Performance Evaluation of a GM-Type Double Inlet Pulse Tube Refrigerator Using Artificial Intelligence Approach with Experimental Validation

Panda, Debashis; Kumar, Manoj; Satapathy, Alok; Sarangi, Sunil; Sahoo, Ranjit Kumar

doi:10.1007/s13369-020-04685-2

Cited by 1 publication

(1 citation statement)

References 52 publications

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“…Researchers have done CFD analysis of PTC for different geometrical and operational parameters with 2D axisymmetric [25,26] and 3D plane-symmetric models [27,28]. For optimization of PTC, CFD models [29] and various artificial intelligence methods like ANN, PSO-ANN, and ANFIS method are used to attain maximum refrigeration and Coefficient of Performance (COP) by giving an optimum range of inputs [30][31][32]. Panda et al [32] revealed that refrigerating capacity and COP increased by 10.8% and 0.76% respectively.…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis of double inlet two-stage inertance pulse tube cryocooler

Choudhari¹,

Gawali²,

Momin³

et al. 2021

IJATEE

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Stirling-type Pulse Tube Cryocoolers (PTC) are designed to meet present and upcoming commercial requirements and needs with durability and low vibrations. Multistaging in Stirling type PTC is one of the major developments reported in recent times for low-temperature achievement, due to improved performance over a period of time. The current study aims to define the methodology for numerical assessment of Double Inlet Two-Stage Pulse Tube Cryocooler (DITSPTC) to achieve cryogenic temperature of 20 K. This paper performs Computational Fluid Dynamics (CFD) simulation of PTC for defining the methodology using the CFD software package and then the same methodology is extended for the analysis ofDITSPTC. The system simulations are performed with frequency of 70 Hz and average pressure of 20 bar. The minimum temperatures obtained from simulations are 95 K and 20 K at the first and second stage respectively.

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