An improved version of the Fast automatic Differentiation using Operator-overloading Technique (FDOT) toolbox is developed in this work. The enhanced sensitivity analysis toolbox utilizes an expression-based tape approach -- a first-of-its-kind implementation in Fortran programming language -- that can significantly reduce the memory footprint while improving the computational efficiency of the adjoint-based automatic differentiation (AD). In the proposed approach, the partial derivatives are calculated for each expression using the reverse adjoint accumulation for the active variables involved on the right-hand-side of that expression. The recorded partial derivative information is then used in a very efficient adjoint evaluation process to calculate the entire Jacobian information. The enhanced toolbox is coupled with the in-house UNstructured PArallel Compressible (UNPAC) flow solver for a robust design optimization framework, called UNPAC-DOF. The efficiency and robustness of the proposed technique and the resulting framework are tested for aerodynamic shape optimization problems applied to airfoil and wing geometries.
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Aerodynamic Shape Optimization Framework Based on a Novel Fully-Automated Adjoint Differentiation Toolbox
A robust and automated design optimization framework is developed in this work. This wrapper program automates the design process by coupling the in-house UNstructured PArallel Compressible (UNPAC) flow solver with a novel toolbox for sensitivity analysis based on the discrete adjoint method. The Fast automatic Differentiation using Operator-overloading Technique (FDOT) toolbox utilizes an advanced recording technique to store the expression tree which can significantly reduce the memory footprint and the computational cost of the adjoint calculations. Additionally, this novel toolbox uses an iterative process to evaluate the sensitivities of the cost function with respect to the entire design space and requires only minimal modifications to the available solver. The design optimization framework, UNPAC-DOF, is then employed for aerodynamic design applications based on a gradient-based optimization algorithm. This framework is used to improve airfoil and wing designs for minimized drag or maximized efficiency.
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- Award ID(s):
- 1803760
- NSF-PAR ID:
- 10105831
- Date Published:
- Journal Name:
- AIAA Aviation 2019
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)A memory efficient framework is developed for the aerodynamic design optimization of helicopter rotor blades in hover. This framework is based on a fully-automated discrete-adjoint toolbox called FDOT. The in-house toolbox is capable of computing sensitivity or gradient information very accurately, and uses an operator-overloading technique that takes advantage of a unique expression-template-based approach for memory and computational efficiency while still being fully-automated with minimal user interventions. The main goal of the present work is to "design" helicopter rotor blades with increased figure-of-merit. Therefore, the flow around the Caradonna-Tung rotor in non-lifting and lifting hover conditions is studied in order to validate the primal and adjoint solvers based on a rotating frame of reference formulation. The efficacy of the optimization framework is first demonstrated for drag minimization of a rotating NACA 0012 airfoil, which resembles a Vertical-Axis Wind Turbine (VAWT) configuration. Finally, the single- and multi-point design optimization results for the Caradonna-Tung rotor are presented. It is important to note that the current approach (FDOT) can be directly coupled -- in a "black-box" manner -- to other existing codes in the Helios computational platform, which is part of CREATE-AV.more » « less
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SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.2514/6.2019-3201
