NO emission characteristics in counterflow diffusion flame of blended fuel of H2/CO2/Ar

Flame structure and NO emission characteristics in counterflow diffusion flame of blended fuel of H₂/CO₂/Ar have been numerically simulated with detailed chemistry. The combination of H₂, CO₂ and Ar as fuel is selected to clearly display the contribution of hydrocarbon products to flame structure and NO emission characteristics due to the breakdown of CO₂. A radiative heat loss term is involved to correctly describe the flame dynamics especially at low strain rates. The detailed chemistry adopts the reaction mechanism of GRI 2.11, which consists of 49 species and 279 elementary reactions. All mechanisms including thermal, NO₂, N₂O and Fenimore are taken into account to separately evaluate the effects of CO₂ addition on NO emission characteristics. The increase of added CO₂ quantity causes flame temperature to fall since at high strain rates a diluent effect is prevailing and at low strain rates the breakdown of CO₂ produces relatively populous hydrocarbon products and thus the existence of hydrocarbon products inhibits chain branching. It is also found that the contribution of NO production by N₂O and NO₂ mechanisms are negligible and that thermal mechanism is concentrated on only the reaction zone. As strain rate and CO₂ quantity increase, NO production is remarkably augmented. Copyright © 2002 John Wiley & Sons, Ltd.     

Poly(butylene terephthalate)–clay nanocomposites prepared by melt intercalation: morphology and thermomechanical properties

Nanocomposites based on poly(butylene terephthalate) (PBT) and an organoclay (Cloisite 30B) were prepared by melt blending using a twin‐screw extruder. Two kinds of PBTs, ie PBT‐A and PBT‐B, with different inherent viscosities (η_inh), were used for this study (η_inh of PBT‐A and PBT‐B were 0.74 and 1.48, respectively). Dispersion of the clay layers in the PBT nanocomposites was characterized by using X‐ray diffraction (XRD) and transmission electron microscopy (TEM). Tensile and dynamic mechanical properties and non‐isothermal crystallization temperatures of the nanocomposites were also examined. Nanocomposites based on the higher‐viscosity PBT (PBT‐B) showed a higher degree of exfoliation of the clay and a higher reinforcing effect when compared to the composites based on the lower‐viscosity PBT (PBT‐A). The clay nanolayers dispersed in PBT matrices lead to increases in the non‐isothermal crystallization temperatures of the PBTs, with such increases being more significant for the PBT‐B nanocomposites than for the PBT‐A nanoocomposites. Copyright © 2004 Society of Chemical Industry     

The function of bleaching earths in the processing of palm,palm kernel and coconut oils

The results presented in the literature, which attempt to elucidate the mechanisms by which triglyceride oils are bleached by earths, are reviewed. The impact of this work and how the mechanistic proposals affect changes in oil properties are considered, with particular emphasis on the needs of the palm oil processor. Important properties include color, metals and phosphorus content and oxidative stability of the oil. Investigations made in our own laboratories have been aimed at elucidating the effect of varying physical and chemical properties of the bleaching earth on the quality of bleached and deodorized oils. Techniques used in this work are pore-size distribution, surface area, scanning and transmission electron microscopy and a variety of chemical and X-ray analysis methods. The ability to vary such parameters in montmorillonite clays by alteration of process conditions to give materials with specific performance characteristics is demonstrated. Comparisons are made between acid-activated montmorillonites and other clay types.     

Effect of Thickness of the p-AlGaN Electron Blocking Layer on the Improvement of ESD Characteristics in GaN-Based LEDs

The following letter presents a study regarding GaN-based light-emitting diodes (LEDs) with p-type AlGaN electron blocking layers (EBLs) of different thicknesses. The study revealed that the LEDs could endure higher electrostatic discharge (ESD) levels as the thickness of the AlGaN EBL increased. The observed improvement in the ESD endurance ability could be attributed to the fact that the thickened p-AlGaN EBL may partly fill the dislocation-related pits that occur on the surface of the InGaN-GaN multiple-quantum well (MQW) and that are due to the strain and the low-temperature-growth process. If these dislocation-related pits are not partly suppressed, they will eventually result in numerous surface pits associated with threading dislocations that intersect the InGaN-GaN (MQW), thereby reducing the ESD endurance ability. The results of the experiment show that the ESD endurance voltages could increase from 1500 to 6000 V when the thickness of the p-AlGaN EBL in the GaN LEDs is increased from 32.5 to 130 nm, while the forward voltages and light output powers remained almost the same.     

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.     

