Qi, Pengfei = 湍流熱對流中速度場結構函數和流動循環的實驗研究 / 齊鵬飛. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 65-69). / Abstracts in English and Chinese. / Qi, Pengfei = Tuan liu re dui liu zhong su du chang jie gou han shu he liu dong xun huan de shi yan yan jiu / Qi Pengfei. / Abstract --- p.i / 摘要 --- p.ii / Acknowledgements --- p.iii / Contents --- p.iv / List of Figures --- p.vi / List of Tables --- p.X / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- What is turbulence? --- p.1 / Chapter 1.2 --- Why study turbulence and experimentally? --- p.2 / Chapter 1.3 --- Turbulent Rayleigh-Benard convection --- p.4 / Chapter 1.4 --- Basic equations and characteristic parameters --- p.S / Chapter 1.4.1 --- Continuity equation --- p.5 / Chapter 1.4.2 --- Momentum equation (Navier-Stokes equation) --- p.5 / Chapter 1.4.3 --- Energy equation --- p.7 / Chapter 1.4.4 --- Averaged equations --- p.9 / Chapter 1.4.5 --- Characteristic parameters --- p.10 / Chapter 1.5 --- Statistical properties in small-scale turbulence --- p.13 / Chapter 1.5.1 --- Phenomenological description and Kolmogorov hypotheses --- p.14 / Chapter 1.5.2 --- Local structure of the velocity fluctuations --- p.15 / Chapter 1.6 --- Large-scale circulation --- p.17 / Chapter 1.7 --- Motivation and Organizations of this thesis --- p.19 / Chapter 1.7.1 --- B059 scaling --- p.19 / Chapter 1.7.2 --- Large-scale circulation --- p.19 / Chapter 1.7.3 --- Organization of the thesis --- p.20 / Chapter 1.8 --- Some words to my experiment and further expectation --- p.21 / Chapter Chapter 2 --- Experimental apparatus and techniques --- p.27 / Chapter 2.1 --- Rectangle cell --- p.27 / Chapter 2.2 --- The power supply and cooler --- p.28 / Chapter 2.3 --- Thermistor and multimeter --- p.29 / Chapter 2.4 --- Particle image velocimetry (PIV) technology --- p.30 / Chapter 2.4.1 --- Seeding particles --- p.31 / Chapter 2.4.2 --- Light source and light-sheet optics --- p.33 / Chapter 2.4.3 --- Imaging system --- p.34 / Chapter 2.4.4 --- Control system --- p.34 / Chapter 2.4.5 --- Analysis method --- p.35 / Chapter Chapter 3 --- Small-scale properties in rectangular cell --- p.37 / Chapter 3.1 --- Introduction --- p.37 / Chapter 3.2 --- Experimental condition --- p.37 / Chapter 3.3 --- Homogeneity --- p.39 / Chapter 3.4 --- Isotropy --- p.40 / Chapter 3.5 --- Scaling of structure function --- p.42 / Chapter Chapter 4 --- Large-scale circulation --- p.51 / Chapter 4.1 --- Introduction --- p.51 / Chapter 4.2 --- Experimental condition and limitation --- p.54 / Chapter 4.3 --- Statistical properties of large-scale circulation period --- p.56 / Chapter 4.4 --- Scaling of the Reynolds number --- p.59 / Chapter 4.5 --- Oscillation period --- p.60 / Chapter Chapter 5 --- Conclusion --- p.63 / Chapter 5.1 --- Small-scale properties in rectangular cell --- p.63 / Chapter 5.2 --- Large-scale circulation --- p.63 / Reference --- p.65

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Shang Xiandong. / "September 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 141-146). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

The complex turbulent flow regimes encountered in many thermal-fluid engineering applications have proven resistant to the effective application of systematic design because of the computational expense of model evaluation and the inherent variability of turbulent systems. In this thesis the integration of the Proper Orthogonal Decomposition (POD) for reduced order modeling of turbulent convection with the application of robust design principles is proposed as a practical design approach. The POD has been used successfully to create low dimensional steady state flow models within a prescribed range of parameters. The underlying foundation of robust design is to determine superior solutions to design problems by minimizing the effects of variation on system performance, without eliminating their causes. The integration of these constructs utilizing the compromise Decision Support Problem (DSP) results in an efficient, effective robust design approach for complex turbulent convective systems. The efficacy of the approach is illustrated through application to the configuration of data center server cabinets. Data centers are computing infrastructures that house large quantities of data processing equipment. The data processing equipment is stored in 2 m high enclosures known as cabinets. The demand for increased computational performance has led to very high power density cabinet design, with a single cabinet dissipating up to 20 kW. The computer servers are cooled by turbulent convection and have unsteady heat generation and cooling air flows, yielding substantial inherent variability, yet require some of the most stringent operational requirements of any engineering system. Through variation of the power load distribution and flow parameters, such as the rate of cooling air supplied, thermally efficient configurations that are insensitive to variations in operating conditions are determined. This robust design approach is applied to three common data center server cabinet designs, in increasing levels of modeling detail and complexity. Results of the application of this approach to the example problems studied show that the resulting thermally efficient configurations are capable of dissipating up to a 50% greater heat load and 15% decrease in the temperature variability using the same cooling infrastructure. These results are validated rigorously, including comparison of detailed CFD simulations with experimentally gathered temperature data of a mock server cabinet. Finally, with the approach validated, augmentations to the approach are considered for multi-scale design, extending approaches domain of applicability.