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Internal combustion (IC) engine based powertrains are one of the most commonly used transmission systems in various industries such as train, ship and power generation industries. The powertrains, acting as the cores of machinery, dominate the performance of the systems; however, the powertrain systems are inevitably degraded in service. Consequently, it is essential to monitor the health of the powertrains, which can secure the high efficiency and pronounced reliability of the machines. Conventional vibration based monitoring approaches often require a considerable number of transducers due to large layout of the systems, which results in a cost-intensive, difficultly-deployed and not-robust monitoring scheme. This study aims to develop an efficient and cost-effective approach for monitoring large engine powertrains. Our model based investigation showed that a single measurement at the position of coupling is optimal for monitoring deployment. By using the instantaneous angular speed (IAS) obtained at the coupling, a novel fault indicator and polar representation showed the effective and efficient fault diagnosis for the misfire faults in different cylinders under wide working conditions of engines; we also verified that by experimental studies. Based on the simulation and experimental investigation, it can be seen that single IAS channel is effective and efficient at monitoring the misfire faults in large powertrain systems.

In the present work, direct numerical simulation is employed to investigate the unsteady flow characteristics and energy performance of low-pressure turbines (LPT) by considering the blades aeroelastic vibrations and inflow wakes. The effects of inflow disturbance (0 < φ < 0.91) and reduced blade vibration (0 < f < 250 Hz) on the turbulent flow behavior of LPTs are investigated for the first time. The transient governing equations on the vibrating blades are modelled by the high-order spectral/hp element method. The results revealed that by increasing the inflow disturbances, the separated bubbles tend to shrink, which has a noticeable influence on the pressure in the downstream region. The maximum wake loss value is reduced by 16.4% by increasing the φ from 0.31 to 0.91. The flow separation is majorly affected by inflow wakes and blade vibrations. The results revealed that the maximum pressure coefficient in the separated flow region of the vibrating blade has been increased by 108% by raising φ from 0 to 0.91. The blade vibration further intensifies the vortex generation process, adding more energy to the flow and the downstream vortex shedding. The vortex generation and shedding are intensified on the vibrating blade compared to the non-vibrating one that is subject to inflow wakes. The results and findings from this paper are also useful for the design and modeling of turbine blades that are prone to aeroelastic instabilities, such as large offshore wind turbine blades.

The thermal masses of components influence the performance of many adsorption heat pump systems. However, typically when experimental adsorption systems are reported, data on thermal mass are missing or incomplete. This work provides original measurements of the thermal masses for experimental sorption heat exchanger hardware. Much of this hardware was previously reported in the literature, but without detailed thermal mass data. The data reported in this work are the first values reported in the literature to thoroughly account for all thermal masses, including heat transfer fluid. The impact of thermal mass on system performance is also discussed, with detailed calculation left for future work. The degree to which heat transfer fluid contributes to overall effective thermal mass is also discussed, with detailed calculation left for future work. This work provides a framework for future reporting of experimental thermal masses. The utilization of this framework will enrich the data available for model validation and provide a more thorough accounting of adsorption heat pumps.

The flow developed on a tidal site can be characterized by combinations of turbulence, shear flows, and waves. Horizontal-axis tidal turbines are therefore subjected to dynamic loadings that may compromise the working life of the rotor and drive train components. To this end, a series of experiments were carried out using a 0.9 m horizontal-axis tidal turbine in a tow tank facility. The experiments included two types of regular waveforms, one of them simulating an extreme wave case, the other simulating a more moderate wave case. The second regular wave was designed to match the peak period and significant wave height of an irregular wave which was also tested. Measurements of torque, thrust, and blade-bending moments were taken during the testing campaign. Speed and torque control strategies were implemented for a range of operational points to investigate the influence that a control mode had in the performance of a tidal stream turbine. The results showed similar average power and thrust values were not affected by the control strategy, nor the influence of either the regular or irregular wave cases. However, it was observed that using torque control resulted in an increase of thrust and blade root bending moment fluctuations per wave period. The increase in fluctuations was in the order of 40% when compared to the speed control cases.

The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of the economic cost minimization into three objectives with the additional maximization of the charging station utilization, and maximization of the reliability level. Compared with the existing models, it captures the interactive impacts between charging infrastructures planning and distribution network planning from the aspects of economy, utilization, and reliability. A multi-stage search strategy is designed to solve the multi-objective problem. The models and the strategy are demonstrated by the test case. The results show that the proposed planning framework can make a trade-off among the three objectives, and offer a perspective to effectively integrate the network constraints from both the transportation network and distribution network.

Effects of oxygen content of fuels on combustion characteristics and emissions were investigated on both an optical single cylinder direct injection (DI) diesel engine and a multi-cylinder engine. Three fuels were derived from conventional diesel fuel (Finnish City diesel summer grade) by blending Rapeseed Methyl Ester (RME) or Diglyme and Butyl-Diglyme of different quantities to make their oxygen content 3%, 3% and 9%, respectively. The experimental results with three tested fuels show that the fuel spray development was not affected apparently by the oxygenating. Compared with the base fuel, the ignition delay to pilot injection was shortened by 0%, 11% and 19% for three oxygenated fuels, respectively. The ignition delay to main injection was shortened by 10%, 19% and 38%, respectively. With regard to emissions, the smoke level was reduced by 24% to 90%, depending on fuel properties and engine running conditions. The penalties of increased NOx emissions and fuel consumption were up to 19% and 24%, respectively.

In this paper, a bi-level energy management framework based on Conditional Value at Risk (CVaR) and game theory is presented in the context of different ownership of multiple microgrid systems (MMGS) and microgrid aggregators (MAs). The energy interaction between MMGS and MAs can be regarded as a master–slave game, where microgrid aggregators as the leaders set the differentiated tariff for each MG to maximize its benefits, and MMGS as the follower responds to the tariff decision specified by the leader through peer-to-peer (P2P) energy sharing. The P2P energy sharing of MMGS can be regarded as a co-operative game, employing asymmetric Nash bargaining theory to allocate the co-operative surplus. The Conditional Value at Risk model was used to characterize the expected losses by microgrid aggregators due to the uncertainties of renewable energy resources. The Karush–Kuhn–Tucker conditions, Big-M method, and strong duality theory were employed to transform the bi-level nonlinear model of energy management into a single-level mixed integer linear programming model. The simulation results show that when MGs adopt the P2P energy-sharing operation mode, the total operating cost of MMGS can be reduced by 7.82%. The simulation results show that the proposed co-operative optimization framework can make the multiple microgrid systems obtain extra benefits and improve the risk resistance of microgrid aggregators.