Current Issue : April - June Volume : 2016 Issue Number : 2 Articles : 4 Articles
Given their potentially enormous risk, process monitoring and fault diagnosis for chemical plants have recently been the focus of\nmany studies. Based on hazard and operability (HAZOP) analysis, kernel principal component analysis (KPCA), wavelet neural\nnetwork (WNN), and fault tree analysis (FTA), a hybrid process monitoring and fault diagnosis approach is proposed in this study.\nHAZOP analysis helps identify the fault modes and determine process variables monitored.The KPCA model is then constructed to\nreduce monitoring variable dimensionality.Meanwhile, the fault features of the monitoring variables are extracted, so then process\nmonitoring can be performed with the squared prediction error (SPE) statistics of KPCA. Then,multiple WNN models are designed\nthrough the use of low-dimensional sample data preprocessed by KPCA as the training and test samples to detect the fault mode\nonline. Finally, FTA approach is introduced to further locate the fault root causes of the fault mode. The proposed approach is\napplied to process monitoring and fault diagnosis in a depropanizer unit. Case study results indicate that this approach can be\napplicable to process monitoring and diagnosis in large-scale chemical plants. Accordingly, the approach can serve as an early and\nreliable basis for technicians� and operators� safety management decision-making....
In the study the yield and kinetic and thermodynamic parameters of the oil extraction process from Jatropha curcas L. using ethanol\nas a solvent were evaluated for different temperatures, moisture contents of the solid phase, and particle sizes.The extraction process\nyield increased with contact time of solid particles with the solvent until reaching equilibrium (saturation of the solvent), for all\nthe temperatures, moisture contents, and average particle sizes. These parameters significantly influenced (95% confidence) the\nextracted oil yield. A convective mass transfer model was used to simulate the extraction process and estimate the kinetic and\nthermodynamic parameters. For all conditions evaluated, values of oil yield in the liquid phase close to equilibrium were obtained\nin approximately 20 min. The variations of enthalpy and entropy were positive, indicating that the process is endothermic and\nirreversible. Values obtained for the variation in Gibbs free energy showed that the extraction process using ethanol as a solvent\nis spontaneous and thermodynamically favorable for the moisture content of 0%, where the smaller the average particle size the\ngreater the spontaneity of the process....
Effect of KOH, reaction temperature and time, and introduced carbonization step on the amount and composition of syngas\nas well as porous properties of the carbon products for CO2 gasification of coconut shell at low temperatures (300ââ?¬â??700âË?Ë?C) was\ninvestigated. Results showed that the presence of potassium hydroxide and gasification temperature had a significant effect on\nthe amount and composition of syngas product and facilitated the rate of hydrogen and carbon monoxide formation. It was also\nfound that carbonization step could promote the generation of hydrogen gas as well as increasing the gas heating value per kg of\ngas. Furthermore, the porosity development of carbon product was found to be influenced by the chemical ratio and gasification\ntemperature.The optimal conditions for achieving high hydrogen composition and specific surface area were to gasify coconut shell\nunder CO2 at 600âË?Ë?C for 60 min with carbonization step and with chemical weight ratio of 3.0. This condition gave the hydrogen\ncomposition as high as 29.70 %weight of produced syngas with heating value of 41.4 MJ/kg of gas and specific surface area of\n2650m2/g of the carbon product....
The ultrasound-assisted extraction (UAE) was initially applied to extract gallic acid from Suaeda glauca Bge. using 70% ethanol as\nextraction solvent. Temperature, liquid-solid ratio, and extraction time were optimized by response surface methodology (RSM),\nobtaining maximum levels of gallic acid (6.30mgââ?¹â?¦gâË?â??1) at 51âË?Ë?C, 19.52mLââ?¹â?¦gâË?â??1, and 42.68 min, respectively.The obtained model was\nstatistically significant (...
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