138 research outputs found
Detached Eddy Simulation on the Turbulent Flow in a Stirred Tank
A detached eddy simulation (DES), a large-eddy simulation (LES), and a k-Īµ-based Reynolds averaged Navier-Stokes (RANS) calculation on the single phase turbulent flow in a fully baffled stirred tank, agitated by a Rushton turbine is presented. The DES used here is based on the Spalart-Allmaras turbulence model solved on a grid containing about a million control volumes. The standard k-Īµ and LES were considered here for comparison purposes. Predictions of the impeller-angle-resolved and time-averaged turbulent flow have been evaluated and compared with data from laser doppler anemometry measurements. The effects of the turbulence model on the predictions of the mean velocity components and the turbulent kinetic energy are most pronounced in the (highly anisotropic) trailing vortex core region, with specifically DES performing well. The LESāthat was performed on the same grid as the DESāappears to lack resolution in the boundary layers on the surface of the impeller. The findings suggest that DES provides a more accurate prediction of the features of the turbulent flows in a stirred tank compared with RANS-based models and at the same time alleviates resolution requirements of LES close to walls
Scale-down studies for the scale-up of a recombinant Corynebacterium glutamicum fed-batch fermentation:loss of homogeneity leads to lower levels of cadaverine production
BACKGROUND: The loss of efficiency and performance of bioprocesses on scale-up is well known, but not fully understood. This work addresses this problem, by studying the effect of some fermentation gradients (pH, glucose and oxygen) that occur at the larger scale in a bench-scale two-compartment reactor [plug flow reactor (PFR) + stirred tank reactor (STR)] using the cadaverine-producing recombinant Corynebacterium glutamicum DM1945 Īact3 Ptuf-ldcC_OPT. The new scale-down strategy developed here studied the effect of increasing the magnitude of fermentation gradients by considering not only the average cell residence time in the PFR (ĻPFR), but also the mean frequency at which the bacterial cells entered the PFR (fm) section of the two-compartment reactor. RESULTS: On implementing this strategy the cadaverine production decreased on average by 26%, 49% and 59% when the ĻPFR was increased from 1 to 2 min and then 5 min respectively compared to the control fermentation. The carbon dioxide productivity was highest (3.1-fold that of the control) at a ĻPFR of 5 min, but no losses were observed in biomass production. However, the population of viable but non-culturable cells increased as the magnitude of fermentation gradients was increased. The new scale-down approach was also shown to have a bigger impact on fermentation performance than the traditional one. CONCLUSION: This study demonstrated that C. glutamicum DM1945 Īact3 Ptuf-ldcC_OPT physiological response was a function of the magnitude of fermentation gradients simulated. The adaptations of a bacterial cell within a heterogeneous environment ultimately result in losses in fermentation productivity as observed here
Computational fluid mixing
Computational fluid dynamics (CFD) is an extremely powerful tool for solving
problems associated with flow, mixing, heat and mass transfer and chemical
reaction. Although the equations of motion for fluid flow were established in the first
half of the nineteenth century (e.g. Navier, 1822; Stokes, 1845), it was not until the
arrival of digital computers in the 1960s and 1970s that it became feasible to perform
numerical simulations of complex engineering flows. In these early days, CFD was a
very much a research tool and most of the early work was aimed at developing
numerical methods, solution algorithms and Reynolds-averaged turbulence models.
However, in the 1980s, the first commercial codes emerged ā e.g. PHOENICS,
FLUENT, FIDAP, Star-CD, FLOW3D (which later became CFX) ā providing general
purpose software packages for both academic and industry users. The aerospace
and automotive industries were amongst the first to embrace the use of CFD in
engineering design, but from the 1990s onwards commercial codes have found
widespread applications, for example in: biomedical engineering, environmental and
atmospheric modelling, meteorology, chemical reaction engineering and more
recently in the food and beverage industries. This chapter will focus on mixing
vessel applications for the last two of these industry sectors, where CFD is
increasingly used to provide process understanding and semi-quantitative analysis.
In their review, Norton and Sun (2006) presented a graph showing the very
significant increase in the number of peer-reviewed papers related to CFD
applications to food process engineering. Figure 0.1 is an updated version of this
graph, containing more recent data and showing that the number of papers that
specifically analyse food mixing operations using CFD is still relatively small. In
contrast, there are a vast numbers of papers on CFD simulation of (i) other food
process operations, (e.g. drying, sterilisation, thermal treatment and extrusion, many
of which are described by Sun (2007)) and (ii) more conventional mixing operations
in the chemicals and specialty product industries (see for example, Marshall and
Bakker (2004)). This chapter will outline the background knowledge required for
CFD studies, present some examples of CFD modelling of mixing vessel flows and
finally will discuss the current difficulties in applying this approach to food mixing processes
Developments in fluidised bed freeze drying
Developments in fluidised bed freeze dryin
Insight into the large-scale upstream fermentation environment using scaled-down models
Scaledādown models are smallāscale bioreactors, used to mimic the chemical (pH, nutrient and dissolved oxygen) and physical gradients (pressure, viscosity and temperature) known to occur in the largeāscale fermenter. Conventionally, before scaling up any bioprocess, smallāscale bioreactors are used for strain selection, characterisation and optimisation. The typical smallāscale environment is homogenous, hence all the cells held within the smallāscale bioreactor can be assumed to experience the same condition at any point in time. However, for the largeāscale bioreactor, this is not the case, due to its inhomogeneous environment. Three different scaledādown models are reviewed here, and the results suggest that a bacterium responds to changes in its environment rapidly and the magnitude of response to environmental oscillations is organismāspecific. The reaction and adaption of a bacterium to an inhomogeneous environment in most cases result in productivity and quality losses. This review concludes that consideration of fermentation gradients should be paramount when researchers screen for high yielding mutants in bioprocess development and doing this would help mitigate performance loss on scaleāup
