Optimization of peroxidase-catalyzed oxidative coupling process for phenol removal from wastewater using response surface methodology

Hydroxylated aromatic compounds (HACs) are considered to be primary pollutants in a wide variety of industrial wastewaters. Horseradish peroxidase (HRP) is suitable for the removal of these toxic substances. However, development of a mathematical model and optimization of the HRP-based treatment considering the economical issues by novel methods is a necessity. In the present study, optimization of phenol removal from wastewater by horseradish peroxidase (HRP) was carried out using response surface methodology (RSM) and central composite design (CCD). As the initial experimental design, 2(4-1) half-fraction factorial design (H-FFD) is accomplished in triplicate at two levels to select the most significant factors and interactions in the phenol removal procedure. Temperature (degrees C), pH, concentration of enzyme (unit mL(-1)), and H202 (mM) were determined as the most effective independent variables. Finally, a fourfactor-five coded level CCD, 30 runs, was performed in order to fit a second-order polynomial function to the results and calculate the economically optimum conditions of the reaction. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.93), the corresponding analysis of variance ((Pmodel > F) < 0.0001) and parity plot (r = 0.96). These analyses indicated that the fitted model is appropriate for this enzymatic system. With the assumption that the minimum enzyme concentration was 0.26 unit mL(-1), the analysis of the response surface contour and surface plots defined the optimum conditions as follows: pH = 7.12, hydrogen peroxide concentration 1.72 mM, and 10 degrees C. This work improves phenol removal operation economically by applying minimum enzyme concentration and highest removal in comparison with previous studies.     

Fracture assessment of graphite V‐notched and U‐notched specimens by using the cohesive crack model

This article explores the capability of the Cohesive Zone Model in predicting the critical load of blunt notched specimens made of coarse‐grained polycrystalline graphite, a brittle material that has gained the attention of researchers because of its favourable properties for protection against thermal loads. To that aim, 39 different tests on U‐notched and V‐notched specimens made of this material, with loading modes raging from mode I to mixed mode I/II, have been modelled by using the Cohesive Zone Model. The model has been implemented through the embedded crack approach, avoiding thus the necessity of defining the crack trajectory prior to the simulation because it is automatically generated once the maximum principal stress overcomes the tensile strength of the material. The numerical predictions obtained show good agreement with the experimental results.     

The application of differential transformation method to nonlinear equations arising in heat transfer

In this paper two nonlinear heat transfer problems were solved by considering variable specific heat coefficient. The calculations are carried out by using differential transformation method (DTM) which is a semi-numerical-analytical solution technique. By using DTM, the nonlinear constrained governing equations are reduced to recurrence relations and related initial conditions are transformed into a set of algebraic equations. The principle of differential transformation is briefly introduced, and then applied for the aforementioned problems. The solutions are subsequently solved by a process of inverse transformation. The current results are then compared with those derived from the variational iteration method (VIM), homotopy perturbation method (HPM), perturbation method (PM) and the exact solutions in order to verify the accuracy of the proposed method. The findings reveal that the DTM can achieve more suitable results in predicting the solution of such problems.     

Thermal buckling analysis of temperature-dependent FG-CNTRC quadrilateral plates

The main objective of the present study is to analyze the thermal buckling of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) quadrilateral plates. Functionally graded patterns are introduced for the distribution of the carbon nanotubes (CNTs) through the thickness direction of the plate. The effective material properties of nanocomposite plate reinforced by CNTs are considered to be temperature-dependent (TD) and estimated using the micromechanical model. By the use of minimum total potential energy principle and based on the first-order shear deformation theory of plates, the stability equations are obtained. In order to use the generalized differential quadrature (GDQ) method and solve the stability equations, the irregular domain of quadrilateral plate is transformed into regular computational domain employing the mapping technique. The efficiency and accuracy of the proposed approach are first validated. Then, a comprehensive parametric study is presented to examine the effects of model parameters on the thermal buckling of FG-CNTRC quadrilateral plates. The results indicate that considering temperature dependency of the material properties plays an important role in the stability of the FG-CNTRC quadrilateral plates subjected to thermal loading.     

