersonic aerodynamic performance qualities for use in the optimization of high-speed civil transport (HSCT) aircraft configurations. This procedure employs methods from statistical design of experiments theory and response surface modeling to create the noise-free algebraic models. Results from a sample HSCT design problem involving ten variables are presented to demonstrate the utility of this method.
- Noisy Aerodynamic Response and Smooth Approximations in HSCT DesignGiunta, Anthony A.; Dudley, J.; Narducci, Robert; Grossman, Bernard M.; Haftka, Raphael T.; Mason, William H.; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1994)Convergence difficulties were encountered in our recent efforts towards a combined aerodynamic-structural optimization of the High Speed Civil Transport (HSCT). The underlying causes of the convergence problems were traced to numerical noise in the calculation of aerodynamic drag components for obstacles to convergence. The first technique employed a sequential approximation optimization method which used large initial move limits on the design variables. This helped dislodge the optimizer out of the local minima in the design space created by the noisy drag data. The second method utilized the aircraft. Two techniques were developed to circumvent the response surface methods to construct smooth approximations to the noisy data. The response surfaces were formed by analyzing several individual HSCT configuration and then fitting polynomial functions to selected objective function data. A simplified example design problem was used to demonstrate the response surface technique and to investigate various other issues relating to the construction of the response surfaces.
- Optimization in Aircraft DesignBurgee, Susan L.; Watson, Layne T.; Giunta, Anthony A.; Balabanov, Vladimir; Grossman, Bernard M.; Haftka, Raphael T.; Mason, William H. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1995)A parallel variable-complexity modeling approach, permitting the efficient use of emerging parallel computing in multidisciplinary optimization (MDO) technology, is presented for the particular instance of High Speed Civil Transport (HSCT) design. In this method simple analyses are used to limit the approximation domain based on the D-optimality criterion through the use of a genetic alogorithm. At the D-optimal points, a refined analysis is performed. The optimization code is composed of a sequence of analysis cycles between aerodynamic and structural calculations. Results for coarse grained parallelization of the aerodynamic and structural codes on an Intel Paragon are presented for an example HSCT design problem involving only two variables. The full HSCT design problem employs twenty-eight design variables.
- Response Surface Models Combining Linear and Euler Aerodynamics for HSCT DesignKnill, Duane L.; Giunta, Anthony A.; Baker, Chuck A.; Grossman, Bernard M.; Mason, William H.; Haftka, Raphael T.; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1998-08-01)A method has been developed to efficiently implement supersonic aerodynamic predictions from Euler solutions into a highly constrained, multidisciplinary design optimization of a High-Speed Civil Transport. The method alleviates the large computational burden associated with performing computational fluid dynamics analyses through the use of variable-complexity modeling techniques, response surface methodologies, and coarse grained parallel computing. Using information gained from lower fidelity aerodynamic models, reduced term response surface models representing a correction to the linear theory response surface model predictions are constructed using Euler solutions. Studies into five, ten, fifteen, and twenty variable design problems show that accurate results can be obtained with the reduced term models at a fraction of the cost of creating the full term quadratic response surface models. Specifically, a savings of 255 CPU hours out of 392 CPU hours required to create the full term response surface model is obtained for the twenty variable problem on a single 75 MHz IP21 processor of a SGI Power Challenge.
- Suitability of Optimization Packages for an MDO EnvironmentHaim, Dan; Giunta, Anthony A.; Holzwarth, M.; Mason, William H.; Watson, Layne T.; Haftka, Raphael T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1996-10-01)An examination of the performance of several optimization packages and their suitability for inclusion in a realistic multidisciplinary design optimization (MDO) environment is conducted. The packages are incorporated into a High-Speed Civil Transport (HSCT) aircraft design code and are used with both a response surface (RS) model and a more detailed, noisy model. While most packages converge to similar designs, there are large variations in CPU times and usability. Results are reported for a SGI workstation.
- Variable-Complexity Response Surface Approximations for Wing Structural Weight in HSCT DesignKaufman, Matthew; Balabanov, Vladimir; Burgee, Susan L.; Giunta, Anthony A.; Grossman, Bernard M.; Haftka, Raphael T.; Mason, William H.; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1996)A procedure for generating and using a polynomial approximation to wing bending material weight of a High Speed Civil Transport (HSCT) is presented. Response surface methodology is used to fit a quadratic polynomial to data gathered from a series of structural optimizations. Several techniques are employed in order to minimize the number of required structural optimizations and to maintain accuracy. First, another weight function based on statistical data is used to identify a suitable model function for the response surface. In a similar manner, geometric and loading parameters that are likely to appear in the response surface model are also identified. Next, simple analysis techniques are used to find regions of the design space where reasonable HCST designs could occur. The use of intervening variables along with analysis of variance reduce the number of polynomial terms in the response surface model function. Structural optimization is then performed by the program GENESIS on a 28-node Intel Paragon. Finally, optimizations of the HSCT are completed both with and without the response surface.
- Wing Design for a High-Speed Civil Transport Using a Design of Experiments MethodologyGiunta, Anthony A.; Balabanov, Vladimir; Haim, Dan; Grossman, Bernard M.; Mason, William H.; Watson, Layne T.; Haftka, Raphael T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1996-07-01)The presence of numerical noise inhibits gradient-based optimization and therefore limits the practicality of performing aircraft multidisciplinary design optimization (MDO). To address this issue, a procedure has been developed to create noise free algebraic models of subsonic and supersonic aerodynamic performance for use in the MDO of high-speed civil transport (HSCT) configurations. This procedure employs methods from statistical design of experiments theory to select a set of HSCT wing designs (fuselage/tail/engine geometry fixed) for which numerous detailed aerodynamic analyses are performed. Polynomial approximations (i.e., response surface models) are created from the aerodynamic data to provide analytical models relating aerodynamic quantities (e.g., wave drag and drag-due-to-lift) to the variables which define the HSCT wing configuration. A multidisciplinary design optimization of the HSCT is then performed using the response surface models in lieu of the traditional, local gradient based design methods. The use of response surface models makes possible the efficient and robust application of MDO to the design of an aircraft system. Results obtained from five variable and ten variable wing design problems presented here demonstrate the effectiveness of this response surface modeling method.