Prediction of bulk modulus and volumetric expansion coefficient of water for leak tightness test of pipelines

To determine whether any pressure variation in pipeline hydrostatic test is a result of temperature changes or the presence of leaks, the calculation of pressure/temperature changes is required for test sections. In these calculations, bulk modulus and volumetric expansion coefficient of fresh or sea water must be taken into account. In this study, a simple-to-use correlation is developed to predict the bulk modulus and volumetric expansion coefficient of both fresh and sea water as a function of temperature and pressure. The proposed correlation helps to cover the bulk modulus and volumetric expansion coefficient of both fresh and sea water for temperatures less than 50 °C (40 °C for sea water) as well as pressures up to 55,000 kPa (550 bar). The results can be used in follow-up calculations to determine whether any pressure variation in pipeline hydrostatic test is a result of temperature changes or the presence of leaks. The proposed correlation showed promising results with average absolute deviations for volumetric expansion coefficient and bulk modulus of water being around 0.58% and 0.08% respectively. The novel correlation is easy to use and will prove to be of immense value for project engineers to test the critical limits accurately.     

Comparison of deposition models for a TEOS LPCVD process

We present a comparison of models describing the pyrolytic deposition of SiO₂ with a low pressure chemical vapor deposition process. In order to meet industrial simulation requirements, e.g. accuracy and fast delivery of results, we present an overview of established and new models, their use within TCAD applications, and their best results which have been obtained by calibrations according to SEM measurements.     

Principal component analysis with optimum order sample correlation coefficient for image enhancement

Principal component analysis (PCA) has been commonly used and has played an important role in remote sensing for information extraction. However, the ordinary PCA based on second‐order covariance or correlation is capable of forming components on the basis of the statistical properties of a majority of pixel values – pixel values around mean values. For many applications, principal components should be constructed on the basis of optimum correlation coefficients so that the components can represent low or high values of minority pixels of interest. A new version of the PCA has been proposed on the basis of an optimum order sample correlation coefficient for enhancing the contribution of the image bands including the low or high minority pixel values that can assist in extracting weak information for image classification and pattern recognition. The ordinary PCA becomes the special case of the new version of the PCA introduced in this paper. The new method was validated with a case study of identification of Au/Cu‐associated alteration zones from a Landsat Thematic Mapper (TM) image in the Mitchell‐Sulphurets district, Canada.     

Artificial immune system-based parameter extraction of proton exchange membrane fuel cell

For a better understanding of the characteristics, performance evaluation and design analysis of proton exchange membrane fuel cell (PEMFC) system an accurate mathematical model is an imperative tool. Although various models have been developed in the literature, because of the shortage of manufacture information about the precise values of the parameters required for the modeling, the parameter extraction is an essential task. So, in order to obtain the PEMFC actual performance, its parameters have to be identified by an optimization technique. Artificial immune system (AIS) is a soft computing method with promising results in the field of optimization problems. In this paper, an AIS-based algorithm for parameter identification of a PEMFC stack model is proposed. In order to study the usefulness of the proposed algorithm, the AIS-based results are compared with the obtained results by the genetic algorithm (GA) and particle swarm optimization (PSO). It is shown that the AIS algorithm is a helpful and reliable technique for identifying the model parameters so that the PEMFC model with extracted parameters agrees with the experimental data well. Moreover, the AIS algorithm outperforms the GA and PSO methods. Therefore, the AIS can be applied to solve other complex identification problems of fuel cell models.     

Passivity‐based adaptive control of a 2‐DOF serial robot manipulator with temperature dependent joint frictions

Mechanical systems are always suffering from the effects of temperature dependent friction forces where the system is operated in a wide range of temperature. Temperature and its variation play an important role in friction force in mechanical systems. If it is not compensated, it will tend to unwanted consequences, including steady‐state errors, limit cycling, and hunting. Therefore, it is necessary to take the temperature effects into account. This has been a strong motivation for the researchers to work on temperature effects on joint friction. In this paper, an adaptive compensation (control) scheme is proposed and applied to a 2‐degree‐of‐freedom serial robot manipulator by taking the temperature effects into account on the joints friction. In the proposed control scheme, the temperature is not required to be sensed. In this paper, joint friction is described by LuGre dynamic model with temperature dependent parameters. These parameters are described by some functions with unknown temperature dependent terms. According to the mathematical and practical concepts, the temperature dependent friction is decomposed into a viscous term and a disturbance term. An adaptive controller is designed to compensate the friction effect and it is shown that the proposed controller relaxes the condition for a priori knowledge about the environment characteristics, including the upper and lower bounds of the environment temperature and the parameters of the functions, describing the temperature dependent joint frictions. The stability and convergence of the joint position and velocity are proved in the sense of Lyapunov and then the proposed method is confirmed by the simulations.     

