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Message Passing Interface Parallelization for Two-Way Coupled Euler-Lagrange Simulation of Microbubble Enhanced HIFU.

Jingsen Ma¹, Aswin Gnanaskandan¹, Chao-Tsung Hsiao¹

¹Dynaflow, Inc., 10621-J Iron Bridge Road, Jessup, MD 20794.

Journal of Fluids Engineering

|August 2, 2021

Summary

This summary is machine-generated.

This study introduces a parallelized computational model for microbubble-enhanced high-intensity focused ultrasound (HIFU) tumor ablation. The method efficiently simulates acoustic and thermal fields, improving treatment characterization.

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Area of Science:

Computational physics and biomedical engineering.
Advanced modeling of ultrasound therapies.

Background:

Microbubble-enhanced high-intensity focused ultrasound (HIFU) shows promise for liver and brain cancer tumor ablation.
Accurate characterization of acoustic and thermal fields is crucial for optimizing HIFU treatments.

Purpose of the Study:

To develop and validate a parallelized computational model for microbubble-enhanced HIFU.
To accurately simulate the coupled acoustic, thermal, and microbubble dynamics during HIFU procedures.

Main Methods:

A coupled Euler-Lagrange model was employed, solving Navier-Stokes equations for the fluid and tracking microbubbles in a Lagrangian manner.
Message Passing Interface (MPI) parallelization using domain decomposition was implemented for efficient computation.
Ghost cells were utilized to manage the coupling of bubble effects across subdomain borders, minimizing communication overhead.

Main Results:

The proposed parallelization scheme was verified for gas effects conservation and validated on a microbubble-enhanced HIFU scenario.
Demonstrated efficient parallelization scaling and performance analysis for the computational model.
The ghost cell strategy effectively handled inter-subdomain coupling without direct bubble information exchange.

Conclusions:

The developed parallelized Euler-Lagrange model provides an efficient and accurate tool for simulating microbubble-enhanced HIFU.
This computational approach can aid in the precise characterization and optimization of HIFU for cancer treatments.