Investigation into the performance of turbulence models for fluid flow and heat transfer phenomena in electronic applications

Computational Fluid Dynamics (CFD) is gradually becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However the mathematical modelling of the erratic turbulent motion remains the key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt changes in the turbulent energy and other parameters situated at near wall regions a particularly fine mesh is necessary which inevitably increases the computer storage and run-time requirements. Turbulence modelling can be considered to be one of the three key elements in CFD. Precise mathematical theories have evolved for the other two key elements, grid generation and algorithm development. The principal objective of turbulence modelling is to enhance computational procedures of efficient accuracy to reproduce the main structures of three dimensional fluid flows. The flow within an electronic system can be characterized as being in a transitional state due to the low velocities and relatively small dimensions encountered. This paper presents simulated CFD results for an investigation into the predictive capability of turbulence models when considering both fluid flow and heat transfer phenomena. Also a new two-layer hybrid kε / kl turbulence model for electronic application areas will be presented which holds the advantages of being cheap in terms of the computational mesh required and is also economical with regards to run-time.

Using EMGs and kinematics data to study the take-off technique of experts and novices for a pole vaulting short run-up educational exercise

This study attempts to characterise the electromyographic activity and kinematics exhibited during the performance of take-off for a pole vaulting short run-up educational exercise, for different expertise levels. Two groups (experts and novices) participated in this study. Both groups were asked to execute their take-off technique for that specific exercise. Among the kinematics variables studied, the knee, hip and ankle angles and the hip and knee angular velocities were significantly different. There were also significant differences in the EMG variables, especially in terms of (i) biceps femoris and gastrocnemius lateralis activity at touchdown and (ii) vastus lateralis and gastrocnemius lateralis activity during take-off. During touchdown, the experts tended to increase the stiffness of the take-off leg to decrease braking. Novices exhibited less stiffness in the take-off leg due to their tendency to maintain a tighter knee angle. Novices also transferred less energy forward during take-off due to lack of contraction in the vastus lateralis, which is known to contribute to forward energy transfers. This study highlights the differences in both groups in terms of muscular and angular control according to the studied variables. Such studies of pole vaulting could be useful to help novices to learn expert's technique.

Enhancing the numerical performance of fire field models (CMS Paper)

This paper describes two new techniques designed to enhance the performance of fire field modelling software. The two techniques are "group solvers" and automated dynamic control of the solution process, both of which are currently under development within the SMARTFIRE Computational Fluid Dynamics environment. The "group solver" is a derivation of common solver techniques used to obtain numerical solutions to the algebraic equations associated with fire field modelling. The purpose of "group solvers" is to reduce the computational overheads associated with traditional numerical solvers typically used in fire field modelling applications. In an example, discussed in this paper, the group solver is shown to provide a 37% saving in computational time compared with a traditional solver. The second technique is the automated dynamic control of the solution process, which is achieved through the use of artificial intelligence techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxation using an integrated production rule engine with a blackboard to monitor and implement the required control changes during solution processing. Initial results for a two-dimensional fire simulation are presented that demonstrate the potential for considerable savings in simulation run-times when compared with control sets from various sources. Furthermore, the results demonstrate the potential for enhanced solution reliability due to obtaining acceptable convergence within each time step, unlike some of the comparison simulations.