Finite element based fatigue life prediction of cylinder head for two-stroke linear engine using stress-life approach

Abstract: This describes the finite element based fatigue life prediction of cylinder head for two-stroke linear engine subjected to variable amplitude loading applicable to electric power generation. A set of Al-alloys, cast iron and forged steel for cylinder head are considered in this study

In-cylinder heat transfer characteristics of hydrogen fueled engine: a steady state approach

Abstract: This study presents in-cylinder heat transfer characteristics of a single cylinder port injection Hydrogen fueled Internal Combustion Engine (H2ICE) using a steady state approach. Problem statement: The differences in characteristics between hydrogen and hydrocarbon fuels are led to the difference in the behavior of physical processes during engine cycle. One of these processes is the in-cylinder heat transfer. Approach: One dimensional gas dynamic model was used to describe the heat transfer characteristics of the engine. The engine speed was varied from 2000-5000 rpm, crank angle from -40° to +100°, while Air-Fuel Ratio (AFR) was changed from stoichiometric to lean limit. Results: The simulated results showed higher heat transfer rate but lower heat transfer to total fuel energy ratio with increasing the engine speed. The in-cylinder pressure and temperature were increased with decreasing AFR and increasing engine speed. The in-cylinder air flow rate was increased linearly with increasing engine speed as well as air fuel ratio. Conclusion/Recommendations: The results showed that the AFR has a vital effect on characteristics variation while the engine speed has minor effect. These results can be utilized for the study of combustion rocess, fuel consumption, emission production and engine performance

Impact of Partial Update on Denoising Algorithms of ECG Signals

This work aims to propose and study the effects of partial update procedure on various ECG denoising algorithms. The partial update algorithms are applied to overcome different types of noises such as Power-Line Interference (PLI), Baseline Wander (BW), Electrode Motion artifacts (EM) and Muscle Artifacts (MA). The impact of partial update (PU) on multiple algorithms and spatially adaptive filters and multi-layer Neural Network (NN) are studied and demonstrated. The performance of different algorithms are evaluated by measuring the Signalto-Noise Ratio after cancellation (Post-SNR), the Mean Square Error (MSE) and the Percent Root Mean Square Difference (PRD%)

Screening for diabetes in Kuwait and evaluation of risk scores

This study aimed to develop a simple risk score to identify individuals at high risk for undiagnosed diabetes in the Kuwaiti adult population and to assess the performance of previously published diabetes risk scores. A cross-sectional survey with a sample of 562 Kuwaiti public sector employees was carried out in 2007. Data were collected through a self-administered questionnaire and a blood glucose test. The overall prevalence of diabetes using American Diabetes Association 2003 criteria was 21.4% (4.1% newly detected). The proposed score had 87% sensitivity and 64% specificity in predicting undetected diabetes using only 4 questions (age, waist circumference, use of blood pressure medication and diabetes in asibling). Most previously published risk scores were not applicable to this population

Bioremediation of copper stressed Trigonella foenum graecum

Copper is one of the heavy metals, although it is an essential microelement through interference with numerous physiological processes, when it absorbed in excess amounts, it can be toxic and induce a number of deleterious effects. A pot experiment was conducted in order to assess the possible effects of Nostoc muscorum (2 g/ kg soil fresh pellets) on the growth and some metabolic activities of Trigonella foenum gracum at 30 and 60 days of growth growing under copper stress. This experimental plant was grown in clay-sandy soil (2:1 W/W) amended either with different concentrations of CuSO4 (0.4, 0.6, 0.8 and 1.0 g/kg soil) or Nostoc mixed with Cu (0.6, 0.8 and 1.0 g/kg soil). Application of Nostoc in a mixture with Cu significantly increased fresh and dry weight of root and shoot, photosynthetic pigments and ctivity at 30 and 60 days of growth when compared with their counterparts of Cu treatment. In addition, the content of K+, Ca2+, P3+ and iron were increased with the exception of a decrease in Cu level at 60 days of growth. On the other hand, the content of starch was significantly decreased at 30 and 60 days of growth. Moreover, the activity of both peroxidase (POD) and superoxide dismutase (SOD) were reduced by applying Nostoc to the soil having different concentrations of Cu

Hybrid CFD-ANN Scheme for Air Flow and Heat Transfer Across In-Line Flat Tubes Array

Flat tubes are vital components of various technical applications including modern heat exchangers, thermal power plants, and automotive radiators. This paper presents the hybridization of computational fluid dynamic (CFD) and artificial neural network (ANN) approach to predict the thermal-hydraulic characteristics of in-line flat tubes heat exchangers. A 2D steady state and an incompressible laminar flow in a tube configuration are considered for numerical analysis. Finite volume technique and body-fitted coordinate system are used to solve the Navier–Stokes and energy equations. The Reynolds number based on outer hydraulic diameter varies between 10 and 320. Heat transfer coefficient and friction are analyzed for various tube configurations including transverse and longitudinal pitches. The numerical results from CFD analysis are used in the training and testing of the ANN for predicting thermal characteristics and friction factors. The predicted results revealed a satisfactory performance, with the mean relative error ranging from 0.39% to 5.57%, the root-mean-square error ranging from 0.00367 to 0.219, and the correlation coefficient (R2) ranging from 99.505% to 99.947%. Thus, this study verifies the effectiveness of using ANN in predicting the performance of thermal-hydraulic systems in engineering applications such as heat transfer modeling and fluid flow in tube bank heat exchangers