Foetal neurodegenerative disease classification using improved deep ResNet classification based VGG-19 feature extraction network

Multimedia Tools and Applications - Neurodegenerative disease defined about death of some brain parts. This disease is the dangerous disease to cure with devastating results. In addition to the...     

Development of epoxy-cyanate ester-clay nanocomposites offering enhanced thermally stability

The preparation and characterization of blends of a series of dicyanate monomers such as 2,2′-bis(4-cyanatophenyl) propane (DCDPP), bis-4-cyanato-biphenyl (DCBP), bis-4-cyanatonaphthalene (DCN), 3,3′-bis(4-cyanatophenyl)sulphide (DCTDP), 3,3′-bis(4-cyanatophenyl)sulphone (DCDPS), and the diglycidyl ether of bisphenol A are reported. These copolymers are combined with a montmorillionite nanoclay and both epoxy-cyanate blends and epoxy-cyanate blends-nanoclay composites are all analyzed for thermal stability, thermal degradation kinetics, flame retardancy, and impact strength. The nanocomposites are further characterized by X-ray diffraction and SEM to determine morphological features, from which structure–property relationships are determined. Dispersion of the nanoclay is of paramount importance, but its inclusion serves to improve char yield and impact strength, when this is achieved. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47754.     

Multi-objective shape optimization using ant colony coupled computational fluid dynamics solver

An adaptation of a parametric ant colony optimization (ACO) to multi-objective optimization (MOO) is presented in this paper. In this algorithm (here onwards called MACO) the concept of MOO is achieved using the reference point (or goal vector) optimization strategy by applying scalarization. This method translates the multi-objective optimization problem to a single objective optimization problem. The ranking is done using ?-dominance with modified L_p metric strategy. The minimization of the maximum distance from the goal vector drives the solution close to the goal vector. A few validation test cases with multi-objectives have been demonstrated. MACO was found to out perform R-NSGA-II for the test cases considered. This algorithm was then integrated with a meshless computational fluid dynamics (CFD) solver to perform aerodynamic shape optimization of an airfoil. The algorithm was successful in reaching the optimum solutions near to the goal vector on one hand. On the other hand the algorithm converged to an optimum outside the boundary specified by the user for the control variables. These make MACO a good contender for multi-objective shape optimization problems.     

Simulation and optimization of sludge hygienization research irradiator

This paper presents an approach to optimize a computational fluid dynamics problem coupled with radiation physics for sludge hygienization research irradiator. This was implemented by mapping results of computational fluid dynamics using recurrent artificial neural network with simplified dose rate evaluation using modified Sievert integral. This methodology led to considerable reduction of computation time while maintaining enough accuracy to validate the experimental results as well as suggest an optimum placement of source pencils using reference point based multi-objective optimization.     

Meshless kinetic upwind method for compressible, viscous rotating flows

This paper presents the split-stencil least square kinetic upwind method for Navier–Stokes (SLKNS) solver using kinetic flux vector splitting (KFVS) scheme with Chapman-Enskog distribution. SLKNS solver operates on an arbitrary distribution of points and uses a novel least squares method which differs from the normal equations approach as it generates the non-symmetric cross-product matrix by selective splitting of the set of neighbours to avoid ill-conditioning. SLKNS also uses the axi-symmetric formulation of the Boltzmann equation and kinetic slip boundary condition. SLKNS is capable of capturing weak secondary flows as well as features of strong rotation characterized by steep density gradient and thin boundary layers towards the peripheral region with a rarefied central core.     

Examining the thermal degradation behaviour of a series of cyanate ester homopolymers

A series of thermally stable dicyanate monomers was prepared containing different thermally stable structural units, namely 2,2′‐bis(4‐cyanatophenyl)propane, bis‐4‐cyanato‐biphenyl, bis‐4‐cyanato naphthalene, 3,3′‐bis(4‐cyanatophenyl)sulfide and 3,3′‐bis(4‐cyanatophenyl)sulfone, was prepared and the identity of the products was confirmed by Fourier transform infrared and NMR spectral methods. The corresponding cyanate homopolymers were prepared and their properties were evaluated and compared. The composites were analysed for their thermal stability and thermal degradation kinetics. The series of homopolymers exhibit excellent thermal characteristics, e.g. relatively high glass transition temperatures of at least 215 °C, which were inversely proportional to the molecular weight between the crosslinks, high thermal decomposition temperature and high activation energies for the decomposition of cured resins. Determination of their limiting oxygen indices indicates that all the homopolymers are characterized as ‘self‐extinguishing’ materials. © 2019 Society of Chemical Industry