Numerical study on air-core vortex inside draining tank using different computational modelling approaches

Accurate numerical simulation of liquid draining is important to study the physics fluid flow. However, liquid draining involves multiphase and rotational flows, where numerical simulation is expensive to accurately recreate these flow behaviors. The accuracy of numerical results has been also debatable and it is mainly affected by the computational modeling approaches. Therefore, this study evaluates different computational modelling approaches such as DNS, RANS k-ε, RANS k-ω and LES turbulence models. The results for the draining time and flow visualization of the generation of an air-core are in a good agreement with the available published data. The Direct Numerical Simulation (DNS) seems most reasonably satisfactory for VOF studies relating air-core compared to other different turbulence modeling approaches

Benchmark on the Dynamics of Liquid Draining Inside a Tank

Immense information and details observation of flow physics inside a draining tank can be achieved by adopting reliable numerical simulations. Yet the accuracy of numerical results has been always debatable and it is mainly affected by the grid convergence error and computational modeling approaches. Hence, this study is divided into two stages. In the first stage, this paper determines a systematic method of refining a computational grid for a liquid draining inside a tank using OpenFOAM software. The sensitivity of the computed flow field on different mesh resolutions is also examined. In order to study the effect of grid dependency, three different grid refinements are investigated: fine, medium and coarse grids. By using a form of Richardson extrapolation and Grid Convergence Index (GCI), the level of grid independence is attained. In this paper, a monotonic convergence criteria is reached when the fine grid has the GCI value below 10% for each parameter. In the second stage, different computational modeling approaches (DNS, RANS k-ε, RANS k-ω and LES turbulence models) are investigated using the finer grid from the first stage. The results for the draining time and flow visualization of the generation of an air-core are in a good agreement with the available published data. The Direct Numerical Simulation (DNS) seems most reasonably satisfactory for VOF studies relating air-core compared to other different turbulence modeling approaches

Benchmark on the Dynamics of Liquid Draining Inside a Tank

Immense information and details observation of flow physics inside a draining tank can be achieved by adopting reliable numerical simulations. Yet the accuracy of numerical results has been always debatable and it is mainly affected by the grid convergence error and computational modeling approaches. Hence, this study is divided into two stages. In the first stage, this paper determines a systematic method of refining a computational grid for a liquid draining inside a tank using OpenFOAM software. The sensitivity of the computed flow field on different mesh resolutions is also examined. In order to study the effect of grid dependency, three different grid refinements are investigated: fine, medium and coarse grids. By using a form of Richardson extrapolation and Grid Convergence Index (GCI), the level of grid independence is attained. In this paper, a monotonic convergence criteria is reached when the fine grid has the GCI value below 10% for each parameter. In the second stage, different computational modeling approaches (DNS, RANS k-ε, RANS k-ω and LES turbulence models) are investigated using the finer grid from the first stage. The results for the draining time and flow visualization of the generation of an air-core are in a good agreement with the available published data. The Direct Numerical Simulation (DNS) seems most reasonably satisfactory for VOF studies relating air-core compared to other different turbulence modeling approaches

Numerical simulation of liquids draining from a tank using openFOAM

Draining a liquid from a cylindrical tank is numerically simulated using OpenFOAM. OpenFOAM is an open source CFD package and it becomes increasingly popular among the academician and also industries. In this paper, comparisons with theoretical and results from previous published data confirmed that Open-FOAM is able to simulate the liquids draining very well. This is done using the gas-liquid interface solver available in the standard library of OpenFOAM

Review on HVAC system optimization towards energy saving building operation

Works on the optimization of heating, ventilation and air-conditioning (HVAC) systems have been done extensively because of its high amount of building electrical energy usage. This paper provides a review on the optimizations works of HVAC systems based on three main approaches – HVAC operational parameters optimization, HVAC controller parameters optimization and building design parameters optimization. For the system’s operational parameters, the optimization is based on the HVAC’s conventional and predictive energy consumption models which is clear the predictive HVAC system models can get better response to reduce energy consumption compare to conventional energy consumption model. In most works, the thermal comfort model, either indicated by the indoor air quality (IAQ) or the predicted mean vote (PMV) was included. It is be noticed that between IAQ comfort index and PMV comfort index the PMV had a better response that can get 46% reduce the energy consumption. In addition, in the HVAC’s controller optimization approach, its objective is to improve the output response of the HVAC system in order to avoid unnecessary energy usage by optimizing the controller parameters that employ controllers such as Fuzzy Logic, Neural Network and Proportional-Integral-Derivative (PID) controllers. It is clear that among the different controller optimizations mentioned above the fuzzy logic tuning optimization has a better response to reduction of energy consumption rather than other controller optimization approach. Meanwhile, the optimization of building design parameters approach is done before the construction of the buildings so as to reduce the energy consumption, where factors such as HVAC system type, construction material type and window dimensions are determined through the optimization process. This paper reviews the works based on the three approaches of HVAC system optimizations with the objective of reducing energy usage without sacrificing the comfort of occupants inside the building that is recommended to us e predictive HVAC system approaches with fuzzy logic controller. Moreover, comparing different tools for building parameter and design optimization including SEDICAE, EXRETopt and EneryPlus, the EXRETopt by using PMV comfort index makes to 62% reduction of energy consumption