Band 18, Heft 3

The objective of the present work was to evaluate the performance of two-stage adsorber of activated carbon from oil palm empty fruit bunch for methylene blue removal. The model was developed to predict optimum adsorbent mass and time at a specified volumes and concentrations of dye solution. Results show that the adsorbent mass can be reduced by 6.67%. Operating time taken to attain the equilibrium in a two-stage adsorber has dramatically decreased from 22 h to 0.52 h. In the performance evaluation, the adsorbent mass in stage-1 is higher than in stage-2, which lessen the workload to achieve equilibrium. A two-stage adsorber aids to optimize the mass and contact time for different percentage of dye removal that economically feasible for industrial applications.

Effective use of waste lignin is always a challenging task, technologies have been applied in the past to get value-added compounds from waste lignin. However, the existing technologies are not economical and efficient to produce the value-added chemicals. Alkali soluble lignin from rice straw hydrolysis residue (RSHR) is subjected to photocatalytic conversion into value-added compounds. Photocatalysis is one of the multifarious advanced oxidation processes (AOPs), carried out with TiO 2 nanoparticles under a 125 W UV bulb. Gas chromatography mass spectroscopy (GCMS) confirmed the formation of vanillin and 4-hydroxybenzaldehyde. RSM and ANN techniques are adopted to optimize the process conditions for the maximization of the products. The response one ( Y 1 ) vanillin (24.61 mg) and second response ( Y 2 ) 4-hydroxybenzaldehyde (19.51 mg) is obtained at the optimal conditions as 7.0 h irradiation time, 2.763 g/L catalyst dose, 15 g/L lignin concentration, and 14.26 g/L NaOH dose for alkali treatment, suggested by face-centered central composite design (CCD). RSM and ANN models are statistically analyzed in terms of RMSE, R 2 and AAD. For RSM the R 2 0.9864 and 0.9787 while for ANN 0.9875 and 0.9847, closer to one warrant the good fitting of the models. Therefore, in terms of higher precision and predictive ability of both models the ANN model showed excellence for both responses as compared to the RSM model.

In the present study, slurry erosion wear was evaluated in 90° horizontal pipe bends of various radius ratios (R/r = 2–10) through a commercial CFD code ANSYS FLUENT. For the suspension of fly ash-water, Euler–Lagrange and two way-coupling methods were employed to predict the slurry erosion wear. The flow through the horizontal bend pipe was simulated using a Standard k – ε turbulence modelling. The computational results were validated with the experimental result of the available literature. Fly ash was taken as the dispersed phase of the solid-liquid combination however water was used as the liquid phase. The fly ash particles size was taken as 150 µm. Various affecting factors, such as velocity (4–10 m/s) and solid concentration (2.5 and 7.5% by volume) of the fly ash, were also studied in this investigation. The erosion rate was maximum in the case of R/r = 4 and minimum for R/r = 10 at all velocities and concentrations. It was also found that the erosion rate increases with the increase in solid concentration and velocity.

The best structure of multicomponent separation techniques can be obtained using optimal distillation sequencing. Because distillation sequences contribute significantly to the fixed and operational cost of the entire chemical process, developing a systematic approach for choosing the most appropriate and economic distillation sequences becomes an important field of study. Due to its high dimensional space and combinatorial nature, synthesis of the optimal conventional distillation column sequence is a tough problem in the field of process plant development and optimization. A novel method for the synthesis of an optimal conventional distillation column sequence is suggested in this study. Genetic algorithm, an evolutionary algorithm is at the heart of the proposed method. The Total Annual Cost (TAC) is the main basis used to evaluate alternative configurations. To estimate the total cost of each sequence, rigorous methods are used to design all columns in the sequence. The proposed method’s performance and that of the conventional quantitative approach are compared using the results of a five component benchmark test problem used by researchers in this field. According to the comparison results, the suggested algorithm outclasses the other methods and is more adaptable than other existing approaches.

In this work, a PID controller along with a noise filter is designed using direct synthesis method for second order stable and unstable processes with time delay. Proposed method involves a single design parameter λ whose value need to be adjusted such that a desired balance between performance and robustness of the system is achieved. Guidelines to select suitable values of λ based on the maximum sensitivity values are provided. Various computer simulations are performed in presence of measurement noise on stable, unstable, integrating and double integrating dynamic systems to illustrate the advantages of suggested control method over some contemporary techniques. Performance measures (integral absolute error and integral squared error) and robustness measures such as maximum sensitivity ( M s ), complimentary sensitivity ( M t ) are calculated for the quantitative performance evaluation of the proposed tuning strategy. The suggested tuning algorithm is simple and it yields improved closed loop response compared to some reported methods, satisfactory robustness and smooth control action in presence of noise.

