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Engineering Journals - Jimmy Lea P/L

DESIGN HEURISTIC OF MIXING TANK


The design of suspension mixing tanks is often embedded in empiricism due to insufficient understanding of the hydrodynamics of dense solid-liquid interaction. This is particularly limiting during the design of mixing tanks or batch reactor for expensive high quality products in the fine chemicals, biological and pharmaceutical processing industries. In this paper, a computational fluid dynamics (CFD)-assisted design approach has been employed to study the effectiveness of mixing tank geometrical configurations to suspend particles. Ten crucial variables were investi-gated and the effects of changing the value of these variables were documented. In addition, a multivariable study involving these ten variables was also conducted to investigate the most im-portant variables among them. Finally, by capturing the essence of the results, a design heuristic was developed which can be applied across the process industry.

SIMULATION TECHNOLOGY

As one of the leading simulation technology consultants, we have delivered air dispersion modelling projects in the built environment sector, gas dispersion modelling in the chemical & petrochemical industry, defence & security, food & beverage, manufacturing, marine & offshore, mining & mineral processing, oil & gas, pharmaceutical, renewable energy, semiconductor and water & wastewater industries. Checking CFD calculations can be tedious whereas conducting physical validations to determine the accuracy of CFD results may be impractical and/or economically prohibitive. The peer reviewed papers on this page aim to explain how CFD validation can be conducted in a laboratory. We have also provided a paper that shows how design heuristic for a mixing tank can be developed using CFD simulation technology.

VALIDATION OF CFD RESULTS VIA PARTICLE IMAGE VELOCIMETRY (PIV)


The manufacture of nitrocellulose, which is the basis of most artillery, rocket and missile propellant, is intrinsically risky due to the energetic nature of the product and the sensitivity of the process.  To optimise the performance of the nitration unit, computational fluid dynamics (CFD) was employed to characterise the nitration unit and to provide detailed, relevant process data emanating from a new perspective.  The actual nitration unit was scaled-down in order to use independent measurements from particle image velocimetry (PIV) to validate the CFD results.  It was only after the model and simulation results were successfully validated that the characterisation of the actual unit was carried out.  With the nitration unit characterised, its optimisation was carried out by performing modelling on different geometrical configurations with a view to selecting one which gives an optimum performance. 

Wind driven rain by Jimmy Lea P/L

WIND DRIVEN RAIN


The daily applications of modelling & simulation technology in the real world are becoming easier due to the availability of powerful multicore computers and commercial simulation software. Design activities which aim to protect buildings and infrastructures from man-made or natural phenomena are examples of how this technology can assist. An example of where modelling & simulation technology is applied in our daily life is in the study of wind-driven rain (WDR). Many people have not heard of the term ‘wind-driven rain or WDR’ until they realise their insurance policy does not cover damage to their properties caused by WDR. Wind-driven rain, as the name implies, is rain droplets propelled by wind blowing from various directions. WDR concerns public and private buildings because it can damage these buildings and reduce the occupants’ comfort and safety. A good example is above-ground train stations which in many cases were designed to rely on natural ventilation to increase passengers’ thermal comfort. When it rains, stations in which the design only addressed natural ventilation but not WDR mean rain droplets carried by the winds will ingress into the station. An approach to minimise if not prevent the ingress of WDR is to address it using computational fluid dynamics (CFD) modelling & simulation. Download the article by clicking the icon on the left and turn to page 24.

Suspension Mixing Tank - Design Heuristic by Jimmy Lea P/L

COMPUTATIONAL FLUID DYNAMICS


As one of the leading CFD consulting companies in Australia, Singapore and the Asia Pacific region, it is important that we demonstrate the accuracy of our simulation results. There are two computational fluid dynamics (CFD) journals in this folder. These CFD simulation - related journals can be downloaded simply by clicking the icon on the left, namely:


Lea J [2009], Suspension mixing tank-design heuristic, Chemical product and process modelling, Volume 4, Issue 1, Article 17, The Berkeley Electronic Press


Fort I [2009], Comments on Lea J [2009] “Suspension mixing tank-design heuristic” Manuscript 1419, Chemical product and process modelling, The Berkeley Electronic Press

In Lea [2009], a computational fluid dynamics (CFD)-assisted design approach has been employed to study the effectiveness of mixing tank geometrical configurations to suspend particles. In contrast, the paper Fort [2009] deals with the analysis, via physical experimentation, of the process characteristics of agitated system with a pitched blade impeller and radial baffles (impeller power input and impeller pumping capacity) under turbulent regime of flow of agitated batch.
Original experimental data are compared with results of CFD simulation in a pilot plant mixing system published in literature. These two papers concluded that the CFD results from Lea [2009] and experimental results from Fort [2009] are in good agreement. Download the article by clicking the icon on the left.

Validation of CFD results using PIV - Jimmy Lea P/L