SUSPENSION MIXING TANK - DESIGN HEURISTIC
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 investigated 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 important variables among them. Finally, by capturing the essence of the results, a design heuristic was developed which can be applied across the process industry.
VALIDATION OF CFD RESULTS VIA PEER-REVIEWED JOURNAL
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 , Suspension mixing tank-design heuristic, Chemical product and process modelling, Volume 4, Issue 1, Article 17, The Berkeley Electronic Press
Fort I , Comments on Lea J  “Suspension mixing tank-design heuristic” Manuscript 1419, Chemical product and process modelling, The Berkeley Electronic Press
In Lea , 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  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  and experimental results from Fort  are in good agreement. Download the article by clicking the icon on the left.
INTRODUCTION TO COMPUTATIONAL FLUID DYNAMICS
Computational ﬂuid dynamics (CFD) was born during World War II, when scientists at Los Alamos National Laboratory were not only developing the atomic bomb, but also the numerical tools to describe the violent ﬂow created by such a device. Among them was mathematician J. von Neumann, who contributed the keystone method of artiﬁcial viscosity for “capturing” shocks in numerical solutions and is regarded as the father of CFD. In the 65 years of its existence, CFD has earned itself a respectable place alongside the established disciplines of theoretical and experimental ﬂuid dynamics. It is a branch of science that attracts mathematicians, physicists, and engineers alike, possibly because of the strong sense of empowerment it confers on its practitioners. Developers of CFD methods create a virtual reality that users may populate with anything that ﬂows, regardless of scale. It could be a trickle of molecules ﬁnding their way through a micro-electro-mechanical system microchannel or air that lifts an entire airplane; it could be the ﬂame moving through a combustion chamber or the melting core of a nuclear reactor gone unstable; it could be the earth’s restless oceans and atmosphere or the gaseous disk of a spiral galaxy. Moreover, the concept of ﬂowing is broad: trafﬁc ﬂows over multilane highways, and an ensemble of stars ﬂows through phase space; both may be treated with CFD. The bottom line: CFD methods allow the user virtual experiments that in the words of P.L Roe, would be “expensive, difﬁcult, or dangerous, [or] impossible” in the real world.
As one of the leading CFD simulation companies in Australia, we are the only CFD simulation company with in-house capability that empowers us to successfully provides CFD analysis services on a daily basis to clients across various industries such as the built environment, chemical & petrochemical and water & wastewater.
The contents in the publications on this page were based on the industry knowledge we have gained whilst working on commercial projects as a top-tier CFD simulation company. 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
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.