Investigations of Automatic Meshing in Modeling a Dry Twin Screw Compressor

In order to design screw compressors for optimal performance, it is crucial to understand the complex fluid flow processes within them. Computational fluid dynamics (CFD) is one approach for doing so. Considerable progress has been made over the last several years in both commercial and academic solution packages for this application; however, due to the complex moving geometries of the screw rotors and the tight clearances between the moving parts, a major challenge that remains is the generation of numerical grids that are increasingly efficient, accurate, robust, and easily created. In this study, an alternate methodology for this problem is presented. The grid is created automatically at every time step based on the instantaneous geometry using a Cartesian cut-cell based method which preserves exactly the changing control volume shapes. Automatic mesh refinement is employed to adaptively increase mesh resolution where the flow variables have large gradients in order to resolve the large-scale flow structures. To address the problem of efficiently modeling the flows in the small clearance gaps, an empirical model is applied so that the cells within the gaps can remain relatively coarse. This removes a major bottleneck from the computational cost and allows more mesh resolution to be applied in accurately capturing the physics of the port flows. The effect of the thermal expansion on the gap sizes is accounted for by considering the heat transfer from the fluid to the solid walls and then periodically solving the solid to steady state using cycle-averaged heat transfer coefficients; the clearances therefore vary throughout the length of the rotors. The model is validated against experimental measurements of the internal pressure, mass flow rate, temperature, and power for two operating conditions. A global grid convergence study demonstrates the spatial and temporal convergence of the numerical model, and establishes necessary computational costs for varying levels of accuracy. It is shown that for the tested configurations, numerically accurate results are achieved with a total turn-around time that is low enough for practical use in engineering applications

Dynamic characteristics and optimal design of the manipulator for automatic tool changer

In order to improve the reliability of changing tool for ATC (automatic tool changer), a horizontal tool changer of machining center is chosen as the example to study the dynamic characteristics in the condition of changing a heavy tool. This paper analyzes the structure and properties of the tool changer by simulation and experiment, and the space trajectory equations of the manipulator and tool are derived. The maximum force is calculated in the processing of changing tool. A virtual platform for the automatic tool changer is built to simulate and verify the dynamic performance of the tool changer; the simulation results show an obvious vibration in the process of changing tool, which increases the probability of failure for changing tool. Moreover, in order to find out the device's vibration reasons, a professional experiment platform is built to test the dynamic characteristics. Based on the testing results for a horizontal tool changer, it is known that the unstable vibration is mainly caused by the collision of the tool. Finally, an optimization method for the manipulator is proposed to reduce this vibration and improve the reliability of the tool changer. The final simulation and experiment results show that the optimized manipulator can grasp the heavy tool stably, and the vibration amplitude is significantly reduced in the process of changing tool

Computational Fluid Dynamics Study on Transonic Axial Compressors using Cartesian Cut-Cell Based Method with Adaptive Mesh Refinement and Boundary Layer Mesh

Axial compressors are used extensively in the energy, power, and transportation industries. Computational Fluid Dynamics (CFD) has been widely used in research and development of dynamic compressors. CFD modeling for such designs often presents great challenges in terms of meshing and computational cost due to moving parts with complex shapes, tiny gaps, and a large range of length scales and time scales to resolve. In this work, a Cartesian cut-cell based method with adaptive mesh refinement (AMR) is used to study Rotor 67, a transonic axial compressor design from NASA. The adopted method is demonstrated to be easily implemented and copmutationally efficient through a mesh convergence study, largely due to the advantage of an autonomously generated Cartesian cut-cell grid and AMR. Additionally, a boundary layer mesh can be used in conjunction with the Cartesian cut-cell mesh in order to resolve the near-wall flow more efficiently. Both the frozen-rotor approach with a single non-inertial reference frame (SRF) and a moving-rotor approach in a single inertial reference frame are used for the computation of the global pressure ratio and the isentropic efficiency as well as the local flow velocity, pressure, and temperature. Results show great grid convergence and good agreement with previously published experimental data for multiple operating conditions in terms of both global and local flow quantities

A Collective Dynamics-based Method for Initial Pebble Packing

ABSTRACT In the simulation of pebble flow in Pebble Bed Reactors (PBR), high-fidelity methods, such as Discrete Element Methods (DEM) and Computational Fluid Dynamics (CFD) methods, are usually employed to simulate the dynamic process of pebbles circulation, accounting for the pebble-to-pebble, pebble-to-reflector wall and pebble-to-fluid interactions. To obtain a realistic model of pebble distribution around dynamic equilibrium state of pebble flow, the simulation based on high-fidelity methods normally resists brute force computation. However, if an initial dense packing of pebbles can be provided, which is close to realistic packing at equilibrium state and can be easily implemented without much computational effort, the long time high-fidelity simulation can be considerably more efficient and take much less time to reach dynamic equilibrium state. In this paper, a collective arrangement method based on a dynamics model is developed to generate an initial pebble distribution at a quasi-equilibrium state. In the new method, pebble positions are generated firstly by a fast sequential process in the full core allowing overlapping, and then a simplified normal contact force model is adopted in the initialization for eliminating the pebble overlap. The adopted model provides an adaptive way to account for the situations in which multiple pebbles are overlapped and different contact forces should be applied for different ratios of overlapping depth and sphere size, thus speeding up the initialization without loss of reliability and making the approach feasible for variable size sphere packing. Moreover, an intermittent vibration function, as an optional process, can be provided to further densify the packing depending on different applications. Comparisons with other existing random packing methods for initialization are made. It is shown that the developed method not only exhibits unique significance and good computation efficiency in speeding up the pebble flow simulation, but also presents desirable potential in other applications as a general packing algorithm for packing uniform-or variable-size spheres in a large container

