Computational fluid dynamics (CFD) approach for characterizing and improving fluid flow for membrane filtration technologies and successful scale-up

There is increasing interest in using computational fluid dynamics (CFD) techniques to obtain better understanding of fluid dynamics of various unit operations, both upstream and downstream bioprocessing, and to use simulated results for process modelling, system characterisation and design optimisation. Membrane filtration technologies and in particular, tangential flow filtration (TFF), have made use of CFD analysis to gain better insight into, for instance, velocity and concentration profiles within channels, optimising spacer geometry and configurations to maximise mass transfer for different TFF setups. The applications and benefits for TFF processes are immense since large volumes of liquid are normally required, both for cleaning and processing, and thus even small increments in efficiency can result in significant cost reductions. In this study, a novel Ultra Scale-Down (USD) membrane filtration device and spacer-filled channels in TFF cassettes were modelled using COMSOL Multiphysics. 2D-axisymmetrical and 3D models were developed, respectively, to simulate the effect of geometry, design and hydrodynamic conditions on flow, wall shear rates and pressure profiles. Laminar flow and Shear Stress Transport (SST) formulations were used and parametric sweeps employed for different geometrical and design parameters. The geometrical configuration, such as clearance of the disc, cone angle and disc diameter, and the resulting hydrodynamics within the system was seen to play a vital role in wall shear rate distributions for the USD device. The change could be attributed to the introduction of secondary recirculating flows and vortices that allow greater degree of axial and radial mixing, as seen from the CFD results. Optimal disc type, namely the axial flow impellers such as pitch-blade turbine and the hydrofoil, and positioning was also identified based on parameters such as wall shear rate distribution along the radial axis of the membrane and maximum shear stress:average wall shear stress ratio. Flow within the screened channel was observed to be very controlled and periodic, especially in regions close to and around the cylindrical fibers of the screen, and an overall accelerated flow within the channel compared to the inlet velocity was observed from the CFD simulations. The aim was to use CFD as a guiding tool to optimise the design of the USD device such that it mimics the average wall shear rate and profiles observed within the screened channels, in order to establish successful and accurate scale-up between the USD device and TFF process, at scale. Experimental validation for the CFD results are also presented, along with other potential applications of the CFD studies carried out, such as modelling flux behaviour in the channel, cake formation and pressure drops. Please click Additional Files below to see the full abstract

Application of Artificial Fish Swarm Algorithm in Radial Basis Function Neural Network

Neural network is one of the branches with the most active research, development and application in computational intelligence and machine study. Radial basis function neural network (RBFNN) has achieved some success in more than one application field, especially in pattern recognition and functional approximation. Due to its simple structure, fast training speed and excellent generalization ability, it has been widely used. Artificial fish swarm algorithm (AFSA) is a new swarm intelligent optimization algorithm derived from the study on the preying behavior of fish swarm. This algorithm is not sensitive to the initial value and the parameter selection, but strong in robustness and simple and easy to realize and it also has parallel processing capability and global searching ability. This paper mainly researches the weight and threshold of AFSA in optimizing RBFNN. The simulation experiment proves that AFSA-RBFNN is significantly advantageous in global optimization capability and that it has outstanding global optimization ability and stability

Design of a large dynamic range readout unit for the PSD detector of DAMPE

A large dynamic range is required by the Plastic Scintillator Detector (PSD) of DArk Matter Paricle Explorer (DAMPE), and a double-dynode readout has been developed. To verify this design, a prototype detector module has been constructed and tested with cosmic rays and heavy ion beams. The results match with the estimation and the readout unit could easily cover the required dynamic range

Influence of natural organic matter in the transport medium on fine particle transport

Although extensive research has been conducted to understand the effects of dissolved organic matter (DOM) on fine particle transport, less attention has been paid to NOM in the transport medium (i.e., immobile rock and sediment grains). The objective of this study is to the roles of NOM in the transport medium in mediating particle transport. We conducted an experimental and modelling study on the transport of nanoscale titanium dioxide (nTiO₂) and illite colloid in columns packed with quartz sand under water-saturated conditions. Peat moss was used as an example NOM and packed in some of the columns to investigate its influence on particle transport. Experimental results showed that NOM may either increase or decrease particle transport depending on the specific conditions. NOM in the transport medium was found to attract particles and reduce particle mobility when the energy barrier between particle and NOM is low or non-existent. NOM also adsorbed to Fe and Al oxyhydroxides and promoted the transport of negatively-charged particles at low pH. Partial dissolution of NOM releases DOM, and the DOM adsorbs to and increases the transport of positively-charged particles. Additionally, NOM changes pore water pH, which influences particle mobility by affecting the interaction energy between the particle and transport medium. Modelling results showed that the deposition sites of peat moss are very heterogeneous, and the NOM from peat moss may reduce particle deposition rate by adsorbing to the particle and/or transport medium. Findings from this study demonstrates that NOM in the transport medium not only changes properties of the medium, but also may alter water chemistry. Therefore, the role of NOM in mediating particle transport is complicated and dependent on the properties of the particle, NOM, and mineralogical composition of the medium

Analytical vectorial structure of non-paraxial four-petal Gaussian beams in the far field

The analytical vectorial structure of non-paraxial four-petal Gaussian beams(FPGBs) in the far field has been studied based on vector angular spectrum method and stationary phase method. In terms of analytical electromagnetic representations of the TE and TM terms, the energy flux distributions of the TE term, the TM term, and the whole beam are derived in the far field, respectively. According to our investigation, the FPGBs can evolve into a number of small petals in the far field. The number of the petals is determined by the order of input beam. The physical pictures of the FPGBs are well illustrated from the vectorial structure, which is beneficial to strengthen the understanding of vectorial properties of the FPGBs

The Linear Relationship between Stock Returns and Interest Rates: Evidence from US Stock Markets

The paper studies the linear relationship between stock returns and interest rates using a sample of US market from 2000 to 2008. The methodology of well tested Ordinary Least Square Model is applied. General results have showed a non-lagged significant positive and a one-day lagged significant negative correlation between returns and interest rates. And the presence of financial crisis is found to have dramatic influence on this specific correlation. In addition, the maturity term of interest rates are also found influential on this relationship