Mepco Schlenk Engineering College

About: Mepco Schlenk Engineering College is a based out in . It is known for research contribution in the topics: Wavelet & Wavelet transform. The organization has 1307 authors who have published 1665 publications receiving 18690 citations.

Effect of 1,4-Dioxane Emulsified Fuel on Diesel Engine Performance and Emission Operating with Varying Injection Timing

Abstract: Numerous investigations were executed in the past to test the impact of emulsion fuels on the diesel engine to reduce the engine-out emissions and salvage the fossil fuel from depletion. This investigation intends to reduce emission and improve the performance of direct ignition (DI) diesel engines through 1,4-dioxane emulsified fuel along with different injection timings. The test fuel (DWSD) was made with 79.8% diesel, 10% water, 10% 1,4-dioxane and 0.2% surfactant. The surfactant used in the preparation is Triton X-100. The test was evaluated with three different injection timings of 19°, 23° and 27° before top dead center (bTDC), and the results were equated with diesel fuel operating at normal timing of 23° bTDC. Brake thermal efficiency (BTE) for 1,4-dioxane emulsified fuel was predominant at 23° and 27° bTDC when compared with diesel fuel. Brake-specific energy consumption (BSEC), carbon monoxide (CO) and unburned hydrocarbon (HC) decreased for 1,4-dioxane emulsified fuel at 27° bTDC. Besides, oxides of nitrogen (NOx) escalated in the advanced injection timing. To sum up, except for NOx, 1,4-dioxane performed better at the injection timing of 27° bTDC concerning the performance and emissions.

Improvement on the machinability characteristics of AA6061-T6/15 wt. % SiC composites by Response Surface methodology

Abstract: A widely used material in engineering is aluminium reinforced with fillers called aluminium matrix composites (AMC). AA6061-T6 was selected as a matrix material in the present study, and silicon carbide (SiC) was chosen as the reinforcement, and the stir casting process produced the same. In the current study, the machining of AA6061-T6/15wt. % SiC composites were carried out using wire electrical discharge machining (WEDM). The input process parameter selected were pulse on (TON), pulse off time (TOFF) and current (IP), whereas responses considered are material removal rate (MRR) and surface roughness. The experiments were carried according to a central composite rotatable design based on Response Surface Methodology (RSM). Analysis of variance (ANOVA) was used to study how input parameters affect output parameters. To obtain improved MRR and decreased surface roughness value, the output was optimised using Desirability Function Analysis (DFA). The results show that factors such as TON, TOFF, and IP are significant variables that influenced MRR and Ra. When TON and IP were increased, there was an increase in MRR and Ra, while when TOFF decreased, it decreased MRR and Ra. Optimisation results revealed that for MRR, optimum parameters are TON set at 2µs and TOFF set at 16 µs and IP by 187.272 A. In surface roughness, the parameters are TON set by 2 µs, TOFF set by 16 µs and IP set by 120 A.

A literature review on hybrid flow shop scheduling

Abstract: Scheduling problems are one of the widely used problems which have both academic and real-life applications. In academic fields, it can be used to test the efficiency of a newly developed solution techniques. As it is known to be NP-hard, these problems are keystones to show the performance of a new or improved method, especially metaheuristics. Apart from the standard scheduling problems, one of its challenging sub-problem is hybrid flow shop (HFS) scheduling. Except from the literature survey of Ruiz and Vazquez-Rodriguez (2010), no recent analysis is given to give the new solution trends in HFS. To solve this missing piece, in this study 219 HFS articles from 2010-2019 period are analysed with the main focus of metaheuristic techniques. Also, analysis based on the citations are given.

De-noising and baseline wandering removal of electrocardiogram using double density discrete wavelet

Abstract: In this paper, an off-line double density discrete wavelet transform based de-noising and baseline wandering removal methods are proposed. Different levels decomposition is used depending upon the noise level, so as to give a better result. When the noise level is low, three levels decomposition is used. When the noise level is medium, four levels decomposition is used. When the noise level is high, five levels decomposition is used. Soft threshold technique is applied to each set of wavelet detail coefficients with different noise level. Donoho's estimator is used as a threshold for each set of wavelet detail coefficients. The results are compared with other classical filters and improvement of signal to noise ratio is discussed. Using the proposed method the output signal to noise ratio is 19.7628 dB for an input signal to noise ratio of -7.11 dB. This is much higher than other methods available in the literature. Baseline wandering removal is done by using double density discrete wavelet approximation coefficients of the whole signal. This is an unsupervised method allowing the process to be used in off-line automatic analysis of electrocardiogram. The results are more accurate than other methods with less effort.