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In this study, a different approach is introduced to generate the kinetic sub-model for the modeling of solid-state pyrolysis reactions based on the thermogravimetric (TG) experimental data over a specified range of heating rates. Gene Expression Programming (GEP) is used to produce a correlation for the single-step global reaction rate as a function of determining kinetic variables, namely conversion, temperature, and heating rate.

For a case study on the coal pyrolysis, a coefficient of determination (R²) of 0.99 was obtained using the generated model according to the experimental benchmark data. Comparison of the model results with the experimental data proves the applicability, reliability, and convenience of GEP as a powerful tool for modeling purposes in the solid-state pyrolysis reactions.

The resulting kinetic sub-model takes advantage of particular characteristics, to be highly efficient, simple, accurate, and computationally attractive, which facilitates the CFD simulation of real pyrolizers under isothermal and non-isothermal conditions.

It should be emphasized that the above-mentioned manuscript is not under evaluation in any journals and submitted exclusively for consideration for possible publication in this journal. The generated kinetic model is in the final form of an algebraic correlation which, in comparison to the conventional kinetic models, suggests several advantages: to be relatively simpler, more accurate, and numerically efficient. These characteristics make the proposed model computationally attractive when used as a sub-model in CFD applications to simulate real pyrolizers under complex heating conditions.

Novel snap-cure polymers (SCPs), as matrix systems for high-performance fibre composite materials, provide high potential for manufacturing of component families with small batch sizes and high variability. Especially, the processing of powdered SCP is associated with relatively simple and inexpensive tools. In addition, because of their curing behaviour, they allow short tooling times so that the production of small batch size components is possible in relatively short cycle times. To enable an efficient manufacturing process, an understanding of the curing process is necessary. An adjustment of the process parameters for a uniform design of the temperature field in the material during the manufacturing process is essential. The paper aims to discuss this issue.

For this, a powder SCP resin system was investigated under process-specific conditions. An experimental test approach for determination of various thermal and kinetic material properties was developed. For the adjustment of the process parameters and monitoring of the curing state during the manufacturing process, a kinetic material model was determined. In the end, the validation of the determined model was performed. For this, the temperature distribution under process- specific conditions was measured in order to monitor the curing state of the material.

The experimental investigation showed an uneven temperature field in the material, which leads to an inhomogeneous curing process. This can lead to residual stresses in the structure, which have a critical impact on the material properties.

The determined kinetic model allows a prediction of the curing reaction and adjustment of the process parameters which is essential, especially for thick-walled components with SCPs.

This paper sets out to show the feasibility of the genetic algorithm inverse method for the determination of the parameters of crystallization kinetics laws in isothermal and non‐isothermal conditions, using multiple experiments.

The mathematical model for crystallization kinetics determination and the numerical methods of its resolution are introduced. Crystallization kinetic parameters determined by approximate physical analysis and the inverse genetic algorithm method are presented. Injection molding simulations taking into account crystallization are performed using the finite element method.

It is necessary to perform the optimization on two parameters, transformed volume fraction and number of spherulites to obtain correct results. It is possible to use results from different samples, in spite of the dispersion of some values.

Experimental data for isothermal and non‐isothermal conditions were used and obtained good results for the parameters of crystallization kinetics laws from which the evolutions of overall crystallization kinetics and crystalline microstructure were deduced. Nevertheless, the dispersion of the experimental data concerning the number of spherulites obtained with different samples is important. The evolution of the number of spherulites is required for the optimization to get correct results.

An important result of this work is that the genetic algorithm optimization can be applied to this problem where the experiments cannot be performed with a single sample and the experimental data for the number of spherulites have low precision. Even if only the crystallization kinetics was considered, the feasibility in molding simulation has been shown.

Simulation of crystallization in injection molding is very important for a later prediction of the end‐use properties.

This study aims to elucidate the dyeing kinetics and thermodynamic relationships of CI Reactive Red 24 (RR24) on cotton fabrics, achieve the recycling of inorganic salts and water resources and obtain comprehensive data on color parameters, fastness and other characteristics of fabrics dyed with the recycled dyeing residual wastewater.

The dyeing wastewater obtained through advanced oxidation technology was used as a medium for dyeing cotton fabrics with RR24. The absorbance value of the dyeing residue served as an evaluation index, and the relevant kinetic and thermodynamic parameters were calculated based on this absorbance. The color parameters and fastness of the fabric samples were measured to compare the performance of different dyeing media.

