scholarly journals pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems

2020 ◽  
Vol 5 (54) ◽  
pp. 2564 ◽  
Author(s):  
Neil Wu ◽  
Gaetan Kenway ◽  
Charles Mader ◽  
John Jasa ◽  
Joaquim Martins
Keyword(s):  
Nonlinear Optimization ◽  
Large Scale ◽  
Constrained Nonlinear Optimization ◽  
Sparse Systems

scholarly journals A Practical Algorithm for General Large Scale Nonlinear Optimization Problems

1999 ◽  
Vol 9 (3) ◽  
pp. 755-778 ◽  
Author(s):  
Paul T. Boggs ◽  
Anthony J. Kearsley ◽  
Jon W. Tolle
Keyword(s):  
Nonlinear Optimization ◽  
Large Scale ◽  
Optimization Problems ◽  
Practical Algorithm

Prediction of Performance and Design via Optimization of Ducted Propellers Subject to Non-axisymmetric Inflows

2005 ◽  
Author(s):  
Spyros A. Kinnas ◽  
Hanseong Lee ◽  
Hua Gu ◽  
Yumin Deng
Keyword(s):  
Nonlinear Optimization ◽  
Pressure Coefficient ◽  
Optimization Method ◽  
Least Square ◽  
Maximum Efficiency ◽  
Design Parameters ◽  
Blade Design ◽  
Constrained Nonlinear Optimization ◽  
Nonlinear Optimization Method ◽  
Ducted Propellers

Recently developed methods at UT Austin for the analysis of open or ducted propellers are presented, and then coupled with a constrained nonlinear optimization method to design blades of open or ducted propellers for maximum efficiency satisfying the minimum pressure constraint for fully wetted case, or the specified maximum allowable cavity area for cavitating case. A vortex lattice method (named MPUF3A) is applied to analyze the unsteady cavitating performance of open or ducted propellers subject to non-axisymmetric inflows. A finite volume method based Euler solver (named GBFLOW) is applied to predict the flow field around the open or ducted propellers, coupled with MPUF-3A in order to determine the interaction of the propeller with the inflow (i.e. the effective wake) or with the duct. The blade design of open or ducted propeller is performed by using a constrained nonlinear optimization method (named CAVOPT-BASE), which uses a database of computed performance for a set of blade geometries constructed from a base-propeller. The performance is evaluated using MPUF-3A and GBFLOW. CAVOPT-BASE approximates the database using the least square method or the linear interpolation method, and generates the coefficients of polynomials based on the design parameters, such as pitch, chord, and camber. CAVOPT-BASE finally determines the optimum blade design parameters, so that the propeller produces the desired thrust for the given constraints on the pressure coefficient or the allowed amount of cavitation.

Sign in / Sign up

Export Citation Format

Share Document