No-wait two stage hybrid flow shop scheduling with genetic and adaptive imperialist competitive algorithms

This article studies a no-wait two-stage flexible flow shop scheduling problem with setup times aiming to minimize the total completion time. The problem is solved using an adaptive imperialist competitive algorithm (AICA) and genetic algorithm (GA). To test the performance of the proposed AICA and GA, the algorithms are compared with ant colony optimisation, known as an effective algorithm in the literature. The performance of the algorithms are evaluated by solving both small and large-scale problems. Their performance is evaluated in terms of relative percentage deviation. Finally the results of the study are discussed and conclusions and potential areas for further study are highlighted.     

Solving the master equation for extremely long time scale calculations

The dynamics of magnetic reversal process plays an important role in the design of the magnetic recording devices in the long time scale limit. In addition to long time scale, microscopic effects such as the entropic effect become important in magnetic nano-scale systems. Many advanced simulation methods have been developed, but few have the ability to simulate the long time scale limit and to accurately model the microscopic effects of nano-scale systems at the same time. We develop a new Monte Carlo method for calculating the dynamics of magnetic reversal at arbitrary long time. For example, actual calculations were performed up to 10⁵⁰ Monte Carlo steps. This method is based on microscopic interactions of many constituents and the master equation for magnetic probability distribution function is solved symbolically.     

Morphological,mechanical, and rheological studies of PVC/ABS blends in the presence of maleic anhydride

A novel method of enhancing compatibility in PVC/ABS blends is the use of ABS‐grafted‐(maleic anhydride) (ABS‐g‐MAH) as a compatibilizer. In this study, maleic anhydride was grafted onto ABS (initiated by peroxide) in an internal mixer. Grafting degree was determined by a back‐titration method, and certain amounts of the resultant ABS‐g‐MAH were added to PVC/ABS blends during their melt blending in the mixer. The weight ratio of PVC to ABS was kept at 70:30. Evaluation of compatibilization was accomplished via tensile and notched Izod impact tests, scanning electron microscopy (SEM), and rheological studies. According to the SEM micrographs, better dispersion of the rubber phase and its finer size in properly compatibilized blends were indications of better compatibility. Besides, in the presence of a proper amount [5 parts per hundred parts of PVC (php)] of ABS‐g‐MAH, PVC/ABS blends showed significantly higher impact strengths than uncompatibilized blends. This result, in turn, would be an indication of better compatibility. In the presence of 5 php of compatibilizer, the higher complex viscosity and storage modulus, as well as a lower loss modulus and loss factor in the range of frequency studied, indicated stronger interfacial adhesion as a result of interaction between maleic anhydride and the PVC‐SAN matrix. J. VINYL ADDIT. TECHNOL., 2010. © 2010 Society of Plastics Engineers     

Hydrogen Generation from CO2 Reforming of Biomass-Derived Methanol on Ni/SiO2 Catalyst

Topics in Catalysis - CO2 reforming of methanol for producing hydrogen was experimentally carried out in a fixed-bed reactor on 10%Ni/SiO2. The 10%Ni/SiO2 was completely reduced during H2...     

An intelligent hybrid meta-heuristic for solving a case of no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines

This paper addresses the problem of no-wait two-stage flexible flow shop scheduling problem (NWTSFFSSP) considering unrelated parallel machines, sequence-dependent setup times, probable reworks and different ready times to actualize the problem. The performance measure used in this study is minimizing maximum completion time (makespan). Because of the complexity of addressed problem, we propose a novel intelligent hybrid algorithm [called hybrid algorithm (HA)] based on imperialist competitive algorithm (ICA) which are combined with simulated annealing (SA), variable neighborhood search (VNS) and genetic algorithm (GA) for solving the mentioned problem. The hybridization is carried out to overcome some existing drawbacks of each of these three algorithms and also for increasing the capability of ICA. To achieve reliable results, Taguchi approach is used to define robust parameters' values for our proposed algorithm. A simulation model is developed to study the performance of our proposed algorithm against ICA, SA, VNS, GA and ant colony optimization (ACO). The results of the study reveal the relative superiority of HA studied. In addition, potential areas for further researches are highlighted.     

