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A detailed analysis of the effects of ground grid configuration on grounding performance has been carried out for uniform and horizontally stratified soils with multiple layers. The results of the analysis reveal that the most efficient and cost-effective design is highly dependent on soil structure type and characteristics. In the absence of ground rods, grounding grids with uniform mesh size are quite efficient in soils having a thin (relative to grid size) high resistivity (relative to the lower layers) top soil, while grids with small mesh size at the periphery of the grid provide optimum performance in uniform soils and soils with low resistivity top soils. Ground rods were found to be effective only when a significant portion of their length is in contact with a low resistivity soil, as expected.

The assessment of voltage stability margins is a promising direction for wide-area monitoring systems. Accurate monitoring architectures for long-term voltage instability are typically centralized and lack scalability, while completely decentralized approaches relying on local measurements tend towards inaccuracy. Here we present distributed linear algorithms for the online computation of voltage collapse sensitivity indices. The computations are collectively performed by processors embedded at each bus in the smart grid, using synchronized phasor measurements and communication of voltage phasors between neighboring buses. Our algorithms provably converge to the proper index values, as would be calculated using centralized information, but but do not require any central decision maker for coordination. Modifications of the algorithms to account for generator reactive power limits are discussed. We illustrate the effectiveness of our designs with a case study of the New England 39 bus system. 10 pages, submitted for publication

AbstractThe presented synthesis of the title compounds (II), (IV), (VI) and (VIII) is extremely simple and highly efficient without the use of any chromatographic purification.

Abstract The influence of the solid-phase wall boundary condition was investigated in Eulerian–Eulerian numerical simulations of a bubbling fluidized bed. Parametric studies of the particle–wall restitution coefficient and specularity coefficient were performed to evaluate their impact on the predicted flow hydrodynamics in terms of bed expansion, local voidage, and solid velocity. Both two- and three-dimensional simulations were conducted and compared with available experimental data on solid velocity and bubble properties. It is found that the wall effect plays an important role in CFD models. Such factors as the voidage at the bubble boundary, averaging method, and minimum bubble size also influence the mean bubble diameter.

This paper presents an experimental study of indoor thermal environment near a full-scale glass facade with different types of shading devices under varying climatic conditions in winter. Interior glazing and shading temperature, operative temperature and radiant temperature asymmetry were measured for facade sections with roller shades and venetian blinds at different positions. Interior glass surface temperatures can be high during sunny days with low outdoor temperature. Shading systems significantly improved operative temperature and radiant temperature asymmetry during cold sunny days, depending on their properties and tilt angle. During cloudy days the impact was smaller, however the shading layers could still decrease the amount of heat loss through the facade. A transient building thermal model, which also calculates indoor environmental indices under the presence of solar radiation, was developed and compared with the experimental measurements. Part II of this paper uses this validated model with a transient, two-node thermal comfort model (including transmitted solar radiation) for assessment of indoor environmental conditions with different building envelope and shading properties, facade location and orientation.

Abstract Residues from the liquefaction of Black Thunder subbituminous and Illinois No. 6 bituminous coals in an autoclave and a bench unit were examined petrographically. Optical microscopy proved valuable for ranking the samples on the basis of overall coal conversion and presence of vitroplast, granular residue and inertinite. It was observed that in the autoclave that runs on Black Thunder coal, K 2 CO 3 was a superior water gas shift reaction catalyst to NaAlO 2 , or a combination of CS 2 and Fe or Mo catalysts. The amount of vitroplast showing vacuoles and cenospheric morphology in the residues was inversely related to the CO conversion, indicating that the mechanism of vitroplast dissolution is linked to the availability of active CO intermediates (e.g. formate ion, HCOO − ). A CO-steam mixture was more effective than syngas or pure H 2 and N 2 in increasing Black Thunder coal conversion, and resulted in greater morphological changes to the coal particles. In contrast, for Illinois No. 6 coal pure H 2 had a greater effect on coal solubilization and overall conversion than pure CO at the same temperature; this was attributed to the absence of carboxylates to react with the formate ions. Higher mesophase and coke contents were detected in some bench unit runs on Black Thunder coal that were operated in counterflow mode. Higher severity, poorer mixing, longer residence time and a reduction in pressure by almost 3.5 MPa are believed to be responsible for the retrogressive reactions forming mesospheres in these cases.

The author comments on the paper by J. Ma et al. (see ibid., vol.17, p.881-5, 2002), pointing out the practical aspects to be considered for actual conditions in the field.

Energy management is an enabling technique to guarantee the reliability and economy of hybrid electric systems. This paper proposes a novel machine learning-based energy management strategy for a hybrid electric bus (HEB), with an emphasized consciousness of both thermal safety and degradation of the onboard lithium-ion battery (LIB) system. Firstly, the deep deterministic policy gradient (DDPG) algorithm is combined with an expert-assistance system, for the first time, to enhance the “cold start” performance and optimize the power allocation of HEB. Secondly, in the framework of the proposed algorithm, the penalties to over-temperature and LIB degradation are embedded to improve the management quality in terms of the thermal safety enforcement and overall driving cost reduction. The proposed strategy is tested under different road missions to validate its superiority over state-of-the-art techniques in terms of training efficiency and optimization performance.