Volume 16, Issue 3

Nowadays, biodiesel is promoted as an alternative and renewable fuel. The mass-transfer limited transesterification reaction is commonly used for biodiesel production, but it could benefit from process intensification technologies. The Simultaneous Mixer-Separator (SMS) is a novel process intensification reactor capable of integrating the mixing and separation of reactants within a single unit. The current study aims to determine the ideal parameters for continuous biodiesel production using an SMS setup that was exclusively designed and fabricated in-home for enhanced biodiesel production. The research statistically analyzed the effect of the space between the rotor and the bottom of reactor ( h ) (0.7, 1.0, 1.3 cm), the diameter ratio between the rotor and the stator ( Dr/Ds ) (0.5, 0.7, 0.9), and the frequency of the rotor’s rotary speed ( R f ) (20, 40, 60 Hz) on biodiesel yield using the Response Surface Methodology (RSM). Optimal oil to fatty acid methyl ester(FAME) conversion of 93.2% and the optimal volumetric production rate of 1,980 (kg FAME/m 3 ·h) were obtained by setting the SMS to a rotational frequency of 39 Hz, an h of 0.7 cm, and a D r /D s of 0.85.

The present work describes a method of automatic fault detection and identification based on a hybrid model (HM): First Principles – Neural Network. The FPM can simulate a wide range of situations while the NN corrects the model output using information from the historical data of the process. Operating conditions corresponding to different types of faults were simulated with the HM and saved with their description in a process state library. To detect a fault, the online measured data was compared with that corresponding to the operation under normal conditions. If a significant deviation was detected, the current state was compared with all the states stored in the process state library and it was identified as the one at the shortest distance. The method was tested with real data from a methanol-water industrial distillation column. During the studied period of operation of the plant, two faults were identified and reported. The proposed method was able to identify such failures more effectively than an equivalent model of first principles. The results obtained show that the proposed method has a great potential to be used in the automatic diagnosis of faults in refining and petrochemical processes.

The modeling of counter-current leaching plant (CCLP) in Koryo Extract Production is presented in this paper. Koryo medicine is a natural physic to be used for a diet and the medical care. The counter-current leaching method is mainly used for producing Koryo medicine. The purpose of the modeling in the previous works is to indicate the concentration distributions, and not to describe the model for the process control. In literature, there are no nearly the papers for modeling CCLP and especially not the presence of papers that have described the issue for extracting the effective components from the Koryo medicinal materials. First, this paper presents that CCLP can be shown like the equivalent process consisting of two tanks, where there is a shaking apparatus, respectively. It allows leachate to flow between two tanks. Then, this paper presents the principle model for CCLP and the state space model on based it. The accuracy of the model has been verified from experiments made at CCLP in the Koryo Extract Production at the Gang Gyi Koryo Manufacture Factory.

Reverse Osmosis (RO) process can be considered as one of the intensively used pioneering equipment for reusing wastewater of several applications. The recent study presented the development of an accurate model for predicting the dimethylphenol removal from wastewater via RO process. The Response Surface Methodology (RSM) was applied to carry out this challenge based on actual experimental data collected from the literature. The independent variables considered are the inlet pressure (5.83–13.58) atm, inlet temperature (29.5–32) ° C, inlet feed flow rate (2.166–2.583) × 10 –4  m 3 /s, and inlet concentration (0.854–8.049) × 10 -3  kmol/m 3 and the dimethylphenol removal is considered as the response variable. The analysis of variance showed that the inlet temperature and feed flow rate have a negative influence on dimethylphenol removal from wastewater while the inlet pressure and concentration show a positive influence. In this regard, F -value of 240.38 indicates a considerable contribution of the predicted variables of pressure and concentration against the process dimethylphenol rejection. Also, the predicted R 2 value of 0.9772 shows the high accuracy of the model. An overall assessment of simulating the performance of RO process against the operating parameters has been systematically demonstrated using the proposed RSM model. Highlights Response Surface Method forms RO model to remove dimethylphenol from wastewater. The model validation is realised based on actual data of dimethylphenol removal. RSM model shows high F-value that pointed out high contribution of the variables. RSM model depicts R 2 of 0.9772 of high-support of the model and experimental data. Effect of main parameters on dimethylphenol removal analysed by 3D counter plots.

This paper presents the simultaneous optimization of the design and operation in nominal conditions of a geothermal plant where the geothermal fluid is split into two streams to feed an Organic Rankine Cycle (ORC) and a District Heating Network (DHN). The topology of the DHN is also investigated. A Mixed Integer Non-Linear Programming (MINLP) optimization problem is formulated and solved using the GAMS software in order to determine the ORC sizing and the DHN topology. In this study, only R-245fa is used as ORC working fluid, an optional Internal Heat Exchanger (IHE) is considered in the ORC and consumers in DHN can be definite or optional. A multi-objective optimization is performed by maximizing the annual net profit and minimizing the total exergy losses in the plant. The weighted sum of objective functions is used to solve the problem. By varying the weight factor, a Pareto front is obtained and the distance to the ideal, but infeasible, solution enabled to choose the best compromise. Four different DHN topologies are observed depending on the weight factor. Using a suitable criterion to make a decision, the selected configuration corresponds to the most expanded DHN with the smallest value of profit. A sensitive analysis shows that, in case of lower geothermal temperature, it is possible to obtain a unique DHN topology whatever the weight factor.

In this work, adsorption desulfurization is considered for making cleaner fuel. New efficient adsorbents have been designed by using two active metal oxides mainly potassium permanganate (KMnO 4 ) and potassium phosphate (KPO 4 ·3H 2 O) on Activated Carbon (AC). Ultrasonic assisted impregnation method (IWI) is used in designing the adsorbents offering high pore volume, pore size, surface chemistry, and high surface area. Use of ultrasonic method increases the dispersion of the active material (groups) on AC leading to increased number of collisions between O-atom on AC-support resulting in high sulfur removal from fuel. KMnO 4 on AC shows higher adsorption capacity towards sulfur than KPO 4 ·3H 2 O at the same operating conditions. New results with respect to sulfur removal has obtained compared with those obtained by previous studies. Finally, the adsorption kinetic parameters of such process are developed. Thomas and Yoon–Nelson models and the experimental data are used for this purpose using linear and non-linear regression analysis. Yoon–Nelson kinetic model fits well with the experiments data better than Thomas kinetic model in the entire adsorption column system.