An investigation into the applicability of the Lattice Boltzmann method to modelling of the flow in a hydrocyclone

The lattice Boltzmann method has gained popularity as a method for simulating fluid flow, particularly multiphase flow. Thus, it has potential in simulating fluid flow in hydrocyclones. While research on the method and its’ application to multiphase flow is mature, there is sparse research on its’ application to hydrocyclones. An overview of the literature on the use of the lattice Boltzmann method for simulating fluid flow in hydrocyclones is presented. A lattice Boltzmann model of single phase flow in a hydrocyclone is presented, which is compared to predictions from a Navier-Stokes based model. The lattice Boltzmann model predicts lower velocities than the Navier-Stokes model in certain areas of the hydrocyclone and higher velocities in other areas. In some areas both models are in close agreement. The lattice Boltzmann model predicts the low pressure region at the underflow and overflow. However, it does not display the low pressure region in the core of the hydrocyclone. It is proposed that these differences are related to the use of the single relaxation time implementation of the lattice Boltzmann method. The possible solution is to use the multiple relaxation time model which is more suitable to high-Reynolds number flows

High-Fidelity Computational Aerodynamics of the Elytron 4S UAV

High-fidelity Computational Fluid Dynamics (CFD) have been carried out for the Elytron 4S Unmanned Aerial Vehicle (UAV), also known as the converticopter "proto12". It is the scaled wind tunnel model of the Elytron 4S, an Urban Air Mobility (UAM) concept, a tilt-wing, box-wing rotorcraft capable of Vertical Take-Off and Landing (VTOL). The three-dimensional unsteady Navier-Stokes equations are solved on overset grids employing high-order accurate schemes, dual-time stepping, and a hybrid turbulence model using NASA's CFD code OVERFLOW. The Elytron 4S UAV has been simulated in airplane mode and in helicopter mode

CFD Assessment of Forward Booster Separation Motor Ignition Overpressure on ET XT 718 Ice/Frost Ramp

Computational fluid dynamics assessment of the forward booster separation motor ignition over-pressure was performed on the space shuttle external tank X(sub T) 718 ice/frost ramp using the flow solver OVERFLOW. The main objective of this study was the investigation of the over-pressure during solid rocket booster separation and its affect on the local pressure and air-load environments. Delta pressure and plume impingement were investigated as a possible contributing factor to the cause of the debris loss on shuttle missions STS-125 and STS-127. A simplified computational model of the Space Shuttle Launch Vehicle was developed consisting of just the external tank and the solid rocket boosters with separation motor nozzles and plumes. The simplified model was validated by comparison to full fidelity computational model of the Space Shuttle without the separation motors. Quasi steady-state plume solutions were used to calibrate the thrust of the separation motors. Time-accurate simulations of the firing of the booster-separation motors were performed. Parametric studies of the time-step size and the number of sub-iterations were used to find the best converged solution. The computed solutions were compared to previous OVERFLOW steady-state runs of the separation motors with reaction control system jets and to ground test data. The results indicated that delta pressure from the overpressure was small and within design limits, and thus was unlikely to have contributed to the foam losses

Investigation of mixed element hybrid grid-based CFD methods for rotorcraft flow analysis

Accurate first-principles flow prediction is essential to the design and development of rotorcraft, and while current numerical analysis tools can, in theory, model the complete flow field, in practice the accuracy of these tools is limited by various inherent numerical deficiencies. An approach that combines the first-principles physical modeling capability of CFD schemes with the vortex preservation capabilities of Lagrangian vortex methods has been developed recently that controls the numerical diffusion of the rotor wake in a grid-based solver by employing a vorticity-velocity, rather than primitive variable, formulation. Coupling strategies, including variable exchange protocols are evaluated using several unstructured, structured, and Cartesian-grid Reynolds Averaged Navier-Stokes (RANS)/Euler CFD solvers. Results obtained with the hybrid grid-based solvers illustrate the capability of this hybrid method to resolve vortex-dominated flow fields with lower cell counts than pure RANS/Euler methods

Target Mass Monitoring and Instrumentation in the Daya Bay Antineutrino Detectors

