microAI: A machine learning tool for fast calculation of lift coefficients in microchannels

TL;DR

This paper introduces microAI, an AI-powered web application that rapidly and accurately calculates lift coefficients in microchannels, significantly reducing computation time compared to traditional DNS methods.

Contribution

The paper presents a novel AI-based webapp for microfluidic lift coefficient calculation, optimizing activation functions and optimizers for improved performance.

Findings

microAI achieves fast and accurate lift coefficient calculations

The tool is user-friendly and accessible online

Optimized neural network parameters enhance convergence

Abstract

There have been multiple methods proposed to calculate lift coefficients in microfluidic channels. One of the most used methods is using Direct Numerical Simulation. DNS is a very accurate yet computationally expensive method. DNS computations comprise most of the time consumed on a microfluidic simulation done by commercial software. This paper proposes a user-friendly, fast, and accurate AI-based webapp named microAI that can calculate the microfluidic lift coefficients of channels. We have also studied the effects of different types of activation functions and optimizers in convergence and the final function's differentiability. microAI is deployed to huggingface and is accessible at \url{https://erfanhamdi.github.io/microAI/}