Experimental and simulation studies on the performance of standing wave thermoacoustic prime mover for pulse tube refrigerator

The thermoacoustic prime mover (TAPM) has gained considerable attention as a pressure wave generator to drive pulse tube refrigerator (PTR) due to no moving parts, reasonable efficiency, use of environmental friendly working fluids etc. To drive PTCs, lower frequencies (f) with larger pressure amplitudes (Delta P) are essential, which are affected by geometric and operating parameters of TAPM as well as working fluids. For driving PTRs, a twin standing wave TAPM is built and studied by using different working fluids such as helium, argon, nitrogen and their binary mixtures. Simulation results of DeltaEc are compared with experimental data wherever possible. DeltaEc predicts slightly increased resonance frequencies, but gives larger Delta P and lower temperature difference Delta T across stack. High mass number working fluid leads to lower frequency with larger Delta P, but higher Delta T. Studies indicate that the binary gas mixture of right composition with lower Delta T can be arrived at to drive TAPM of given geometry. (C) 2013 Elsevier Ltd and IIR. All rights reserved.

Experimental investigation of a thermoacoustic refrigerator driven by a standing wave twin thermoacoustic prime mover

The objective of this study is to analyse the performance of thermoacoustic refrigerator (TAR) measured in terms of hot end temperature and temperature difference across refrigerator stack with two different spacing namely 0.4 mm and 0.8 mm and stack used in refrigerating section was made of low thermal conductivity materials namely Mylar sheet and photographic film & the experiments were carried out at 1 MPa pressure using helium as working fluid. High powered acoustic wave with frequency of 460 Hz and pressure amplitude of congruent to 0.07 MPa was obtained from twin thermoacoustic prime mover (TAPM) and this acoustic wave produced temperature difference of 16 degrees C across the Mylar sheet stack made of 0.4 mm spacing in refrigerator section. From this study, it has been inferred that twin TAPM can act as efficient drive for TAR. (C) 2013 Elsevier Ltd and IIR. All rights reserved.

Spatially Adaptive Kernel Regression Using Risk Estimation

An important question in kernel regression is one of estimating the order and bandwidth parameters from available noisy data. We propose to solve the problem within a risk estimation framework. Considering an independent and identically distributed (i.i.d.) Gaussian observations model, we use Stein's unbiased risk estimator (SURE) to estimate a weighted mean-square error (MSE) risk, and optimize it with respect to the order and bandwidth parameters. The two parameters are thus spatially adapted in such a manner that noise smoothing and fine structure preservation are simultaneously achieved. On the application side, we consider the problem of image restoration from uniform/non-uniform data, and show that the SURE approach to spatially adaptive kernel regression results in better quality estimation compared with its spatially non-adaptive counterparts. The denoising results obtained are comparable to those obtained using other state-of-the-art techniques, and in some scenarios, superior.