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.     

Lossless,Passive Transportation of Low Surface Tension Liquids Induced by Patterned Omniphobic Liquidlike Polymer Brushes

Surfaces enabling directional liquid transportation are of great interest for a wide range of applications such as water collection, microfluidics, and heat transfer systems. Surfaces capable of lossless, long-range passive transportation of low surface tension (LST) liquids using wettability patterned, liquidlike coatings with minimal contact angle hysteresis are reported. Lossless LST droplet travel distances over 150 mm are achieved, enabled by a two-phase transportation mechanism: morphological transformation from a bulge to a channel shape, followed by directional transportation along the asymmetrical wedge-shaped channel. The developed surfaces can split, merge, and precisely transport various low-surface tension liquids, including alcohols, alkanes, and solvents. The developed transportation strategy can also enhance LST liquid dropwise condensation through continuous removal of the condensate, even on horizontally positioned surfaces without the assistance of gravity.     

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.     

A hybrid multi-criteria decision-making model for firms competence evaluation

In this paper, we present a hybrid multi-criteria decision-making (MCDM) model to evaluate the competence of the firms. According to the competence-based theory reveals that firm competencies are recognized from exclusive and unique capabilities that each firm enjoy in marketplace and are tightly intertwined within different business functions throughout the company. Therefore, competence in the firm is a composite of various attributes. Among them many intangible and tangible attributes are difficult to measure. In order to overcome the issue, we invite fuzzy set theory into the measurement of performance. In this paper first we calculate the weight of each criterion through adaptive analytic hierarchy process (AHP) approach (A³) method, and then we appraise the performance of firms via linguistic variables which are expressed as trapezoidal fuzzy numbers. In the next step we transform these fuzzy numbers into interval data by means of α-cut. Then considering different values for α we rank the firms through TOPSIS method with interval data. Since there are different ranks for different α values, we apply linear assignment method to obtain final rank for alternatives.     

A soft robotics nonlinear hybrid position/force control for tendon driven catheters

Minimally invasive steerable catheters, commonly implemented in cardiac ablation, are currently operated by interventionalists exposing them to X-ray radiation and requiring the dexterity for accurate steering. To conduct robot-assisted cardiac ablation, highly accurate stable control platform for precise force/position control on the moving tissue is required. This paper introduces hybrid force/position control strategy to apply a constant force to the cardiac tissue while tracking the desired trajectory. The position controller is based on a nonlinear model predictive tracking control satisfying the input constraints. Cosserat rod theory is incorporated for the distal shaft modeling of tendon-driven catheters, and the model is reformulated for controller design and stability proof. Lyapunov-based stability analysis is conducted. To apply the controller, the force-displacement mapping of the cardiac tissue is obtained through ex vivo experimental tests. The performance of the controller is evaluated, and the catheter is capable of regulating the force with the RMSE of 4.9 mN and tracking the position with the RMSE of 0.89 mm. The promising results verify the potential of the application of the introduced approach in real applications including in vitro and clinical cardiac ablation.     

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.