Parametric simulation and performance analysis of a solar gas turbine power plant from thermodynamic and exergy perspectives

Using solar energy in gas turbine cycles is a new method that can improves the efficiency of gas turbines. Placing a solar receiver before a combustion chamber can raise the temperature of the air coming into the chamber and reduce the consumption of fuel in the chamber. The system that combines a solar energy receiver with a gas turbine cycle is technically called a “solar gas turbine”. The goal of this paper is the parametric simulation and performance analysis of a gas turbine cycle equipped with a solar receiver from thermodynamic and exergy aspects of view. The selected parameters in this study, include the pressure ratio of compressor, the temperature of gases at the turbine inlet and the direct normal irradiance. The obtained results indicate that the fuel consumption of this combined system is reduced by using a solar receiver and the temperature of gases entering the combustion chamber increased. The reduction of consumed fuel, in turn, reduces the rate of exergy destruction in the combustion chamber. Another important point is that the solar receiver itself has the least amount of exergy destruction. The net power generated by a solar gas turbine cycle is 10 % higher than that produced by a simple gas turbine cycle. Also, the studies show that the electrical efficiency of a solar gas turbine cycle is about 41 % higher than the simple gas turbine cycle.

     

Staphylococcal susceptibility to penicillin G

In acute Staphylococcal infections, antimicrobial drug therapy must often be initiated before culture results and antibiotic susceptibility testing are completed. Three hundred and ten cultures of coagulase-positive Staphylococcus aureus were tested for antibiotic sensitivity by the Kirby-Bauer method at the Nemazee Hospital in Shiraz, Iran. The overall resistance to penicillin G was 97.10% whereas over 99% of the isolated Staphylococci were sensitive to the penicillinase-resistance penicillin cloxacillin. A penicillinase-resistant penicillin should therefore be used in the initial management of all serious Staphylococcal infections until the organism responsible for infection can be shown to be specifically sensitive to penicillin G.     

AVLR-EBP: A Variable Step Size Approach to Speed-up the Convergence of Error Back-Propagation Algorithm

A critical issue of Neural Network based large-scale data mining algorithms is how to speed up their learning algorithm. This problem is particularly challenging for Error Back-Propagation (EBP) algorithm in Multi-Layered Perceptron (MLP) Neural Networks due to their significant applications in many scientific and engineering problems. In this paper, we propose an Adaptive Variable Learning Rate EBP algorithm to attack the challenging problem of reducing the convergence time in an EBP algorithm, aiming to have a high-speed convergence in comparison with standard EBP algorithm. The idea is inspired from adaptive filtering, which leaded us into two semi-similar methods of calculating the learning rate. Mathematical analysis of AVLR-EBP algorithm confirms its convergence property. The AVLR-EBP algorithm is utilized for data classification applications. Simulation results on many well-known data sets shall demonstrate that this algorithm reaches to a considerable reduction in convergence time in comparison to the standard EBP algorithm. The proposed algorithm, in classifying the IRIS, Wine, Breast Cancer, Semeion and SPECT Heart datasets shows a reduction of the learning epochs relative to the standard EBP algorithm.     

Common understanding in a multi-agent system using ontology-guided learning

Traditionally, communication among agents has been established based on the group commitment to a common ontology which is unfortunately often too strong or unrealistic. In the real world of communicating agents, it is preferred to enable agents to exchange information while they keep their own individual ontology. While this assumption makes agents represent their knowledge more independently and give them more flexibility, it also adds to the complexity of communication. We believe that agents can overcome this complexity by using their learning capability. The agents can learn any concept they do not know but want to communicate about with other agents in the multi-agent system where they work in. Our goal in this paper is to present a general method for agents using ontologies to teach each other concepts to improve their communication, and therefore cooperation abilities. In our method, a particular agent that understands a concept only ambiguously intends to learn it by receiving positive and negative examples for that concept from the other agents. Then, utilizing one of the known concept learning methods, the agent learns the concept in question. In case of conflicts in the received set of examples, the learning agent asks other agents again to get involved in the learning process by taking votes. While this method allows agents not to share common ontologies, it enables agents to establish common grounds on the concepts known only by some of them if these common grounds are needed during cooperation. In fact, the learned concepts by an agent are compromised among the views of other agents the method improves the autonomy of agents using them significantly.     

Room Temperature Exchange Bias in Multifunctional Sb<Subscript>2</Subscript>FeO<Subscript>6</Subscript> Multiferroic

Sb₂FeO₆ was prepared and its crystal structure was examined using x-ray diffraction (XRD). From the latter, it was found that the former adopted the tetragonal structure with space group P42/mnm. Room temperature hysteresis loop (M- H) measurements clarified the evidence of exchange bias. Semiconducting-like behavior was predominant where the correlated barrier hopping is the principal mechanism. The gained results pushed us to classify the Sb₂FeO₆ as a type-I multiferroic material.     

