Application of smart classification techniques to non-destructive testing of composites

Composites manufactured for applications in the automotive industry were non-destructively tested to determine damage using the following techniques: (1) Low frequency tapping. (2) High frequency (C-Scan). (3) Visual imaging. (4) Low and high temperature pulse video thermography. Various levels of impact energy were applied to the following types of composites (I) RIM: Reaction injection moulded. (II) Woven Glass. (III) GMT: Glass mat thermoplastic. Some interesting results were obtained which could be explained through analytical and numerical modelling. These results were analyzed through developments of the following algorithms: (a) A novel approach to damage detection using wavelength variation and sequence grouping software. (b) Correlation of the various NDT techniques through one mathematical equation and software. (c) The introduction of the uniformity factor concept and software to account for variations among samples quality in relation to experimental results. (d) The development of smart classification system together with standard neural network algorithms for prediction and classification. The objectives of this research were all achieved

MATHEMATICAL MODELING OF THE PROGRAMING FIELD IN A NEURAL SWITCH USING THE SEMI-INFINITE COPLANAR ELECTRODE APPROXIMATION

The design and mathematical modeling of the programing electric field in a neural switch is carried out. The specified function for the switch is to operate as a synaptic processor behaving in an adaptive manner and suitable to be used as a compact programable device with other artificial neural network hardware. Modeling of the switch is carried out by means of complex mathematical analysis employing the Schwarz–Christoffel transform. The effect of inter-electrode separation on the field strength is analyzed in two dimensions. The realized power law function of the programing field is discussed and explained.Neural, mathematical modeling, synapse, memory, information processing

Abyssal circulation in the Indian Ocean from a 1 / 12 ∘ resolution global hindcast

Abyssal pathways and volume transports in the Indian Ocean obtained from a 1 / 12 ∘ global data assimilative hindcast for the years 2004–2006 are presented. The known features of bottom water circulation such as boundary currents and inter-basin exchanges are well represented in the hindcast solution. Further, the hindcast solution reveals a basin-wide, anti-cyclonic deep circulation pattern with the main inflow located in the east, in the Perth Basin, and outflow in the west along the African continent and Madagascar. Inter-basin westward transport at 10 ∘ S across the Ninetyeast Ridge and along the Mascarene Plateau connect the inflow and outflow locations. The model develops a net bottom water inflow of 10 ± 8 Sv ( mean ± standard deviation ) across 32 ∘ S , below approximately 3500 m of which 4 ± 7 Sv are returned south across the same latitude in the deep layers between 2000 and 3500 m. Significant variability on intra-seasonal, semi-annual and annual time scales is present in the abyssal flow fields. The vertical mixing algorithm, based on resolved vertical shear, suggests enhanced diapycnal upwelling in the vicinity of the Central Indian Ridge

Very large eddy simulation of the Red Sea overflow

Mixing between overflows and ambient water masses is a critical problem of deep-water mass formation in the downwelling branch of the meridional overturning circulation of the ocean. Modeling approaches that have been tested so far rely either on algebraic parameterizations in hydrostatic ocean circulation models, or on large eddy simulations that resolve most of the mixing using nonhydrostatic models. In this study, we examine the performance of a set of turbulence closures, that have not been tested in comparison to observational data for overflows before. We employ the so-called very large eddy simulation (VLES) technique, which allows the use of k – ε models in nonhydrostatic models. This is done by applying a dynamic spatial filtering to the k – ε equations. To our knowledge, this is the first time that the VLES approach is adopted for an ocean modeling problem. The performance of k – ε and VLES models are evaluated by conducting numerical simulations of the Red Sea overflow and comparing them to observations from the Red Sea Outflow Experiment (REDSOX). The computations are constrained to one of the main channels transporting the overflow, which is narrow enough to permit the use of a two-dimensional (and nonhydrostatic) model. A large set of experiments are conducted using different closure models, Reynolds numbers and spatial resolutions. It is found that, when no turbulence closure is used, the basic structure of the overflow, consisting of a well-mixed bottom layer (BL) and entraining interfacial layer (IL), cannot be reproduced. The k – ε model leads to unrealistic thicknesses for both BL and IL, while VLES results in the most realistic reproduction of the REDSOX observations