The Experts below are selected from a list of 5433 Experts worldwide ranked by ideXlab platform
Laurent M Matuana - One of the best experts on this subject based on the ideXlab platform.
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Nanoclay reinforced HDPE as a matrix for wood-plastic composites
Composites Science and Technology, 2008Co-Authors: Omar Faruk, Laurent M MatuanaAbstract:Abstract This study was aimed at identifying the best approach of incorporating nanoclay into wood-plastic composites (WPCs) to enhance their mechanical properties. Two different methods of introducing nanoclays into HDPE-based WPCs were examined. The first method involved the reinforcement of HDPE matrix with nanoclay, which was then used as a matrix in the manufacture of the wood-plastic composites (melt Blending Process). The second method consisted of a direct addition of nanoclay into HDPE/wood-flour composites during conventional dry compounding (direct dry Blending Process). The mechanical properties of injection molded WPCs were characterized using flexural, tensile, and dynamic mechanical analysis tests. In addition, the effect of five different types of nanoclays on the mechanical properties of HDPE was examined to identify the most effective nanoclay type for wood-plastic composites. The degree of nanoclay intercalation in HDPE-based nanocomposites was characterized by means of X-ray diffraction method and transmission electron microscopy. The melt Blending Process, in which nanoclay/HDPE nanocomposite was used as matrix, appeared to be the best approach of incorporating nanoclay in WPCs. The experimental results indicated that the mechanical properties of HDPE/wood-flour composites could be significantly improved with an appropriate combination of the coupling agent content and nanoclay type in the composites.
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Nanoclay reinforced HDPE as a matrix for wood-plastic composites
Composites Science and Technology, 2008Co-Authors: Omar Faruk, Laurent M MatuanaAbstract:This study was aimed at identifying the best approach of incorporating nanoclay into wood-plastic composites (WPCs) to enhance their mechanical properties. Two different methods of introducing nanoclays into HDPE-based WPCs were examined. The first method involved the reinforcement of HDPE matrix with nanoclay, which was then used as a matrix in the manufacture of the wood-plastic composites (melt Blending Process). The second method consisted of a direct addition of nanoclay into HDPE/wood-flour composites during conventional dry compounding (direct dry Blending Process). The mechanical properties of injection molded WPCs were characterized using flexural, tensile, and dynamic mechanical analysis tests. In addition, the effect of five different types of nanoclays on the mechanical properties of HDPE was examined to identify the most effective nanoclay type for wood-plastic composites. The degree of nanoclay intercalation in HDPE-based nanocomposites was characterized by means of X-ray diffraction method and transmission electron microscopy. The melt Blending Process, in which nanoclay/HDPE nanocomposite was used as matrix, appeared to be the best approach of incorporating nanoclay in WPCs. The experimental results indicated that the mechanical properties of HDPE/wood-flour composites could be significantly improved with an appropriate combination of the coupling agent content and nanoclay type in the composites. © 2008 Elsevier Ltd. All rights reserved.
Jian Zhang - One of the best experts on this subject based on the ideXlab platform.
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optimal operation control of the raw slurry Blending Process using the case based reasoning and neural network
International Journal of Advanced Mechatronic Systems, 2010Co-Authors: Shaocheng Tong, Jian Zhang, Tian-you ChaiAbstract:Raw slurry Blending Process is a key unit in the sintering alumina industry. In this Blending Process, raw materials are grinded and blended in the mills to produce raw slurry. The optimal operation control objective is to make the quality indices of raw slurry into their targeted ranges. Flow rates of raw materials are the key factors that affect the quality indices of raw slurry. So, in order to realise the optimal operation control objective, right set points of flow rates must be obtained. However, due to the dynamics between quality indices and control loops of flow rates with complex natures, such as strong non-linearity, heavy coupling and difficulty of description by the accurate model, such a control objective is difficult to be realised by existing control methods. An intelligent optimal control method, which is comprised of the setting layer and the loop control layer, is proposed. In the setting layer, case-based reasoning (CBR) and neural network are adopted to obtain right set points of the control loops. In the loop control layer, the actual flow rates of raw materials follow their set points obtained from the setting layer. At last, the results of industry experiments have proven the effectiveness of the proposed method.
