IMRFit: Interactive Simulation and Constitutive-Model Fitting for Inertial Microcavitation Rheometry
Abstract
Inertial microcavitation rheometry (IMR) characterizes the high-rate mechanical response of soft materials from the rapid expansion and collapse of a microscopic bubble. In a typical IMR experiment, high-speed imaging provides the bubble radius as a function of time, R(t), and material parameters are identified by comparing the measured response with simulations that couple bubble dynamics to a constitutive description of the surrounding medium. This inverse analysis requires repeated forward simulations and careful control of experimental inputs, material parameters, and fitting settings. IMRFit is an open-source Python desktop application that brings these steps into an interactive environment for forward simulation, parameter identification, and constitutive-model comparison. Users can import experimental radius-time data, select a bubble-dynamics formulation and constitutive model, inspect simulated responses, fit material parameters, and organize batch fitting and parameter-sweep jobs. IMRFit includes Neo-Hookean Kelvin-Voigt and generalized Maxwell-Ogden-based models, among other constitutive options, and supports additional models through JSON descriptors and Python solver entry points. It also integrates fitting-window selection, visualization, and data export into a single workflow.
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BibTeX
@misc{wang2026imrfit,
title = {{IMRFit: Interactive Simulation and Constitutive-Model Fitting for Inertial Microcavitation Rheometry}},
author = {Sicong Wang and Zixiang Tong and Jin Yang},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.32119},
eprint = {2610.32119},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.32119},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - IMRFit: Interactive Simulation and Constitutive-Model Fitting for Inertial Microcavitation Rheometry
AU - Sicong Wang
AU - Zixiang Tong
AU - Jin Yang
PY - 2026
DA - 2026/10/23
PB - arXiv
DO - 10.48550/arxiv.2610.32119
UR - https://arxiv.org/abs/2610.32119
AB - Inertial microcavitation rheometry (IMR) characterizes the high-rate mechanical response of soft materials from the rapid expansion and collapse of a microscopic bubble. In a typical IMR experiment, high-speed imaging provides the bubble radius as a function of time, R(t), and material parameters are identified by comparing the measured response with simulations that couple bubble dynamics to a constitutive description of the surrounding medium. This inverse analysis requires repeated forward simulations and careful control of experimental inputs, material parameters, and fitting settings. IMRFit is an open-source Python desktop application that brings these steps into an interactive environment for forward simulation, parameter identification, and constitutive-model comparison. Users can import experimental radius-time data, select a bubble-dynamics formulation and constitutive model, inspect simulated responses, fit material parameters, and organize batch fitting and parameter-sweep jobs. IMRFit includes Neo-Hookean Kelvin-Voigt and generalized Maxwell-Ogden-based models, among other constitutive options, and supports additional models through JSON descriptors and Python solver entry points. It also integrates fitting-window selection, visualization, and data export into a single workflow.
ER -