State feedback linearization and adaptive model predictive control applied to a simulated MSMPR crystalliser [Abstract]
State feedback linearization and adaptive model predictive control applied to a simulated MSMPR crystalliser [Abstract
Microneedle assisted micro-particle delivery from gene guns: experiments using skin-mimicking agarose gel
A set of laboratory experiments has been carried out to determine if micro-needles (MNs) can enhance penetration depths of high-speed micro-particles delivered by a type of gene gun. The micro-particles were fired into a model target material, agarose gel, which was prepared to mimic the viscoelastic properties of porcine skin. The agarose gel was chosen as a model target as it can be prepared as a homogeneous and transparent medium with controllable and reproducible properties allowing accurate determination of penetration depths. Insertions of various MNs into gels have been analysed to show that the length of the holes increases with an increase in the agarose concentration. The penetration depths of micro-particle were analysed in relation to a number of variables, namely the operating pressure, the particle size, the size of a mesh used for particle separation and the MN dimensions. The results suggest that the penetration depths increase with an increase of the mesh pore size, because of the passage of large agglomerates. As these particles seem to damage the target surface, then smaller mesh sizes are recommended; here, a mesh with a pore size of 178 Ī¼m was used for the majority of the experiments. The operating pressure provides a positive effect on the penetration depth, that is it increases as pressure is increased. Further, as expected, an application of MNs maximises the micro-particle penetration depth. The maximum penetration depth is found to increase as the lengths of the MNs increase, for example it is found to be 1272 Ā± 42, 1009 Ā± 49 and 656 Ā± 85 Ī¼m at 4.5 bar pressure for spherical micro-particles of 18 Ā± 7 Ī¼m diameter when we used MNs of 1500, 1200 and 750 Ī¼m length, respectively
Microneedle-assisted microparticle delivery by gene guns: experiments and modeling on the effects of particle characteristics.
Abstract Microneedles (MNs) have been shown to enhance the penetration depths of microparticles delivered by gene gun. This study aims to investigate the penetration of model microparticle materials, namely, tungsten (<1āĪ¼m diameter) and stainless steel (18 and 30āĪ¼m diameters) into a skin mimicking agarose gel to determine the effects of particle characteristics (mainly particle size). A number of experiments have been processed to analyze the passage percentage and the penetration depth of these microparticles in relation to the operating pressures and MN lengths. A comparison between the stainless steel and tungsten microparticles has been discussed, e.g. passage percentage, penetration depth. The passage percentage of tungsten microparticles is found to be less than the stainless steel. It is worth mentioning that the tungsten microparticles present unfavourable results which show that they cannot penetrate into the skin mimicking agarose gel without the help of MN due to insufficient momentum due to the smaller particle size. This condition does not occur for stainless steel microparticles. In order to further understand the penetration of the microparticles, a mathematical model has been built based on the experimental set up. The penetration depth of the microparticles is analyzed in relation to the size, operating pressure and MN length for conditions that cannot be obtained in the experiments. In addition, the penetration depth difference between stainless steel and tungsten microparticles is studied using the developed model to further understand the effect of an increased particle density and size on the penetration depth
PIV study of the flow field generated by a sawtooth impeller
Stereoscopic and high-speed particle image velocimetry (PIV) techniques have been
employed to study the flow field induced by a sawtooth (EkatoMizer) impeller,
operated in the fully turbulent flow regime at an impeller speed of 1500 rpm.
Ensemble-averaged mean flow fields and turbulence quantities were calculated for a
region close to the impeller blades. The flow was found to be anisotropic near the
impeller and exhibited return-to-isotropy behaviour further away from it. Macroinstabilities
were found to have a high probability of occurrence in the discharge
stream. All three velocity components from the stereo-PIV measurements were used
to estimate the dissipation rate, by adopting a large eddy simulation (LES) analogy.
Spurious vectors distorting the dissipation rate calculation were identified, and
various standard deviation filters were applied for vector validation. By evaluating the
filtered dissipation rate profiles against the multi-fractal intermittency model of
Meneveau and Sreenivasan (1991), the global standard deviation filter was found to
be the most suitable type. The ratio of the maximum to the mean dissipation rate for
the EkatoMizer discharge stream was found to be similar to that reported for
Rushton disk turbine and pitched-blade turbine impellers in the literature, raising
questions about the reported high-shear advantage of sawtooth impellers
Microneedle assisted micro-particle delivery by gene guns: mathematical model formulation and experimental verification
Gene gun is a micro-particles delivery system which accelerates DNA loaded micro-particles to a high speed so as to enable penetration of the micro-particles into deeper tissues to achieve gene transfection. Previously, microneedle (MN) assisted micro-particles delivery has been shown to achieve the purpose of enhanced penetration depth of micro-particles based on a set of laboratory experiments. In order to further understand the penetration process of micro-particles, a mathematical model for MN assisted micro-particles delivery is developed. The model mimics the acceleration, separation and deceleration stages of the operation of a gene gun (or experimental rig) aimed at delivering the micro-particles into tissues. The developed model is used to simulate the particle velocity and the trajectories of micro-particles while they penetrate into the target. The model mimics the deceleration stage to predict the linear trajectories of the micro-particles which randomly select the initial positions in the deceleration stage and enter into the target. The penetration depths of the micro-particles are analyzed in relation to a number of parameters, e.g., operating pressure, particle size, and MNs length. Results are validated with experimental results obtained from the previous work. The results also show that the particle penetration depth is increased from an increase of operating pressure, particle size and MN length. The presence of the pierced holes causes a surge in penetration distance. Ā© 2014 Elsevier Ltd. All rights reserved
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