A new adaptation of mapping method to study mixing of multiphase flows in mixers with complex geometries

The main objective of the present work is to modify the traditional mapping method for the simulation of distributive mixing of multiphase flows in geometries involving moving parts such as, internal mixers or twin-screw extruders without a limitation on their geometrical periodicity. The periodicity condition, limits the results of traditional mapping method to tracking mapping mesh between specific discrete time intervals or distances for that geometry is repeated, hence, result is only for fixed orientation of rotors. Imaginary domain method is introduced to track mapping mesh from one state to the next free of geometrical periodicity limitations. In this work the method is introduced and its applicability and accuracy is discussed in details. A two-dimensional (2D) simulation of mixing of two Newtonian fluids with different viscosities in an intermeshing internal mixer is used as a test case study. In this example the key issues of ability to predict mixing state in details for all orientations of rotors is presented. To reduce diffusion errors of mapping method in the boundaries of the rotors, mapping mesh refinement technique that relies upon one single reference mesh is also presented.     

Spatial bound whale optimization algorithm: an efficient high-dimensional feature selection approach

Neural Computing and Applications - Selecting a subset of candidate features is one of the important steps in the data mining process. The ultimate goal of feature selection is to select an optimal...     

Hesperidin Promotes Osteogenesis and Modulates Collagen Matrix Organization and Mineralization In Vitro and In Vivo

This study evaluated the direct effect of a phytochemical, hesperidin, on pre-osteoblast cell function as well as osteogenesis and collagen matrix quality, as there is little known about hesperidin’s influence in mineralized tissue formation and regeneration. Hesperidin was added to a culture of MC3T3-E1 cells at various concentrations. Cell proliferation, viability, osteogenic gene expression and deposited collagen matrix analyses were performed. Treatment with hesperidin showed significant upregulation of osteogenic markers, particularly with lower doses. Mature and compact collagen fibrils in hesperidin-treated cultures were observed by picrosirius red staining (PSR), although a thinner matrix layer was present for the higher dose of hesperidin compared to osteogenic media alone. Fourier-transform infrared spectroscopy indicated a better mineral-to-matrix ratio and matrix distribution in cultures exposed to hesperidin and confirmed less collagen deposited with the 100-µM dose of hesperidin. In vivo, hesperidin combined with a suboptimal dose of bone morphogenetic protein 2 (BMP2) (dose unable to promote healing of a rat mandible critical-sized bone defect) in a collagenous scaffold promoted a well-controlled (not ectopic) pattern of bone formation as compared to a large dose of BMP2 (previously defined as optimal in healing the critical-sized defect, although of ectopic nature). PSR staining of newly formed bone demonstrated that hesperidin can promote maturation of bone organic matrix. Our findings show, for the first time, that hesperidin has a modulatory role in mineralized tissue formation via not only osteoblast cell differentiation but also matrix organization and matrix-to-mineral ratio and could be a potential adjunct in regenerative bone therapies.     

Gain‐scheduled filtering for linear parameter‐varying systems using inexact scheduling parameters with bounded variation rates

This paper is concerned with the problem of full‐order H₂ linear parameter‐varying filter design for continuous‐time systems with bounded rate of variations under the condition that the scheduling parameters do not exactly fit the real ones. The scheduling parameters and their derivatives are supposed to belong to polytopes with known vertices. The synthesis conditions are formulated in terms of parameter‐dependent bilinear matrix inequalities by means of parameter‐dependent Lyapunov function and introducing some extra variables for the filter design. An iterative procedure is presented to cast the bilinear matrix inequalities problem into a linear matrix inequality optimization problem. The design of robust filters for both time‐varying and time‐invariant systems can be viewed as particular cases of the proposed method. The merit of the method presented in this paper lies in two fields. The first pertains to dealing with the measurement uncertainty in a less conservative manner than available approaches in the gain‐scheduled filtering problem. The second is to provide more efficient methods than the existing ones in the literature for the robust filter design. Copyright © 2015 John Wiley & Sons, Ltd.     

Shifted robust multi-objective test problems

In 2013 Gaspar-Cunha et al. proposed a set of novel robust multi-objective benchmark functions to increase the difficulty of the current test problems and effectively mimic the characteristics of real search spaces. Despite the merits of the proposed benchmark problems, it is observed that the robust Pareto optimal fronts are located on the boundaries of the search space, which may result in the infeasibility of solutions obtained in case of perturbations along the negative side of the second parameter. This paper modifies the proposed test functions by Gaspar-Cunha et al. to mimic real problems better and allow the parameters to be fluctuated by any degree of perturbations. In fact, the robust fronts are shifted to the centre of the search space, so that any degree of uncertainties can be considered. The paper considers theoretical and experimental analysis of both set of test functions as well.     

Column and batch reactive transport experiment parameter estimation using a genetic algorithm

This paper focuses on the application of a genetic algorithm (GA) in estimating the fate and transport parameters of a reacting solute from the column and batch experiments involving a saturated porous medium. A program is developed using C++ to model the column and batch data using kinetically controlled one- or two-site sorption models including linear and/or nonlinear forms. The objective of the algorithm is to minimize the sum of squared differences between the measured and modeled solute concentration data associated with column effluent (i.e., “breakthrough curves”). The GA is capable of estimating transport and reactions parameters such as forward and reverse reaction rates and parameters of the nonlinear reaction models, from a given set of measured data. Further simulations have been performed to estimate the appropriate configurations of the GA, which assist the method in estimating the fate and transport parameters more efficiently. It is shown that a wide range of the GA parameters can lead to convergence to appropriate estimations. The results obtained from this study show that the capability of GAs to fit the column and batch experiment data is promising.     

An efficient approach for damage identification based on improved machine learning using PSO-SVM

Engineering with Computers - Structural health monitoring (SHM) and Non-destructive Damage Identification (NDI) using responses of structures under dynamic excitation have an imperative role in the...