Zhang et al., 2012 - Google Patents
Determination of the scalar friction factor for nonspherical particles and aggregates across the entire Knudsen number range by direct simulation Monte Carlo (DSMC)Zhang et al., 2012
View PDF- Document ID
- 17997303037747289371
- Author
- Zhang C
- Thajudeen T
- Larriba C
- Schwartzentruber T
- Hogan Jr C
- Publication year
- Publication venue
- Aerosol Science and Technology
External Links
Snippet
The friction factor of an aerosol particle depends upon the Knudsen number (Kn), as gas molecule–particle momentum transfer occurs in the transition regime. For spheres, the friction factor can be calculated using the Stokes–Millikan equation (with the slip correction …
- 239000002245 particle 0 title abstract description 153
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
- G01N15/02—Investigating particle size or size distribution
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
- G06F1/16—Constructional details or arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
- G01N15/10—Investigating individual particles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Determination of the scalar friction factor for nonspherical particles and aggregates across the entire Knudsen number range by direct simulation Monte Carlo (DSMC) | |
| Gopalakrishnan et al. | Determination of the transition regime collision kernel from mean first passage times | |
| Gopalakrishnan et al. | Coulomb-influenced collisions in aerosols and dusty plasmas | |
| Sorensen | The mobility of fractal aggregates: a review | |
| Yin et al. | Hindered settling velocity and microstructure in suspensions of solid spheres with moderate Reynolds numbers | |
| Zheng | Thermophoresis of spherical and non-spherical particles: a review of theories and experiments | |
| John et al. | Investigation of heat and mass transfer in a lid-driven cavity under nonequilibrium flow conditions | |
| Antonopoulou et al. | Numerical and experimental analysis of the sedimentation of spherical colloidal suspensions under centrifugal force | |
| Gopalakrishnan et al. | The unipolar diffusion charging of arbitrary shaped aerosol particles | |
| Thajudeen et al. | Langevin simulation of aggregate formation in the transition regime | |
| Zhang et al. | A new mesh-independent model for droplet/particle collision | |
| Tomilov et al. | Tracer diffusion in colloidal suspensions under dilute and crowded conditions with hydrodynamic interactions | |
| Zhang et al. | Diffusion tensors of arbitrary-shaped nanoparticles in fluid by molecular dynamics simulation | |
| Wang et al. | Evaluation of dynamic airflow structures in a single-aisle aircraft cabin mockup based on numerical simulation | |
| Corson et al. | Analytical expression for the friction coefficient of DLCA aggregates based on extended Kirkwood–Riseman theory | |
| Lin et al. | Penetration efficiency and distribution of aerosol particles in turbulent pipe flow undergoing coagulation and breakage | |
| Thajudeen et al. | Forced and natural convection in aggregate-laden nanofluids | |
| Shanley et al. | A numerical model for simulating the motions of ellipsoidal fibers suspended in low reynolds number shear flows | |
| Chen et al. | Falling clouds of particles with finite inertia in viscous flows | |
| Moskal et al. | Estimation of the diffusion coefficient of aerosol particle aggregates using Brownian simulation in the continuum regime | |
| Heinson et al. | Crossover from ballistic to Epstein diffusion in the free-molecular regime | |
| Hamid et al. | Anisotropic velocity fluctuations and particle diffusion in sedimentation | |
| Tian et al. | Brownian diffusion of fibers | |
| Liu et al. | Inferring the size distribution of 3D particle clusters in metal matrix nanocomposites | |
| Liu et al. | Thermophoresis of nanoparticles in the transition regime |