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Fuzzy Optimal Control for Operation of the Raw Slurry Blending Process
2009 Fourth International Conference on Innovative Computing Information and Control (ICICIC), 2009Co-Authors: Shaocheng Tong, Jian Zhang, Chunxia WangAbstract:In the raw slurry Blending Process, red mud, alkali powder, Blending ore and limestone are translated into ball mills to produce the raw slurry whose quality indices include calcium ratio, alkali ratio and water content. The optimal control objective is to make the quality indices of raw slurry into their targeted ranges. However, due to the dynamics between the quality indices and the flow-rate of feedstock with complex natures, such as the difficulty of description by the accuracy model, it is difficult to realize this control objective by the existing operation control methods. A novel operation control method based-on fuzzy rules reasoning, which can control the quality indices of the raw slurry into their targeted ranges, is proposed. Meanwhile, in the operation control, fuzzy rules are automatically extracted from the Blending Process data. At last, industry experiments are implemented to prove the effectiveness of the proposed method.
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preparation and dielectric properties of polyimide silica nanocomposite films prepared from sol gel and Blending Process
Polymers for Advanced Technologies, 2007Co-Authors: Jian Zhang, Youyi XuAbstract:Using poly(amic acid) (PAA) as a precursor followed by thermal imidization, the polyimide/silica nanocomposite films were prepared via an improved sol–gel Process and a Blending Process, respectively. FT-IR, TEM and TGA measurements were used to characterize the structure and properties of the obtained films. The results confirmed that the introduction of silica did not yield negative effects on the conversion of the PAA precursor to the polyimide. With the increase of silica content, the aggregation of silica appeared in the polyimide matrix, and the thermal stability decreased slightly for both kinds of films. The dielectric constant (e) of both films increased slowly with the increase of the silica concentration. The dielectric constant of the obtained polyimide/silica nanocomposite films displayed good stability within a wide range of temperatures or frequency. Based on modeling relation between e and silica content, the difference in dielectric properties for two kinds of nanocomposites are discussed. Copyright © 2007 John Wiley & Sons, Ltd.
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Preparation and dielectric properties of polyimide/silica nanocomposite films prepared from sol–gel and Blending Process
Polymers for Advanced Technologies, 2007Co-Authors: Jian Zhang, Youyi XuAbstract:Using poly(amic acid) (PAA) as a precursor followed by thermal imidization, the polyimide/silica nanocomposite films were prepared via an improved sol–gel Process and a Blending Process, respectively. FT-IR, TEM and TGA measurements were used to characterize the structure and properties of the obtained films. The results confirmed that the introduction of silica did not yield negative effects on the conversion of the PAA precursor to the polyimide. With the increase of silica content, the aggregation of silica appeared in the polyimide matrix, and the thermal stability decreased slightly for both kinds of films. The dielectric constant (e) of both films increased slowly with the increase of the silica concentration. The dielectric constant of the obtained polyimide/silica nanocomposite films displayed good stability within a wide range of temperatures or frequency. Based on modeling relation between e and silica content, the difference in dielectric properties for two kinds of nanocomposites are discussed. Copyright © 2007 John Wiley & Sons, Ltd.
Omar Faruk - One of the best experts on this subject based on the ideXlab platform.