Analyzing the fractal feature of nickel thin films surfaces modified by low energy nitrogen ion

Fractal concepts are used to explore how different energies (10, 20 and 50 keV) and fluence of 5 × 10¹⁷ N⁺ cm^?2 affect the morphology of nickel thin film. The nickel thin film with thickness of 100 nm is prepared by electron beam evaporation technique at room temperature on stainless steel (AISI 316) substrates. The nanoscale three‐dimensional (3‐D) surface micro‐morphologies are investigated by atomic force microscopy (AFM). Interface width is used to describe the surface height fluctuations. The autocorrelation function with height‐height correlation function give the quantitative data about the morphology of surface. The value of roughness exponent and fractal dimension is computed by height‐height correlation function. Fractal measure is an important analysis which provides fundamental insights into the texture characteristics and a direct way of testing their functional role.     

Geometric quality assessment of in situ blocks in dimension stone quarries

The profitability of stone quarries depends on the appearance (color and texture) and, more importantly, on the size of the blocks, which is determined by the three-dimensional discontinuity pattern of the rock mass. However, to date there is no comprehensive criterion by which to assess the size of blocks in quarries. The aim of the study reported here is to identify factors that facilitate decision-making on the desirability of an individual block and ultimately on all blocks for extraction as a dimension stone. To this end, we first developed a novel algorithm to calculate the largest rectangular parallelepiped that can be placed inside a block and then defined a regularity factor (α) and a quarry block shape factor (q) that enable the geometric quality of the block to be assessed more accurately than currently possible. The sensitivity analysis of these factors showed that the change in angle relative to the change in spacing has the greater effect on the geometric quality. The proposed factors displayed a good performance in a comparison analysis of four sites of the Dareh Bokhari travertine quarry complex located in Mahallat, Markazi province, Iran. Based on the results, blocks at sites 2 and 4 have the lowest and the highest geometric quality, respectively, which is in accordance with the operational conditions at the respective sites. Moreover, comparison of the values of factor q obtained from applying various cutting planes indicated that to maximally increase block production capacity, the current cutting direction at site 4 should be adjusted 33° eastward.

     

Application of fractal dimensions to study the structure of flocs formed in lime softening process

The use of fractal dimensions to study the internal structure and settling of flocs formed in lime softening process was investigated. Fractal dimensions of flocs were measured directly on floc images and indirectly from their settling velocity. An optical microscope with a motorized stage was used to measure the fractal dimensions of lime softening flocs directly on their images in 2 and 3D space. The directly determined fractal dimensions of the lime softening flocs were 1.11-1.25 for floc boundary, 1.82-1.99 for cross-sectional area and 2.6-2.99 for floc volume. The fractal dimension determined indirectly from the flocs settling rates was 1.87 that was different from the 3D fractal dimension determined directly on floc images. This discrepancy is due to the following incorrect assumptions used for fractal dimensions determined from floc settling rates: linear relationship between square settling velocity and floc size (Stokes’ Law), Euclidean relationship between floc size and volume, constant fractal dimensions and one primary particle size describing entire population of flocs. Floc settling model incorporating variable floc fractal dimensions as well as variable primary particle size was found to describe the settling velocity of large (>50 μm) lime softening flocs better than Stokes’ Law. Settling velocities of smaller flocs (<50 μm) could still be quite well predicted by Stokes’ Law. The variation of fractal dimensions with lime floc size in this study indicated that two mechanisms are involved in the formation of these flocs: cluster-cluster aggregation for small flocs (<50 μm) and diffusion-limited aggregation for large flocs (>50 μm). Therefore, the relationship between the floc fractal dimension and floc size appears to be determined by floc formation mechanisms.     

Stochastics multi-objective modelling of simultaneous reconfiguration of power distribution network and allocation of DGs and capacitors

This paper suggests a method based on stochastic multi-objective modelling for optimally siting and sizing of distributed generations and capacitors and simultaneously network reconfiguration, in order to take more advantages of recent developed technologies. With respect to the widespread effect of uncertainties of load forecasting and market price, some strategies must be devised so as to well incorporate them into the problem. The mentioned problem can be regarded as a multi-objective optimisation problem for which NSGA-II accompanied by fuzzy set theory are chosen. The main aim of DisCo is to provide highly reliable power at the lowest possible costs. Besides, voltage deviation and voltage stability as the criteria of power quality in distribution networks and emission pollutant reduction are treated as independent objective functions. Eventually, to validate the effectiveness of the proposed scheme, simulations are carried out and the results are compared to the initial configuration.