Tube‐in‐tube heat exchangers are widely used in food processing industries and wastewater treatment for both heating and cooling. Enhancement techniques namely active, passive, and compound are developed to reduce the thermal resistance in heat exchangers by improving convective heat transfer with or without increase in surface area. The present experimental study is aimed at analyzing the influence of vibrations on the convective heat transfer of a parallel flow tube‐in‐tube heat exchanger. The heat exchanger is placed in horizontal position and is subjected to transverse vibrations under turbulent fluid flow conditions. Experiments were performed at four frequencies (20, 40, 60, and 100 Hz), three amplitudes (1, 2, and 3 m/s2), and three vibration generator positions along its length, in the Reynolds number range of 10 710 to 21 420. An enhancement in Nusselt number is found with vibration than without vibration throughout the entire range of Reynolds numbers. A maximum enhancement of 33% at 40 Hz frequency, 3 m/s2 amplitude, and vibration generator position at three‐fourth of the tube length was observed. Empirical correlations are developed for Nusselt number to determine the heat transfer coefficient with vibration with an error of ±10%.
Purpose This paper aims to deal with heat transfer enhancement because of transverse vibration on counter flow concentric pipe heat exchanger. Experiments were performed at different vibrator positions with varying amplitudes and frequencies. Design/methodology/approach Tests are carried out at 4 different vibration frequencies (20, 40, 60 and 100 Hz), 3 vibration amplitudes (23, 46 and 69 mm) and at 3 vibrator positions (1/4, 1/2 and 3/4 of pipe length) with respect to hot water inlet under turbulent flow condition. Findings Experimental results indicate that Nusselt number is enhanced to a maximum extent of 44% with vibration when compared to Nusselt number without vibration at a frequency of 40 Hz, an amplitude of 69 mm and at a vibrator position of one-fourth of pipe length with respect to hot water inlet. Originality/value Empirical correlation is developed from experimental data to estimate the heat transfer coefficient with vibration for experimental frequency range with an error estimate of approximately ±10%.
This paper describes experimental investigations on convective heat transfer in counter flow double pipe heat exchanger under transverse vibration for single-phase flow with twisted tape insert in the inner tube. Experiments were conducted on twisted tape inserted counter flow double pipe heat exchanger under vibration for twist ratio from 7 to 17, amplitude from 23 to 69 mm, frequency from 20 to 100 Hz and Reynolds number (Re) changing from 10710 to 21420. A maximum gain of 91% in Nusselt number (Nu) was obtained at 40 Hz frequency and 69 mm amplitude for twist ratio of 7 and Re of 10710. The maximum value of performance evaluation criteria with compound enhancement technique on double pipe heat exchanger reached 1.38 in turbulent flow conditions. Empirical correlations for Nu were developed and predicted values were found to be within ± 9% of experimental values for both frequency ranges.
Purpose This paper aims to deal with the optimization of engine operational parameters such as load, compression ratio and blend percentage of fuel using a combined approach of particle swarm optimization (PSO) with Derringer’s desirability. Design/methodology/approach The performance parameters such as brake thermal efficiency (BTHE), brake specific fuel consumption (BSFC), CO, HC, NOx and smoke are considered as objectives with compression ratio, blend percentage and load as input factors. Optimization is carried out by using PSO coupled with the desirability approach. Findings From results, the optimum operating conditions are found to be at compression ratio of 18.5 per cent of fuel blend and 11 kg of load. At this input’s parameters of the engine, outputs performance parameters are found to be 34.84 per cent of BTHE, 0.29 kg/kWh of BSFC, 2.86 per cent of CO, 13 ppm of HC, 490 ppm of NOx and 26.25 per cent of smoke. Originality/value The present study explores the abilities of both particle swarm algorithm and desirability approach when used together. The combined approach resulted in faster convergence and better prediction capability. The present approach predicted performance characteristics of the variable compression ratio engine with less than 10 per cent error.
Purpose The present work aims at improving the performance of the engine using optimized fuel injection strategies and operating parameters for plastic oil ethanol blends. To optimize and predict the engine injection and operational parameters, response surface methodology (RSM) and artificial neural networks (ANN) are used respectively. Design/methodology/approach The engine operating parameters such as load, compression ratio, injection timing and the injection pressure are taken as inputs whereas brake thermal efficiency (BTHE), brake-specific fuel consumption (BSFC), carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NOx) and smoke emissions are treated as outputs. The experiments are designed according to the design of experiments, and optimization is carried out to find the optimum operational and injection parameters for plastic oil ethanol blends in the engine. Findings Optimum operational parameters of the engine when fuelled with plastic oil and ethanol blends are obtained at 8 kg of load, injection pressure of 257 bar, injection timing of 17° before top dead center and blend of 15%. The engine performance parameters obtained at optimum engine running conditions are BTHE 32.5%, BSFC 0.24 kg/kW.h, CO 0.057%, HC 10 ppm, NOx 324.13 ppm and smoke 79.1%. The values predicted from ANN are found to be more close to experimental values when compared with the values of RSM. Originality/value In the present work, a comparative analysis is carried out on the prediction capabilities of ANN and RSM for variable compression ratio engine fuelled with ethanol blends of plastic oil. The error of prediction for ANN is less than 5% for all the responses such as BTHE, BSFC, CO and NOx except for HC emission which is 12.8%.
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