Volume 9, Issue 1 -

In this article, the finite element method (FEM) was applied for modeling of multi-tube fixed bed catalytic reactor (FBCR). For this purpose, a more sophisticated 2D pseudo-heterogeneous model was used to calculate steady-state temperature and partial pressure profiles through the reactor. This model has a vast capability in the prediction of temperature and partial pressure distribution, separately, in the fluid and catalyst phases. The finite element results were compared with de wasch and Froment ’s numerical work which developed for a well-established reaction in the multi-tube FBCR (o-xylene partial oxidation). The R -squared analysis indicated that the FEM results agree favorably with finite difference results which reported in the literature. Numerical solution coincidence of FEM and FDM increases with reduction of inlet gas temperature. The results show that the finite element as a powerful numerical method can be used to describe the multi-tube fixed bed catalytic reactor.

In this work, we developed a model, using a fractional factorial design to study the tensile strength of a film of polyethylene HDPE plastic degradable. The model includes four factors that could potentially affect the resistance of the film: linear polyethylene or low-density polyethylene LDPE, calcium carbonate added as a mineral filler to reduce the cost of the film and the film thickness; an oxo-degradable additive (prooxidant) consisting of a transition metal salt is included in small quantities (typically 2–3%) to the conventional plastic during the manufacturing process in order to get a degradable material, when disposed of in an appropriate environment. Statistical studies corresponding to the analysis of variance show that the prooxidant has no effect on the resistance of the film. The thickness is by far the most important parameter, and it is possible to reach a strength corresponding to 500% of the elongation at break of the film for an appropriate mixture by taking some precautions related to the proportion of the mineral filler. The proposed linear model is valid in the experimental field of the various factors; it leads to a good correlation between the observed and calculated values with a relative bias that does not exceed 3%.

The performance of a pilot-scale spray dryer is investigated experimentally and theoretically. The governing equations for flow field, heat and mass transfer, and particle trajectory are solved by applying computational fluid dynamics (CFD). The effects of inlet air temperature and initial particle diameter on the outlet humidity and particle residence time are examined. These parameters should be considered carefully in proper designing of spray dryers especially for the heat-sensitive products. The model is validated with an error of 5.5%.

Inconsistent ranking is a well-known drawback of antioxidant capacity (AOC) profiling methodologies that use free-radical species as oxidant. This problem leads to assay results that are not biorelevant. Linear free energy relationships (LFER) theory predicts proton transfer (PT) kinetics as a surrogate for biorelevant hydrogen atom transfer (HAT) kinetics. Computational antioxidant capacity simulation (CAOCS), based on real-time proton transfer kinetics modeling (PTKM) of polyphenols and phenol-like small molecules, inspired a novel AOC profiling methodology. Kinetic data acquired by incremental addition of resorcinol to an oxidized probe (phenol red), was fitted to mono-exponential decay equation (MED). Absorbance decay data from strongly antioxidant phenol-like molecules (e.g. ascorbic acid) and a new chromogenic probe (phenolphthalein) was fitted to MED and bi-exponential decay equation. The preferred model and corresponding best-fit rate constant ( K ptt ) was identified by comparison of fits, using Akaike’s Information Criterion (AICc). Photometric phenolphthalein assay (PPA)-derived metric was normalized with photometric phenol red assay (PPRA) results by using a function developed from proton concentration differential between phenolphthalein and phenol red, with respect to decay threshold to plateau (assay endpoint) interval. pKa dependence of the CAOCS’ metric is a signature of structure–function relationships, and hence, biorelevance. It is shown, unambiguously, that a combination of two phenolic probe molecules, an analytical system devoid of free radicals, and statistical identification of preferred exponential decay fit to PT kinetics data, constitutes a novel algorithm for AOC profiling of polyphenols and phenol-like molecules. This methodology holds a promise of utility in quality assurance of dietary supplements.