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Nanoclay reinforced HDPE as a matrix for wood-plastic composites
Composites Science and Technology, 2008Co-Authors: Omar Faruk, Laurent M MatuanaAbstract:Abstract This study was aimed at identifying the best approach of incorporating nanoclay into wood-plastic composites (WPCs) to enhance their mechanical properties. Two different methods of introducing nanoclays into HDPE-based WPCs were examined. The first method involved the reinforcement of HDPE matrix with nanoclay, which was then used as a matrix in the manufacture of the wood-plastic composites (melt Blending Process). The second method consisted of a direct addition of nanoclay into HDPE/wood-flour composites during conventional dry compounding (direct dry Blending Process). The mechanical properties of injection molded WPCs were characterized using flexural, tensile, and dynamic mechanical analysis tests. In addition, the effect of five different types of nanoclays on the mechanical properties of HDPE was examined to identify the most effective nanoclay type for wood-plastic composites. The degree of nanoclay intercalation in HDPE-based nanocomposites was characterized by means of X-ray diffraction method and transmission electron microscopy. The melt Blending Process, in which nanoclay/HDPE nanocomposite was used as matrix, appeared to be the best approach of incorporating nanoclay in WPCs. The experimental results indicated that the mechanical properties of HDPE/wood-flour composites could be significantly improved with an appropriate combination of the coupling agent content and nanoclay type in the composites.
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Nanoclay reinforced HDPE as a matrix for wood-plastic composites
Composites Science and Technology, 2008Co-Authors: Omar Faruk, Laurent M MatuanaAbstract:This study was aimed at identifying the best approach of incorporating nanoclay into wood-plastic composites (WPCs) to enhance their mechanical properties. Two different methods of introducing nanoclays into HDPE-based WPCs were examined. The first method involved the reinforcement of HDPE matrix with nanoclay, which was then used as a matrix in the manufacture of the wood-plastic composites (melt Blending Process). The second method consisted of a direct addition of nanoclay into HDPE/wood-flour composites during conventional dry compounding (direct dry Blending Process). The mechanical properties of injection molded WPCs were characterized using flexural, tensile, and dynamic mechanical analysis tests. In addition, the effect of five different types of nanoclays on the mechanical properties of HDPE was examined to identify the most effective nanoclay type for wood-plastic composites. The degree of nanoclay intercalation in HDPE-based nanocomposites was characterized by means of X-ray diffraction method and transmission electron microscopy. The melt Blending Process, in which nanoclay/HDPE nanocomposite was used as matrix, appeared to be the best approach of incorporating nanoclay in WPCs. The experimental results indicated that the mechanical properties of HDPE/wood-flour composites could be significantly improved with an appropriate combination of the coupling agent content and nanoclay type in the composites. © 2008 Elsevier Ltd. All rights reserved.
Chunxia Wang - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Optimal Control for Operation of the Raw Slurry Blending Process
2009 Fourth International Conference on Innovative Computing Information and Control (ICICIC), 2009Co-Authors: Shaocheng Tong, Jian Zhang, Chunxia WangAbstract:In the raw slurry Blending Process, red mud, alkali powder, Blending ore and limestone are translated into ball mills to produce the raw slurry whose quality indices include calcium ratio, alkali ratio and water content. The optimal control objective is to make the quality indices of raw slurry into their targeted ranges. However, due to the dynamics between the quality indices and the flow-rate of feedstock with complex natures, such as the difficulty of description by the accuracy model, it is difficult to realize this control objective by the existing operation control methods. A novel operation control method based-on fuzzy rules reasoning, which can control the quality indices of the raw slurry into their targeted ranges, is proposed. Meanwhile, in the operation control, fuzzy rules are automatically extracted from the Blending Process data. At last, industry experiments are implemented to prove the effectiveness of the proposed method.
Feng Qian - One of the best experts on this subject based on the ideXlab platform.
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Real Time Optimization of the Gasoline Blending Process with Unscented
2020Co-Authors: Hui Cheng, Weimin Zhong, Feng QianAbstract:Gasoline Blending is a critical Process in petroleum refineries. Real-time optimization (RTO) techniques have been popular with the applications for the Blending Process for optimization purpose. However the dependency of RTO on the measurement of the component impairs its applicability. Therefore how to utilize the Blending model and the product measurement to free RTO from the component measurement is the major research topic in this paper. Unscented Kalman Filter, due to its ability to estimate the parameter for nonlinear model, is chosen to estimate component properties based on the product measurement. The RTO strategy is then proposed with the UKF method for the recipe calculation periodically. Furthermore, the proposed RTO is tested with the gasoline Blending benchmark problem, while the results are compared with the ideal Blending case. The accuracy of the component estimation and the efficiency of the RTO are verified with the results.