Comparative evaluation of back-propagation neural network learning algorithms and empirical correlations for prediction of oil PVT properties in Iran oilfields

This paper presents a new approach to improve the performance of neural network method to PVT oil properties prediction. The true value of PVT properties which is determined based on the accurate data is a challenge of the petroleum industry. The main goal of the following investigation would be the performance comparison of various back-propagation learning algorithms in neural network that could be applied for PVT prediction. Up to now, no procedure has been presented to determine the network structure for some complicated cases, therefore; design and production of neural network would be almost dependent on the user's experience. To prevent this problem, neural network based recommended procedure in this study was applied to present the advantages. To show the performance of this procedure, several learning algorithms were investigated for comparison. One of the most common problems in neural network design is the topology and the parameter value accuracy that if those elements selection was correctly and optimally, the designer would achieve better results. Since, fluids of different regions have varying hydrocarbon properties, therefore, the empirical correlations in different hydrocarbon systems should be investigated to find their accuracies and limitations. In this study, an investigation of different empirical correlations along with the artificial neural networks in Iran oilfields has been presented. Then, the new model of artificial neural network for prediction of PVT oil properties in Iran crude oil presented. To test this new method, it was evaluated by collecting dataset from 23 different oilfields in Iran (south, central, western and continental shelf). In this study, two networks for prediction of bubble point pressure values (P_b) and the oil formation volume factor at bubble point (B_ob) were designed. The parameters and topology of the optimum neural networks were determined and in order to consider the effect of these networks designing on results, their performances were compared with various empirical correlations. According to comparison between the obtained results, it shows that the improved method presented has better performance rather than empirical and current methods in neural network designing in petroleum applications for these predictions.     

Chip formation in microscale milling and correlation with acoustic emission signal

This work investigated the effects of different workpiece materials on chip formation and associated mechanisms in microcutting. The wavelet transformation technique was used to decompose acoustic emission (AE) signals generated from orthogonal micromilling of different workpiece materials. This allowed studying energy levels corresponding to deformation mechanisms. Resulting chip forms were characterised. The results indicated that the computed energies of decomposed frequency bands can be positivity correlated with chip morphology. The work provides significant and new knowledge on the utility and importance of AE signals in characterising chip formation in micromachining. Understanding chip formation mechanisms is important in managing the size effect in micromachining.     

Preparation of Silane-Grafted and Moisture Cross-Linked Low Density Polyethylene: Part I: Factors Affecting Performance of Grafting and Cross-Linking

In the present work, the silane grafting and water cross-linking of low density polyethylene (LDPE) were investigated. The grafting reaction was carried out in an internal mixer and polyethylene cross-linking was done in hot water. The effect of silane, peroxide, catalyst, carbon black, cross-linking time, and cross-linking temperature on the grafting and cross-linking processes are reported. Vinyl trimethoxy silane (VTMO) and di-cumyl peroxide (DCP) were selected as grafting agent and initiator respectively. Silane grafting on polyethylene was determined using Fourier transform infrared (FTIR) spectroscopy and torque monitoring of the mixer. Absorption peak due to –Si–OCH₃ groups in FTIR and torque increasing due to silane grafting in the mixer illustrated that silane-grafting reactions occurred. The FTIR data demonstrated that the extent of silane grafting was increased as the concentration of silane and peroxide was increased. Thermogravimetry analysis (TGA) determined that the thermal stability of LDPE increased by increasing the amount of silane grafting. Gel fraction increased with silane and peroxide concentration. As the percent of of catalyst increase the time scale for specified gel content shifted to shorter times. Incorporation of carbon black into LDPE decreased the extent of silane grafting and gel fraction. Water temperature increasing in cross-linking stage reduced the time to maximum degree of cross-linking.     

The effect of initiator‐to‐monomer ratio on the properties of the polybutadiene‐ol synthesized by free radical solution polymerization of 1,3‐butadiene

Polybutadiene‐ol was synthesized by solution radical polymerization of 1,3‐butadiene in the presence of hydrogen peroxide as initiator and 2‐propanol as solvent. The ratio of initiator to monomer molar concentration, [I₀]/[M₀], was varied while temperature, reaction time and the type and amount of solvent were kept constant. The effects on the M_n; M_w; M_v; PDI, OH‐number and functionality of the synthesized polyols were studied. By taking several samples during a polymerization batch and analyzing them, the time of reaction was chosen as 100 min, after which the PDI changed dramatically. M_n decreased exponentially with increasing [I₀]/[M₀] according to the relationship M_n = 565.55 ([I₀]/[M₀])^?0.7553. The decrease observed in M_w gradually levelled off with increasing [I₀]/[M₀] and molecular weight distribution broadened at larger values of [I₀]/[M₀]. The OH‐number increases with [I₀]/[M₀]. In addition to the number‐average molecular weight, functionality is dependent on the number of hydroxyl‐terminated chain radicals in the reaction medium. Copyright © 2003 Society of Chemical Industry