Simulation of smoke from a burning vehicle and pollution levels caused by traffic jam in a road tunnel

Detailed analyses of smoke movement from a burning vehicle in a road tunnel have been carried out for the westbound Melbourne City Link tunnel. The time-averaged equations for velocity, pressure, temperature, and mass fraction of emissions were solved for transient condition using the CFD software FLUENT 6.0. For the analysis, a burning bus was assumed to release an equivalent energy of burning 500 l of diesel in 6 min, with vehicles upstream of the fire at a standstill. On the other hand, the vehicles downstream of the fire had enough time to escape from the tunnel through the exit portal. Due to the action of jet fans, most of the smoke was pushed downstream of the fire. The smoke had also dispersed about 55 m upstream of the fire, putting the passengers in this region at great risk. The emissions released from the vehicles in the jam, with their engines running, also posed a threat to human health. Within 8 min after the fire had started, the mass concentrations of O₂, CO₂ and CO were in the ranges of 0.12–0.15, 0.08–0.11 and 0.0006–0.0014, respectively. Therefore, quick evacuation of the passengers is essential in the event of a fire in the tunnel.     

Synthesis of poly(methyl methacrylate)/silica nanocomposite through emulsion polymerization using dimethylaminoethyl methacrylate

Polymer/Silica nanocomposite latex particles were prepared by emulsion polymerization of methyl methacrylate (MMA) with dimethylaminoethyl methacrylate (DM). The reaction was performed using a nonionic surfactant and in the presence of silica nanoparticles as the seed. The polymer‐coated silica nanoparticles with polymer content and number average particle sizes ranged from 32 to 93 wt % and 114–310 nm, respectively, were obtained depending on reaction conditions. Influences of some synthetic conditions such as MMA, DM, surfactant concentration, and the nature of initiator on the coating of the silica nanoparticles were studied. Electrostatic attraction between anionic surface of silica beads and cationic amino groups of DM is the main driving force for the formation of the nanocomposites. It was demonstrated that the ratio of DM/MMA is important factor in stability of the system. The particle size, polymer content, efficiency of the coating reaction, and morphology of resulted nanocomposite particles showed a dependence on the amount of the surfactant. Zeta potential measurements confirmed that the DM was located at the surface of the nanocomposites particles. Thermogravimeteric analysis indicated a relationship between the composition of polymer shell and polymer content of the nanocomposites. The nanocomposites were also characterized by FTIR and differential scanning calorimetry techniques. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Uniform modeling of parameter dependent nonlinear systems

This paper addresses the problem of approximating parameter dependent nonlinear systems in a unified framework. This modeling has been presented for the first time in the form of parameter dependent piecewise affine systems. In this model, the matrices and vectors defining piecewise affine systems are affine functions of parameters. Modeling of the system is done based on distinct spaces of state and parameter, and the operating regions are partitioned into the sections that we call ’multiplied simplices’. It is proven that this method of partitioning leads to less complexity of the approximated model compared with the few existing methods for modeling of parameter dependent nonlinear systems. It is also proven that the approximation is continuous for continuous functions and can be arbitrarily close to the original one. Next, the approximation error is calculated for a special class of parameter dependent nonlinear systems. For this class of systems, by solving an optimization problem, the operating regions can be partitioned into the minimum number of hyper-rectangles such that the modeling error does not exceed a specified value. This modeling method can be the first step towards analyzing the parameter dependent nonlinear systems with a uniform method.     

Oil thermal annealed nano‐structured indium tin oxide thin films for display applications

Indium tin oxide‐coated thin films (200 nm) are deposited on glass substrates by using R.f. sputtering technique. Here, we investigate the influence of new technique of treatment, which is called as “oil thermal annealing” on the nano‐structured indium tin oxide thin films at fixed temperature (150 °C) which improves adhesion strength, electrical conductivity and optical properties (transmittance) of the films. Oil thermal annealing is used to reduce inherent defects that may be introduced during the prepared thin film and cooling processes. Proposed technique is highly suitable for liquid crystal displays, solar cells and organic light emitting diodes, and many other display‐related applications.     

A pseudo-spectral scheme for the approximate solution of a time-fractional diffusion equation

We consider an initial-boundary-value problem for a time-fractional diffusion equation with initial condition u₀(x) and homogeneous Dirichlet boundary conditions in a bounded interval [0, L]. We study a semidiscrete approximation scheme based on the pseudo-spectral method on Chebyshev–Gauss–Lobatto nodes. In order to preserve the high accuracy of the spectral approximation we use an approach based on the evaluation of the Mittag-Leffler function on matrix arguments for the integration along the time variable. Some examples are presented and numerical experiments illustrate the effectiveness of the proposed approach.     

