A parametric study for distortional buckling stress on cold-formed steel using a neural network

The process of prediction of distortional buckling stress of cold-formed steel members is often cumbersome and it is also difficult to perform parametric studies in this field to investigate the effect of geometric parameters on Elastic Distortional Buckling Stress (EDBS). To overcome this difficulty a neural network based model and formulation which was presented in a companion paper by the author [Pala M. A new formulation for distortional buckling stress in cold formed steel members. Journal of Constructional Steel Research 2006;62:716-22] is proposed as an alternative approach to investigate the effect of geometric parameters on distortional buckling stress. The model considers the effect of web height, flange width, angle of lip, lip length and flange thickness. The results of the Neural Network model are quite satisfactory and are consistent with the literature.     

The applicability of neural networks in the determination of soil profiles

The drilling of a number of boreholes to determine the soil profile of a given area is time consuming and costly. This paper describes estimated soil profiles obtained using a model based on artificial neural networks (ANN). ANN is a powerful data-modelling tool capable of capturing and representing complex relationships between input and output. It deals with many multi-variate problems for which an exact analytical model does not exist or is very difficult and time consuming to develop. The main settlement in the Adapazari region was selected to demonstrate the capability of such model. The results obtained using ANN are promising when compared with the soil profile obtained from boreholes.      

A new apparatus to establish the spontaneous combustion propensity of coals and coal-shales

Coal and coal-shale both tend to undergo spontaneous combustion under favourable atmospheric conditions. The Wits-Ehac index has been developed in South Africa since the late 1980's to test the spontaneous combustion liability of coal. However, in some cases, the Wits-Ehac index fails to produce tangible results when testing coal-shales. To overcome this problem, a new apparatus has been developed to test carbonaceous materials such as coal and coal-shale under chemical reactions with oxygen and an index has been obtained. This index is called the Wits-CT index. The equipment emulates the influence of oxygen adsorption on carbonaceous material for a period of 24 h without a heating system.The Wits-CT index uses the total carbon content of the sample and the temperature variations obtained from the samples during reaction with oxygen to predict the spontaneous combustion liability. Eighteen samples have been analyzed using both indices and the results are in-line. It was found that coals and coal-shales with higher values of the Wits-CT index are more liable to spontaneous combustion.Further research on different coal-shales is underway in order to establish an extensive database for coal and coal-shales, together with known incidences of self-heating.     

Mechanical and electrical properties of Bi<Subscript>1.5-x</Subscript>La<Subscript>x</Subscript>Zn<Subscript>0.92</Subscript>Nb<Subscript>1.5</Subscript>O<Subscript>6.92</Subscript> pyrochlore ceramics

BiFeO₃-Pb(Mg_1/3Nb_2/3)O₃-PbTiO₃ (BF-PMN-PT) ternary ceramics with pure perovskite phase were prepared through a two-step solid reaction method. Based on structural analysis, the ternary phase diagram of BF-PMN-PT solid solution at room temperature has been established. The Curie temperature T_C, remnant polarization P_r and piezoelectric constant d₃₃ vary in the range of 138 to 225 °C, 15.12 to 23.65 μC/cm² and 129 to 276 pC/N, respectively. The coercive field Ec increases gradually from 5.77 to 29.56 kV/cm upon PT content increasing. The magnetic study suggests that the magnetism turns from diamagnetism for PMN-PT to paramagnetism for BF-PMN-PT by adding BiFeO₃ into PMN-PT and adding more content of BF does not change the paramagnetism further.     

Steady‐state analysis of a novel ZVT interleaved boost converter

In this paper, a novel soft‐switched interleaved boost converter composed of two‐cell boost conversion units and an auxiliary circuit is proposed and investigated. The proposed auxiliary circuit is implemented using only one auxiliary switch and a minimum number of passive components without an effective increase in the cost and the complexity of the converter. The main advantage of this auxiliary circuit is that it not only provides zero‐voltage‐transition (ZVT) for the main switches but also provides soft switching for the auxiliary switch and diodes. Though all semiconductor devices operate under soft switching, they do not have any additional voltage and current stresses. The proposed converter operates successfully in soft‐switching operation mode for a wide range of input voltage level and the load. In addition, it has advantages such as fewer structure complications, lower cost and ease of control. Since the two‐cell interleaved boost units are identical, operational analysis and design for the converter module become quite simple. In this study, the detailed steady‐state theoretical analysis of the proposed converter is presented, which is verified exactly by simulation and experiments carried out on a prototype of a 120 W and 50 kHz/cell interleaved boost converter. The practical results confirm the results obtained from theoretical analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

A new dynamic security enhancement method via genetic algorithms integrated with neural network based tools

In this paper, a new dynamic security assessment and generation rescheduling method utilizing genetic algorithms (GAs) which are integrated with probabilistic neural networks (PNNs) and adaptive neuro fuzzy inference systems (ANFISs) is proposed for the preventive control of large power systems against transient instabilities. By the proposed approach, PNNs are employed in a feasible manner to calculate the security regions accurately during the assessment and control. The security constrained generation rescheduling is implemented through a GA which optimizes the total fuel cost or the generation shifting during the preventive control. The steady-state solutions of the variables required for the GA are smoothly performed by the use of an ANFIS. The proposed methods are demonstrated on the 17-generator 163-bus Iowa power system and on the 50-generator 145-bus IEEE test system successfully and the effectiveness of the approaches is discussed.     

Artificial neural network modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules

This article presents the artificial neural network modelling of the operating current of a 120 Wp of mono-crystalline photovoltaic module. As an alternative method to analytical modelling approaches, this study uses the advantages of neural networks such as no required knowledge of internal system parameters, less computational effort and a compact solution for multivariable problems. Generalised regression neural network model is used in the present article to predict the operating current of the photovoltaic module. To show its merit, the current predicted from the artificial neural network modelling is compared to that from the analytical model. The five-parameter analytical model is drawn from the equivalent electrical circuit that includes light-generated current, diode reverse saturation current, and series and shunt resistances. The operating current predicted from both the neural and analytical models are compared to the measured current. Results have shown that the artificial neural network modelling provides a better prediction of the current than the five-parameter analytical model.     

Phase transformations in Ti-6Al-4V-xH alloys

Microstructures, phases, and phase transformations in Ti-6Al-4V alloy specimens containing 0, 10, 20, and 30 at. pct hydrogen were investigated using optical microscopy (OM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and microhardness testing. Alloying with hydrogen was achieved by holding the specimens in a pure hydrogen atmosphere of different pressures at 780 °C for 24 hours. The phases present in the temperature range of 20 °C to 1000 °C were determined by microstructural characterization of the specimens quenched from different temperatures. Increasing the hydrogen addition from 0 to 30 at. pct lowered the beta-transus temperature of the alloy from 1005 °C to 815 °C, significantly slowed down the kinetics of the beta-to-alpha transformation, and led to formation of an orthorhombic martensite instead of the hexagonal martensite found in quenched specimens containing 0 pct H. A hydride phase was detected in specimens containing 20 and 30 at. pct hydrogen. The time-temperature-transformation (TTT) diagrams for beta-phase decomposition were determined at different hydrogen concentrations. The nose temperature for the beginning of the transformation decreased from 725 °C to 580 °C, and the nose time increased from 12 seconds to 42 minutes when the hydrogen concentration was increased from 0 to 30 at. pct.     

Spontaneous combustion liability of coal and coal-shale: a review of prediction methods

International Journal of Coal Science & Technology - This study presents a review of the various methods to predict the spontaneous combustion liability of coal and coal-shale. The relative...