Neural network based approach for determining the shear strength of circular reinforced concrete columns

The objective of this study is to investigate the adequacy of neural networks (NN) as a quicker, more secure and more robust method to determine the shear strength of circular reinforced concrete columns. In the application of the NN model, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN model is developed, trained and tested through a based MATLAB program. The data used for training and testing NN model are gathered from literature. NN based model outputs are compared with ACI, ATC-32, ASCE and CALTRANS codes outcomes on the basis of the experimental results. This comparison demonstrated that the NN based model is highly successful to determine the shear strength of circular reinforced concrete columns.     

Optimization of MnO2/vertically aligned carbon nanotube composite for supercapacitor application

The optimization strategy for producing manganese oxide supercapacitors based on vertically aligned carbon nanotubes (VACNTs) deposited on large area electrodes is presented. A single sequential process of sputtering, annealing and plasma enhanced chemical vapour deposition (PECVD) is applied to produce dense and uniform VACNTs electrodes. As dielectric layer of the supercapacitor, manganese oxide is electrodeposited lining the surface of the VACNTs electrodes. The control of the growing parameters such as catalyst thickness layer, temperature and deposition time for tuning the density, length and diameter of the VACNTs and their structure are found to be key points for the optimization of the MnO₂ electrodeposition process in view to improve the efficiency of the supercapacitor devices.The electrochemical properties of the obtained electrodes are characterized using cyclic voltammetry and galvanostatic charge-discharge techniques. A specific capacitance of 642 Fg⁻¹ is obtained for MnO₂/VACNTs nanocomposite electrode at a scan rate of 10 mV s⁻¹.     

Adsorption and precipitation behaviour of petroleum sulfonates from Saudi Arabian limestone

The adsorption behaviour of a petroleum sulfonate (TRS10-410) on Saudi Arabian limestone has been studied as a function of salinity, surfactant concentration and pH. The adsorption data on limestone exhibit the significant effect of mineral solubility in controlling the surfactant depletion. Release of Ca²⁺ ions from the semi-soluble limestone matrix produces precipitation of the surfactant followed by its redissolution at concentrations exceeding the critical micelle concentration (CMC). This characteristic behaviour generates an apparent adsorption maximum which is of considerable interest in surfactant flooding. The precipitation tolerance of TRS10-410 has also been investigated in the presence of Na⁺ and Ca²⁺ ions to quantitatively describe the precipitation behaviour of this surfactant. The adsorption and precipitation data are analyzed to elucidate the mechanism of surfactant adsorption on limestone and that of surfactant precipitation by inorganic ions.     

Transmission losses based MW contingency ranking

Contingency ranking and selection is an indispensable tool for static security analysis. Several performance indices suffer either from misranking or computational inefficiencies. This paper presents a new performance index for MW line flow contingency selection and ranking. The proposed index is derived from real power transmission losses. It is a quadratic function of bus voltage angles and can easily be calculated from real power flows or DC load flow. It improves both the selectivity and the ranking of second order performance index without excessive computational effort. The proposed method is tested on IEEE 24-bus reliability test system and IEEE 30-bus test system. The results are compared with those of the conventional second order performance index and of the tenth order reference performance index from the point of ranking and selectivity.     

Graphene plasmonics for tunable terahertz metamaterials

Plasmons describe collective oscillations of electrons. They have a fundamental role in the dynamic responses of electron systems and form the basis of research into optical metamaterials. Plasmons of two-dimensional massless electrons, as present in graphene, show unusual behaviour that enables new tunable plasmonic metamaterials and, potentially, optoelectronic applications in the terahertz frequency range. Here we explore plasmon excitations in engineered graphene micro-ribbon arrays. We demonstrate that graphene plasmon resonances can be tuned over a broad terahertz frequency range by changing micro-ribbon width and in situ electrostatic doping. The ribbon width and carrier doping dependences of graphene plasmon frequency demonstrate power-law behaviour characteristic of two-dimensional massless Dirac electrons. The plasmon resonances have remarkably large oscillator strengths, resulting in prominent room-temperature optical absorption peaks. In comparison, plasmon absorption in a conventional two-dimensional electron gas was observed only at 4.2?K (refs 13, 14). The results represent a first look at light-plasmon coupling in graphene and point to potential graphene-based terahertz metamaterials.     

RF-induced heating of interventional devices at 23.66 MHz

Objective

Low-field MRI systems are expected to cause less RF heating in conventional interventional devices due to lower Larmor frequency. We systematically evaluate RF-induced heating of commonly used intravascular devices at the Larmor frequency of a 0.55 T system (23.66 MHz) with a focus on the effect of patient size, target organ, and device position on maximum temperature rise.

Materials and methods

To assess RF-induced heating, high-resolution measurements of the electric field, temperature, and transfer function were combined. Realistic device trajectories were derived from vascular models to evaluate the variation of the temperature increase as a function of the device trajectory. At a low-field RF test bench, the effects of patient size and positioning, target organ (liver and heart) and body coil type were measured for six commonly used interventional devices (two guidewires, two catheters, an applicator and a biopsy needle).

Results

Electric field mapping shows that the hotspots are not necessarily localized at the device tip. Of all procedures, the liver catheterizations showed the lowest heating, and a modification of the transmit body coil could further reduce the temperature increase. For common commercial needles no significant heating was measured at the needle tip. Comparable local SAR values were found in the temperature measurements and the TF-based calculations.

Conclusion

At low fields, interventions with shorter insertion lengths such as hepatic catheterizations result in less RF-induced heating than coronary interventions. The maximum temperature increase depends on body coil design.

     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

The Use of Digital Image Processing Method to Estimate the Foam Characteristics of Polyurethane

Four air-bubbled polyurethane (PU) foams with different polyol:PMDI wt.% are produced, respectively. The chemical reaction mechanisms of polyurethane and bubble formation are proposed by performing standard Gibbs free energy calculations using the DFT M06-2X/6-31+G(d,p) method. The local minima, transition states, and intermediates in reaction mechanisms are detected. It is concluded that both reactions are exothermic. Then, raw images of the produced PU foams are taken with a 13 MP mobile phone camera, which can be considered inexpensive, and the mean radii of the pores are calculated by an image processing based method (IPBM) on a standard desktop computer with an i5 processor. It is determined that there is a close relationship between the calculated mean radius and instrumentally measured thermal conductivity coefficient of the foams. However, the thermal conductivity coefficients are independent of the calculated number and percentage of the pores. The mean radii of the samples calculated by the proposed IPBM are close to that of the SEM, with acceptable relative errors of less than 10%. Finally, it is concluded that IPBM, which is a more cost-effective, cleaner, and faster method than SEM, might replace SEM in the air bubble analysis of PU foams.