Integration of mobile vehicles for automated material handlingusing Profibus and IEEE 802.11 networks

This paper focuses on a method to integrate mobile devices such as a mobile robot, automated guided vehicle, and unmanned container transporter to form an automated material handling system. In this paper, the stationary devices are connected via a Profibus network while the mobile devices are communicating via an IEEE 802.11 wireless LAN. In order to integrate these two networks, a protocol converter is developed on a PC platform that runs two interacting processes with shared internal buffers. The protocol converter performs a role of translator between two different protocols by converting the format of a data frame. In addition to this basic conversion function, the protocol converter has a virtual polling algorithm to reduce the uncertainty involved in accessing the wireless network. Finally, the integrated network. of Profibus and IEEE 802.11 is experimentally evaluated for its data latency and throughput, which shows the feasibility of the Profibus-IEEE 802.11 network for industrial applications involving mobile devices     

Structural properties of 0.65Pb(Mg1/3Nb2/3)O3–0.35PbTiO3 relaxor ferroelectric thin films on SrRuO3 conducting oxides

Coating of 0.65Pb(Mg_1/3Nb_2/3)O₃–0.35PbTiO₃ (PMN–PT) relaxor ferroelectrics by a sol–gel method is followed by growth of epitaxial SrRuO₃ (SRO) metallic oxide electrodes on SrTiO₃ (STO) single-crystal substrate by pulsed laser deposition. High-quality PMN–PT films on SRO with preferred growth orientation were successfully fabricated by controlling the operation parameters. Structural properties of relaxor ferroelectric PMN–PT thin films on SRO/STO substrates have been studied by X-ray diffraction (XRD), transmission electron microscopy (TEM) and atomic force microscopy (AFM). In-plane and out-of-plane alignments of the heterostructure are confirmed and the structural twinning of the materials are also revealed.     

Microstructural investigation of long-term degradation mechanisms in GFRP dowel bars for jointed concrete pavement

Steel dowel bar is used to transfer loads in concrete pavement slab. However, once the steel dowel bar corrodes, it may cause faults, such as joint freezing in concrete pavement, level differences resulting from spalling or decreased efficiency of load transfer, etc., which are the same problems experienced by typical reinforcing steel. This study evaluated the applicability of glass fiber-reinforced polymer (GFRP) dowel bar as a substitute for steel dowel bar. A microstructural analysis was conducted to examine the decrease in durability of GFRP dowel bar exposed to deterioration environments. To analyze the deterioration mechanism of GFRP dowel bar, scanning electron microscopy was employed and the porosity was measured by the gas absorption method. It was concluded that the longer the GFRP dowel bar was exposed to deterioration environments, the more the interlaminar shear stress decreased. This result was validated by the microstructural analysis. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Integrated modelling under uncertainty in watershed-level assessment and management.

Uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modelling system (modified-BASINS) under uncertainty is described and demonstrated for use in receiving-water quality prediction and watershed management. A Monte Carlo simulation was used to investigate the effect of various uncertainty types on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorus (T-P) in the Hwaong Reservoir, considering three uncertainty types, would be less than about 4.4 and 0.23 mg L(-1), respectively, in 2012, with 90% confidence. The effects of two watershed management practices, wastewater treatment plants (WWTP) and constructed wetlands (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaong Reservoir to less than 3.4 and 0.14 mg L(-1), 24 and 41% improvements, respectively, with 90% confidence. Overall, the Monte Carlo simulation in the integrated modelling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on the probability and level of risk, and its application is recommended.     

A run-to-run controller for a chemical mechanical planarization process using least squares generative adversarial networks

Achieving high processing quality for chemical mechanical planarization (CMP) in semiconductor manufacturing is difficult due to the distinct process variations associated with this method, such as drift and shift. Run-to-run control aims to maintain the targeted process quality by reducing the effect of process variations. The goal of controller learning is to infer an underlying output–input reverse mapping based on input–output samples considering the process variations. Existing controllers learn reverse mapping by minimizing the total mapping error for sample data. However, this approach often fails to generate inputs for unseen target outputs because conditional input distributions on target outputs are not captured in the learning. In this study, we propose a controller based on a least squares generative adversarial network (LSGAN) that can capture the input distributions. GANs are deep-learning architectures composed of two neural nets: a generator and a discriminator. In the proposed model, the generator attempts to produce fake input distributions that are similar to the real input distributions considering the process variation features extracted using convolutional layers, while the discriminator attempts to detect the fake distributions. Competition in this game drives both networks to improve their performance until the generated input distributions are indistinguishable from the real distributions. An experiment using the data obtained from a work-site CMP tool verified that the proposed model outperformed the comparison models in terms of control accuracy and computation time.