Experimental Investigation of Adiabatic Film Cooling Effectiveness and Heat Transfer Coefficients over a Gas Turbine Blade Leading Edge Configuration

Increasing the rotor inlet temperature is one of the key technologies in raising gas turbine engine performance, for which the turbine blades need to be cooled. Film cooling is one of the efficient cooling techniques to cool the hot section components of a gas turbine engines. In film cooling, a gas which is cooler than the main stream is passed onto the external surface via small slots or rows of holes within the surface. In the present study, the experimental investigation was conducted for an adiabatic film effectiveness and heat transfer coefficients over a gas turbine blade leading edge model at a subsonic cascade tunnel facility of CSIR-National Aerospace Laboratories, Bangalore. This study aims at investigating the effect of blowing ratio on the adiabatic film cooling effectiveness and heat transfer coefficients experimentally for the 20 Degree hole inclination angles gas turbine blade leading edge model. The blade leading edge model was fabricated using the Rapid Proto Typing method using a very low thermal conductivity nylon based alloy material. This study aims at bringing the optimized blowing ratio values for the considered hole diameter of leading edge configuration. The comparative results showed that the blowing ratio beyond 2.0 does not have any improvement in the adiabatic film cooling effectiveness

Synthesis, structure and ionic conductivity in scheelite type Li_0.5Ce_0.5-xLn_xMoO₄ (x = 0 and 0.25, Ln = Pr, Sm)

Scheelite type solid electrolytes, Li0.5Ce0.5-xLnxMoO4 (x = 0 and 0.25, Ln = Pr, Sm) have been synthesized using a solid state method. Their structure and ionic conductivity (σ) were obtained by single crystal X-ray diffraction and ac-impedance spectroscopy, respectively. X-ray diffraction studies reveal a space group of I41/a for Li0.5Ce0.5-xLnxMoO4 (x = 0 and 0.25, Ln = Pr, Sm) scheelite compounds. The unsubstituted Li0.5Ce0.5-xLnxMoO4 showed lithium ion conductivity ∼10−5-10−3 Ω−1cm−1 in the temperature range of 300-700°C (σ = 2.5 × 10−3 Ω−1cm−1 at 700°C). The substituted compounds show lower conductivity compared to the unsubstituted compound, with the magnitude of ionic conductivity being two (in the high temperature regime) to one order (in the low temperature regime) lower than the unsubstituted compound. Since these scheelite type structures show significant conductivity, the series of compounds could serve in high temperature lithium battery operations

A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

Purpose: To develop a deep learning approach to de-noise optical coherence tomography (OCT) B-scans of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device (Spectralis) for both eyes of 20 subjects. For each eye, single-frame (without signal averaging), and multi-frame (75x signal averaging) volume scans were obtained. A custom deep learning network was then designed and trained with 2,328 "clean B-scans" (multi-frame B-scans), and their corresponding "noisy B-scans" (clean B-scans + gaussian noise) to de-noise the single-frame B-scans. The performance of the de-noising algorithm was assessed qualitatively, and quantitatively on 1,552 B-scans using the signal to noise ratio (SNR), contrast to noise ratio (CNR), and mean structural similarity index metrics (MSSIM). Results: The proposed algorithm successfully denoised unseen single-frame OCT B-scans. The denoised B-scans were qualitatively similar to their corresponding multi-frame B-scans, with enhanced visibility of the ONH tissues. The mean SNR increased from $4.02 \pm 0.68$ dB (single-frame) to $8.14 \pm 1.03$ dB (denoised). For all the ONH tissues, the mean CNR increased from $3.50 \pm 0.56$ (single-frame) to $7.63 \pm 1.81$ (denoised). The MSSIM increased from $0.13 \pm 0.02$ (single frame) to $0.65 \pm 0.03$ (denoised) when compared with the corresponding multi-frame B-scans. Conclusions: Our deep learning algorithm can denoise a single-frame OCT B-scan of the ONH in under 20 ms, thus offering a framework to obtain superior quality OCT B-scans with reduced scanning times and minimal patient discomfort

Courage and nobility in sport – anecdotes from cricket

We are both unabashed cricket romantics and believe that however much the external attributes of cricket may have changed, the quintessential qualities of courage and nobility remain forever entwined with the game. In this essay we will describe why courage and nobility in sport is such a moving emotion and ennobling aspect of the game