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Item type:Publication, Access status: with files , Adaptive tolerances for staggered solution algorithms in fluid-structure interaction(Springer, 2026); ; ; ; Staggered solution algorithms are a well-known alternative to monolithic approaches for solving strongly coupled multi-field problems. A coupling between the subproblems is achieved by exchanging coupling quantities between the solvers. Implicit coupling schemes are realized by letting the solvers solve each load or time step repeatedly until convergence up to a given coupling tolerance is achieved. In fluid-structure interaction as well as a variety of other problem classes, the equations governing the individual fields are nonlinear. Accordingly, each solver performs an inner iterative solution procedure that terminates once an inner tolerance is reached. The basic idea of this work builds on the possibility to adaptively adjust these inner tolerances based on carefully designed rules while preserving the black-box nature of the solvers. The resulting coupling scheme yields significant improvements in computational efficiency compared to classical schemes where the inner solver tolerances are held fixed. This is demonstrated in several numerical examples. The idea is tested in combination with state-of-the-art convergence acceleration schemes and can be realized within any staggered solution approach by only minor modifications to the participating solvers.Publicationtype: Journal Article56 26 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adjoint-assisted robust shape optimization of an idealized arterial bypass graft using the FOSM methodThis paper presents the shape optimization of an idealized arterial bypass graft under uncertainties. The underlying blood flow problem is numerically solved using computational fluid dynamics (CFD) simulations, able to account for mechanical hemolysis and non-Newtonian viscosity properties of blood. The employed hemolysis and non-Newtonian models utilize a set of parameters that are considered uncertain in this work. To this end, the optimization problem is rendered robust and targets the minimization of the first two statistical moments of a hemolysis index. The propagation of the uncertainties to the hemolysis index is done through the first-order second-moment method (FOSM). The necessary derivatives are computed by the adjoint method and finite differences. Several steady-state robust shape optimization simulations of the idealized bypass graft are presented. Selected optimized shapes are further assessed by means of additional fluid–structure interaction (FSI) simulations under unsteady conditions.Publicationtype: Journal Article28 21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Hemodynamics in arterial bypass graft anastomoses with varying cuff sizes and proximal flow paths: a fluid–structure interaction studyThis article investigates the effect of the cuff size of arterial bypass grafts and the flow conditions on the hemodynamics in the anastomosis (connection) to the artery, using numerical simulations. We consider a fluid-structure interaction problem which is solved based on a partitioned scheme. Additionally, we employ computational fluid dynamics to investigate the effect of a rigid wall assumption. The work focuses on clinically relevant hemodynamic quantities associated with the development of intimal hyperplasia. We also include a model for the prediction of hemolysis into the simulation. The results show that even minor changes of the cuff size can result into significant differences in the corresponding quantities of interest. The importance of the inflow path is shown to be lower than that of the cuff size. The usually employed rigid wall assumption is found to be adequate to address wall shear stress oscillations but falls short on predicting maximum and minimum wall shear stress-related quantities of interest.Publicationtype: Journal Article28 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adjoint shape optimization of blood flow applications under uncertainties(2025); This thesis aims to advance traditional gradient-based shape optimization techniques by incorporating blood-specific features. The work can be broadly classified into four main categories, (a) computational blood flow modeling, (b) parameter-free shape optimization, (c) the continuous adjoint method and (d) robust shape optimization. As regards (a), this work presents key aspects related to the computational fluid dynamics (CFD) or fluid-structure interaction (FSI) simulations employed for the solution of the blood flow problem (primal problem). The underlying primal problem is enhanced to account for blood damage (hemolysis) by the numerical solution of an additional partial differential equation (PDE). The minimization of hemolysis is one of the main objectives of interest in this work. In order to account for the shear-thinning behavior of blood, several non-Newtonian viscosity models are also employed. The numerical solution of the primal problem is verified against analytical solutions and literature-reported results when deemed necessary. The shape optimization problem is formulated based on a parameter-free approach. To this end, the identification of the shape gradient or at least, a suitable descent direction, based on the shape sensitivity is addressed. Several methods that compute the descent direction based on the solution of one (or two) additional PDE(s) are presented. Auxiliary aspects related to the optimization problem are also discussed in the context of (b). The thesis presents the novel derivation of continuous adjoint equation systems dual to the blood-specific problems. Specifically, contributions to (c) relate to the development of the continuous adjoint to the steady-state Navier-Stokes equations for an incompressible fluid with hemolysis modeling and with non-Newtonian viscosity properties. The accuracy of the novel systems in estimating the shape sensitivity is assessed against second-order accurate finite difference (FD) studies. On the topic of (d), this work focuses on the necessary uncertainty quantification techniques able to drive a robust shape optimization procedure. The problem is considered uncertain by means of the employed parameters or the boundary conditions thus rendering the objective functional a statistical quantity. The optimization targets the minimization of the statistical moments of the objective functional through the use of methods based on sampling or the method of moments. The biomedical applications studied in this thesis refer to an idealized medical device and an idealized bypass-graft.Publicationtype: Doctoral Thesis119 141 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Parameter-free shape optimization: Various shape updates for engineering applications(Multidisciplinary