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RISS 인기검색어
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- 저자 : Weina Ren (검색결과 3 건)
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Complete conversion of cellulose to water soluble substances by pretreatment with ionic liquids
Weina Liu,Weize Wu,Yucui Hou,Shuhang Ren,Wenhua Wang 한국화학공학회 2012 Korean Journal of Chemical Engineering Vol.29 No.10
Pretreatment of cellulose to water soluble substances (WSS) can enhance its efficient conversion in water solvent, such as ethanol fermentation. In this work, we found ionic liquid (IL), 1-methyl-3-methylimidazolium dimethylphosphate ([Mmim][DMP]), could convert efficiently cellulose to obtain WSS, and the product WSS and IL mixture could be separated by ethanol anti-solvent way. Effects of ILs, time, temperature and water on cellulose conversion were investigated. NMR, FTIR, XRD and SEM were employed to study the mechanism of cellulose conversion with ILs. The results indicate that [Mmim][DMP] has a greater ability to interact with cellulose than [Bmim][Cl] under the same conditions. Cellulose can be completely converted into WSS in [Mmim][DMP] under all the investigated temperatures from 140 to 160 oC. Increasing temperature is beneficial to the conversion rate of cellulose. But the presence of water can decrease the conversion rate of cellulose. During the treatment by [Mmim][DMP], the hydroxyls of cellulose can form hydrogen bonds with both anion and cation of [Mmim][DMP], and after the treatment the inter- and intramolecular hydrogen bonds of cellulose and the compact structure of cellulose are collapsed.
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Improved AQPSO Algorithm for Solving the Model of the Skin Effect Electric Heating System
Ding Li,Ding Xinghua,Ren Weina,Lin Aiguo 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.5
In view of the importance of the skin-eff ect electric heat tracing system of the submarine oil pipeline in heating and condensation reduction, it is necessary to start from the skin electric heating mechanism and construct its complete mathematical model to realize the effi cient operation of the system. Aiming at the problem of unknown parameters in the model of the skin-eff ect electric heat tracing system, an improved adaptive quantum behaviour particle swarm optimization algorithm (AQPSO) based on the quantum behaviour particle swarm optimization algorithm is proposed, in order to eff ectively identify the model parameters. In the algorithm design, in view of the high dependence of the basic QPSO algorithm on the shrinkage and expansion coeffi cients, the particle aggregation factor is introduced, and the shrinkage and expansion coeffi cients are redesigned. In view of the diff erent proportions of the fi tness value of the individual optimal position, the weight coeffi cient is introduced to construct the best position of the average weight to realize the improvement of the basic QPSO algorithm. The simulation results show that the AQPSO algorithm has better performance than QPSO in terms of convergence accuracy and robustness. This algorithm not only overcomes the inherent premature defects of particle swarms, but also improves the accuracy of the algorithm and obtains accurate model parameters. It can be seen that the improved adaptive quantum behaviour particle swarm algorithm has certain feasibility and eff ectiveness in the parameter identifi cation of Hammerstein model.
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Research on Deep-Sea Pipeline Tube Bundle Heating System
Li Ding,Xinghua Ding,Weina Ren,Yingying Mu,Aiguo Lin 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.6
In order to ensure the safety of deep-sea submarine pipelines, this paper focuses on the analysis of the axial temperature distribution model of the submarine pipeline and the distribution parameter circuit model of the tube bundle heating system. Combined with these two models, theoretical analysis shows that the heating eff ect of the tube bundle heating system depends on the distributed circuit parameters and power frequency of the system. In order to improve the heat tracing effi ciency, the power frequency needs to be adjusted according to the change of the load temperature, so the power supply frequency of the tube bundle heating system based on the Hammerstein model is optimized. Using a neuro-fuzzy algorithm, not only the theoretical values of heating power and power frequency are obtained, but also the drawbacks of determining the above parameters based on engineering experiments are avoided. Moreover, the pipeline heating is effi cient and stable, the dynamic response is fast, and the working condition is also well adapted.
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