Selecting effective features on prediction of delay in servicing ships arriving to ports using a combination of Clonal Selection and Grey Wolf Optimization algorithms—Case study: Shahid Rajaee port in Bandar Abbas

Predicting the delay in servicing incoming ships to ports is crucial for maritime transportation. In this study, we use support vector regression (SVR) in order to accurately predict this delay for ships arriving to the terminal No. 1 of Shahid Rajaee's port in Bandar Abbas. To achieve this goal, a combination of Clonal Selection and Grey Wolf Optimization algorithms (named as CLOGWO) is used for two purposes: (i) selecting the most important features among the features that affect prediction of this delay and (ii) optimizing SVR parameters for a more accurate prediction. Performance of the proposed method was compared with Genetic Algorithm (GA), Clonal Selection (CS), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO) algorithms on the following metrics: correlation, rate of feature reduction, root mean square error (RMSE), and normalized RMSE (NRMSE). Evaluations on Shahid Rajaee dataset showed that the mean value of these metrics in 10 independent runs of the proposed method were 0.867, 74.45%, 0.080, and 9.02, respectively. These results and evaluations on standard datasets indicate that the proposed method provides competitive results with other evolutionary algorithms.     

Voronoi based discrete least squares meshless method for heat conduction simulation in highly irregular geometries

A new technique is used in Discrete Least Square Meshfree(DLSM) method to remove the common existing deficiencies of meshfree methods in handling of the problems containing cracks or concave boundaries. An enhanced Discrete Least Squares Meshless method named as VDLSM(Voronoi based Discrete Least Squares Meshless) is developed in order to solve the steady-state heat conduction problem in irregular solid domains including concave boundaries or cracks. Existing meshless methods cannot estimate precisely the required unknowns in the vicinity of the above mentioned boundaries. Conducted researches are limited to domains with regular convex boundaries. To this end, the advantages of the Voronoi tessellation algorithm are implemented. The support domains of the sampling points are determined using a Voronoi tessellation algorithm. For the weight functions, a cubic spline polynomial is used based on a normalized distance variable which can provide a high degree of smoothness near those mentioned above discontinuities. Finally, Moving Least Squares(MLS) shape functions are constructed using a varitional method. This straight-forward scheme can properly estimate the unknowns(in this particular study, the temperatures at the nodal points) near and on the crack faces, crack tip or concave boundaries without need to extra backward corrective procedures, i.e. the iterative calculations for modifying the shape functions of the nodes located near or on these types of the complex boundaries. The accuracy and efficiency of the presented method are investigated by analyzing four particular examples. Obtained results from VDLSM are compared with the available analytical results or with the results of the well-known Finite Elements Method(FEM) when an analytical solution is not available. By comparisons, it is revealed that the proposed technique gives high accuracy for the solution of the steady-state heat conduction problems within cracked domains or domains with concave boundaries and at the same time possesses a high convergence rate which its accuracy is not sensitive to the arrangement of the nodal points. The novelty of this paper is the use of Voronoi concept in determining the weight functions used in the formulation of the MLS type shape functions.     

Dynamic Simulation of Multibody Systems Using a New State-Time Methodology

This paper presents a new methodology demonstrating the feasibility and advantages of a state-time formulation for dynamic simulation of complex multibody systems which shows potential advantages for exploiting massively parallel computing resources. This formulation allows time to be discretized and parameterized so that it can be treated as a variable in a manner similar to the system state variables. As a consequence of such a state-time discretization scheme, the system of governing equations yields to a set of loosely coupled linear-quadratic algebraic equations that is well-suited in structure for some families of nonlinear algebraic equations solvers. The goal of this work is to develop efficient multibody dynamics algorithm that is extremely scalable and better able to fully exploit anticipated immensely parallel computing machines (tera flop, peta flop and beyond) made available to it.     

Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach

Reservoirs are built to provide a powerful tool to control and manage surface water resources in order to cover inconsistency between water resources and demands. Due to finite available water and the increasing demands for water especially in arid and semi-arid regions like Iran, reservoirs must be optimally operated in order to use water in the most efficient way. This study applies the Interior Search Algorithm (ISA) to solve large scale reservoirs system operation optimization problems. The ISA is a meta-heuristic algorithm inspired from a systematic methodology of architecture process and mirror work utilized by Persian designers for decoration. Unlike other meta-heuristic algorithms, the ISA just have one parameter to tune which is a great advantage. In this study the parameter of the ISA tuned automatically using a linear equation. A real-world one-reservoir operation problem (i.e. Karun-4) and two large scale benchmark problems (i.e. four-reservoir and ten-reservoir operation problem) were employed to show the effectiveness of the ISA. The results shows the high ability of the ISA to solve reservoirs system operation problems as it achieved solutions 99.97, 99.99 and 99.95 % of global optimum for Karun-4 reservoir, four-reservoir and ten-reservoir system operation problems, respectively. These results are the best results reported so far in the studied problems. Comparing results of the ISA with those of non-linear programming (NLP), linear programming (LP), genetic algorithm (GA) and other meta-heuristic algorithms indicates fast convergence to global optimum. Considering the results, it can be stated that the ISA is a powerful tool to optimize complex large scale reservoir system operation problems.     