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A novel chemical composition estimation model for cement raw material Blending Process
Chinese Journal of Chemical Engineering, 2019Co-Authors: Weimin Zhong, Feng QianAbstract:Abstract Raw material Blending Process is an essential part of the cement production Process. The main purpose of the Process is to guarantee a certain oxide composition for the raw meal at the outlet of the mill by regulating the four raw materials. But the chemical compositions of raw materials vary from time to time, resulting in difficulties to control the oxide compositions to a predefined value. Therefore, a novel algorithm to estimate the chemical compositions of the raw materials is developed. The paper mainly consists of two parts. In model construction part, a novel constrained least square model is proposed to overcome the deviation introduced by long-term drift of the material components, and the model parameters are estimated with an online strategy. And in validation part, the approach is implemented to two examples including datasets from simulation model and the actual industrial Process. The final results show the effectiveness of the proposed method.
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A novel adaptive algorithm with near-infrared spectroscopy and its application in online gasoline Blending Processes
Chemometrics and Intelligent Laboratory Systems, 2015Co-Authors: Kaixun He, Hui Cheng, Feng Qian, Wenli DuAbstract:Abstract Near-infrared (NIR) spectroscopy has been widely used to estimate product qualities. Although numerous studies on NIR modeling methods have been conducted, few papers have reported the online application of an NIR spectrometer in the gasoline Blending Process. This study presents a novel adaptive modeling method to establish an NIR model for the gasoline Blending Process. This method is based on the local learning and recursive modeling framework. Based on the framework, the proposed method can adjust the model structure from two aspects: (i) in sampling intervals, the model is updated with a local learning strategy, and the weights of the training samples can be gradually adjusted; and (ii) when new reference samples become available, the new data pairs are selected and added to the training data set based on an effective evaluation mechanism. The high performance of the proposed algorithm was demonstrated through a spectroscopic data set from a real gasoline Blending Process. The research octane number (RON), as the most important properties of gasoline, was estimated. Several modeling methods such as recursive partial least squares (RPLS), partial least squares (PLS), and locally weighted PLS were utilized for comparison. The results show that the proposed approach produce more accurate results than the traditional RPLS and locally weighted PLS algorithms.
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ICAIC (2) - An Application of the Particle Swarm Optimization on the Gasoline Blending Process
Communications in Computer and Information Science, 2011Co-Authors: Hui Cheng, Weimin Zhong, Feng QianAbstract:In this paper, an optimization strategy on the basis of the particle swarm optimization (PSO) method is proposed to determine the optimal recipe offline for the gasoline Blending Process. An octane number model is proposed for optimization. Furthermore, the proposed strategy has been applied onsite at a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the Blending Process and significantly decrease the quality giveaways and Blending cost. The stability of the gasoline production has been improved as well.
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Real Time Optimization of the Gasoline Blending Process with Unscented Kalman Filter
2011 International Conference on Internet Computing and Information Services, 2011Co-Authors: Hui Cheng, Weimin Zhong, Feng QianAbstract:Gasoline Blending is a critical Process in petroleum refineries. Real-time optimization (RTO) techniques have been popular with the applications for the Blending Process for optimization purpose. However the dependency of RTO on the measurement of the component impairs its applicability. Therefore how to utilize the Blending model and the product measurement to free RTO from the component measurement is the major research topic in this paper. Unscented Kalman Filter, due to its ability to estimate the parameter for nonlinear model, is chosen to estimate component properties based on the product measurement. The RTO strategy is then proposed with the UKF method for the recipe calculation periodically. Furthermore, the proposed RTO is tested with the gasoline Blending benchmark problem, while the results are compared with the ideal Blending case. The accuracy of the component estimation and the efficiency of the RTO are verified with the results.
