Efficient simulation of blood flow past complex endovascular devices using an adaptive embedding technique

The simulation of blood flow past endovascular devices such as coils and stents is a challenging problem due to the complex geometry of the devices. Traditional unstructured grid computational fluid dynamics relies on the generation of finite element grids that conform to the boundary of the computational domain. However, the generation of such grids for patient-specific modeling of cerebral aneurysm treatment with coils or stents is extremely difficult and time consuming. This paper describes the application of an adaptive grid embedding technique previously developed for complex fluid structure interaction problems to the simulation of endovascular devices. A hybrid approach is used: the vessel walls are treated with body conforming grids and the endovascular devices with an adaptive mesh embedding technique. This methodology fits naturally in the framework of image-based computational fluid dynamics and opens the door for exploration of different therapeutic options and personalization of endovascular procedures

Computational fluid dynamics of stented intracranial aneurysms using adaptive embedded unstructured grids

Recently, there has been increased interest in the use of stents as flow diverters in the endovascular treatment of cerebral aneurysms as an alternative to surgical clipping or endovascular embolization with coils. The aim of aneurysm stenting is to block the flow into the aneurysm in order to clot the blood inside the aneurysm and effectively isolate it from the circulation and prevent bleeding from the aneurysm. A hybrid meshing approach that combines body‐fitted grids for the vessels and adaptive embedded grids for the stents is proposed and analyzed. This strategy simplifies considerably the geometry modeling problem and allows accurate patient‐specific hemodynamic simulations with endovascular devices. This approach is compared with the traditional body‐fitted approach in the case of the flow around a circular cylinder at representative Reynolds number and an idealized aneurysm model with a stent. A novel technique to map different stent designs to a given patient‐specific anatomical model is presented. The methodology is demonstrated on a patient‐specific hemodynamic model of an aneurysm of the internal carotid artery constructed from a 3D rotational angiogram and stented with two different stent designs. The results show that the methodology can be successfully used to model patient‐specific anatomies with different stents thereby making it possible to explore different stent design

Inverse asymptotic treatment: capturing discontinuities in fluid flows via equation modification

A major challenge in developing accurate and robust numerical solutions to multi-physics problems is to correctly model evolving discontinuities in field quantities, which manifest themselves as interfaces between different phases in multi-phase flows, or as shock and contact discontinuities in compressible flows. When a quick response is required to rapidly emerging challenges, the complexity of bespoke discretization schemes impedes a swift transition from problem formulation to computation, which is exacerbated by the need to compose multiple interacting physics. We introduce "inverse asymptotic treatment" (IAT) as a unified framework for capturing discontinuities in fluid flows that enables building directly computable models based on off-the-shelf numerics. By capturing discontinuities through modifications at the level of the governing equations, IAT can seamlessly handle additional physics and thus enable novice end users to quickly obtain numerical results for various multi-physics scenarios. We outline IAT in the context of phase-field modeling of two-phase incompressible flows, and then demonstrate its generality by showing how localized artificial diffusivity (LAD) methods for single-phase compressible flows can be viewed as instances of IAT. Through the real-world example of a laminar hypersonic compression corner, we illustrate IAT's ability to, within just a few months, generate a directly computable model whose wall metrics predictions for sufficiently small corner angles come close to that of NASA's VULKAN-CFD solver. Finally, we propose a novel LAD approach via "reverse-engineered" PDE modifications, inspired by total variation diminishing (TVD) flux limiters, to eliminate the problem-dependent parameter tuning that plagues traditional LAD. We demonstrate that, when combined with second-order central differencing, it can robustly and accurately model compressible flows

Liquid simulation with mesh-based surface tracking

Animating detailed liquid surfaces has always been a challenge for computer graphics researchers and visual effects artists. Over the past few years, researchers in this field have focused on mesh-based surface tracking to synthesize extremely detailed liquid surfaces as efficiently as possible. This course provides a solid understanding of the steps required to create a fluid simulator with a mesh-based liquid surface. The course begins with an overview of several existing liquid-surface-tracking techniques and the pros and cons of each method. Then it explains how to embed a triangle mesh into a finite-difference-based fluid simulator and describes several methods for allowing the liquid surface to merge together or break apart. The final section showcases the benefits and further applications of a mesh-based liquid surface, highlighting state-of-the-art methods for tracking colors and textures, maintaining liquid volume, preserving small surface features, and simulating realistic surface-tension waves

Clinical application of image‐based CFD for cerebral aneurysms

During the last decade, the convergence of medical imaging and computational modeling technologies has enabled tremendous progress in the development and application of image‐based computational fluid dynamics modeling of patient‐specific blood flows. These techniques have been used for studying the basic mechanisms involved in the initiation and progression of vascular diseases, for studying possible ways to improve the diagnosis and evaluation of patients by incorporating hemodynamics information to the anatomical data typically available, and for the development of computational tools that can be used to improve surgical and endovascular treatment planning. However, before these technologies can have a significant impact on the routine clinical practice, it is still necessary to demonstrate the connection between the extra information provided by the models and the natural progression of vascular diseases and the outcome of interventions. This paper summarizes some of our contributions in this direction, focusing in particular on cerebral aneurysms

High-order gas-kinetic scheme with TENO class reconstruction for the Euler and Navier-Stokes equations

The high-order gas-kinetic scheme(HGKS) with WENO spatial reconstruction method has been extensively validated through many numerical experiments, demonstrating its superior accuracy efficiency, and robustness. Compared with WENO class schemes, TENO class schemes exhibit significantly improved robustness, low numerical dissipation and sharp discontinuity capturing. In this paper, two kinds of fifth-order HGKS with TENO class schemes are designed. One involves replacing WENO5 scheme with the TENO5 scheme in the conventional WENO5-GKS. WENO and TENO schemes only provide the non-equilibrium state values at the cell interface. The slopes of the non-equilibrium state along with the equilibrium values and slopes, are obtained by additional linear reconstruction. Another kind of TENO5-D GKS is similar to WENO5-AO GKS. Following a strong scale-separation procedure, a tailored novel ENO-like stencil selection strategy is proposed such that the high-order accuracy is restored in smooth regions by selecting the candidate reconstruction on the large stencil while the ENO property is enforced near discontinuities by adopting the candidate reconstruction from smooth small stencils. The such TENO schemes are TENO-AA and TENO-D scheme. The HGKS scheme based on WENO-AO or TENO-D reconstruction take advantage of the large stencil to provide point values and slopes of the non-equilibrium state. By dynamically merging the reconstructed non-equilibrium slopes, extra reconstruction of the equilibrium state at the beginning of each time step can be avoided. The simplified schemes have better robustness and efficiency than the conventional WENO5-GKS or TENO5-GKS. TENO-D GKS is also as easy to develop as WENO-AO GKS to high-order finite volume method for unstructured mesh.Comment: arXiv admin note: text overlap with arXiv:2304.05572; text overlap with arXiv:1905.08489 by other author

Cartesian Cut-Cell Method with Local Grid Refinement for Wave Computations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76364/1/AIAA-2006-2522-630.pd

Recent Progress in Image Deblurring

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.Comment: 53 pages, 17 figure