This paper proposes a simulation model for the heat transfer of the wood plastic composite (WPC), manufactured by using the compression moulding technique. A generalised one-dimensional model for transient heat transfer during hot pressing is proposed based on mathematical equations and engineering principles. Finite difference approach is applied using numerical methods, and a solution to the problem is obtained using explicit method. MATLAB is used for programming purpose. The results obtained from the simulation model are then validated with the experimental data available in the literature. It is observed that the simulation results are in close agreement with the experimental results within an acceptable range. The model is integrated with the GUI in the form of simulation software, and the user does not need knowledge of MATLAB. A case study is also performed for the application of the model. This simulation model can be useful for gaining the insight during compression moulding process and may be helpful to optimize the hot-pressing parameters to improve the quality of WPC, while reducing the pressing time.

Ultrasonic processing is an effective tool to attain required mixing while providing the necessary activation energy in the field of biofuels. In this regard, optimization of fast transesterification of waste cooking oil is very important. The goal of this research paper is therefore to determine the effect of important parameters such as methanol to oil molar ratio, catalyst concentration (potassium hydroxide), temperature, and horn position on oil conversion to methyl ester in ultrasonic mixing method. Result of experiments showed that the optimum conditions for the transesterification process have been obtained as molar ratio of alcohol to oil as 6:1, catalyst concentration of 1 wt.%, temperature as 45°C, and horn position at the interface of methanol to oil. The results show that the ultrasonic method decreases the reaction time as much as up to eight times compare to the conventional stirring. For practically evaluating the theoretical optimum point using genetic algorithm, the obtained values were verified experimentally. In order to perform this, the catalyst concentration, temperature, and the time of reaction were determined, and the values are 1%, 48°C, and 449s, respectively. For the obtained values, the biodiesel conversion was 93.2%, so that the experimental optimum value is closed to that of the theoretical values. As a result, experimental data confirmed the obtained values from optimization method in this research work.

The objective of present research work is to develop a neural network–based model predictive control scheme (NN-MPC) for distillation column. To fulfill this objective, an existing laboratory setup of continuous binary-type distillation column (BDC) is used. An equation-based model that uses the fundamental physical and chemical laws along with valid normal assumptions is validated for this experimental setup. Model predictive control (MPC) is one of the main process control techniques explored in the recent past for various chemical engineering applications; therefore, the conventional MPC scheme and the proposed NN-MPC scheme are applied on the equation-based model to control the methanol composition. In NN-MPC scheme, a three-layer feedforward neural network model has been developed and is used to predict the methanol composition over a prediction horizon using the MPC algorithm for searching the optimal control moves. The training data is acquired by the simulation of the equation-based model under the variation of manipulated variables in the defined range. Two cases have been considered, one is for set point tracking and another is for feed flow disturbance rejection. The performance of the control schemes is compared on the basis of performance parameters namely overshoot and settling time. NN-MPC and MPC schemes are also compared with conventional PID controller. The results show the improvement in settling time with NN-MPC scheme as compared to MPC and conventional PID controller for both the cases.

In this work, one-dimensional heterogeneous model has been developed for an intercooled horizontal ammonia synthesis reactor (HASR) of the Khorasan petrochemical plant. The model is further extended to simulate the HASR with two quench flows. The mass balance, energy balance, and pressure drop equations have been solved simultaneously by fourth-order Runge–Kutta method using MATLAB software to obtain concentration, temperature, and pressure profiles along the reactor beds. For effectiveness factor calculation, a modified shooting method has been used to solve two point boundary value differential equations. The simulation results are compared with the plant data, and good agreement is achieved. In the following, a new configuration for HASR is proposed. The proposed design combines intercooled and two quench flow HASRs. Hence, comparing to the conventional HASR with two quench flows and intercooled HASR, it has higher nitrogen conversion and consequently higher ammonia production rate. The simulation results are compared with the conventional HASRs in order to demonstrate the improved performance of the proposed reactor.