A single-phase p-type ac–ac converter with reduced components count and high boost factor

This paper proposes a new single-phase direct step-up ac–ac converter by modifying the p-type impedance source. It provides a high boost factor as well as high efficiency, while only six parts are required to design it, involving just two bidirectional power switches. A safe commutation method has been applied to power switches to make the converter snubber-free and high efficient. Input and output harmonic filters are no longer required since input and output currents variate continuously with small ripple and low total harmonic distortion (THD). The proposed topology only modulates the output voltage amplitude, not the phase and frequency, so the output frequency is identical to the input frequency and constant. Thus, it can be utilized in step-up conversion applications, like inductive power transmission from low ac voltage sources. Input and output have the same ground, which is a good protective feature. In this paper, the operating principle of the converter is demonstrated. Experimental results have been represented to evaluate the performance of the converter. For this purpose, an experimental prototype has been fabricated. Results are investigated and compared with other previous step-up ac–ac converters. Results confirm the theory, operating principle, and performance of the converter.     

New Approach to High-Pressure Nuclear Magnetic Resonance with Anvil Cells

A novel approach that uses radio-frequency microcoils in the high-pressure region of anvil cells with Nuclear Magnetic Resonance (NMR) experiments is described. High-sensitivity Al NMR data at 70 kbar for Al metal are presented for the first time. An expected decrease in the Al Knight shift at 70 kbar is observed, as well as an unexpected change in the local charge symmetry at the Al nucleus. The latter is not predicted by chemical structure analysis under high pressure.     

Modeling industrial thickener using computational fluid dynamics (CFD), a case study: Tailing thickener in the Sarcheshmeh copper mine

Separation of particles from liquid in the large gravitational tanks is widely used in mining and industrial wastewater treatment process. Thickener is key unit in the operational processes of hydrometallurgy and is used to separate solid from liquid. In this study, population balance models were combined with computational fluid dynamics (CFD) for modeling the tailing thickener. Parameters such as feed flow rate, flocculant dosage, inlet solid percent and feedwell were investigated. CFD was used to simulate the industrial tailing thickener with settled bed of 120 m diameter which is located in the Sarcheshmeh copper mine. Important factor of drag force that defines the rake torque of rotating paddles on the bed was also determined. Two phases turbulence model of Eulerian/Eulerian in accordance with turbulence model of k-ε was used in the steady-state. Also population balance model consists of 15 groups of particle sizes with Luo and Lehr kernel was used for aggregation/breakage kernel. The simulation results showed good agreement with the operational data.     

Ionic conduction and crystal structure of aluminum doped NASICON-type LiGe<Subscript>2</Subscript>(PO<Subscript>4</Subscript>)<Subscript>3</Subscript> glass-ceramic crystallized at different times and temperatures

In this communication, NASICON-type glass-ceramic (lithium germanium phosphate, LiGe₂(PO₄)₃) was prepared as lithium super ionic conductor using aluminum as dopant for ionic conduction improvement. The solid solution was Li_1?+?xAl_xGe_2-x(PO₄)₃ (x?=?0.5) that Ge⁴⁺ ions were partially substituted by Al³⁺ ions in crystal structure. Initial glasses were converted to glass-ceramics at different times and temperatures for maximum ionic conduction achievement. The crystals were characterized by X-ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Energy-Dispersive X-ray spectroscopy (EDX), Differential Scanning Calorimetry (DSC) and Complex Impedance Spectroscopy (CIS) methods. The maximum lithium ion conductivity for glass-ceramic, 5.32?×?10^?3 S/cm at 26 °C was obtained for specimen crystallized at 850 °C for 8 h with minimum activation energy of 0.286 eV. Increasing the crystallization temperature results in secondary phase formation in grain boundary and increasing in crystallization time results in microcracks formation in specimen. Both phenomena decreased the ionic conductivity.