CFD simulation of liquid nitrogen flow inside a cryogenic chamber used for micromachining of soft polymer

Cryogenic-assisted micromachining is seen as a possible solution to fabricate microchannel directly on soft polymer, by increasing the stiffness of the workpiece surface by reducing cryogenic chamber temperature. However, because of large temperature difference at various position of the cooling area inside the chamber, under cryogenic cooling condition, determination of workpiece temperature at machining time is very difficult. Unfortunately, very limited research work has investigated the complicated physical phenomena of cryogenic cooling responsible for temperature distribution occurring inside the chamber during machining process. These phenomena may affect the cryogenic flow characteristics in over or under-cooling of soft polymer as workpiece, thus the performance of the cryogenic machining. In this work, computational fluid dynamic (CFD) model is developed and applied to investigate the liquid nitrogen (LN 2 ) flow inside the cryogenic chamber under direct cooling (DC) and novel perforated wall cooling (PWC) techniques. The major objective is to evaluate the influence of several parameters (temperature and pressure) on the LN 2 flow inside the chamber and role of the innovative PWC technique in temperature distribution with comparison to DC approach. Results of this study offer two important conclusions for reliable cryogenic micromilling of soft polymer. First, uniform temperature distribution inside the chamber is possible by novel PWC approach and second, peripheral temperature of the chamber shows less fluctuation with surface temperature of the workpiece.

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Publication Details

Journal
Journal of Micromanufacturing
Published
2024-11-20
DOI
https://doi.org/10.1177/25165984241295486
Citations
3
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
0.64
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article

CFD simulation of liquid nitrogen flow inside a cryogenic chamber used for micromachining of soft polymer

Partha Sarathi Mallick, Karali Patra
3 citations
Journal of Micromanufacturing
Advanced machining processes and optimization
0.64
article

CFD simulation of liquid nitrogen flow inside a cryogenic chamber used for micromachining of soft polymer

Partha Sarathi Mallick, Karali Patra
article en
3 citations

Abstract

Cryogenic-assisted micromachining is seen as a possible solution to fabricate microchannel directly on soft polymer, by increasing the stiffness of the workpiece surface by reducing cryogenic chamber temperature. However, because of large temperature difference at various position of the cooling area inside the chamber, under cryogenic cooling condition, determination of workpiece temperature at machining time is very difficult. Unfortunately, very limited research work has investigated the complicated physical phenomena of cryogenic cooling responsible for temperature distribution occurring inside the chamber during machining process. These phenomena may affect the cryogenic flow characteristics in over or under-cooling of soft polymer as workpiece, thus the performance of the cryogenic machining. In this work, computational fluid dynamic (CFD) model is developed and applied to investigate the liquid nitrogen (LN 2 ) flow inside the cryogenic chamber under direct cooling (DC) and novel perforated wall cooling (PWC) techniques. The major objective is to evaluate the influence of several parameters (temperature and pressure) on the LN 2 flow inside the chamber and role of the innovative PWC technique in temperature distribution with comparison to DC approach. Results of this study offer two important conclusions for reliable cryogenic micromilling of soft polymer. First, uniform temperature distribution inside the chamber is possible by novel PWC approach and second, peripheral temperature of the chamber shows less fluctuation with surface temperature of the workpiece.

Journal of Micromanufacturing
Indian Institute of Technology Patna (IN)
Openalex Percentile: Top 35%
Advanced machining processes and optimization
0.64
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