Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
There are 3 main types of wind turbines, their difference lies mainly in their type of rotor, the direction of their axis, and the shape of their blades. For the vertical axis, wind turbines are the Darrieus, Giromill, and Savonius. In the present study, a simulation of a variant of the savonius rotor is made by adapting an aerodynamic profile on its blades based on the design characteristics of a NACA 6506 profile. For the execution of the same, there will be a solid modeling software, in which will generate the geometry and physical characteristics of the selected design to be used in the savonius rotor variant, after this and with the help of Computational Fluid Dynamics (CFD) simulation, the fluid-dynamic behavior is evaluated, and the coefficient of performance of the same. Results were obtained from the comparison between the behavior of the designed rotor concerning its conventional savonius shape, where its generated power, power coefficient, and reached speeds are shown, analyzing that the adaptation of an aerodynamic profile improves the behavior of the rotor as it increases wind speed
Due to the huge number of devices that will connected in the near future within the Internet environment, this will lead to significant momentum in the data exchange over the Internet, which will reduce the speed of data transfer and reduce the speed of data processing reaching inefficient work, that leading to inability to meet the requirements of work. The future is Internet of Things (IoT), ability to incorporate intelligence devices to make use of contextual information, collecting information’s with the regards of a given situation to select appropriate path with the huge numbers of device and applications, the key idea is that rather than sending acknowledge across the network, the problem is high energy consumption, increase time delay and may cause an unbalanced load in a network. Therefore, we propose an efficient protocol that addresses these cases in order to increase the efficiency of the work to an acceptable level. In this paper, the design of the protocol based on distribute Learning, information’s of each nodes (things), these factors are exchanged among neighbors. Each node allows sharing their information’s with rounding neighbors to achieve additional information about the adapting routing in the network and each node such as a system that can use local information gathered from neighbors. This proposal based on three basic principles: Energy consumption, time delay and load balancing
