Percolation

In physics, chemistry and materials science, percolation (from Latin percōlāre, "to filter" or "trickle through") refers to the movement and filtering of fluids through porous materials. It is described by Darcy's law. Broader applications have since been developed that cover connectivity of many systems modeled as lattices or graphs, analogous to connectivity of lattice components in the filtration problem that modulates capacity for percolation.

For the mathematical and statistical physics term, see percolation theory.
In coffee percolation, soluble compounds leave the coffee grounds and join the water to form coffee. Insoluble compounds (and granulates) remain within the coffee filter.
Percolation in a square lattice (Click to animate)

Background

During the last decades, percolation theory, the mathematical study of percolation, has brought new understanding and techniques to a broad range of topics in physics, materials science, complex networks, epidemiology, and other fields. For example, in geology, percolation refers to filtration of water through soil and permeable rocks. The water flows to recharge the groundwater in the water table and aquifers. In places where infiltration basins or septic drain fields are planned to dispose of substantial amounts of water, a percolation test is needed beforehand to determine whether the intended structure is likely to succeed or fail.

Percolation typically exhibits universality. Statistical physics concepts such as scaling theory, renormalization, phase transition, critical phenomena and fractals are used to characterize percolation properties. Percolation is the downward movement of water through pores and other spaces in the soil due to gravity. Combinatorics is commonly employed to study percolation thresholds.

Due to the complexity involved in obtaining exact results from analytical models of percolation, computer simulations are typically used. The current fastest algorithm for percolation was published in 2000 by Mark Newman and Robert Ziff.[1]

Examples
  • Coffee percolation, where the solvent is water, the permeable substance is the coffee grounds, and the soluble constituents are the chemical compounds that give coffee its color, taste, and aroma.
  • Movement of weathered material down on a slope under the earth's surface.
  • Cracking of trees with the presence of two conditions, sunlight and under the influence of pressure.
  • Collapse and robustness of biological virus shells to random subunit removal (experimentally verified fragmentation and disassembly of viruses).[2][3]
  • Robustness of networks to random and targeted attacks.[4]
  • Transport in porous media.
  • Epidemic spreading.[5][6]
  • Surface roughening.
  • Dental percolation, increase rate of decay under crowns because of a conducive environment for strep mutants and lactobacillus
  • Potential sites for septic systems are tested by the "perk test". Example/theory: A hole (usually 6–10 inches in diameter) is dug in the ground surface (usually 12–24" deep). Water is filled in to the hole, and the time is measured for a drop of one inch in the water surface. If the water surface quickly drops, as usually seen in poorly-graded sands, then it is a potentially good place for a septic "leach field". If the hydraulic conductivity of the site is low (usually in clayey and loamy soils), then the site is undesirable.
  • Traffic percolation.[7]
gollark: I just stick mine into corners of my towers.
gollark: Exhaustive search is impractical. There are probably better ways.
gollark: See, this (and me not knowing the rules) is why I just ignored it for now.
gollark: If I figure out the moderator rules and get this simulator working (and hook it up to a genetic algorithm library) I hope it will be possible to design reactors which are stupider than any before.
gollark: Mine is 9x9x9, runs LEN-236 oxide at 34kRF/t or so, and is entirely passively cooled at the cost of several thousand glowstone.

See also

References
  1. Newman, Mark; Ziff, Robert (2000). "Efficient Monte Carlo Algorithm and High-Precision Results for Percolation". Physical Review Letters. 85 (19): 4104–4107. arXiv:cond-mat/0005264. Bibcode:2000PhRvL..85.4104N. CiteSeerX 10.1.1.310.4632. doi:10.1103/PhysRevLett.85.4104. PMID 11056635.
  2. Brunk, Nicholas E.; Lee, Lye Siang; Glazier, James A.; Butske, William; Zlotnick, Adam (2018). "Molecular jenga: The percolation phase transition (collapse) in virus capsids". Physical Biology. 15 (5): 056005. Bibcode:2018PhBio..15e6005B. doi:10.1088/1478-3975/aac194. PMC 6004236. PMID 29714713.
  3. Lee, Lye Siang; Brunk, Nicholas; Haywood, Daniel G.; Keifer, David; Pierson, Elizabeth; Kondylis, Panagiotis; Wang, Joseph Che-Yen; Jacobson, Stephen C.; Jarrold, Martin F.; Zlotnick, Adam (2017). "A molecular breadboard: Removal and replacement of subunits in a hepatitis B virus capsid". Protein Science. 26 (11): 2170–2180. doi:10.1002/pro.3265. PMC 5654856. PMID 28795465.
  4. R. Cohen and S. Havlin (2010). "Complex Networks: Structure, Robustness and Function". Cambridge University Press.
  5. Parshani, Roni; Carmi, Shai; Havlin, Shlomo (2010). "Epidemic Threshold for the Susceptible-Infectious-Susceptible Model on Random Networks". Physical Review Letters. 104 (25): 258701. arXiv:0909.3811. Bibcode:2010PhRvL.104y8701P. doi:10.1103/PhysRevLett.104.258701. ISSN 0031-9007. PMID 20867419.
  6. Grassberger, Peter (1983). "On the Critical Behavior of the General Epidemic Process and Dynamical Percolation". Mathematical Biosciences. 63 (2): 157–172. doi:10.1016/0025-5564(82)90036-0.
  7. D. Li, B. Fu, Y. Wang, G. Lu, Y. Berezin, H.E. Stanley, S. Havlin (2015). "Percolation transition in dynamical traffic network with evolving critical bottlenecks". PNAS. 112 (3): 669–72. Bibcode:2015PNAS..112..669L. doi:10.1073/pnas.1419185112. PMC 4311803. PMID 25552558.CS1 maint: multiple names: authors list (link)

Further reading
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