Numerical Flow Simulation in FDA's "Critical Path" benchmark blood pump

Table of Contents

1 Introduction

1.1 Ventricular Assist Device

1.2 History of VADs

1.3 Operating Conditions for VAD

1.4 Role of Computational Fluid Dynamics

2 Literature Review

2.1 Blood

2.1.1 Red Blood Cells

2.2 Blood Rheology

2.3 Blood damage

2.4 Numerical Hemolysis Prediction

3 Description of Turbulence Modeling

3.1 RANS/URANS

3.1.1 Shear Stress Transport model

4 Experimental Study

5 Pre-Processing

5.1 Structure of FDA blood pump

5.2 Mesh Information

5.2.1 Mesh Overview

5.2.2 Mesh Generation

6 Computation

7 Results and Discussion

7.1 Convergence

7.2 Pressure Head

7.3 Flow Field

7.4 Wall Shear Stress and Hemolysis Comparison

8 Conclusion

Research Objectives and Key Topics

This thesis aims to validate the effectiveness of Computational Fluid Dynamics (CFD) in analyzing hemodynamics and predicting hemolysis within the FDA’s "Critical Path" benchmark blood pump. By performing unsteady incompressible flow simulations and comparing the results against experimental data, the research evaluates the accuracy of current numerical methods and turbulence modeling in a biomedical context.

• Hemodynamic performance analysis of rotary blood pumps
• Implementation of block-structured mesh generation for complex geometries
• Application of URANS and the k-ω SST turbulence model
• Comparative study of hemolysis prediction using Power Law models
• Validation of CFD results against PIV experimental benchmarks

Excerpt from the Thesis

Summary of Chapters

1 Introduction: Provides an overview of heart failure, the necessity of VADs, and the specific role of CFD in improving blood pump design.

2 Literature Review: Discusses the rheological properties of blood, the mechanisms of blood damage, and existing numerical approaches for hemolysis prediction.

3 Description of Turbulence Modeling: Explains the theoretical framework behind RANS and URANS, focusing on why the k-ω SST model was selected.

4 Experimental Study: Summarizes the inter-laboratory PIV experimental setup and the protocols used to create validation data for the FDA benchmark pump.

5 Pre-Processing: Details the CAD geometry, the mesh generation process using ICEM CFD, and the considerations for near-wall refinement.

6 Computation: Outlines the boundary conditions, solver settings, and numerical schemes used within ANSYS CFX to run the transient simulation.

7 Results and Discussion: Analyzes convergence, pressure head, velocity fields, and compares numerical results with empirical benchmarks.

8 Conclusion: Synthesizes findings on the accuracy of CFD simulations and suggests areas for future improvement in hemolysis modeling.

Keywords

Computational Fluid Dynamics, Ventricular Assist Device, Blood pump, block-structured hexahedral mesh, URANS, k-ω SST, hemolysis, Power Law, stress-based model, Eulerian approach, Hemodynamics, FDA benchmark, Numerical simulation, Pressure head, Wall shear stress.

Frequently Asked Questions

What is the primary focus of this master's thesis?

The thesis focuses on using Computational Fluid Dynamics (CFD) to analyze flow fields and predict hemolysis within the FDA’s "Critical Path" benchmark blood pump.

What are the main research themes?

The work covers mesh generation for complex geometries, the application of URANS turbulence models, validation against PIV experimental data, and the implementation of stress-based blood damage models.

What is the main objective of this study?

The goal is to test the credibility and accuracy of CFD simulations in predicting flow patterns and hemolysis compared to established experimental results for the FDA blood pump.

Which scientific methods were applied?

The study utilizes URANS simulations with the k-ω SST turbulence model and the Power Law model for Eulerian hemolysis prediction.

What is addressed in the main part of the thesis?

The main part covers the literature review on blood rheology, detailed mesh generation, numerical computation steps in ANSYS CFX, and a comprehensive discussion of the resulting flow fields and shear stress.

Which keywords best describe this research?

Key terms include Computational Fluid Dynamics, Ventricular Assist Device, hemolysis, URANS, and the k-ω SST turbulence model.

Why is hemolysis prediction critical for VAD development?

High shear stress within blood pumps can cause the rupture of red blood cells, leading to hemolysis; predicting this is vital to ensuring device hemocompatibility for patients.

How did the author handle the discrepancy in pressure head results?

The author discusses that discrepancies likely stem from turbulence model selection and uncertainties in Reynolds numbers identified in inter-laboratory experimental studies.