03:30 PM - 03:55 PM
Static Aeroelastic Design Optimization of Lightweight Structures: Computational Challenges and Opportunities
Static aeroelastic design optimization of flexible, lightweight aircraft involves the simultaneous design of both aerodynamics and structures. Static aeroelastic analysis itself is a computationally expensive problem that often requires the use of high-performance computing techniques. Simulation-based design optimization of static aeroelastic systems presents many computational challenges and opportunities for the application of novel optimization techniques that have the potential to reduce computational times.
03:55 PM - 04:20 PM
Quasi-Newton Jacobian Estimates for Matrix-Free Structural Optimization
In structural optimization problems with failure constraints, the computational cost is dominated by computing the gradients of all the constraints. Using a "matrix-free" optimizer can reduce this cost significantly by requiring only appropriate matrix-vector products with the full constraint Jacobian. To keep the total number of matrix-vector products small, we will advocate estimating the constraint Jacobian within the matrix-free optimizer using a quasi-Newton method. Results from structural test problems demonstrate that the computational cost scales well compared to traditional SQP algorithms.
04:20 PM - 04:45 PM
Implementation of a Matrix-Free Augmented Lagrangian Algorithm
In many applications, problems are so large that we cannot compute/store explicit Jacobians and don't have access to Hessian information. We will outline a matrix-free algorithm for solving nonlinear problems with both
equalities and inequalities. Our algorithm is based on an augmented Lagrangian approach and relies on matrix-vector products only. We also show some numerical results on the CUTEr and COPS collections.