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Posted: 4 years ago 2020年7月9日 GMT-4 08:38

Updated: 4 years ago 2020年7月9日 GMT-4 09:19

Hello Harsha, This is an interesting question. I do not have a full answer that would work out of the box in COMSOL, but I see two work-arounds. Hopefully someone with more experience can provide a better solution 1. Export the volume fraction and pressure fields, then work out the problem in python 2. Compute an approximated average using a Gaussian as a substitute for the Dirac distribution I will focus on solution n°2: The point is that you are interested in the quantity P_{avg} = (1/S) \times \iiint \delta\left(\phi(\vec{x} - \frac{1}{2}\right) \times P(\vec{x}) d^3\vec{x} where \phi(\vec x) is the volume fraction field, P(\vec x) is the pressure field and S is the meniscus area S = \iiint \delta\left(\phi(\vec{x}) - \frac{1}{2}\right) d^3\vec{x} The idea is to approximate \delta with a narrow normal distribution \delta(u) = \lim_{\sigma \to 0} \frac{1}{\sigma \sqrt{2\pi}} e^{-\frac{1}{2}\left(\frac{u}{\sigma}\right)^2} So for \sigma small enough, you can take \delta(u) \simeq \frac{1}{\sigma \sqrt{2\pi}} e^{-\frac{1}{2}\left(\frac{u}{\sigma}\right)^2}. Where \sigma has the dimension of u and is to be interpreted as the width of a small averaging window around the meniscus value \phi_m = 1/2. So, I would define this expression in COMSOL using the usual integration operators, then trace this quantity has a function of \sigma. As it get smaller, P_{avg} should converge, until \sigma becomes too small compared to the mesh spacing I presume. I wish I knew a more efficient answer to your question.