Simulation of the Peritectic Phase Transition in Fe-C Alloys

In this work, a multi-phase cellular automaton (CA) model is extended for the quantitative simulation of peritectic phase transition. First, the effects of cooling rate/supersaturation and temperature on the peritectic transformation kinetics in Fe-C alloys are investigated by utilizing the present CA model. The CA simulations show that supersaturations in the parent phases (liquid and δ-ferrite) increase the L/γ interface growth velocity remarkably, but tinily for the δ/γ interface migration velocity. There exists a transition supersaturation for isothermal transformations, at which the growth rates of the two interfaces are equal. The transition supersaturation is found to increase with decreasing temperature. Microstructural evolution at different cooling rates during peritectic transformation is simulated using the experimental conditions. At low cooling rates, the δ/γ interface propagates at a higher velocity than the L/γ interface. At high cooling rates, however, the γ-phase grows more into the L-phase with a cellular morphology. Then, the proposed CA model is applied to simulate the microstructural evolution during peritectic reaction. It is observed that the γ-phase propagates along the L/δ interface and finally encircles the δ-phase. Meanwhile, the intervenient γ-phase grows in thickness through peritectic transformation. The CA simulations are compared reasonably well with the experimental data and analytical calculations.

A Calculation Method for the Coupling of Temperature and Concentration during Inconel 718 Alloy Solidification

Due to the temperature and concentration determine the kinetic undercooling of interface growth and nucleation undercooling inside the melt, they play an important role in the solidification microstructure of the alloy. In this paper, the effect of temperature gradient and cooling rate on the dynamic undercooling was studied and the mechanism of the concentration at the solid-liquid interface on the kinetic undercooling during the continuous cooling process was analyzed. A calculation method for the coupling of temperature and concentration during Inconel 718 alloy solidification was developed, which can solve the problem that the concentration and temperature are difficult to be calculated at the same time in the numerical calculation.

A Comparison of Interface Growth Models Applied to Rayleigh–Taylor and Richtmyer–Meshkov Instabilities

Sophisticated numerical models that contain fluid interfaces rely upon interface evolution models to approximate the transition to turbulence near interfaces, in the presence of Rayleigh–Taylor (RTI) or Richtmyer–Meshkov (RMI) instability. Semi-analytical models have been developed in recent decades to predict the interface growth from an initial state into the nonlinear regime. Two of these models are considered in this study. They are the Goncharov and the z-models. Both of these interface models have strengths and weaknesses, which are examined here. Both of them have been implemented in the xRAGE compressible flow solver, which models fluid interfaces. The flow solver provides the fluids acceleration as a body force to the interface model. The purpose of such interface model is to evolve the early times of interface position as a subgrid model within a compressible flow simulation in order to then initialize a turbulence model. In this work, the interface models are assessed and compared for their evolution of RTI and RMI. The z-model performed better than the Goncharov model for all cases that were explored.

Age Prediction using Image Dataset using Machine Learning

Gender is a central feature of our personality still. In our social life it is also an significant element. Artificial intelligence age predictions can be used in many fields, such as smart human-machine interface growth , health, cosmetics, electronic commerce etc. The prediction of people's sex and age from their facial images is an ongoing and active problem of research. The researchers suggested a number of methods to resolve this problem, but the criteria and actual performance are still inadequate. A statistical pattern recognition approach for solving this problem is proposed in this project.Convolutionary Neural Network (ConvNet / CNN), a Deep Learning algorithm, is used as an extractor of features in the proposed solution. CNN takes input images and assigns value to different aspects / objects (learnable weights and biases) of the image and can differentiate between them. ConvNet requires much less preprocessing than other classification algorithms. While the filters are hand-made in primitive methods, ConvNets can learn these filters / features with adequate training.In this research, face images of individuals have been trained with convolutionary neural networks, and age and sex with a high rate of success have been predicted. More than 20,000 images are containing age, gender and ethnicity annotations. The images cover a wide range of poses, facial expression, lighting, occlusion, and resolution.

Towards a better understanding of the oxide film growth mechanism in E110 zirconium alloy under high-temperature oxidation in steam

High-temperature oxidation of E110 (Zr-1%Nb) zirconium alloy in steam at Т = 1100°C to various degrees has been carried out. Based on the studies of morphology and microstructure of the oxide film and metal, as well as on review of previously published results, the mechanism of alloy oxidation has been proposed, which includes oxide thickening close to the oxide/metal interface, growth of the thickened areas and their conversion into nodules, growth of the nodules and crowning of the metal surface (white spots), clustering of nodules under the formed oxide, formation of a double (white on the surface) oxide film and delamination of the oxide upper layer.

ANALYTIC SELF-SIMILAR SOLUTIONS OF THE KARDAR-PARISI-ZHANG INTERFACE GROWING EQUATION WITH VARIOUS NOISE TERMS

The one-dimensional Kardar-Parisi-Zhang dynamic interface growth equation with the self-similar ansatz is analyzed. As a new feature additional analytic terms are added. From the mathematical point of view, these can be considered as various noise distribution functions. Six different cases were investigated among others Gaussian, Lorentzian, white or even pink noise. Analytic solutions are evaluated and analyzed for all cases. All results are expressible with various special functions like Kummer, Heun, Whittaker or error functions showing a very rich mathematical structure with some common general characteristics.

Solid–solid interface growth of conductive metal–organic framework nanowire arrays and their supercapacitor application

A dual-temperature zone CVD-assisted approach is developed for producing conductive porous metal catecholate MOF Cu3(HHTP)2 nanowire arrays that are grown on the interface between a solid Cu foil and a solid organic precursor.