Long range force implementation (LRF)

[PhasicFlow]

Core Concept: Enhancing Spherical Particle Simulations with Long-Range Forces

The primary goal is to augment the existing simulation framework to accurately model systems involving spherical particles interacting via long-range forces (LRF) without relying on coarse-graining techniques. This enhancement will enable the simulation of a broader range of physical phenomena, including:

• Electrostatic Interactions: Coulombic forces between charged particles.
• Van der Waals Forces: Attractive or repulsive forces due to induced dipole interactions.
• Liquid Bridge Forces: Capillary forces arising from liquid menisci between particles.
• Magnetic Dipole Forces: Interactions between magnetic particles.
• Other Potential LRFs: Expanding the framework to accommodate future LRF models.

Framework Design: Flexibility and Extensibility

• Modular Force Implementation:
  • Create a modular structure where each LRF type is implemented as a separate class or function, while these classes/functions are integrated into another class where all the required operations and calculations are performed and this class interacts with other parts of the code (as the interface for other parts).
  • This allows for easy addition of new force models without modifying existing code.
• Dedicated Solver for LRF Systems:
  • Develop a specialized solver optimized for systems with LRFs. This solver should handle the computational complexity associated with long-range interactions efficiently.
  • Consider using algorithms which are specific for LRFs or the ones that are currently available in PhasicFlow.
• Interaction with Walls:
  • Define clear rules for how particles with LRFs interact with walls. This may involve:
    • Implementing wall-particle LRF models.
    • Introducing boundary conditions that account for LRFs.
    • Defining special wall interactions for each type of force.
• Computational Efficiency:
  • LRF calculations can be computationally expensive. Implement optimized algorithms and data structures to minimize computational cost.
  • Consider using parallel processing techniques to accelerate simulations.

User Experience: Dictionary-Based Input

• interaction Dictionary Template:
  • The interaction dictionary within the caseSetup folder will serve as the primary interface for defining LRF parameters.
  • A structured dictionary format will ensure clarity and ease of use.
• Dictionary Structure:
  • forceType: Specifies the type of LRF (e.g., "electrostatic," "vanDerWaals," "liquidBridge").
  • parameters: A sub-dictionary containing force-specific parameters (e.g., charge, Hamaker constant, surface tension).
  • cutoffRadius: Defines the cutoff distance for LRF calculations (if applicable).
  • wallInteraction: A sub-dictionary defining wall-particle interaction parameters
  • solverOptions: Options to define the type of solver, and solver parameters, like PME parameters for electrostatic interactions.

The design of dictionary always helps us to better think about the design of the code and how this part is going to interact with other parts of the code. So, this is very important for us.

[wanqing0421]

For contact search, we can define a contact radius to reduce the calculation load.

[PhasicFlow]

Absolutely! A threshold radius should be defines within which the LRF is effective. This can be a bit larger to make it possible to update the neighbor list updates less frequent. The radius is force-specific, so it should be calculated by program or it can also input by the user. The user should be asked for the enlargement ration, which is defined as the actual radius to threshold radius.
More thoughts on this?