Dyeing cotton with RR24 in both media follows pseudo-second-order kinetics. When dyeing with wastewater media, the dye adsorption in the first 45 min increased by 0.082–1.29 g/kg compared with conventional dyeing. Furthermore, the half-dyeing time was shortened by 4.19–11.99 min and the equilibrium adsorption amount was reduced by 0.277–0.302 g/kg. The adsorption of RR24 on cotton fabrics conformed to the Freundlich model. Fabrics dyed using recycled wastewater exhibit a deeper color, with reduced red light and enhanced blue light, resulting in an overall deeper apparent color.

These dyeing kinetics and thermodynamic properties are beneficial for comprehending and interpreting the dyeing performance and behavior of reactive dyes in dyeing wastewater. They lay a theoretical foundation for the treatment and recycling of dyeing wastewater.

The purpose of this paper is to study the inhibition effect of Tween‐40 on the corrosion of cold rolled steel (CRS) in 1.0‐8.0 M HCl over the temperature range of 20‐50°C. It also aims to make an attempt to correlate both thermodynamic parameters and kinetic parameters with the inhibition effect.

The inhibition efficiencies of Tween‐40 are investigated by weight loss and potentiodynamic polarization methods.

Tween‐40 acts as a good inhibitor in 1.0 M HCl, and inhibition efficiency increases with the inhibitor concentration, while it decreases with HCl concentration and temperature. The adsorption of inhibitor on the CRS surface obeys the Langmuir adsorption isotherm equation. The inhibition effect is satisfactorily explained by both thermodynamic and kinetic parameters. Polarization curves show that Tween‐40 is a mixed‐type inhibitor in hydrochloric acid.

The experimental data have been treated with adsorption theory and kinetic equations successfully. Both the thermodynamic and kinetic parameters can be obtained, and used in explaining the inhibition effect satisfactorily.

The purpose of this paper is to develop the multi-objective optimization approach and its numerical implementation to synthesise the model-base control for the part curing at autoclave processing, which supplies the stability and uniformity of the structure and mechanical properties of the material within the cured composite part.

The approach includes conversion of the cured part and mold geometry from their computer-aided design (CAD) to computer-aided engineering (CAE) representation, a finite element (FE) formulation of the coupled forward heat transfer/thermal kinetic problem with the parameters of prepreg, which should be determined by the thermal analysis, and, finally, a mapping of the area of 4D design space (thermal control parameters) to 2D objective space, whose coordinates are the maximum deviations of degree of cure and temperature within the cured part calculated at each call of the FE model.

The present modeling and optimization approach to the cure process control of the prepreg with thermosetting resin, as well as the means of visualizing optimization results, allow providing insight into complex curing phenomena, estimating the best achievable quality indicators of manufactured composite parts, finding satisfactory parameters of the control law and deciding considering all manufacturing constraints.

The research can be effectively used to optimize the cure process control for a wide class of polymeric composite parts, even with a complex geometry, but it requires the exact conversion of the geometry of the modeled part from the CAD to CAE environment, which implies the need for excluding all topological imperfections of original CAD model to eliminate the possible formation of void elements and other reasons that do not allow the correct FE meshing. Because thermal, rheological and kinetics parameters, which include the governing equations of cure process, depend on the reinforcing fibers, and especially on the resin properties, the thermal testing for the new modeled prepreg needs to be performed.

Computer implementation of the proposed approach and numerical method for model-based optimal control synthesis for composite part cure process can be used in aircraft, rotorcraft, ship and automotive technologies at the design of manufacturing process of the large composite parts with complex shape.

This will allow much better quality for large-scale composite parts, excluding very expensive, time-, energy- and material-consuming multiple cure process testing.

This is first time the problem of optimal control synthesis for curing the large-scale composite parts of complex shape was solved.

The purpose of this paper is to examine the batch adsorption system of a cationic dye (methylene blue, widely used in various sectors) on two adsorbents; ZSM-5 zeolite which was prepared with the molar composition: 0.2057 Na₂O-0.00266 Al₂O₃-SiO₂-0.68 (pyrrolidine)-40 H₂O-0.12 H₂SO₄.

By the hydrothermal synthesis method, and the purified clay and is analyzed by IR and DRX method.

For this, the authors conducted a parametric study of adsorption and effect of several important parameters on the adsorption of BM on the material used, in particular, the contact time (equilibrium is established after 120 min), different concentrations of adsorbents, different masses, the pH and temperature. The experiments demonstrated the crucial role of these parameters. A kinetic study was done and kinetic models were applied to the experimental results such as the pseudo-first order, pseudo-second order.

This work is original.

This study’s aim is to introduce a high-performance sorbent for the removal of both anionic (Congo red; CR) and cationic (methylene blue; MB) dyes from aqueous solutions.

