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Equation-Based Modeling Blog Posts

Why Do Golf Balls Have Dimples?

October 1, 2021

Why do golf balls have dimples? Can I model a golf ball with COMSOL Multiphysics? Can I use simulation to optimize my shot and make a par? Find answers to these questions and more…

Micromagnetic Simulation with COMSOL Multiphysics®

September 24, 2021

A guest blogger from Fudan University in China used the Physics Builder in COMSOL Multiphysics to create a “Micromagnetics Module” for performing micromagnetic simulations.

How to Model Metabolic Reaction Networks with COMSOL®

August 4, 2021

Certain ice creams, puddings, and candies have an extremely vivid yellow color that comes from vitamin B2. The manufacturing of this supplement is one example of a metabolic reaction network…

Combining Adaptive Mesh Refinement with Data Filtering

March 19, 2021

In a follow-up to our previous blog post on data filtering, we demonstrate how to implement adaptive mesh refinement and a Helmholtz filter for a thermal model with a nonuniform heat load.

Using Data Filtering to Improve Model Performance

March 17, 2021

Want to include experimental data in your model as a load or boundary condition, but the data varies over space or time and is noisy? Try implementing data filtering, such as a Helmholtz filter.

Using Global Equations to Introduce Fully Coupled Goal Seeking

January 20, 2021

Learn how to introduce a goal-seeking equation, combined with a fully coupled approach, to solve a nonlinear model. (Follow-up to an earlier blog post on goal seeking with a segregated solver.)

Introducing Goal Seeking into the Segregated Solver

January 19, 2021

Did you know that you can adjust a model input to achieve a desired output in your nonlinear problems? The process involves implementing a global equation into the segregated solver.

Equation-Based Modeling with a Space-Time Discretization

September 24, 2020

In COMSOL Multiphysics®, almost any expression in a computational model can be modified. For example, using a space-time discretization can make optimization problems easy and fast to implement.

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