A complete VARMA modelling methodology based on scalar components

Abstract. This article proposes an extension to scalar component methodology for the identification and estimation of VARMA models. The complete methodology determines the exact positions of all free parameters in any VARMA model with a predetermined embedded scalar component structure. This leads to an exactly identified system of equations that is estimated using full information maximum likelihood.     

A particle swarm optimization for a fuzzy multi-objective unrelated parallel machines scheduling problem

This paper proposes a novel multi-objective model for an unrelated parallel machine scheduling problem considering inherent uncertainty in processing times and due dates. The problem is characterized by non-zero ready times, sequence and machine-dependent setup times, and secondary resource constraints for jobs. Each job can be processed only if its required machine and secondary resource (if any) are available at the same time. Finding optimal solution for this complex problem in a reasonable time using exact optimization tools is prohibitive. This paper presents an effective multi-objective particle swarm optimization (MOPSO) algorithm to find a good approximation of Pareto frontier where total weighted flow time, total weighted tardiness, and total machine load variation are to be minimized simultaneously. The proposed MOPSO exploits new selection regimes for preserving global as well as personal best solutions. Moreover, a generalized dominance concept in a fuzzy environment is employed to find locally Pareto-optimal frontier. Performance of the proposed MOPSO is compared against a conventional multi-objective particle swarm optimization (CMOPSO) algorithm over a number of randomly generated test problems. Statistical analyses based on the effect of each algorithm on each objective space show that the proposed MOPSO outperforms the CMOPSO in terms of quality, diversity and spacing metrics.     

Fullerene: biomedical engineers get to revisit an old friend

1. Download high-res image (169KB)
2. Download full-size image

     

The synthesis of nano-sized ZSM-5 zeolite by dry gel conversion method and investigating the effects of experimental parameters by Taguchi experimental design

In this study ZSM-5 Nano particles with high crystallinity were synthesized using a dry gel conversion technique. An L9 orthogonal array of the Taguchi method was applied to investigate the effect of synthesis parameters, such as crystallization time, gel drying temperature, molar composition of template (TPAOH) and water content in the crystallization stage on crystallinity and particle size of the ZSM-5 catalyst. The products were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Beside short crystallization time, the particle sizes were considerably smaller in comparison with those prepared using the hydrothermal method. The results showed that the particle size and crystallinity increased with increasing water content and crystallization time. The effects of gel drying temperature and molar composition of template were found to be more complex, however. Comparing to hydrothermal method, ZSM-5 samples synthesized with the dry gel conversion exhibited higher selectivity to gasoline than other hydrocarbons.     

A new feature selection algorithm and composite neural network for electricity price forecasting

In a competitive electricity market, the forecasting of energy prices is an important activity for all the market participants either for developing bidding strategies or for making investment decisions. In this paper, a new forecast strategy is proposed for day ahead prediction of electricity price, which is a complex signal with nonlinear, volatile and time dependent behavior. Our forecast strategy includes a new two stage feature selection algorithm, a composite neural network (CNN) and a few auxiliary predictors. The feature selection algorithm has two filtering stages to remove irrelevant and redundant candidate inputs, respectively. This algorithm is based on mutual information (MI) criterion and selects the input variables of the CNN among a large set of candidate inputs. The CNN is composed of a few neural networks (NN) with a new data flow among its building blocks. The CNN is the forecast engine of the proposed strategy. A kind of cross-validation technique is also presented to fine-tune the adjustable parameters of the feature selection algorithm and CNN. Moreover, the proposed price forecast strategy is equipped with a few auxiliary predictors to enrich the candidate set of inputs of the forecast engine. The whole proposed strategy is examined on the PJM, Spanish and Californian electricity markets and compared with some of the most recent price forecast methods.     

Fracture Assessment of U-Notched Graphite Plates Under Tension

The experimentally obtained tensile load-bearing capacity of fifteen U-notched polycrystalline graphite plates reported in literature was theoretically estimated by means of two well-known brittle fracture models, namely the mean stress (MS) and the point stress (PS) criteria. The results showed that while the mean discrepancies between the experimental and the theoretical results for both the models are very good and approximately equal, the discrepancies are significantly different for various notch tip radii. Meanwhile, the results of MS and PS criteria were compared with the results of the strain energy density (SED) criterion reported in literature. Relatively similar value of mean discrepancy was also obtained for the SED model. It was demonstrated in this research that for small values of the notch tip radius, the MS model is the most appropriate failure criterion while the PS and SED criteria are much better models for medium radii. Moreover, for large notch tip radii, the MS and PS criteria are better choices for tensile fracture assessment of U-notched graphite plates than the SED criterion.     

