thermal conductivity of polymer composites filled (Pro-ver)

thermal conductivity of polymer composites filled (Pro-ver)
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Updated 19 Nov 2024

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1. More accurate modeling of physical properties of particles:
Temperature dependent thermal conductivity: The thermal conductivity of particles and matrix can depend on temperature. In other words, the thermal conductivity changes non-linearly or in a certain temperature range. This can simulate the thermal behavior more accurately.
Variable particle size and color: In addition to random sizes, you can also change particle characteristics such as optical refraction index, ability to absorb or emit heat, etc.
2. More accurate simulation of particle collision:
Model of elastic and inelastic collisions: The simulation of particle collisions can be modeled as elastic (conservation of kinetic energy) or inelastic (reduction of energy). In these models, the lost energy can be distributed as heat or other changes in the system.
Microscopic models: Instead of simple collision models (which only consider distance and speed), you can use microscopic collision models such as Molecular Dynamics or Monte Carlo models to more accurately simulate particles.
3. Effect of fluid flow (turbulent and stable state):
Fluid flow simulation: If the particles are in a liquid or gas medium, fluid flow simulation (for example, using Navier-Stokes equations) can also model the changes in temperature and flow velocity in the medium.
Phase reactions: If composite materials or multiphase compounds are modeled, phase reactions such as mass transfer, heat transfer, and phase fluctuations (including melting, evaporation, and condensation) can be accurately modeled.
4. Temperature and energy modeling in several scales:
Nanoscale simulation: To model the thermal behavior of particles at the nanoscale, you need a more detailed understanding of the heat transfer of nanomaterials and the thermal coupling between particles. This can include molecular simulations or models such as Ballistic Heat Transport or Diffusive Heat Transport.
Modeling with Finite Element Analysis (FEA): This method allows you to analyze more detailed models of the thermal and mechanical behavior of systems by dividing space into smaller elements. You can model the effects of stress and thermal stresses in these systems.
5. Using more advanced physical models:
Nonlinear heat transfer models: Actually, heat transfer models are more simply considered to be linear, but heat transfer can actually be non-linear. Models such as the Fourier Law of Heat Conduction can be adapted to nonlinear temperature variations.
Non-equilibrium thermodynamics: Modeling energy and heat transfer from a non-equilibrium thermodynamic perspective, which includes non-equilibrium processes such as diffusion and chemical reactions, can lead your simulation to higher accuracy in more complex models.
6. Adding chemical and mechanical processes:
If the particles are changing shape or chemically reacting, the effects of these changes on physical properties (such as thermal conductivity or changes in particle size) must be considered.
For example, in composite materials, chemical reactions may occur between the particles and the matrix, causing changes in the physical properties and temperature of the system.

Cite As

Masoumeh Porostad (2024). thermal conductivity of polymer composites filled (Pro-ver) (https://www.mathworks.com/matlabcentral/fileexchange/176018-thermal-conductivity-of-polymer-composites-filled-pro-ver), MATLAB Central File Exchange. Retrieved .

Reza Anbarshahi

MATLAB Release Compatibility
Created with R2024b
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.0