The performance and safety of a retainer-type ball valve have been evaluated for use in a high-pressure pipeline to a district heating plant. The retainer-type ball valve is a developed valve improving the defects of the leaks that may occur in the general valves such as the floating ball valve or trunnion ball valve. To verify the valve design, a numerical analysis of the design has been applied to investigate safety factors and to determine the flow coefficients for the DN300 and DN400 standard sizes. The conditions used for the numerical analysis was based on the international standards ISO 5208, IEC 60534-2-3, and a high-pressure pipeline to a district heating plant. The structural analysis results comprise deformations, equivalent stresses, and safety factors, and the flow analysis results show the flow coefficient, the pressure distribution, the velocity vectors, and the flow patterns for each rotation angle. These results confirmed the characteristics and reliability of the retainer-type ball valve and, based on these studies, we proposed a retainer-type ball valve as a solution to solve the leakage problem.
This study presents a Lattice Boltzmann Method (LBM) coupled with a momentum-exchange approach/fictitious domain (MEA/FD) method for the simulation of particle suspensions. The method combines the advantages of the LB and the FD methods by using two unrelated meshes, namely, a Eulerian mesh for the flow domain and a Lagrangian mesh for the solid domain. The rigid body conditions are enforced by the momentum-exchange scheme in which the desired value of velocity is imposed directly in the particle inner domain by introducing a pseudo body force to satisfy the constraint of rigid body motion, which is the key idea of a fictitious domain (FD) method. The LB-MEA/FD method has been validated by simulating two different cases, and the results have been compared with those through other methods. The numerical evidence illustrated the capability and robustness of the present method for simulating particle suspensions.
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.