Journal of Computational Physics
ACM Transactions on Mathematical Software (TOMS)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A finite difference scheme for solving the Timoshenko beam equations with boundary feedback
Journal of Computational and Applied Mathematics
Efficient aerodynamic shape optimization in MDO context
Journal of Computational and Applied Mathematics
Stability of a coupling technique for partitioned solvers in FSI applications
Computers and Structures
Minimal Repetition Dynamic Checkpointing Algorithm for Unsteady Adjoint Calculation
SIAM Journal on Scientific Computing
Performance of partitioned procedures in fluid-structure interaction
Computers and Structures
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
The Journal of Machine Learning Research
On the Similarities Between the Quasi-Newton Inverse Least Squares Method and GMRes
SIAM Journal on Numerical Analysis
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Unsteady fluid-structure interaction (FSI) simulations are generally time-consuming. Gradient-based methods are preferred to minimise the computational cost of parameter identification studies (and more in general optimisation) with a high number of parameters. However, calculating the cost function's gradient using finite differences becomes prohibitively expensive for a high number of parameters. Therefore, the adjoint equations of the unsteady FSI problem are solved to obtain this gradient at a cost almost independent of the number of parameters. Here, both the forward and the adjoint problems are solved in a partitioned way, which means that the flow equations and the structural equations are solved separately. The application of interest is the identification of the arterial wall's stiffness by comparing the motion of the arterial wall with a reference, possibly obtained from non-invasive imaging. Due to the strong interaction between the fluid and the structure, quasi-Newton coupling iterations are applied to stabilise the partitioned solution of both the forward and the adjoint problem.