Comparison of modal analysis results of laser vibrometry and nearfield acoustical holography measurements of an aluminum plate

Noise and vibration has long been sought to be reduced in major industries: automotive, aerospace and marine to name a few. Products must be tested and pass certain levels of federally regulated standards before entering the market. Vibration measurements are commonly acquired using accelerometers; however limitations of this method create a need for alternative solutions. Two methods for non-contact vibration measurements are compared: Laser Vibrometry, which directly measures the surface velocity of the aluminum plate, and Nearfield Acoustic Holography (NAH), which measures sound pressure in the nearfield, and using Green’s Functions, reconstructs the surface velocity at the plate. The surface velocity from each method is then used in modal analysis to determine the comparability of frequency, damping and mode shapes. Frequency and mode shapes are also compared to an FEA model. Laser Vibrometry is a proven, direct method for determining surface velocity and subsequently calculating modal analysis results. NAH is an effective method in locating noise sources, especially those that are not well separated spatially. Little work has been done in incorporating NAH into modal analysis.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.