The Daya Bay experiment measures sin^2 2{\theta}_13 using functionally identical antineutrino detectors located at distances of 300 to 2000 meters from the Daya Bay nuclear power complex. Each detector consists of three nested fluid volumes surrounded by photomultiplier tubes. These volumes are coupled to overflow tanks on top of the detector to allow for thermal expansion of the liquid. Antineutrinos are detected through the inverse beta decay reaction on the proton-rich scintillator target. A precise and continuous measurement of the detector's central target mass is achieved by monitoring the the fluid level in the overflow tanks with cameras and ultrasonic and capacitive sensors. In addition, the monitoring system records detector temperature and levelness at multiple positions. This monitoring information allows the precise determination of the detectors' effective number of target protons during data taking. We present the design, calibration, installation and in-situ tests of the Daya Bay real-time antineutrino detector monitoring sensors and readout electronics.Comment: 22 pages, 20 figures; accepted by JINST. Changes in v2: minor revisions to incorporate editorial feedback from JINS

Experimental validation of a fluid dynamics based model of the UF Falcon concentrator in the ultrafine range

The process of separating ultrafine particles, say below 80 μm, on the basis of density is a true technical challenge. Indeed, the separation process itself becomes very much size dependent with such fine particles, so that large enough density differentials are necessary for offsetting the strong particle size effect. Our study is concerned with understanding the limitations of the UF Falcon concentrator, an enhanced gravity separator specifically designed for treating slurries with ultrafines. To this end, based on a number of hypotheses, we have already derived and published a theoretical model of the UF Falcon concentrator for treating dilute suspensions. This paper presents the validation and calibration of this model, based on experimental measurements carried out under controlled conditions using a laboratory scale concentrator. By comparing measured and predicted separation results for particles with known size distribution and density, the work validates the key model hypotheses, thereby confirming our understanding of the physics of the separation process. Moreover, by changing operating conditions in a systematic manner, the work is able to calibrate the model so that it can be used to make quantitative prediction of the UF Falcons performance

Large deviations sum-queue optimality of a radial sum-rate monotone opportunistic scheduler

A centralized wireless system is considered that is serving a fixed set of users with time varying channel capacities. An opportunistic scheduling rule in this context selects a user (or users) to serve based on the current channel state and user queues. Unless the user traffic is symmetric and/or the underlying capacity region a polymatroid, little is known concerning how performance optimal schedulers should tradeoff "maximizing current service rate" (being opportunistic) versus "balancing unequal queues" (enhancing user-diversity to enable future high service rate opportunities). By contrast with currently proposed opportunistic schedulers, e.g., MaxWeight and Exp Rule, a radial sum-rate monotone (RSM) scheduler de-emphasizes queue-balancing in favor of greedily maximizing the system service rate as the queue-lengths are scaled up linearly. In this paper it is shown that an RSM opportunistic scheduler, p-Log Rule, is not only throughput-optimal, but also maximizes the asymptotic exponential decay rate of the sum-queue distribution for a two-queue system. The result complements existing optimality results for opportunistic scheduling and point to RSM schedulers as a good design choice given the need for robustness in wireless systems with both heterogeneity and high degree of uncertainty.Comment: Revised version. Major changes include addition of details/intermediate steps in various proofs, a summary of technical steps in Table 1, and correction of typos

Fundamental understanding of swirling flow pattern in hydrocyclones

This work is concerned with establishing and validating a physics-based model that describes the swirling flow inside hydrocyclones. The physics is embedded in a Computational Fluid Dynamics (CFD) simulation model whose key features are presented and justified in the paper. Some features are selected in such a way that the model can eventually be used to simulate dense flow inside hydrocyclones. Nevertheless, its underlying physics is here within validated against dilute flow conditions. The model applies a Eulerian multi-fluid modelling approach for fluid–particle turbulent flows, and is computed using the semi-industrial code NEPTUNE_CFD. Simulation results are successfully compared to water split, velocity profiles inside the hydrocyclone and partition function measurements, either produced using our own experimental setup or from the literature. The work finds velocity profiles to be the most discriminating parameter for validation of the physics that describes the swirling flow inside the hydrocyclone. Water split on the other hand shows no relation to the choice of turbulence model and hence cannot be used to validate a mechanistic model of the hydrocyclone. The physics-based model presented here is the first building block towards describing and understanding hydrocyclone flow under dense regime