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Poly Alpha Olefins (PAO) are extensively used as cooling fluid for thermal management in avionics cooling applications owing to their superior physical and chemical properties, such as greater fluidity at low temperature, lower volatility, a higher viscosity index, lower pour point, better oxidative and thermal stability as well as low toxicity. Solvents doped with minute concentration of nanoparticles are termed as “Nanofluid”. Anomalous enhancements in thermo-physical property values as well as in heat transfer performance of nanofluids have been reported using nanofluids (compared to that for the neat solvent). The thermal interfacial resistance between the nanoparticle and the solvent molecules (Kapitza Resistance) is the dominant factor controlling the efficacy of the nanofluids for cooling applications.

In this paper a new dc-side active filtering system is proposed for aircraft electric power systems. The proposed active filter provides a continuous adjustable reactive power (both in phase and frequency) in the dc-link to meet the changing requirements which arise due to unbalanced and nonlinear loads at the 400(Hz) output. Furthermore, the active filter eliminate the additional capacitive kVA required in the dc-link caused by unbalanced and nonlinear loads. Results from a laboratory prototype active filter are also discussed.

Artificial Neural Network(ANN) techniques are used to develop a system to detect High Impedance Faults(HIFs) in electric power distribution lines. Encouraging results were observed with a simple Multi-layer Perceptron(MLP) trained with the backpropagation learning algorithm. Although the results are not significantly better than those reported with other algorithmic approaches, ANN techniques have potential advantages over the other approaches; namely, ability to train the system easily to accommodate different feeder characteristics, ability to adapt and so become a better detector with experience and better fault tolerance. When these features are incorporated, the system is expected to perform better than existing systems. The system we developed for the current phase, the training strategies used, the tests conducted and the results obtained are discussed in this paper. Also background discussions on existing HIF detection techniques, and ANN techniques can be found in this paper.

Electric vehicles offer cleaner transportation with lower emissions, thus their increased popularity. Although, electric powertrains contribute to quieter vehicles, the shift from internal combustion engines to electric powertrains presents new Noise, Vibration, and Harshness challenges. Unlike traditional engines, electric powertrains produce distinctive tonal noise, notably from motor whistles and gear whine. These tonal components have frequency content, sometimes above 10 kHz. Furthermore, the housing of the powertrain is the interface between the excitation from the driveline via the bearings and the radiated noise (NVH). Acoustic features of the radiated noise can be predicted by utilising the transmitted forces from the bearings. Due to tonal components at higher frequencies and dense modal content, full flexible multibody dynamics simulations are computationally expensive.