An integrated artificial neural network-genetic algorithm clustering ensemble for performance assessment of decision making units

This study proposes a non-parametric efficiency frontier analysis method based on artificial neural network (ANN) and genetic algorithm clustering ensemble (GACE) for measuring efficiency as a complementary tool for the common techniques of the efficiency studies in the previous studies. The proposed ANN GA algorithm is able to find a stochastic frontier based on a set of input–output observational data and do not require explicit assumptions about the functional structure of the stochastic frontier. Furthermore, it uses a similar approach to econometric methods for calculating the efficiency scores. Moreover, the effect of the return to scale of decision making unit (DMU) on its efficiency is included and the unit used for the correction is selected based on its scale (under constant return to scale assumption). Also, in this algorithm, GA is used to cluster DMUs to increase DMUs’ homogeneousness. It should be noted that data envelopment analysis (DEA) is sensitive to the presence of the outliers and statistical noise. It is also not capable of performing prediction and forecasting. This is shown by two examples related to outlier situations. However, the proposed algorithm is capable of handling outliers and noise and DEA is used as a benchmark to show advantages of the proposed algorithm. Also, the proposed algorithm and conventional algorithm are compared in viewpoint of DEA through statistical t-test. The proposed approach is applied to a set of actual conventional power plants to show its applicability and superiority.     

The Study of Surface Properties of Tokamak First Wall Using TiN Coated on Stainless Steel

Structural properties of the synthesized TiN thin film on 316L stainless steel (S.S.316L) were studied to determine its potential application as a protective layer for first wall of Tokamaks. For this purpose we deposited TiN on stainless steel 316L (TiN/S.S.316L) via DC magnetron sputtering method and annealing at 700 °C. Before and after exposure, samples were analyzed by using scanning electron microscopy (SEM), X-ray diffraction (XRD) and a spectrophotometer. The XRD analysis for studying crystalline structure of samples shows the position and intensity of XRD peaks has changed after exposing to 500 shots of Tokamak. It was found that the S.S.316L sample was severely damaged, its reflection dropped significantly but the SEM images show that plasma exposure has not created any cracks and lines on the surface of the TiN/S.S.316L sample and mass of dust particle has been assembled in some area of the sample.     

Removal of Acid Orange 7 and Remazol Black 5 reactive dyes from aqueous solutions using a novel biosorbent

This study utilizes canola stalks (CS), an agro-residue, as a biosorbent to remove two different dyes, namely Acid Orange 7 (AO7) and Remozol Black 5 (RB5) from aqueous solutions. The effects of operational parameters on the efficiency of dye removal including pH, adsorbent mass, initial dye concentration and contact time have been investigated. For both tested dyes, the maximum absorption capacity was reached at initial pH 2.5 and 120 min contact time. The results showed that the absorption of both dyes depended on the pH of milieu, temperature, dye and CS concentrations. Freundlich and Langmuir models were used to analyze the obtained experimental data. The isotherms are found to be linear over the entire concentration range for both dyes. The highest value of linear correlation coefficients for AO7 (0.9926) and RB5 (0.9882) showed that the Langmuir is the best model to fit the experimental data. Kinetic study of absorption was done applying the pseudo first-order and the pseudo second-order equations. Absorption of both dyes could be well predicted by the pseudo second-order equation. The obtained results are very promising since: (i) high levels of dye removal (> 90%) were achieved with low contact times biosorbent/dye (less than 20 min contact); and (ii) the whole CS can be successfully used as biosorbent of AO7 and RB5 dyes in aqueous solution without needing any chemical modifications.     

Human Factors Effects and Analysis in Maintenance: A Power Plant Case Study

This paper proposes a methodical approach for identifying and reducing human error in maintenance activities, the human factors effect and analysis. Human factors effect and analysis presents a roadmap for selecting significant human factors affecting maintenance management as well as the most effective solutions using cost–benefit analysis. Safety and operational consequences of each human factor are compared to preventive and recovery risk controls to select the preferred risk control method. Because human factor programs are not implemented in many maintenance departments, quantitative data are rare. Thus, expert judgment may help to compare potential solutions. In order to show the applicability of the proposed approach a power plant in Kenya is selected as a case study. Procedure usage, fatigue, knowledge and experience, and time pressure are identified as the most important human factors. Training, task planning /shift management, knowledge management, scheduling as well as incident report programs are the most cost‐effective solutions for performing human factors program. The proposed approach would improve system reliability by recognizing human related failures. Furthermore, unexpected incident and accident may be reduced having knowledge about potential risk factors. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of high porosity metal foams as air-cooled heat exchangers to high heat load removal systems

A numerical study has been conducted to investigate the fluid flow and heat transfer of an air-cooled metal foam heat exchanger under the high speed laminar jet confined by two parallel walls for which the range of the Reynolds number is 600–1000. Two independent numerical solvers were used and cross-validated being a FORTRAN code and the commercially available software CFD-ACE. The effects of local thermal non-equilibrium, thermal dispersion, porosity, and pore density on the heat transfer augmentation are examined for different Reynolds numbers. Application of energy flux vectors, for convection visualization, is also illustrated for a more comprehensive analysis of the problem. Finally, the performance of the metal foam heat exchanger is compared to that of conventional finned design. It is observed that the heat removal rate can be greatly improved at almost no excess cost.     

