Background: Heat exchanger is a device in many industrial applications and energy conversion systems. Various heat exchangers are designed for different industrial processes and applications. Shell and tube heat exchanger (STHE) has its own importance in the process industries. Methods: Experimental and numerical simulations are carried for a single shell and multiple pass heat exchangers with different tube geometries i.e. circular tubes to elliptical tubes. The experiment was carried out with hot fluid in tube side and cold fluid in shell side with circular tubes at 600 tube orientation and 25 % baffle cut. Heat transfer rates and pressure drops are calculated for various Reynolds numbers from 4000 to 20000. Fluent software is used for numerical investigations. Both circular and elliptical tube geometries with 450,600 and 900 orientations are used for the numerical studies. In addition to 25 % baffle cut, quarter baffle cut and mirror quarter baffle cut arrangements are used for comparison. The experimental values of heat transfer rates and pressure drops over shell side and tube side along the length of STHE are compared with those obtained from fluent software. Results and Conclusion: It is found that the elliptical tube geometry with mirror quarter baffle cut at 450 tube orientation is 10 % higher than existing shell and tube heat exchanger and the pressure drop decrement in tube side shows up to 25 %.
Heat-transfer has been performed on a sandwich thermal protection system (TPS) for future flight vehicles. The sandwich structures are built from thin walled metal sheets. These structures as a part of the airframe outer cover provide thermal protection to the interior parts mounted inside the vehicle. The temperature protection materials used for sandwich structures should have high strength even at the elevated temperatures. It is easier to simulate the 150 0 C (after 150 0 C material properties are changed) temperature on the Aluminium sandwich structures and find the temperature gradient across the sandwich depth. Though the experiment was done on hexagonal cells honeycomb, the ANSYS analyses have been done for both square cell's sandwich panel and hexagonal honeycomb panel for comparison. Experiments are done on using Al alloy honeycomb sandwich panels and the validations of experimental work using ANSYS analysis have been performed. ANSYS modeling, analysis has been done for both, the square and hexagonal honeycomb sandwich panels of the Al alloy. This paper focuses on the heat transfer analysis and in exploring the ways to reduce the heat transfer effect with the methods mentioned above, which could be effectively used for flight vehicle applications.
Almost all thermal/chemical industries are equipped with heat exchangers in order to enhance the thermal efficiency. The performance of a shell and tube heat exchanger depends significantly on the design parameters like the tube crosssectional area, tube orientation, baffle cut, etc. However, there are no specific relationships among these parameters to obtain an optimal design, such that the heat transfer rate is maximized and the pressure drop is minimized. Therefore, experimental and numerical simulations are carried out for a heat exchanger at various process parameters. Heat exchanger considered in this investigation is a single shell-multiple pass type device. For the performed experimental datasets, a generalized regression neural network is applied to generate a relation among the input and output process parameters.
In our day to day hectic schedule humans have got so adaptive to technology that tremendous pressure is built on researchers to produce better equipment with greater output & easier way of human usage. One among these is Heat exchanger which is a device for trading heat and providing comfortable environment either for humans or the equipment .This paper aims at finding a solution in improvement of the thermal performance of the heat exchanger by implementing a statistical tool derived from Artificial Neural Network. The name of the tool is GRNN. (Generalized Regression Neural Network) From a sparse data of inputs (Temperatures, Angle orientation & mass flow rates) the outputs of (outlet temperatures & drop in pressure) are found out using this tool. An experiment is also conducted to find the heat transfer rates and pressure drops. To enhance the heat transfer rate three elliptical shaped leaf strips are introduced in the tube with opposite orientation and same direction. The results obtained from both the sources are compared and the percentage of error is calculated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.