Mitigation of the impact of transformer inrush current on voltage sag by TCSC

Thyristor Controlled Series Capacitor (TCSC) as a dynamic system, besides its capability in increasing power transfer in transmission lines, can be used to enhance different power system issues. In this paper, the effect of TCSC on voltage sag following transformer inrush current is investigated. It is shown that excessive transient inrush current occurring during transformer energizing can be mitigated by TCSC. Hence, voltage sag as one of the key components of the power quality is alleviated for the sensitive loads that are connected to the same bus which the power transformer is energized from. During a fault, TCSC can improve the voltage sag by limiting the current and help to keep the voltage as high as possible. Moreover, the inrush currents and the associated voltage sags that usually occur after clearing heavy single- or multistage faults are mitigated by the presence of TCSC. The model used for simulating inrush current is based on the characteristics of the major hysteresis loop out of which the internal trajectories are defined using the translation principal and a linear compensation to generate closed loops. An arctangent relation between the flux and the exciting current is defined. The expression parameters are deduced by curve fitting empirical data defining the major loop or the single-valued saturation characteristic.     

Hard- and soft-modeling approaches for resolution of complex formation of Co2+ and Ni2+ with glycine

Principal component analysis (PCA) was used to obtain information about the number of components in the complex formation equilibria of Co(2+) and Ni(2+) with glycine (Gly). In order to obtain a clearer insight into these complex formation systems, multivariate curve resolution-alternating least squares (MCR-ALS) was used. Using MCR-ALS as a soft-modeling method, well-defined concentration and spectral profiles were obtained under unimodality, non-negativity, and closure constraints. Based on the obtained results, an equilibrium model was proposed and subsequently, a hard-modeling method was used to resolve the complex formation equilibria completely. Due to the presence of multiple equilibria, the resolution of such systems is very difficult. The Co-Gly system was best described by a model consisting of M(GlyH), M(Gly), M(Gly)(2), M(Gly)(2)H, and M(Gly)(3) (M = Co(2+)) with the overall stability constants determined to be 7.10 ± 0.011, 5.14 ± 0.006, 9.28 ± 0.009, 13.75 ± 0.016, and 11.10 ± 0.010, respectively. On the other hand, the system of Ni-Gly was best fitted by a model containing M(GlyH), M(Gly), M(Gly)(2), M(Gly)(3), and M(Gly)(2)(OH) (M = Ni(2+)) with overall stability constants of 10.95 ± 0.04, 6.41 ± 0.03, 11.31 ± 0.03, 15.39 ± 0.06, and 14.32 ± 0.02, respectively.     

Comparing thermal and mechanochemical decomposition of ammonium paratungstate (APT)

In this research, the possibility of mechanochemical decomposition of ammonium paratungstate (APT) has been studied, and compared with thermal decomposition method. For this purpose, APT powders were milled using a planetary ball mill up to 36 h and under air atmosphere. For thermal decomposition, APT powders were heated for 30 minutes at 300 and 450 °C in air atmosphere. X-ray diffraction (XRD), differential scanning calorimeter (DSC), and thermo gravimetric analyzer (TGA) were used to study the decomposition progress, and products. The XRD results showed that APT completely decomposed to WO₃ by thermal decomposition, while the final product of mechanochemical decomposition was WO₃ (H₂O)_0.5. According to DSC and TGA results, during thermal decomposition, ammonia and water released in four steps, and leaved WO₃. By mechanochemical decomposition crystal water and ammonia liberated from APT structure, but structural water of APT remained. In both methods, an X-ray amorphous phase was the intermediate product of APT decomposition.     

Estimating Young's modulus of zona pellucida by micropipette aspiration in combination with theoretical models of ovum

The zona pellucida (ZP) is the spherical layer that surrounds the mammalian oocyte. The physical hardness of this layer plays a crucial role in fertilization and is largely unknown because of the lack of appropriate measuring and modelling methods. The aim of this study is to measure the biomechanical properties of the ZP of human/mouse ovum and to test the hypothesis that Young''s modulus of the ZP varies with fertilization. Young''s moduli of ZP are determined before and after fertilization by using the micropipette aspiration technique, coupled with theoretical models of the oocyte as an elastic incompressible half-space (half-space model), an elastic compressible bilayer (layered model) or an elastic compressible shell (shell model). Comparison of the models shows that incorporation of the layered geometry of the ovum and the compressibility of the ZP in the layered and shell models may provide a means of more accurately characterizing ZP elasticity. Evaluation of results shows that although the results of the models are different, all confirm that the hardening of ZP will increase following fertilization. As can be seen, different choices of models and experimental parameters can affect the interpretation of experimental data and lead to differing mechanical properties.