Life Sciences Applications: Modeling and Simulation for Biomedical Device Design SGC 2013
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1 Life Sciences Applications: Modeling and Simulation for Biomedical Device Design SGC 2013
2 Modeling and Simulation for Biomedical Device Design Biomedical device design and the regulatory agencies Modeling capabilities for the design of various devices Respiratory Medical equipment Cardiovascular Fluid Structure Interaction (FSI): implicit coupling of STAR-CCM+ and Abaqus
3 Medical Device Application Range Macro Devices Stents Pumps Heartvalves Artificial Organs Catheters Pacemakers Respiratory Aids Micro Devices Lab on a Chip Implanted sensors Implanted drug delivery Diagnostics MRI/CT Scanners Ultrasound Life Support Lung/Heart Machine Dialysis Monitors Blood Pressure ECG, EEG, dissolved gases Therapeutic Lasers Infusion Pumps
4 ASME V&V 40 Committee forming a V&V committee that is application-specific to the medical device industry Some Example Cases: FDA CPI I Nozzle Hemolysis Modeling Drug delivery to the eye, by intravitreal injection Oscillatory Pipe Flow Flow in a Flexible Pipe CFD Challenge Aneurysms Porous media modeling (Fiber bundles) Oxygenator Particle tracking etc. etc..
5 Inhaler Modeling at ARUP STAR-CCM+ at VIASYS (Carefusion) Healthcare
6 Mouth Cavity Inhalation Model Mouth Cavity
7 Simpleware lung demo case Simpleware was used to obtain the complex geometry from MRI of the human body
8 Microfluidics Formation of droplet in flow-focusing geometry 8
9 Heat Transfer, Electronics Cooling & Noise Modelling Ventilation flow and convective cooling as required for MRI/CT scanners, ICU devices Surface wrapping utilized to automatically prepare surface Volumetric heat sources Multiple fan models with fan curves
10 Workflow: Meshing of Patient Specific Data Surface Wrapping, STL Cleanup & Polyhedral Meshing Rapid Turnaround of Complex Geometry AAA (Abdominal Aortic Aneurysm) Geometry Provided by Computational Clinical Modeling, New Jersey (Chris Ebeling) Dissected Aorta Polyhedral Mesh, Geometry Provided by the Methodist DeBakey Heart and Vascular Center, Houston (Dr. Christof Karmonik, Dr. Mark Davies, Dr. Alan Lumsden, Dr. Jean Bismuth)
11 Model setup Cardiovascular flow wave form from applied at the inlet Material properties of blood (Newtonian Approximation)» Density = 1056 kg m -3» Dynamic Viscosity = Pas Windkessel parameters to define the outlet condition:» Z = 1.1x10 7 [kg m -4 s -1 ]» R = 1.45x10 8 [kg m -4 s -1 ]» C = 1.45x10-8 [m 4 s 2 kg -1 ] R 1 C 1 Z 1 R 2 Z 2 C 2 Z 3 R 3 C 3 Laminar flow model Implicit Unsteady model (dt = s) Coupled implicit solver Simulation was run for a number of cycles to ensure a period response was achieved. C 4 Z 4 R 4
12 Preliminary Results Analytical solution [2] Maximum outlet pressure = 93mmHg. Analytical Solution Numerical solution Maximum outlet pressure = 92.2 mmhg [2] Brown A. G., Patient-Specific Local and Systemic Haemodynamics in the Presence of a Left Ventricular Assist Device, PhD Thesis, The University of Sheffield.
13 Fluid Structure Interaction Driven by highly compliant vessels and membranes, structurally impacted by mechanical devices. STAR-CCM+ couples directly to Abaqus (Simulia) through a co-simulation API fully coupled, implicit, two-way FSI Examples include: Blood Pumps (LVADs), Vena Cava Filter, Stents, Graft Bypass, Diagnostics for Arterial Flows or Lung Models etc. etc.
14 Counter Intuitive: Pulse through an Extremely Flexible Tube Pressure pulse in fluid travels only at a speed of near 50 m/s when bulk modulus of the solid is 0.1GPa. For completely rigid pipe: pulse would travel at sound speed of the fluid (1500 m/s). Kinetic energy is primarily being converted into radial strain energy in the solid when it travels there is nothing left to push the pulse down the pipe. The step size is chosen so that for the expect wave speed, the wave travels one cell down the axis. So the smaller the modulus, the smaller the wave speed, the larger the time step yet still accurate and stable!! Damon Afkari, Universidad Politécnica de Madrid
15 FSI Simulation of Pulsatile Blood Flow in Aortic Arch: Coupling Abaqus and STAR-CCM+ Universidad Politécnica de Madrid, Damon Afkari: PhD Student Developed Proprietary Explicit Coupling Methodology Now Implicit Coupling with Abaqus Focus on Fast Turn Around to Aid Surgeon Decision Making Aortic Dissection
16 FSI for Heart Valve Biomechanics (University of Connecticut, Prof. Wei Sun, Dr. Eric Sirois) CAD
17 CFD Meshing & Morphing Polyhedral mesh 0.43 mm base size Leaflet motion -> Star-CCM+ morphing Separate motion for each leaflet Interpolated and mapped Arbitrary Lagrangian-Eulerian (ALE) mesh morphing Automated re-meshing for low quality or zero-volume cells Minimum points in a gap of 4 nodes used to control proximity Mesh varied from ~700k to 1.8M Valve Leaflet Cross-section of CFD model showing polyhedral mesh.
18 Leaflet Motion Comparison Experiment FEA 1 st Run Leaflet Motion FEA 2 nd Run Leaflet Motion CFD 1 st Run Far-Field Pressure CFD 2 nd Run Hemodynamics Comparison
19 CFD Velocity Magnitude and WSS Side view Top view Bottom view WSS
20 Heart Valve FSI: Edwards LifeSciences FSI & Overset Meshes Biomedical FSI Applications Stent Implants: AAA, Coronary, Carotid Arteries etc. Vena Cava Filters Heart Valves Graft Bypass Aneurysm Diagnostics Models Respiratory/Lung Models
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