Jordan is a country with highly fossil fuel deficiency and thus other energy sources are needed to be explored. Solar energy in Jordan is highly recognized as a good source of energy and an excellent substitute to the fossil fuel. The solar energy in this article is obtained via data bases and modeling techniques for the specified place coordinate and angle of inclination. The angles of sun irradiations are different throughout the year; therefore solar energy needs to be magnified by optimizing the angle of inclination of solar cells. In this research, the optimized angles throughout the year are obtained to be in the range: 10˚ -60˚. Solar energy can serve the residential building, the findings of this research show that every 1 m 2 of the solar cell may contribute to about 60% -70% of customer needs of electricity throughout the year. The application of solar energy concept in the design of building will play an important role in energy sustainability.
Highway Capacity Manual (HCM) assumes that traffic flow rates are equally distributed between lanes, which is not always the case. Lane distribution and speed are influenced by lateral clearance on the roadsides. In Jordan, the absence of well-marked lanes and poor lane discipline results in under-utilizing of the freeway capacity. The objective of this study is to look into the impact of the presence of roadside objects on lane distribution and speed. Test sections were selected on six-lane freeway segments located in sub-urban areas on tangent highway segments. Speed measurements and distribution counts made for each lane on a directional three-lane segment of the freeway. The results showed that lane distribution significantly varies depending on lateral clearance and traffic. As lateral displacement increases, right-lane-use and left-lane-use increases while the middle-lane use remains almost at the same level. Average speed increases as the lateral clearance increases. The results also showed that average speed and lane distribution for 1.5m lateral clearances are very similar to no obstacle conditions. The impact of an obstacle is more significant on the right lane while the use of the left lane fluctuates with a significant increase if traffic flow rates reach high levels.
The mechanical strength, mass loss and dynamic elastic modulus of Portland cement concrete incorporating recycled glass powder (GP) as a cement replacement material or crushed glass aggregate (GA) as a fine aggregate replacement material subjected to different cycles of freezing and thawing were investigated. A series of 11 concrete mixing proportions was designed with a constant water/cement ratio of 0·5 including fractions of GP or GA. Tests were conducted on 100 × 100 × 100 mm cubes, 100 × 200 mm cylinders and 100 × 100 × 500 mm prisms. The tests of compressive strength, flexural strength and indirect tension were used to examine the impact of the inclusion of different percentages of glass (GP or GA) on the mechanical properties of concrete cured for 7, 28 and 60 d. Two non-destructive testing approaches (ultrasonic pulse velocity and resonance frequency) were used in the freezing and thawing test. The test results indicated that, compared with conventional concrete, the mechanical strength characteristics of concrete containing GP or GA were more enhanced. The use of GP decreased the deterioration of the concrete under the effect of frost action, whereas the use of GA had an adverse influence on the frost resistance of the concrete.
The aim of this study is to control the performance of wastewater treatment plants for treating inorganic materials. Samples of wastewater were investigated along a year. Fuzzy logic modeling procedures were performed onto investigational data to explore with time the concentrations of inorganics in aeration tanks at two stations in Jordan. Model results show that biological treatment of wastewater is not effective to decrease the concentration of inorganic materials. The concentration of each inorganic material at given time and place is being tracked via Fuzzy system. Sugeno-Fuzzy Inference System (FIS) is herein generated by subtractive clustering. The rule extraction method first uses the subtractive clustering function to determine the number of rules and antecedent membership functions and then uses learning estimation to determine each rule's consequent equations. Training technique is conducted using hybrid learning algorithm. It applies a combination of the least-squares method and the back propagation gradient descent method for training FIS membership function parameters to emulate a given training data set. Intelligent monitoring system is then applied; sensors and data logger system provide inputs to fuzzy logic controller. The fuzzy controller uses the FIS generated from experimental data and then the monitor about certain inorganic compound is achieved. The idea of this study is to track inorganic materials concentration at place and time together in the same model that is handy to check it promptly. It provides dynamic control system that is not only records data about concentrations but also gives a decision to comply with standards.
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