Biodiesel purification is one of the most important downstream processes in biodiesel industries. The removal of glycerol from crude biodiesel is commonly conducted by an extraction method using water, however this method results in a vast amount of wastewater and needs a lot of energy. In this study, microfiltration membrane was used to remove glycerol from biodiesel, and a process simulation was carried out for an industrial scale biodiesel purification plant using a microfiltration membrane system. The microfiltration experiment using a simulated feed solution of biodiesel containing glycerol and water showed that the membrane process produced purified biodiesel that met the international standards. The result of the process simulation of a multi-stage membrane system showed that the membrane area could be minimized by optimizing the concentration factor of every stage with the aid of a computer program that was written in Phyton programming language with Visual Studio Code. The overall productivity of a single stage membrane system was the same with that of the multi-stage system, however the single stage system required a larger membrane area. To produce 750 m 3  day −1 of purified biodiesel, a multi-stage membrane system consisting of 10 membrane modules required a total membrane area of 1515 m 2 that was 57% smaller compared to the single stage system consisting of one membrane module. This membrane area reduction was equivalent to a reduction of the total capital cost of 30%. Based on the analysis of the total capital cost, it was found that the optimum number of stages was 4 since it showed a minimum value of the total capital cost with a membrane area of 1620 m 2 that was equivalent to the reduction of the total capital cost of 34%. The result of this simulation showed that the multi-stage microfiltration membrane has great potential to replace the conventional method in biodiesel industries.

In oil refineries, fluid catalytic cracking (FCC) is a major unit consisting of several process variables and multiple products. Since FCC units are given prime importance as they are contributing a large share in profits, the optimal operation of FCC is always desirable while considering the changing economic scenarios with respect to the products. However, optimization of FCC is quite challenging due to the complex nature of the process. In this work, using Aspen HYSYS V9 ® catcracker module, process data of FCC was obtained using central composite design (CCD). Second order regression equations for the selected responses were obtained using Analysis of variance (ANOVA) approach. The interaction effects of feed flow, feed temperature, feed pressure, air blower discharge temperature and catalyst circulation rate on responses (yield of products) were presented. Further, the optimization was performed based on a multi-response optimization technique in the Design expert software and the optimal values of the input variables were obtained for the chosen objectives (representing various operation scenarios). The optimal operation scenarios that were obtained for the objectives were validated successfully. This work highlights the use of statistics based soft computing techniques for the optimization of complex chemical engineering operations such as FCC.

The present numerical study is aimed at investigating the effect of rotation on heat transfer to non-Newtonian nanofluid flowing through a pipe. Non-Newtonian fluid flow under laminar condition with heat transfer finds the applications in various industries like food processing, pharmaceutical and polymer etc. Various proportions (1–3%) of copper nanoparticles are mixed with water to study the heat transfer rates non-Newtonian nanofluid flowing through the rotating pipe. Effect of rotation rate on heat transfer rates are also studied. In this study for 1% nanofluid at a constant rotation rate of 0.8, the Nusselt number is increased by 119.45%. The highest thermal performance factor (TPF) is 1.74, observed at N  = 0.8, Pe  = 5000, and for 1% volume concentration of non-Newtonian nanofluid.

In this study, the statistical modeling and optimization of the regeneration of spent bleaching earth (SBE) for re-use in the bleaching of crude palm oil (CPO) oil was examined. Having a good model will assist with the successful optimal regeneration of SBE and hence minimize the environmental pollution associated with its current disposal method which is based on dumping as landfills. The SBE samples were de-oiled with the Soxhlet extraction method, using n-hexane for 1 h at 60 °C; treated at temperatures ranging from 300–500 °C; at carbonization time between 30 and 45 min; and with hydrochloric acid concentrations between 1 and 2 M, at a constant stirring time of 30 min, respectively. The operating conditions for the experiment were according to the Central Composite Design (CCD) experimental design using the Design Expert software version 13. The modeling and optimization of the SBE regeneration process was carried out with the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques. Five regression models were developed from the RSM approach and the best one selected based on model selection parameters recommended in the literature. Similarly, ten ANN models with the number of neurons in the hidden layer that varied from 2 to 16 were considered and the best one selected using the mean square error (MSE) and correlation coefficients (R) for the training, validation and testing performances. Results showed that the ANN technique led to a model with a better predictive ability than the RSM one. The optimum experimental bleachability of 71.5% for the regenerated de-oiled SBE was obtained at carbonization temperature of 500 °C, hydrochloric acid concentration of 2M and carbonization time of 45min. Using the Genetic Algorithm (GA), the ANN model resulted in an optimum bleachability of 70.87% with corresponding optimum factors at 468.19 °C, 2 M and 45 min, while the RSM approach gave an optimum bleachability of 73.52% at the corresponding factors of 498.99 °C, 1.57 M and 41.14 min for the carbonization temperature, acid concentration and carbonization time, respectively. The optimum experimental bleachability of the regenerated SBE achieved was 12.5% higher than that of virgin bleaching earth (VBE).

The study of flow and mixing dynamics for conventional micromixers as well as micromixers with split and recombine (SAR) units has been carried out using laminar and transport diluted physics modules. Initially, a pilot numerical analysis was done for the basic Y-shaped curved, rectangular and triangular serpentine micromixers. Later, SAR units have been added to these basic designs and the effect of SAR units on the performance characteristics viz., mixing index, pressure drop, performance index and pumping power has been studied. In-depth qualitative analysis was also carried out to visualize the flow and mixing dynamics for the Reynolds number in the range from 0.1–50. The study results revealed that the square shaped chambers and circular obstacle based rectangular serpentine micromixer (SCCO-RSM) demonstrated better performance as compared to the other designs. The proposed micromixer is the better candidate for microfluidics applications such as Lab-On-a-Chip (LOC), Micro-Total-Analysis-Systems (µTAS) and Point of Care Testing (POCT), etc.