Heat transfer process and fluid flow in a solar chimney used for natural ventilation are investigated numerically in the present work. Solar chimney was tested by selecting different positions of absorber namely: at the back side, front side, and at the middle of the air gap. CFD analysis based on finite volume method is used to predict the thermal performance, and air flow in two dimensional solar chimney under unsteady state condition, to identify the effect of different parameters such as solar radiation. Results show that a solar chimney with absorber at the middle of the air gap gives better ventilation performance. A comparison between the numerical and previous experimental results shows fair agreement.

Creep testing is an important part of the characterization of composite materials. It is crucial to determine long-term deflection levels and time-to-failure for these advanced materials. The work is carried out to investigate creep behavior on isotropic composite columns. Isotropy property was obtained by making a new type of composite made from a paste of particles of carbon fibers mixed with epoxy resin and E-glass particles mixed with epoxy resin. This type of manufacturing process can be called the compression mold composite or the squeeze mold composite. Experimental work was carried out with changing the fiber concentration (30, 40 and 50% mass fraction), cross section shape, and type of composite. The creep results showed that th

The two dimensional steady, combined forced and natural convection in vertical channel is
investigated for laminar regime. To simulate the Trombe wall channel geometry properly, horizontal
inlet and exit segments have been added to the vertical channel. The vertical walls of the channel are
maintained at constant but different temperature while horizontal walls are insulated. A finite
difference method using up-wind differencing for the nonlinear convective terms, and central
differencing for the second order derivatives, is employed to solve the governing differential
equations for the mass, momentum, and energy balances. The solution is obtained for stream
function, vorticity and temperature as dependent variables

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

Abstract  

All central air conditioning systems contain piping system with various components, sizes, material, and layouts. If such systems in operating mode, the flow in piping system and its component such as valves can produce severe vibration due to some flow phenomenon’s. In this research, experimental measurements and numerical simulation are used to study the flow-induced vibration in valves. Computational fluid dynamics (CFD) concepts are included with one-way and two-way fluid-structure interaction concepts by using finite element software Package (ANSYS 14.57). Detection analysis is performed on flow characteristics under operation conditions and relations with structural vibration. Most of

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai