Nonlinear optical behavior of alkyne terminated phthalocyanines in solution and when embedded in polysulfone as thin films: Effects of aggregation

We report here for the first time, on the comparative studies of the photophysical and optical limiting behavior of our two novel phthalocyanines namely 2(3), 9(10), 16(17), 23(24)-tetrakis-(4-(5-methylhex-1-yn-3-yloxy)) phthalocyanines 2, and 2(3), 9(10), 16(17), 23(24)-tetrakis-(4-(5-methylhex-1-yn-3-yloxy)) phthalocyaninato zinc (II) (3) in solution and thin films. Nonlinear optical (NLO) properties of the samples in solution and contained in polysulfone (PSU) thin films were evaluated using Z-scan technique at 532 nm and 10 ns pulsed duration. Effects of aggregation and disaggregation on the NLO performance of metal-free phthalocyanine are reported in detail. Our findings showed that the prepared Pcs show larger nonlinear absorption coefficient and lower limiting thresholds when embedded in polysulfone films compared to in solutions. The values of nonlinear susceptibility and hyperpolarizability recorded for 3-PSU in this work are respectively, ∼2.09 × 10⁻⁸ esu and ∼1.02 × 10⁻²⁶ esu. These values are among the largest values reported for phthalocyanines and other macrocycles doped on polymer matrices.     

A node-based smoothed finite element method (NS-FEM) for upper bound solution to visco-elastoplastic analyses of solids using triangular and tetrahedral meshes

A node-based smoothed finite element method (NS-FEM) was recently proposed for the solid mechanics problems. In the NS-FEM, the system stiffness matrix is computed using the smoothed strains over the smoothing domains associated with nodes of element mesh. In this paper, the NS-FEM is further extended to more complicated visco-elastoplastic analyses of 2D and 3D solids using triangular and tetrahedral meshes, respectively. The material behavior includes perfect visco-elastoplasticity and visco-elastoplasticity with isotropic hardening and linear kinematic hardening. A dual formulation for the NS-FEM with displacements and stresses as the main variables is performed. The von-Mises yield function and the Prandtl–Reuss flow rule are used. In the numerical procedure, however, the stress variables are eliminated and the problem becomes only displacement-dependent. The numerical results show that the NS-FEM has higher computational cost than the FEM. However the NS-FEM is much more accurate than the FEM, and hence the NS-FEM is more efficient than the FEM. It is also observed from the numerical results that the NS-FEM possesses the upper bound property which is very meaningful for the visco-elastoplastic analyses which almost have not got the analytical solutions. This suggests that we can use two models, NS-FEM and FEM, to bound the solution, and can even estimate the global relative error of numerical solutions.     

Development of an adaptive fuzzy logic-based inverse dynamic model for laser cladding process

The precision, performance, and robustness of model-based controllers depend, to a large extent, on the accuracy of the inverse dynamic model which is incorporated in the design of the controller. Due to complex nature of the laser cladding process and presence of time-varying uncertainties, derivation of an accurate mathematical inverse dynamic model of the process is very difficult, and involves many unknown parameters. The inverse dynamic model of the complex nonlinear laser cladding process, which is difficult to be described mathematically, can be described by a fuzzy logic-based inverse dynamic model constructed form input–output data. In this paper, the development of an adaptive fuzzy inverse dynamic model of the laser cladding process, using a systematic fuzzy modelling approach is presented. In a closed-loop laser cladding process, the scanning speed of the substrate is required to produce a clad with desired geometry and quality. In this paper, a fuzzy inverse dynamic model that describes the scanning speed as a function of the cladding parameters in particular the clad height is developed. The developed fuzzy model is validated by comparing the model output with experimental data. The results are very promising and show that fuzzy models can accurately describe the process dynamics.     

A multi-agent system model of a diesel engine using rule induction

The proliferation of a multi-agent system (MAS) and ideas from Artificial Intelligence (AI)/distributed AI have changed the way systems, in general are controlled, and operation of a system (diesel engine) in particular is automated. In this paper a distributed multi-agent architecture for a diesel engine and the knowledge sources that handle electricity generation is developed. Electronic devices and components used for data handling are described. The sensed data are presented in fuzzy logic and calculated in entropy values and depicted in a decision hierarchy. A comparative performance assessment of the proposed multi-agent based system with an existing system is presented and discussed.     

PSO-based single multiplicative neuron model for time series prediction

Single multiplicative neuron model is a novel neural network model introduced recently, which has been used for time series prediction and function approximation. The model is based on a polynomial architecture that is the product of linear functions in different dimensions of the space. Particle swarm optimization (PSO), a global optimization method, is proposed to train the single neuron model in this paper. An improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. The proposed CRPSO, PSO, back-propagation algorithm and genetic algorithm are employed to train the model for three well-known time series prediction problems. The experimental results demonstrate the superiority of CRPSO-based neuron model in efficiency and robustness over the other three algorithms.     

Characterisation and control of bubbling behaviour in gas–solid fluidised beds

Bubbling fluidised beds are often exploited for the good mixing of phases they promote, which is required in many chemical processes. However, the bubbles cause heterogeneity in the fluidised system, and their dynamics must be understood for good process control. In this paper, the dynamic behaviour of the bubbles in a planar gas–solid fluidised bed is described analytically and experimentally validated. The bed resembles a temporary buffer of gas for which the bubble residence time in the bed is important. Subsequently, a closed-loop controller was developed using visual feedback to regulate the process.     

Stabilization and nonlinear control for a novel trirotor mini-aircraft

The dynamical model of an original trirotor helicopter is presented in this paper. The helicopter is composed of three rotors with constant pitch propellers; two fixed rotors turning in opposite directions and one rotor that can be tilted to control the yaw displacement. The dynamical model is obtained via the Euler–Lagrange approach and a nonlinear control strategy is proposed. The roll and the forward displacement are controlled by using a nested saturations control law. The pitch and lateral displacement are controlled in a similar way. The nonlinear controller performance is tested on real experiments using a trirotor rotorcraft. It is shown that the controller is robust to large perturbations on the orientation angles and that it has better behavior than a classical linear state-feedback controller.