Sodium silicate is adopted as a substrate for GO and AgNPs with positive charge are used as modifiers. The synthesized nanocomposite is characterized by FTIR, FESEM, EDS, BET and XRD techniques. Then, some of the most effective parameters on the removal of CR and MB dyes such as solution pH, sorbent dose, adsorption equilibrium time, primary dye concentration and salt effect are optimized using the spectrophotometry technique.

The authors successfully achieved notable maximum adsorption capacities (Qmax) of CR and MB, which were 41.15 and 37.04 mg g⁻¹, respectively. The required equilibrium times for maximum efficiency of the developed sorbent were 10 and 15 min for CR and MB dyes, respectively. Adsorption equilibrium data present a good correlation with Langmuir isotherm, with a correlation coefficient of R2 = 0.9924 for CR and R2 = 0.9904 for MB, and kinetic studies prove that the dye adsorption process follows pseudo second-order models (CR R2 = 0.9986 and MB R2 = 0.9967).

The results showed that the proposed mechanism for the function of the developed sorbent in dye adsorption was based on physical and multilayer adsorption for both dyes onto the active sites of non-homogeneous sorbent.

The as-prepared nano-adsorbent has a high ability to remove both cationic and anionic dyes; moreover, to the high efficiency of the adsorbent, it has been tried to make its synthesis steps as simple as possible using inexpensive and available materials.

The purpose of this paper is to study the effect of silicon and phosphorus content in steel suitable for galvanizing on its corrosion and inhibitor adsorption processes in steels/cetyltrimethylammonium bromide combined and KI (mixture)/5.0 M hydrochloric acid systems has been studied in relation to the temperature using chemical (weight loss), Tafel polarization, electrochemical impedance spectroscopy (EIS), scanning electronic microscope (SEM) analysis and Optical 3D profilometry characterization. All the methods used are in reasonable agreement. The kinetic and thermodynamic parameters for each steels corrosion and inhibitor adsorption, respectively, were determined and discussed. Results show that the adsorption capacity for Steel Classes A and B are better than Steel Class C surfaces depending on their silicon and phosphorus content. Surface analyses via SEM and Optical 3D profilometry was used to investigate the morphology of the steels before and after immersion in 5.0 M HCl solution containing mixture. Surface analysis revealed improvement of corrosion resistance of Steels Classes A and B in the presence of mixture more than Classes C. It has been determined that the adsorbed protective film on the steels surface heterogeneity markedly depends on steels compositions, that is, the heterogeneity increases with decreasing silicon and phosphorus content.

The effect of silicon and phosphorus content in Steels Classes A, B and C on its corrosion and inhibitor mixture adsorption processes in 5.0 M HCl solution has been studied by weight loss, potentiodynamic polarization, EIS and surface analysis.

The inhibition efficiency of mixture follows the order: (Steel Class A) > (Steel Class B) > Steel Class C) and depends on their compositions in the absence of mixture according on their silicon and phosphorus content, that is, the corrosion rate increases with increasing of the silicon and phosphorus content. A potentiodynamic polarization measurement indicates that the mixture acts as mixed-type inhibitor without changing the mechanism of corrosion process for the three classes of mild steels.

Corrosion rate mild steels in 5.0 M HCl depends on their compositions in the absence of mixture according to their silicon and phosphorus content, that is, the corrosion rate increases with increasing silicon and phosphorus content. The adsorbed protective film on the steels surface heterogeneity markedly depends on steels class’s compositions, that is, the heterogeneity increases with decreasing silicon and phosphorus content.

The purpose of this paper is to extract electrochemical reaction kinetics parameters, such as Tafel slope, exchange current density and equilibrium potential, which cannot be directly measured, this study aims to propose an improved particle swarm optimization (PSO) algorithm.

In traditional PSO algorithms, each particle’s historical optimal solution is compared with the global optimal solution in each iteration step, and the optimal solution is replaced with a certain probability to achieve the goal of jumping out of the local optimum. However, this will to some extent undermine the (true) optimal solution. In view of this, this study has improved the traditional algorithm: at each iteration of each particle, the historical optimal solution is not compared with the global optimal solution. Instead, after all particles have iterated, the optimal solution is selected and compared with the global optimal solution and then the optimal solution is replaced with a certain probability. This to some extent protects the global optimal solution.

The polarization curve plotted by this equation is in good agreement with the experimental values, which demonstrates the reliability of this algorithm and provides a new method for measuring electrochemical parameters.

This study has improved the traditional method, which has high accuracy and can provide great support for corrosion research.