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:
In this study, the temperature profile of the sodium nitrate phase change material NaNO3 is characterized, using a spherical macro encapsulation technique to increase the heat transfer properties, simulating through computer tools the behavior of this material when it is used as an alternative source of energy for heat. exchange processes, where the primary energy source has interruptions in the heat supply, the data obtained show for the proposed model that the system is capable of maintaining the outlet temperature for at least 20s and a temperature drop of 50K for 60s, being promising data for the use of these materials in heat exchange processes as is the energy support of solar collectors
Internet of Things (IoT) is now one of the most challenging research fields that still has much to be discovered. Since it consists of a wide range of elements like devices, humans, animals, and others, there is a big need to find a simple way of its network simulation. Although there were previous trials to do this, a need exists to combine both modeling and simulation of IoT networks in one frame. In this work we propose a crossbreed approach that enables specialists to display IoT and reproduce OMNeT++, through giving mapping rules between the operator worldview and the OMNeT++ test system. The PDR and RTT results are plotted by varying the number of smart objects (SOs) and subnets for both large and low number scales. Increasing the number of subnetworks in a specific region badly influences both RTT and PDR