Model updating of multistory shear buildings for simultaneous identification of mass,stiffness and damping matrices using two different soft-computing methods

In this research, two novel methods for simultaneous identification of mass–damping–stiffness of shear buildings are proposed. The first method presents a procedure to estimate the natural frequencies, modal damping ratios, and modal shapes of shear buildings from their forced vibration responses. To estimate the coefficient matrices of a state-space model, an auto-regressive exogenous excitation (ARX) model cooperating with a neural network concept is employed. The modal parameters of the structure are then evaluated from the eigenparameters of the coefficient matrix of the model. Finally, modal parameters are used to identify the physical/structural (i.e., mass, damping, and stiffness) matrices of the structure. In the second method, a direct strategy of physical/structural identification is developed from the dynamic responses of the structure without any eigenvalue analysis or optimization processes that are usually necessary in inverse problems. This method modifies the governing equations of motion based on relative responses of consecutive stories such that the new set of equations can be implemented in a cluster of artificial neural networks. The number of neural networks is equal to the number of degree-of-freedom of the structure. It is shown the noise effects may partially be eliminated by using high-order finite impulse response (FIR) filters in both methods. Finally, the feasibility and accuracy of the presented model updating methods are examined through numerical studies on multistory shear buildings using the simulated records with various noise levels. The excellent agreement of the obtained results with those of the finite element models shows the feasibility of the proposed methods.     

Two-Dimensional Simulation Model of Sediment Removal and Flow in Rectangular Sedimentation Basin

A steady, two-dimensional numerical model was created to study the hydrodynamics of a rectangular sedimentation basin under turbulent conditions. The strip integral method was used to formulate the flow equations, using a forward marching scheme for solving the governing partial differential equations of continuity, momentum, advection–diffusion, turbulent kinetic energy, and its dissipation. In this way the flow equations were converted to a set of ordinary differential equations (ODEs) in terms of the key physical parameters. These parameters, along with a set of shape functions, describe flow variables including the velocity, the concentration of suspended sediments, and both the kinetic energy and its dissipation rate. Four Gaussian distributions were investigated, one corresponding to each flow parameter. In order to calculate the turbulent shear stresses, a two-equation turbulence model (i.e., k-ε model) was used. A fourth order Runge–Kutta method numerically integrates the set of ODEs. Simulation results were compared with experimental data, and close agreement (generally within 5–10%) was observed.     

A Sliding Mode Controller Based on Robust Model Reference Adaptive Proportional-integral Control for Stand-alone Three-phase Inverter

This paper proposes a sliding mode controller based on robust model reference adaptive proportional-integral (RMRA-PI) control for a stand-alone voltage source inverter (SA-VSI). The proposed controller has two control loops where the coefficients of PI controller are regulated by the adaptive sliding law. This method is used to regulate the output voltage of the inverter under different load conditions and uncertainty, and adapts the output to the reference model to reduce the total harmonic distortion (THD). In this paper, the stability of the proposed controller is proven by using Lyapunov’s theory and Barbalet’s lemma. The proposed controller performs well in voltage regulation such as low THD under sudden load change and uncertainty. Also, the results of the proposed controller are compared with PI controller to show the effectiveness of the presented control system.     

Microstructure Refinement After the Addition of Titanium Particles in AZ31 Magnesium Alloy Resistance Spot Welds

Microstructural evolution of AZ31 magnesium alloy welds without and with the addition of titanium powders during resistance spot welding was studied using optical microscopy, scanning electron microscopy, and transmission electron microscopy (TEM). The fusion zone of AZ31 magnesium alloy welds could be divided into columnar dendritic zone (CDZ) and equiaxed dendritic zone (EDZ). The well-developed CDZ in the vicinity of the fusion boundary was clearly restricted and the coarse EDZ in the central region was efficiently refined by adding titanium powders into the molten pool, compared with the as-received alloy welds. A microstructural analysis showed that these titanium particles of approximately 8 μm diameter acted as inoculants and promoted the nucleation of α-Mg grains and the formation of equiaxed dendritic grains during resistance spot welding. Tensile-shear testing was applied to evaluate the effect of titanium addition on the mechanical properties of welds. It was found that both strength and ductility of magnesium alloy welds were increased after the titanium addition. A TEM examination showed the existence of an orientation matching relationship between the added Ti particles and Mg matrix, i.e., [ 0 1[`1]0 ]<sub>\textMg</sub> //  [ 1[`2] 1[`3] ]<sub>\textTi</sub>  \textand ( 000 2 )<sub>\textMg</sub> //  ( 10[`1]0)_\textTi \left[ {0 1\bar{1}0} \right]_{\text{Mg}} // \, \left[ { 1\bar{2} 1\bar{3}} \right]_{\text{Ti}} \,{\text{and}}\,\left( {000 2} \right)_{\text{Mg}} // \, ( 10\bar{1}0)_{\text{Ti}} in some grains of Ti polycrystal particles. This local crystallographic matching could promote heterogeneous nucleation of the Mg matrix during welding. The diameter of the added Ti inoculant should be larger than 1.8 μm to make it a potent inoculant.