Digital Publishing Institute (MDPI), 2023-08-25); ; ; Scopus© Citations 2 61 179 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Shape transformation approaches for fluid dynamic optimization(Multidisciplinary Digital Publishing Institute (MDPI), 2023-05-31); ; The contribution is devoted to combined shape- and mesh-update strategies for parameter-free (CAD-free) shape optimization methods. Three different strategies to translate the shape sensitivities computed by adjoint shape optimization procedures into simultaneous updates of both the shape and the discretized domain are employed in combination with a mesh-morphing strategy. Considered methods involve a linear Steklov–Poincaré (Hilbert space) approach, a recently suggested highly non-linear p-Laplace (Banach space) method, and a hybrid variant which updates the shape in Hilbert space. The methods are scrutinized for optimizing the power loss of a two-dimensional bent duct flow using an unstructured, locally refined grid that initially displays favorable grid properties. Optimization results are compared with respect to the optimization convergence, the computational effort, and the preservation of the mesh quality during the optimization sequence. Results indicate that all methods reach, approximately, the same converged optimal solution, which reduces the objective function by about 18% for this classical benchmark example. However, as regards the preservation of the mesh quality, more advanced Banach space methods are advantageous in comparison to Hilbert space methods even when the shape update is performed in Hilbert space to save costs. In specific, while the computational cost of the Banach space method and the hybrid method is about 3.5 and 2.5 times the cost of the pure Hilbert space method, respectively, the grid quality metrics are 2 times and 1.7 times improved for the Banach space and hybrid method, respectively.Publicationtype: Journal ArticleScopus© Citations 1 108 169 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adjoint shape sensitivities of blood flows considering non-newtonian propertiesThis article discusses the derivation and numerical implementation of an adjoint system, to the primal Navier–Stokes equations, for the computation of shape sensitivities of ducted blood flows considering non-Newtonian fluid properties. The ever-growing advancements in blood flow simulations are, naturally, accompanied by an increased interest in the optimization of related medical devices. In the majority of the computational studies, the Newtonian assumption is used to describe the rheology of blood. While this assumption has been shown to satisfactorily capture the flow when it is governed by high shear rates, it falls short at low shear rates. A rich variety of viscosity models has been proposed to tackle this shortcoming. In this article we show how such models can be incorporated into an adjoint system targeting to produce the shape sensitivity which can be used by a gradient-based optimization method for the minimization of an objective functional. A general formulation of the adjoint equations is proposed, in which contributions of the non-Newtonian properties explicitly occur. The numerical implementation is discussed and the validity of the method is assessed by means of numerical experiments of steady blood flows in a 2D stenosed duct, where results are compared against second-order finite-difference (FD) studies. The proposed methodology is then applied to CAD-free, gradient-based shape optimizations of an idealized 3D arterial bypass-graft operating at three relevant Reynolds numbers. It is observed that the impact of the adjoint viscosity treatment is amplified in low shear-rate flow regimes while fades for higher shear-rates, analogous to its primal counterpart.Publicationtype: Journal ArticleScopus© Citations 1 46 197 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A fluid-structure interaction study of hemodynamics in arterial bypass-graft anastomoses(2022-06); ; ; This paper reports on numerical experiments on arterial bypass-graft anastomoses. Bypass-grafts are oftentimes used in surgical procedures to divert blood around narrowed or occluded parts of an artery. The diverted blood flow is crucial to the success of the operation as it may lead to undesirable peculiarities that can result to a renewed occlusion in the distal connection of the graft. However, an a priori prediction of detrimental hemodynamic aspects due to undesirable flow properties is difficult to perform in vitro or in vivo conditions. To this end, this work targets to enhance our understanding of harming mechanisms through in silico experiments using computational fluid dynamics (CFD) and fluid-structure interaction (FSI) simulations. The latter are realized through a partitioned coupled approach which is verified for a 2D benchmark case against literature-reported results. Finally, we present numerical results on grafts with different cuff sizes. Wall shear stress (WSS), oscillatory shear index (OSI) and hemolysis are monitored and compared in the context of either rigid or elastic walls and cuff sizes. Special interest is given to the prediction of hemolysis induction which is often not considered in such studies. We show that wall elasticity is the key parameter in terms of WSS prediction while cuff size mainly affects the estimation of OSI.Publicationtype: Conference Paper46 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Adjoint-based shape optimization for the minimization of flow-induced hemolysis in biomedical applicationsThis paper reports on the derivation and implementation of a shape optimization procedure for the minimization of hemolysis induction in biomedical devices. Hemolysis is a blood damaging phenomenon that may occur in mechanical blood-processing applications where large velocity gradients are found. An increased level of damaged blood can lead to deterioration of the immune system and quality of life. It is, thus, important to minimize flow-induced hemolysis by improving the design of next-generation biomedical machinery. Emphasis is given to the formulation of a continuous adjoint complement to a power-law hemolysis prediction model dedicated to efficiently identifying the shape sensitivity to hemolysis. The computational approach is verified against the analytical solutions of a benchmark problem and computed sensitivity derivatives are validated by a finite differences study on a generic 2D stenosed geometry. The application included addresses a 3D ducted geometry which features typical characteristics of biomedical devices. An optimized shape, leading to a potential improvement in hemolysis induction up to 22%, is identified. It is shown, that the improvement persists for different, literature-reported hemolysis-evaluation parameters.Publicationtype: Journal ArticleScopus© Citations 7 202 259