Synthesis of highly isotactic poly 1-hexene using Fe-doped Mg(OEt)2/TiCl4/ED Ziegler–Natta catalytic system

In this article, polymerization of 1-hexene with FeCl_3-doped Mg(OET)₂/TiCl₄/electron donor (ED) catalytic system is presented. For this purpose, first a number of TiCl₄ catalysts supported on Mg(OEt)₂ and Fe-doped Mg(OEt)₂ supports were prepared with ethylbenzoate or dibutylphthalate as the internal EDs. After successive catalysts synthesis, they were employed in 1-hexene polymerization using cyclohexyl methyl dimethoxysilane as external ED as well as without it. The catalysts activity and molecular weight distribution (MWD) of poly 1-hexenes (PHs) were influenced strongly by both FeCl₃ doping and donor presence so that a remarkable increase in the catalyst activity was seen in doped catalysts. Deconvolution of MWD curves revealed that increase in the type of active centers by introducing FeCl₃ into the support should be responsible for the broadening of MWD of PHs. ¹³CNMR analysis indicated that while isotacticity does not change considerably by Fe doping, EDs increase its amount as high as 8–21%. Second, the stereoselective behavior of active Ti species in doped and undoped catalysts was fully explored by molecular modeling using density functional theory (DFT) method. Finally, with the aid of rheological measurements, the processability of polymers were evaluated and then the gel permeation chromatography (GPC) results were approved through the values obtained from model fitting as well as changes in moduli crossover modulus.     

Thermal Analysis of Non-linear Convective–Radiative Hyperbolic Lumped Systems with Simultaneous Variation of Temperature-Dependent Specific Heat and Surface Emissivity by MsDTM and BPES

With the advent of temperatures near absolute zero, it is often claimed that at very low temperatures the effect of thermal wave propagation must be included by the hyperbolic heat conduction equation (HHCE). In this paper the non-linear convective–radiative HHCE is investigated. Opposite to common numerical analyses, analytical expressions are obtained for the temperature variations by the multi-step differential transformation method. Some conclusions about alteration of the specific heat of the material, temperature steeping, and Vernotte number have been formulated.     

Failure Analysis and Repair of a Catastrophically Damaged Gas Turbine Compressor Disk Using SEM Technique and CFD Analysis

During a major overhaul of an 85?MW gas turbine unit in Iran-Rey power plant, 39 cracks were detected with different lengths and locations on the compressor disk of stage 11. All of the cracks initiated from the dovetail regions. Preliminary visual inspections and further micro-fractography using the scanning electron microscope demonstrated that the fretting fatigue phenomenon was the main cause of failure. Four repair methods were suggested to restart the unit. The first one was to remove all of the cracks from the disk by machining, or the so-called blending. The second, third, and fourth ways were to remove the entire rotor blades of stage 11, to remove the entire rotor and stator blades of the stage 11 simultaneously, and to remove those rotor blades of stage 11 corresponding to the damaged dovetails, respectively. Although the first way of solution was initially carried out on the damaged disk, the first author offered that restarting the unit with the blended disk is not reliable enough because of the presence of a large number of repair points on the disk. Using the numerical investigations based on the computational fluid dynamics, it was found that only the second suggestion (i.e., removing the entire rotor blades of the stage 11) might be applicable. Ultimately, the entire stage 11 rotor blades were removed from the blended disk, and the gas turbine unit was successfully restarted without encountering abnormal operation. Although the performed process resulted in approximately 20% output power loss compared with the unit's power before the blades' removal, the unit was quickly restored to be ready to restart, and the electric power could be generated during the period of peak consumption.     

Quantitative characterization of carrier injection across metal–organic interfaces using Bardeen theory

We have investigated the contact between a metal and an organic/polymeric (o/p) material and we have introduced a relation for carrier injection using Bardeen theory. A series of narrow barriers is considered in the semiconductor side to account for the localized nature of the carriers in the o/p material. As an application of the model, we have calculated the hopping rate of carriers in terms of the contact parameters. Also, we have discussed the hopping of carriers deep into the organic dielectric. Finally, we have explored the hopping rate in practical contacts between polyfluorene-based polymers and different electrodes.