Analysis of Model Parameters for a Polymer Filtration Simulator
We examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along wit...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
|
| Series: | Modelling and Simulation in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2011/138143 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832559071967838208 |
|---|---|
| author | N. Brackett-Rozinsky S. Mondal K. R. Fowler E. W. Jenkins |
| author_facet | N. Brackett-Rozinsky S. Mondal K. R. Fowler E. W. Jenkins |
| author_sort | N. Brackett-Rozinsky |
| collection | DOAJ |
| description | We examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along with statistical relationships that define debris distributions and retention probabilities. The flow of polymer fluid, and suspended debris particles, is tracked to determine how well a filter performs and how long it operates before clogging. A filter may have multiple layers, characterized by thickness, porosity, and average pore diameter. In this work, the thickness of each layer is fixed, while the porosities and pore diameters vary for a two-layer and three-layer study. The effects of porosity and average pore diameter on the measures of filter quality are calculated. For the three layer model, these effects are tested for statistical significance using analysis of variance. Furthermore, the effects of each pair of interacting parameters are considered. This allows the detection of complexity, where in changing two aspects of a filter together may generate results substantially different from what occurs when those same aspects change separately. The principal findings indicate that the first layer of a filter is the most important. |
| format | Article |
| id | doaj-art-51fde3ccb75e4bd59ccbaf8119297a9b |
| institution | Kabale University |
| issn | 1687-5591 1687-5605 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Modelling and Simulation in Engineering |
| spelling | doaj-art-51fde3ccb75e4bd59ccbaf8119297a9b2025-02-03T01:30:49ZengWileyModelling and Simulation in Engineering1687-55911687-56052011-01-01201110.1155/2011/138143138143Analysis of Model Parameters for a Polymer Filtration SimulatorN. Brackett-Rozinsky0S. Mondal1K. R. Fowler2E. W. Jenkins3UCLA Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095-1555, USADepartment of Mathematics, Clarkson University, Potsdam, NY 13699-5815, USADepartment of Mathematics, Clarkson University, Potsdam, NY 13699-5815, USADepartment of Mathematical Sciences, Clemson University, Clemson, SC 29634, USAWe examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along with statistical relationships that define debris distributions and retention probabilities. The flow of polymer fluid, and suspended debris particles, is tracked to determine how well a filter performs and how long it operates before clogging. A filter may have multiple layers, characterized by thickness, porosity, and average pore diameter. In this work, the thickness of each layer is fixed, while the porosities and pore diameters vary for a two-layer and three-layer study. The effects of porosity and average pore diameter on the measures of filter quality are calculated. For the three layer model, these effects are tested for statistical significance using analysis of variance. Furthermore, the effects of each pair of interacting parameters are considered. This allows the detection of complexity, where in changing two aspects of a filter together may generate results substantially different from what occurs when those same aspects change separately. The principal findings indicate that the first layer of a filter is the most important.http://dx.doi.org/10.1155/2011/138143 |
| spellingShingle | N. Brackett-Rozinsky S. Mondal K. R. Fowler E. W. Jenkins Analysis of Model Parameters for a Polymer Filtration Simulator Modelling and Simulation in Engineering |
| title | Analysis of Model Parameters for a Polymer Filtration Simulator |
| title_full | Analysis of Model Parameters for a Polymer Filtration Simulator |
| title_fullStr | Analysis of Model Parameters for a Polymer Filtration Simulator |
| title_full_unstemmed | Analysis of Model Parameters for a Polymer Filtration Simulator |
| title_short | Analysis of Model Parameters for a Polymer Filtration Simulator |
| title_sort | analysis of model parameters for a polymer filtration simulator |
| url | http://dx.doi.org/10.1155/2011/138143 |
| work_keys_str_mv | AT nbrackettrozinsky analysisofmodelparametersforapolymerfiltrationsimulator AT smondal analysisofmodelparametersforapolymerfiltrationsimulator AT krfowler analysisofmodelparametersforapolymerfiltrationsimulator AT ewjenkins analysisofmodelparametersforapolymerfiltrationsimulator |