A dynamic task scheduling framework based on chicken swarm and improved raven roosting optimization methods in cloud computing

Scheduling means devoting tasks among computational resources, considering specific goals. Cloud computing is facing a dynamic and rapidly evolving situation. Devoting tasks to the computational resources could be done in numerous different ways. As a consequence, scheduling of tasks in cloud computing is considered as a NP-hard problem. Meta-heuristic algorithms are a proper choice for improving scheduling in cloud computing, but they should, of course, be consistent with the dynamic situation in the field of cloud computing. One of the newest bio-inspired meta-heuristic algorithms is the chicken swarm optimization (CSO) algorithm. This algorithm is inspired by the hierarchical behavior of chickens in a swarm for finding food. The diverse movements of the chickens create a balance between the local and the global search for finding the optimal solution. Raven roosting optimization (RRO) algorithm is inspired by the social behavior of raven and the information flow between the members of the population with the goal of finding food. The advantage of this algorithm lies in using the individual perception mechanism in the process of searching the problem space. In the current work, an ICDSF scheduling framework is proposed. It is a hybrid (IRRO-CSO) meta-heuristic approach based on the improved raven roosting optimization algorithm (IRRO) and the CSO algorithm. The CSO algorithm is used for its efficiency in satisfying the balance between the local and the global search, and IRRO algorithm is chosen for solving the problem of premature convergence and its better performance in bigger search spaces. First, the performance of the proposed hybrid IRRO-CSO algorithm is compared with other imitation-based swarm intelligence methods using benchmark functions (CEC 2017). Then, the capabilities of the proposed scheduling hybrid algorithm (IRRO-CSO) are tested using the NASA-iPSC parallel workload and are compared with the other available algorithms. The obtained results from the implementation of the hybrid IRRO-CSO algorithm in MATLAB show an improvement in the average best fitness compared with the following algorithms: IRRO, RRO, CSO, BAT and PSO. Finally, simulation tests performed in cloud computing environment show improvements in terms of reduction of execution time, reduction of response time and the increase in throughput by using the proposed hybrid IRRO-CSO approach for dynamic scheduling.     

Activity-based costing in flexible manufacturing systems with a case study in a forging industry

The objective of this paper is to apply the activity-based costing (ABC) approach together with traditional costing (TC) for parts costing in flexible manufacturing systems (FMS) with the A(2) level of automation. We propose a new model for the implementation of ABC using the product cost tree concept. First, the required resources and activities for each part are recorded, and then their costs are calculated using the appropriate cost formulae. This model was applied in a forging industry. A comparison and analysis between ABC and TC was then carried out based on the computational results obtained from the case study. The results indicate that the ABC outputs are more reliable than the TC outputs, and thus the ABC approach is a more acceptable tool for parts costing in FMS.     

MIP-based heuristics for lotsizing in capacitated pure flow shop with sequence-dependent setups

Lotsizing in capacitated pure flow shop with sequence-dependent setups has been considered in this paper. An exact formulation of the problem is provided as a mixed-integer program. It is well known that the capacitated lotsizing and scheduling problem (CLSP) is NP-hard. The introduction of serially arranged machines and sequence-dependent setups makes the problem even more complicated. Five MIP-based heuristics based on iterative procedures are provided. The first three heuristics are based on the original model but to solve non-small instances of problem, the last two heuristics are based on permutation flow shop problem which ignores the majority of combinations. To test the accuracy of heuristics, two lower bounds are developed and compared against the optimal solution. The trade-offs between solution quality and computational times of heuristics are also provided.     

Comparison of High-Energy He+ and D+ Irradiation Impact on Tungsten Surface in the IR-IECF Device

Polycrystalline tungsten specimens were irradiated in the Iranian Inertial Electrostatic Confinement Fusion device (IR-IECF) by high energy (~100 keV) and high fluency (~10¹⁹ ions/cm²) helium and deuterium plasma to investigate the implantation impact of high energetic ions on tungsten as a candidate for fusion first wall material. Comparison of the exposure by He and D₂ plasma and influence of high temperature (~1,100 °C) implantation of each ion has been examined. Scanning electron microscopy was used to investigate surface morphology changes for various ion fluencies. Results showed the onset of visible surface pores formation especially for helium implanted samples which increased with higher implant fluencies, eventually resulting in a rough and flaky surface structure, unlike deuterium implanted samples on which smoothening of the surface occurred. Microhardness measurements were used to evaluate mechanical properties of implanted tungsten. Each specimen sustained surface hardening after implantation which was observed to increase with greater ion dose. The phase formation and structural evolution were studied by X-ray diffractometry method.