International Journal of Modeling, Simulation, and Scientific Computing

The freight logistics includes all the processes needed to supply industry, retailers and wholesalers and final customers with goods. Such processes generate a flow of goods that, in the global supply chain, mainly relies on the activities carried out within worldwide container terminals. In this paper, the authors present a simulation model of a real container terminal. After some preliminary analyses, the simulation model is first used with Design of Experiments and Analysis of Variance to investigate the effects of different resources allocations (i.e., number of forklifts and tractors) and some parameters (i.e., inter-arrival times, container unloading time) on the container terminal performances in terms of total number of handled containers per day. Then, based on the results achieved through the Design of Experiments and Analysis of Variance, the simulation model is used with genetic algorithms to carry out a range allocation optimization on berth assignment to incoming ships and number of tractors serving each quay crane. The aim of the optimization is the minimization of the average time spent by each ship in the port area (decreasing, as consequence, costs and increasing service level provided to final customers).

A perturbation algorithm Multiple Scales Modified Lindstedt–Poincare (MSMLP), combination of method of Multiple Scales and modified Lindstedt–Poincare is proposed for the solution of Quintic Duffing equation which combines the advantages of both the methods. Solution obtained by the MSMLP method is compared with the Multiple Scales method and accurate closed form approximate solution of the Quintic Duffing equation. The proposed method produces better results for a wide range of amplitude values of oscillations and strong nonlinearities. Numerical simulation has been performed in MATHEMATICA 7.0.

In this paper, we present a third-order central weighted essentially nonoscillatory (CWENO) reconstruction for computations of hyperbolic conservation laws in three space dimensions. Simultaneously, as a Godunov-type central scheme, the CWENO-type central-upwind scheme, i.e., the semi-discrete central-upwind scheme based on our third-order CWENO reconstruction, is developed straightforwardly to solve 3D systems by the so-called componentwise and dimensional-by-dimensional technologies. The high resolution, the efficiency and the nonoscillatory property of the scheme can be verified by solving several numerical experiments.

In this work, element free Galerkin method (EFGM) has been used to obtain the solution of edge crack problem under mechanical loads as it provides a versatile technique to model static as well as moving crack problems without any requirement of remeshing. At first, some techniques are presented for enriching the EFG approximations near the crack tip such as extrinsic and intrinsic enrichment. Extrinsic enrichment involves the addition of solution form to the trial function, whereas the EFG basis is expanded to include few terms from crack tip solution in intrinsic enrichment. Apart from enrichment techniques, four basic techniques of smoothing meshless approximations near nonconvex boundaries are also presented such as diffraction, transparency, see through and wedge model. These techniques are then used for the parameteric analysis of an edge crack problem under mode-1 loading and results obtained using different approaches are compared with each other as well as with exact solution. Among these techniques, the extrinsic PU enrichment technique was found to be more accurate as compared to other approaches. Extrinsic PU enrichment technique has also been used for the analysis of a shear edge crack problem. In all these techniques, the value of mode-1 stress intensity factor and mode-2 stress intensity factor has been evaluated by interaction integral approach. Effect of crack orientation is also studied for different cases.

A dispersion model for the estimation of crosswind integrated concentrations in the surface-based inversion is proposed. The generalized forms of eddy diffusivity with spatial dependence in both horizontal and vertical directions and vertical height-dependent wind speed are considered. In view of the computational limitation associated with numerical models for Dirac-delta function, the source term is expressed as a limiting case of normal distribution. The accuracy of the employed numerical scheme to solve the resulting partial differential equation with appropriate physically relevant boundary conditions is checked with those obtained from the respective analytical solutions available in literature for the particular forms of eddy diffusivity and wind speed. Concentrations computed from the proposed model are found close to those obtained from analytical models. The concentrations obtained from the proposed model are evaluated for the generalized functional forms of eddy diffusivity (Degrazia and Moraes, 1992; Degrazia et al., 2001) and diabatic logarithmic profile as well as power-law profile of wind speed with the observations from Hanford (Doran et al., 1984) and Copenhagen (Gryning and Lyck, 1984) diffusion experiments in stable and unstable conditions, respectively. Majority of the cases i.e., 64% and 96% are predicted in factor of two to observations in both stable and unstable conditions, respectively.

In this paper, the modeling and control design of a biomimetic robotic fish is presented. The Anguilliform robotic fish consists of N links and N - 1 joints, and the driving forces are the torques applied to the joints. Considering kinematic constraints, Lagrangian formulation is used to obtain the dynamics of the fish model. The computed torque control method is applied first, which can provide satisfactory tracking responses for fish joints. Since this robotic fish is essentially an underactuated system, the reference trajectories for the orientation of the N links are planned in such a way that, at a neighborhood of the equilibrium point, the tracking task of N angles can be achieved by using N - 1 joint torques. To deal with parameter uncertainties that exist in the actual environment, sliding mode control is adopted. Considering feasibility and complexity issues, a simplified sliding mode control algorithm is given. A four-link robotic fish is modeled and simulated, and the results validate the effectiveness of reference planning and the proposed controllers.

This paper presents a technique for deriving least-squares-based polynomial bubble functions to enrich the standard linear finite elements, employed in the formulation of Galerkin weighted-residual statements. The element-level linear shape functions are enhanced using supplementary polynomial bubble functions with undetermined coefficients. The enhanced shape functions are inserted into the model equation and the residual functional is constructed and minimized by using the method of the least squares, resulting in an algebraic system of equations which can be solved to determine the unknown polynomial coefficients in terms of element-level nodal values. The stiffness matrices are subsequently formed with the standard finite elements assembly procedures followed by using these enriched elements which require no additional nodes to be introduced and no extra degree of freedom incurred. Furthermore, the proposed technique is tested on a number of benchmark linear transport equations where the quadratic and cubic bubble functions are derived and the numerical results are compared against the exact and standard linear element solutions. It is demonstrated that low order bubble enriched elements provide more accurate approximations for the exact analytical solutions than the standard linear elements at no extra computational cost in spite of using relatively crude meshes. On the other hand, it is observed that a satisfactory solution of the strongly convection-dominated transport problems may require element enrichment by using significantly higher order polynomial bubble functions in addition to the use of extremely fine computational meshes.

Soft computing has attracted many research scientists, decision makers and practicing researchers in recent years as powerful computational intelligent techniques, for solving unlimited number of complex real-world problems particularly related to research area of optimization. Under the uncertain and turbulence environment, classical and traditional approaches are unable to obtain a complete solution with satisfaction for the real-world problems on optimization. Therefore, new global optimization methods are required to handle these issues seriously. One such method is hybrid Genetic algorithms and Pattern search, a generic, flexible, robust, and versatile framework for solving complex problems of global optimization and search in real-world applications.