Aero-optical distortions of a subsonic boundary layer in a spanwise direction were experimentally investigated at different Mach numbers. Convective speeds were extracted as a function of distance from the wall and compared with hot-wire mean velocities. It was found that optically-extracted velocities match hot-wire velocities in the log-region of the boundary layer, suggesting that wavefront sensors can be used to non-intrusively extract the skin friction coefficient using the Clauser method. Aero-optical spectra at different wallnormal distances were also measured and from them characteristic streamwise length scales were estimated. Finally, weighed density fluctuation profiles and the spanwise correlation lengths were measured in wall-normal direction.

Data centers are the computational hub of the next generation. Rise in demand for computing has driven the emergence of high density datacenters. With the advent of high density, mission-critical datacenters, demand for electrical power for compute and cooling has grown. Deployment of a large number of high powered computer systems in very dense configurations in racks within data centers will result in very high power densities at room level. Hosting business and mission-critical applications also demand a high degree of reliability and flexibility. Managing such high power levels in the data center with cost effective reliable cooling solutions is essential to feasibility of pervasive compute infrastructure. Energy consumption of data centers can also be severely increased by over-designed air handling systems and rack layouts that allow the hot and cold air streams to mix. Absence of rack level temperature monitoring has contributed to lack of knowledge of air flow patterns and thermal management issues in conventional data centers. In this paper, we present results from exploratory data analysis (EDA) of rack-level temperature data collected over a period of several months from a conventional production datacenter. Typical datacenters experience surges in power consumption due to rise and fall in compute demand. These surges can be long term, short term or periodic, leading to associated thermal management challenges. Some variations may also be machine-dependent and vary across the datacenter. Yet other thermal perturbations may be localized and momentary. Random variations due to sensor response and calibration, if not identified, may lead to erroneous conclusions and expensive faults. Among other indicators, EDA techniques also reveal relationships among sensors and deployed hardware in space and time. Identification of such patterns can provide significant insight into data center dynamics for future forecasting purposes. Knowledge of such metrics enables energy-efficient thermal management by helping to create strategies for normal operation and disaster recovery for use with techniques like dynamic smart cooling.

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Measurements of time-resolved aero-optical distortions caused by subsonic boundary layers in the spanwise direction were performed at different heights away from the wall. The wall upstream of the measurement station was either heated or cooled to introduce heat-fluxrelated density variations into the boundary layer. It was demonstrated that the aero-optical deflection angle spectra are self-similar across the boundary layer and the convective speeds of aero-optical structures at different heights are approximately the same for all tested cases. From the collected aero-optical data, the fluctuating density profiles were directly calculated at different heights and compared with the ones predicted by the Extended SRA. It was shown that the Extended SRA incorrectly predicts fluctuating density profiles for strong cooling and heating cases and possible reasons for this discrepancy are discussed. Finally, it was shown that the experimentally-measured fluctuating density profiles correctly predict the aerooptical distortions in the wall-normal direction.

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