Turbulence modelling and its impact on CFD predictions for cooling of electronic components

This paper will discuss Computational Fluid Dynamics (CFD) results from an investigation into the accuracy of several turbulence models to predict air cooling for electronic packages and systems. Also new transitional turbulence models will be proposed with emphasis on hybrid techniques that use the k-ε model at an appropriate distance away from the wall and suitable models, with wall functions, near wall regions. A major proportion of heat emitted from electronic packages can be extracted by air cooling. This flow of air throughout an electronic system and the heat extracted is highly dependent on the nature of turbulence present in the flow. The use of CFD for such investigations is fast becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However turbulence models remain a 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 fluctuations experienced by the turbulent energy and other parameters located at near wall regions and shear layers a particularly fine computational mesh is necessary which inevitably increases the computer storage and run-time requirements. The PHYSICA Finite Volume code was used for this investigation. With the exception of the k-ε and k-ω models which are available as standard within PHYSICA, all other turbulence models mentioned were implemented via the source code by the authors. The LVEL, LVEL CAP, Wolfshtein, k-ε, k-ω, SST and kε/kl models are described and compared with experimental data.

Turbulence modelling for electronic cooling: A review

This paper is intended to provide a general review of the current capabilities of turbulence models within the specific area of electronic cooling. The work discussed in this paper is aimed at examining currently available turbulence models and the formulation of a new two-layer hybrid kElki model which is specifically designed for electronic application areas. A classic backward facing step configuration will be used to evaluate the performance of the turbulence models in the prediction of separated flows. The preliminary results suggest that the hybrid ke/kl turbulence model is a promising zonal model to pursue.

Event models for tumor classification with SAGE gene expression data

Serial Analysis of Gene Expression (SAGE) is a relatively new method for monitoring gene expression levels and is expected to contribute significantly to the progress in cancer treatment by enabling a precise and early diagnosis. A promising application of SAGE gene expression data is classification of tumors. In this paper, we build three event models (the multivariate Bernoulli model, the multinomial model and the normalized multinomial model) for SAGE data classification. Both binary classification and multicategory classification are investigated. Experiments on two SAGE datasets show that the multivariate Bernoulli model performs well with small feature sizes, but the multinomial performs better at large feature sizes, while the normalized multinomial performs well with medium feature sizes. The multinomial achieves the highest overall accuracy.

Modelling of jet-impingement cooling for power electronics

The use of an innovative jet impingement cooling system in a power electronics application is investigated using numerical analysis. The jet impingement system, outlined by Skuriat et al, consists of a series of cells each containing an array of holes. Cooling fluid is forced through the device, forming an array of impingement jets. The jets are arranged in a manner, which induces a high degree of mixing in the interface boundary layer. This increase in turbulent mixing is intended to induce higher Nusselt numbers and effective heat transfer coefficients. Enhanced cooling efficiency enables the power electronics module to operate at a lower temperature, greatly enhancing long-term reliability. The results obtained through numerical modelling deviates markedly from the experimentally derived data. The disparity is most likely due to the turbulence model selected and further analysis is required, involving evaluation of more advanced turbulence models.

Assessment of the degradation of Aspirin by Differential Scanning Calorimetry (DSC)

Purpose. To study thermal stability of Aspirin and define thermal events that are associated with the thermal degradation of aspirin. Methods. Experiments were performed using a DSC 823e (Mettler Toledo, Swiss). Aspirin is prone to thermal degradation upon exposure to high temperatures. The melting point of aspirin is 140.1±0.4ºC (DSC). Aspirin has been examined by heating samples to 120ºC, 155ºC and 185ºC with subsequent cooling to -55ºC and a final heating to 155ºC. Although different heating and cooling ranges have been used, only results obtained at a rate of 10ºC/min will be presented. All runs where conducted in hermetically sealed pans. Results. Upon heating the sample to 120ºC no significant thermal event can be detected. After cooling the sample and reheating a glass transition can be observed at ~-8ºC, followed by the melting of aspirin at ~139ºC. By heating the sample to 155ºC melting of aspirin has been detected at ~139ºC. On cooling and subsequent heating a glass transition occurs at ~-32ºC, together with a broad crystallisation (onset at ~38ºC and peak maximum at ~57ºC) followed by a broad melting with an onset at 94ºC and peak maximum at ~112ºC. Finally, by heating the sample to 185ºC melting at ~ 139ºC was observed, and upon cooling and reheating a glass transition was detected at ~-26ºC and no further events could be recorded. Conclusions. This research demonstrates that the degradation steps of Aspirin depend on the thermal treatment. The main degradation products of different thermal treatments are currently unknown it is clear that acetic acid, which is one of the degradation products, acts as an antiplasticiser by lowering the glass transition temperature. In addition, due to the presence of the degradation products in liquid form (observed by hot stage microscopy), Aspirin is still present in the sample and recrystallises during the second heating step and melts at much lower temperatures.