A hybrid computer simulation-artificial neural network algorithm for optimisation of dispatching rule selection in stochastic job shop scheduling problems

Industrial systems are constantly subject to random events with inevitable uncertainties in production factors, especially in processing times. Due to this stochastic nature, selecting appropriate dispatching rules has become a major issue in practical problems. However, previous research implies that using one dispatching rule does not necessarily yield an optimal schedule. Therefore, a new algorithm is proposed based on computer simulation and artificial neural networks (ANNs) to select the optimal dispatching rule for each machine from a set of rules in order to minimise the makespan in stochastic job shop scheduling problems (SJSSPs). The algorithm contributes to the previous work on job shop scheduling in three significant ways: (1) to the best of our knowledge it is the first time that an approach based on computer simulation and ANNs is proposed to select dispatching rules; (2) non-identical dispatching rules are considered for machines under stochastic environment; and (3) the algorithm is capable of finding the optimal solution of SJSSPs since it evaluates all possible solutions. The performance of the proposed algorithm is compared with computer simulation methods by replicating comprehensive simulation experiments. Extensive computational results for job shops with five and six machines indicate the superiority of the new algorithm compared to previous studies in the literature.     

Assessment of water depth change patterns in 120° sharp bend using numerical model

In this study,FLUENT software was employed to simulate the flow pattern and water depth changes in a 120° sharp bend at four discharge rates.To verify the numerical model,a 90° sharp bend was first modeled with a three-dimensional numerical model,and the results were compared with available experimental results.Based on the numerical model validation,a 120° bend was simulated.The results show that the rate of increase of the water depth at the cross-section located 40 cm before the bend,compared with the cross-sections located 40 cm and 80 cm after the bend,decreases with the increase of the normal water depth in the 120° curved channel.Moreover,with increasing normal water depth,the dimensionless water depth change decreases at all cross-sections.At the interior cross-sections of the bend,the transverse water depth slope of the inner half-width is always greater than that of the outer half-width of the channel.Hence,the water depth slope is nonlinear at each crosssection in sharp bends.Two equations reflecting the relationships between the maximum and minimum dimensionless water depths and the normal water depth throughout the channel were obtained.     

Applicability of a magnetic bucky gel for microextraction of mercury from complicated matrices followed by cold vapor atomic absorption spectroscopy

ABSTRACT

A new eco-friendly bucky gel nano sorbent consisting of magnetic grapheneoxide (MGO) and an ionic liquid (IL) was used based on dispersive extraction technique followed by cold vapor atomic absorption spectroscopy for determination of mercury in river water, milk, omega-3 supplements, and lipstick. The optimum conditions for extraction were 50 mg of sorbent (mass ratio IL/MGO: 26), 8 min vortexing, acetate buffer pH = 4, and for desorption 3 min vortexing of HNO₃ (1 mL). The limits of detection, quantification, preconcentration factor and extraction recovery were found at 0.57, 1.88 µg L^?1, 21 and 84%. Relative standard deviation (RSD) was 6.5% (n = 3).     

A new extended matrix logarithm formulation for the simulation of viscoelastic fluids by spectral elements

This study presents a new algorithm developed in order to remove instabilities observed in the simulation of unsteady viscoelastic fluid flows in the framework of the spectral element method. In this study, we consider a particular model of the finite extensible nonlinear elastic family, FENE-P, but the method could be applied to other differential constitutive equations. Two distinct constraints for the FENE-P equation are imposed: (i) the square of the corresponding finite extensibility parameter of the polymer must be an upper limit for the trace of the conformation tensor and (ii) the eigenvalues of the conformation tensor should remain positive at all steps of the simulation. Negative eigenvalues cause the unbounded growth of instabilities in the flow. The proposed transformation is an extension of the matrix logarithm formulation originally presented by Fattal and Kupferman [1] and [2]. To evaluate the capability of this new algorithm with the classical conformation tensor, comprehensive studies have been done based on the linear stability analysis to show the influence of this method on the resulting eigenvalue spectra and explain its success to tackle high Weissenberg numbers. With this new method one can tackle high Weissenberg number flow at values of practical interest. A neat improvement of the computational algorithm with stable convergence has been demonstrated in this study.     

Direct Electrochemistry and Electrocatalysis of Hemoglobin on Bimetallic Au–Pt Inorganic–Organic Nanofiber Hybrid Nanocomposite and Mesoporous Molecular Sieve MCM-41

A glassy carbon electrode modified with MCM-41 and bimetallic inorganic–organic nanofiber hybrid nanocomposite was prepared and used for determination of trace levels of hydrogen peroxide (H₂O₂). The direct electron transfer (DET) and electrocatalysis of hemoglobin (Hb) entrapped in the MCM-41 modified Au–Pt inorganic–organic nanofiber hybrid nanocomposite electrode (Au–PtNP/NF/GCE) were investigated by using cyclic voltammetry in 0.1 M pH 7.0 phosphate buffer solution. Due to its uniform pore structure, high surface area and good biocompatibility, the mesoporous silica sieve MCM-41 provided a suitable matrix for immobilization of biomolecules. The MCM-41 modified Au–Pt inorganic–organic nanofiber hybrid nanocomposite electrode showed significant promotion to DET of Hb, which exhibited a pair of well-defined and quasi-reversible peaks for heme Fe(III)/Fe(II) with a formal potential of ?0.535 V (vs. Ag/AgCl). Additionally, the Hb immobilized on the MCM-41 modified electrode showed excellent electrocatalytic activity toward H₂O₂ reduction.