Pd/Cu-Free Cobalt-Catalyzed Suzuki and Heck Using Green Bio-Magnetic Hybrid and DFT-Based Theoretical Study

Catalysis Letters - Several highly efficient and magnetically recyclable cobalt catalytic systems were prepared using magnetic chitosan and some safe and available organic compounds...     

Synthesis of novel polyimides containing side‐chain azo‐2‐naphthol moieties

An amine‐ester derivative of isoeugenol was prepared in three steps. This amine‐ester was converted to diazonium salt and subsequently was reacted with 2‐naphthol and a novel isoeugenol ester‐azo derivative as a new monomer was obtained in quantitative yield. This monomer was characterized by high‐field ¹H‐NMR, IR, and elemental analysis and then was used for the preparation of model compound and polymerization reactions. 4‐Phenyl‐1,2,4‐triazoline‐3,5‐dione was allowed to react with this new monomer. The reaction was very fast and gave only one double adduct by Diels–Alder and ene pathways in excellent yield. The polymerization reactions of novel monomer with bistriazolinediones [bis(p‐3,5‐dioxo‐1,2,4‐triazolin‐4‐ylphenyl)methane and 1,6‐bis(3,5‐dioxo‐1,2,4‐triazolin‐4‐yl)hexane] were carried out in N,N‐dimethylacetamide at room temperature. The reactions were exothermic, fast, and gave novel heterocyclic polyimides by repetitive Diels–Alder‐ene polyaddition reactions. Some structural characterization and physical properties of these novel heterocyclic polyimides are reported. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 1942–1951, 2003     

An Efficient Finite Difference Method for The Time‐Delay Optimal Control Problems With Time‐Varying Delay

In this paper, an efficient finite difference method is presented for the solution of time‐delay optimal control problems with time‐varying delay in the state. By using the Pontryagin's maximum principle, the original time‐delay optimal control problem is first transformed into a system of coupled two‐point boundary value problems involving both delay and advance terms. Then the derived system is converted into a system of linear algebraic equations by using a second‐order finite difference formula and a Hermite interpolation polynomial for the first‐order derivatives and delay terms, respectively. The convergence analysis of the proposed approach is provided. The new scheme is also successful for the optimal control of time‐delay systems affected by external persistent disturbances. Numerical examples are included to demonstrate the validity and applicability of the new technique. Some comparative results are included to illustrate the effectiveness of the proposed method.     

Synthesis and characterization of novel polyimides containing triazoles units in the main chain by click chemistry

In this study, some polyimides containing triazoles units in the main chain was prepared from the polymerization of dialkynes including imide linkages and diazides in the presence of Cu (I) catalyst in yield of 76.2–87.6%, with inherent viscosity of 0.37–0.53 dL g^?1. The obtained polymers are soluble in polar aprotic solvents such as N,N‐dimethyformamide (DMF), N,N‐dimethyacetamide (DMAc), dimethyl sulfoxide (DMSO), and N‐methyl‐2‐pyrrolidone (NMP). These polymers were characterized using FT‐IR, ¹H‐NMR, and elemental analysis techniques. Their thermal stability was evaluated with thermogravimetric (TGA) analysis and differential scanning calorimetry (DSC) techniques under a nitrogen atmosphere which is indicative of their good thermal stability. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Effect of Heat Transfer on the First and Second Law Efficiency Analysis and Optimization of an Air-standard Atkinson Cycle

In this paper, the first and second-law analysis for the thermodynamic air-standard Atkinson cycle with an account for heat transfer is performed using finite-time thermodynamics. In order to have more accurate evaluations, the effects of thermodynamic and design key parameters on the performance characteristics of Atkinson cycle are shown. Further, artificial neural network and imperialist competition algorithm are employed to predict and optimize the net work output value versus the minimum cycle temperature and also the compression ratio. The results obtained show that the heat loss is an effective factor of the performance of the cycle and it should be considered in the analysis and comparison of practical internal combustion engines.     

A regional-scale engineering geological study for selecting suitable rock masses for constructing unlined oil storage caverns in Southern Zagros,Iran

Bulletin of Engineering Geology and the Environment - The southern section of the Zagros zone in southwestern Iran, a well-known sedimentary basin, was investigated to address two key questions:...     

A multi-objective facility location model with batch arrivals: two parameter-tuned meta-heuristic algorithms

Many research works in mathematical modeling of the facility location problem have been carried out in discrete and continuous optimization area to obtain the optimum number of required facilities along with the relevant allocation processes. This paper proposes a new multi-objective facility-location problem within the batch arrival queuing framework. Three objective functions are considered: (I) minimizing the weighted sum of the waiting and the traveling times, (II) minimizing the maximum idle time pertinent to each facility, and (III) minimizing the total cost associated with the opened facilities. In this way, the best combination of the facilities is determined in the sense of economical, equilibrium, and enhancing service quality viewpoints. As the model is shown strongly NP-hard, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) are proposed to solve the model. Not only new coding is developed in these solution algorithms, but also a random search algorithm is proposed to justify the efficiency of both algorithms. Since the solution-quality of all meta-heuristic algorithms severely depends on their parameters, design of experiments and response surface methodologies have been utilized to calibrate the parameters of both algorithms. Finally, computational results obtained by implementing both algorithms on several problems of different sizes demonstrate the performances of the proposed methodology.     

A multi-product multi-period inventory control problem under inflation and discount: a parameter-tuned particle swarm optimization algorithm

In this paper, a seasonal multi-product multi-period inventory control problem is modeled in which the inventory costs are obtained under inflation and all-unit discount policy. Furthermore, the products are delivered in boxes of known number of items, and in case of shortage, a fraction of demand is considered backorder and a fraction lost sale. Besides, the total storage space and total available budget are limited. The objective is to find the optimal number of boxes of the products in different periods to minimize the total inventory cost (including ordering, holding, shortage, and purchasing costs). Since the integer nonlinear model of the problem is hard to solve using exact methods, a particle swarm optimization (PSO) algorithm is proposed to find a near-optimal solution. Since there is no bench mark available in the literature to justify and validate the results, a genetic algorithm is presented as well. In order to compare the performances of the two algorithms in terms of the fitness function and the required CPU time, they are first tuned using the Taguchi approach, in which a metric called “smaller is better” is used to model the response variable. Then, some numerical examples are provided to demonstrate the application and to validate the results obtained. The results show that, while both algorithms have statistically similar performances, PSO tends to be the better algorithm in almost all problems.     

An extended compromise ratio method for fuzzy group multi-attribute decision making with SWOT analysis

The technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi-attribute decision making (MADM) method that is used to identify the most attractive alternative solution among a finite set of alternatives based on the simultaneous minimization of the distance from an ideal solution (IS) and the maximization of the distance from the nadir solution (NS). We propose an alternative compromise ratio method (CRM) using an efficient and powerful distance measure for solving the group MADM problems. In the proposed CRM, similar to TOPSIS, the chosen alternative should be simultaneously as close as possible to the IS and as far away as possible from the NS. The conventional MADM problems require well-defined and precise data; however, the values associated with the parameters in the real-world are often imprecise, vague, uncertain or incomplete. Fuzzy sets provide a powerful tool for dealing with the ambiguous data. We capture the decision makers’ (DMs’) judgments with linguistic variables and represent their importance weights with fuzzy sets. The fuzzy group MADM (FGMADM) method proposed in this study improves the usability of the CRM. We integrate the FGMADM method into a strengths, weaknesses, opportunities and threats (SWOT) analysis framework to show the applicability of the proposed method in a solar panel manufacturing firm in Canada.