A Monte Carlo simulation of thermal-driven fluid: flux rate and density profile

Pandey, Ras B.; Gettrust, Joseph F.

doi:10.1016/s0378-4371(00)00610-5

Cited by 2 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using an interacting lattice gas model for fluid, we study the fluid flow through such media by Monte Carlo methods [6,7]. In particular, we are studying the effect of temperature and pressure gradients on the flow rate response and evaluate the permeability.…”

Section: (A) Interface Growthmentioning

confidence: 99%

Impact of random numbers on parallel Monte Carlo application

Pandey¹

2002

View full text Add to dashboard Cite

Date ,govA number of graduate students are involved at various level of research in this project.We investigate the basic issues in materials using Monte Carlo simulations with specific interest in heterogeneous materials. Attempts have been made to seek collaborations with the DOE laboratories. Following are specific details. Graduate students:Following graduate students have been involved in this project: A. Balasubramaniam, Frank Bentrem, Luke Para Cueva, Xiaoli Huan, V. Mandula, A Rajendran, V. Ramanujam, Jun Xie, and Shurong Zheng. BeIitrem and Xie are advanced graduate students who are studying the interface growth in polymer deposition at an impenetrable substrate. Ramanujam and Rajendran were helping visualizing the growth process. Cueva is trying to model the transport properties of heterogeneous media using interacting lattice gas with the help of Monte Carlo simulations. Balasubramaniam, Huan, Mandula, and Zheng were helping with the role of random numbers in these simulations. Progress and Outcome:This project has been very productive and helped students in their education. we have found many interesting results which are presented in the following: (A) Interface growth:Monte Carlo simulations are performed to study the interface growth and roughness in electrophoretic deposition of polymer chains in three dimensional lattice. A coarse grained model of polymer chain is used where a chain of length N is generated on the trail of a random walk of N steps with excluded volume constraints. Chains are released from one end of the sample and driven by a field E toward the substrate at the opposite end. KinkJump (K), crank-shaft (C), and reptation (R) segmental dynamics are used to move chains with a Metropolis algorithm. We address the questions, how does the interface grow? How does the steady-state interface width scale with the parameters such as temperature (T), field (E), molecular weight? a \

show abstract

Section: (A) Interface Growthmentioning

confidence: 99%

Impact of random numbers on parallel Monte Carlo application

Pandey¹

2002

View full text Add to dashboard Cite

show abstract

Gradient Driven Flow: Lattice Gas, Diffusion Equation and Measurement Scales

Pandey

Wood

Gettrust

2001

Int. J. Mod. Phys. C

View full text Add to dashboard Cite

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.

show abstract

A Monte Carlo simulation of thermal-driven fluid: flux rate and density profile

Cited by 2 publications

References 13 publications

Impact of random numbers on parallel Monte Carlo application

Impact of random numbers on parallel Monte Carlo application

Gradient Driven Flow: Lattice Gas, Diffusion Equation and Measurement Scales

Contact Info

Product

Resources

About