Abstract:It is well-known that buses comprise an important part of mass transportation and that there are many types of buses.At present, the bus transportation is cheaper and easier to use than other means of transportation. However, buses have some disadvantages such as air pollution due to engine exhaust. This study is an attempt to reduce the gas emissions from buses by reducing the aerodynamic drag. Several ideas were applied to achieve this goal including slight modification of the outer shape of the bus. Thus, six different cases were investigated. A computational model was developed to conduct this study. It was found that reduction in aerodynamic drag up to 14% can be reached, which corresponds to 8.4 % reduction in fuel consumption. Also, Neuro-Fuzzy technique was used to predict the aerodynamic drag of the bus in different cases.
Malls like any retailing centers face exposure for a host of risks including fire, which is no stranger to shopping malls. Fires in closed malls, patronized by lots of people, can cause many fatalities among panicked people running and pushing to get out of these burning places and great damage to the property itself. This computational study covers the possibilities of smoke propagation and evacuation due to hazardous fires in a large shopping center (mall) in Makkah, Saudi Arabia. The mall occupies 50,753 m 2 and has two main floors. It contains 144 stores in the ground floor and 56 stores in the upper floor. It has five gates, one elevator, four escalators and five emergency exit stairs. The study is divided into two parts. Part I concerns four scenarios of fire simulation. Part II considers corresponding four scenarios of evacuation. The present results explain how fast the smoke may spread in such buildings and its mechanism to move from one floor to another. The smoke propagation/movement is highly affected by the architecture of the building and the type of activities inside it.
Heat recovery wheels represent key components in air handling units (AHU) that can be used in commercial and industrial building airconditioning systems for energy saving. For example, in health facilities, heat transfer process is to be applied in airconditioning systems for heat recovery of the exhaust (return) air from the patient's room without contamination. Thus, heat recovery wheels are much suitable for such applications. Heat recovery wheels are also known as heat conservation wheels. A conservation wheel consists of a rotor with permeable storage mass fitted in a casing, which operates intermittently between two sections of hot and cold fluids. The rotor is driven by a low-speed electric motor. Thus, the two streams of exhaust and fresh air are alternately passed through the wheel. The present investigation considers computationally the different parameters that affect the operation of heat recovery wheels. These parameters signify actual operating conditions such as flow velocity, shape of cross-section of flow path, and wall material. Moreover, both the artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques were utilized to predict the critical characteristics of the heat exchange system. These artificial intelligence techniques use the present computational results as training and verification data.
Development is an ongoing process in all areas and this research studied of a cooling system for a local factory and evaluated to determine the efficiency and capacity of the cooling capacity of the factory at the desired level. ِAfter evaluating the cooling system and studying the case of the local factory, the heat gain loads in the factory was calculated internally and externally and found that there is a deficit in the cooling system by 45% and the suggestion is to improve the cooling system without affecting production or manpower. Accordingly, three points have been developed to improve the cooling system and the first point is reducing the heat gained from lighting by changing fluorescent bulbs by the LED and this step will reduce the heat gain from lighting by 64%. The second point is to reduce the volume space of production zones by installing the ceiling of the gypsum board where the height was reduced from eight to five meters, which reduced the heat gained by 37% from the walls. The third point is the installation of better insulation materials and has been proposed rock wool material for the roof and the material Rigid expanded board for walls and these materials have reduced 85% of the heat gain from the roof and 20% of the walls. The total rate of improvement in the cooling system completely (internal and external heat gain) is 25% or in other words, can be through the implementation of these points reduce cooling load by 25%.
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