Study on Pebble-Fluid Interaction Effect in Pebble Bed

INTRODUCTION In pebble bed reactors (PBRs), fuel pebbles containing TRISO particles continuously circulate within the core during operation, while the coolant fluid, either helium gas (in Pebble Bed Gas-cooled Reactors) or molten flibe salt (in Pebble Bed-Advanced High Temperature Reactors), continuously passes through the pebbles to transfer the heat generated by fission reactions out of the core. Such a design has many advantages in fuel efficiency and reactor safety. To accurately predict its neutronic and thermal-hydraulic behavior, high fidelity simulations are needed to obtain accurate pebble distributions and coolant fluid porosity distributions In PBRs, both pebble flow and coolant flow exist. They are not independent from each other but coupled through pebble-fluid interactions such as the fluid drag force and the pressure gradient force. In previous work Two scenarios with different fidelities are investigated: 1) Simulation of the pebble flow and the coolant flow without coupling. The spatial distribution of steady-state pebble flow is first calculated by DEM, and then the coolant field is calculated by CFD approach based on this static pebble distribution. 2) Fully coupled pebble flow and fluid flow simulation via DEM-CFD approach, in which the dynamic interactions between both flows are considered at each simulation step. By comparing the pebble/coolant behaviors under these two scenarios, the effects of pebble-fluid interactions on both flows are quantitatively analyzed. For pebble flow, the interaction impact on the average pebble speed and axial distributions is studied. For coolant flow, the influence on the axial/radial profile of velocity and pressure drop is investigated

Characteristic analysis and fluctuation control for a underactuated spherical underwater robot

With robots used widely in many fields in recent years, the underwater robot with various characteristics has been thoroughly researched. As a new type of underwater spherical robot, BYSQ-2 uses the heavy pendulum to adjust the attitude, which is flexible and novel. However, it has been not fully understood that how the heavy pendulum would affect the underactuated robot’s regular movement. In this paper a fluctuation characteristic for the robot is shown, and then an adaptive control method is proposed to suppress the fluctuation. Based on the simplified structure of the robot, a swing phenomenon of the heavy pendulum is found. Moreover, the reason for the fluctuation is analyzed in the processes of the accelerating and pitching. A dynamic equation for this model is established to accurately calculate the characteristic, and the virtual simulation proves the validity of the theoretical calculation. The characteristics of this coupling fluctuation are summarized by changing motion parameters and structure parameters. The results prove that the pendulum’s length and the controlling process are closely related with the velocity fluctuation of the robot. Moreover, in order to suppress the fluctuations, a pitching controller is designed to prevent the heavy pendulum from swinging based on the method of neural network sliding mode. The RBF neural network is used to compensate the nonlinearity and disturbance uncertainties, and two sliding mode structures make the swing rapidly inhibited. At the same time, the pitch angle's error also got convergence. The stability of the control system is proof by Lyapunov and Barbalat theories. Finally, the simulation and experiment show that the control method is feasible and excellent, which can fulfill the suppressed control for the fluctuation of the robot

Experiment, simulation and analysis on coupling hydrodynamic forces under key parameters for a spherical underwater exploration robot

As a novel underwater exploration robot, BYSQ-2 spherical robot uses the heavy pendulum to change the attitudes with the characteristics of small steering resistance and high compressive strength. However, the greater water resistance in the process of moving forward obstructs the rapid movement, because the robot has a spherical shell and only one propeller. The maximum speed was obtained only 0.6 m/s according to experimental tests and theoretical calculations. In order to improve the movement speed, the robot’s virtual assembly model was built to study the coupling hydrodynamic forces between the spherical shell and the propeller by CFD method. The coupling hydrodynamic forces were analyzed and summarized under different key structural parameters that include the pipe diameter and the shell diameter. Furthermore, in the conditions of different rotational speed, propeller thrust and water resistance of robot were simulated and calculated. According to the simulation results of the model with the appropriate structural parameters, it was demonstrated that the speed of the robot was improved obviously in the process of moving forward

The Exploration and Evaluation of Generating Affective 360∘^\circ Panoramic VR Environments Through Neural Style Transfer

Affective virtual reality (VR) environments with varying visual style can impact users' valence and arousal responses. We applied Neural Style Transfer (NST) to generate 360$^\circ$ VR environments that elicited users' varied valence and arousal responses. From a user study with 30 participants, findings suggested that generative VR environments changed participants' arousal responses but not their valence levels. The generated visual features, e.g., textures and colors, also altered participants' affective perceptions. Our work contributes novel insights about how users respond to generative VR environments and provided a strategy for creating affective VR environments without altering content