The Ni-Al-Zr Multiphase Diffusion Simulations

Author(s):  
Bartek Wierzba ◽  
Jolanta Romanowska ◽  
Maryana Zagula-Yavorska ◽  
Janusz Markowski ◽  
Jan Sieniawski

AbstractThe generalized Darken method allows a quantitative description of diffusion mass transport in multi-phase materials. The method characterizes the diffusion zone by phase volume fractions. The results of the calculations are compared with experimental concentration’s profiles of nickel, zirconium and aluminum in zirconium doped aluminide coatings deposited on pure nickel by the PVD and CVD methods.

2016 ◽  
Vol 61 (2) ◽  
pp. 587-592 ◽  
Author(s):  
J. Romanowska ◽  
B. Wierzba ◽  
J. Markowski ◽  
M. Zagula-Yavorska ◽  
J. Sieniawski

Abstract The generalized Darken method was applied to simulate the diffusion between γ-Ni| γ’-Ni3Al and γ’-Ni3Al|β-NiAl interfaces. The results of calculations were compared with the experimental concentration’s profiles of nickel, aluminum and hafnium in aluminide and hafnium doped aluminide coatings deposited by the CVD and PVD methods on pure nickel. The method deals with the Wagner’s integral diffusion coefficients and thermodynamic data - activities of components. The experimental results agree with the simulated ones.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Wook Kim ◽  
Seong-Hoon Kang ◽  
Se-Jong Kim ◽  
Seungchul Lee

AbstractAdvanced high strength steel (AHSS) is a steel of multi-phase microstructure that is processed under several conditions to meet the current high-performance requirements from the industry. Deep neural network (DNN) has emerged as a promising tool in materials science for the task of estimating the phase volume fraction of these steels. Despite its advantages, one of its major drawbacks is its requirement of a sufficient amount of training data with correct labels to the network. This often comes as a challenge in many areas where obtaining data and labeling it is extremely labor-intensive. To overcome this challenge, an unsupervised way of learning DNN, which does not require any manual labeling, is proposed. Information maximizing generative adversarial network (InfoGAN) is used to learn the underlying probability distribution of each phase and generate realistic sample points with class labels. Then, the generated data is used for training an MLP classifier, which in turn predicts the labels for the original dataset. The result shows a mean relative error of 4.53% at most, while it can be as low as 0.73%, which implies the estimated phase fraction closely matches the true phase fraction. This presents the high feasibility of using the proposed methodology for fast and precise estimation of phase volume fraction in both industry and academia.


Author(s):  
Licheng Guo ◽  
Zhihai Wang ◽  
Naotake Noda

This study aimed to develop a method to build a ‘bridge’ between the macro fracture mechanics model and stochastic micromechanics-based properties so that the macro fracture mechanics model can be expanded to the fracture mechanics problem of functionally graded materials (FGMs) with stochastic mechanical properties. An analytical fracture mechanics model is developed to predict the stress intensity factors (SIFs) in FGMs with stochastic uncertainties in phase volume fractions. Considering the stochastic description of the phase volume fractions, a micromechanics-based method is developed to derive the explicit probabilistic characteristics of the effective properties of the FGMs so that the stochastic mechanical properties can be combined with the macro fracture mechanics model. A thought for choosing the samples efficiently is proposed so that the stable probabilistic characteristic of SIFs can be obtained with a very small sample size. The probability density function of SIFs can be determined by developing a histogram from the generated samples. The present method may provide a thought to establish an analytical model for the crack problems of FGMs with stochastic properties.


Author(s):  
Lalit M. Pant ◽  
Sushanta K. Mitra ◽  
Marc Secanell

Porous transport layers are an integral part of polymer electrolyte fuel cells (PEMFC). In order to optimize the catalyst layer performance and reduce catalyst consumption, a thorough understanding of mass transport through porous media is necessary. Currently, there is a lack of experimental measurements of effective mass transport properties of porous transport layers. Further, mass transport theories in the literature, such as the binary friction model by Kerkhof [1], have not been extensively validated for porous media. In the present study, mass transport measurements have been performed on the porous media of a PEMFC, namely a GDL and an MPL. The experimental setup described by Pant et al. [2] has been used. The setup uses the diffusion bridge/counter-diffusion technique for the mass transport measurements. The experimental setup has the advantage that it can be used to perform studies for pure diffusion and convection-diffusion mass transport. The setup also facilitates measurement of permeability of porous media, which can then be used in convection-diffusion studies. Preliminary permeability measurements of GDL and MPL from the setup show good agreement with values available in literature. In preliminary experimentation, the conventional diffusivity correlations like Bruggeman equation have been found to overpredict the diffusivities.


Author(s):  
Azam Thatte

A novel rotary liquid piston multi-phase pump that transfers pressure energy from high pressure motive fluid stream to a low pressure process fluid stream within a high speed multi-ducted rotor is presented. The multiple ducts in the rotor act like cylinders of a rotating liquid piston pump with the liquid-to-liquid interface between the working fluid and the motive fluid acting like a piston. This novel pump has promise to solve challenges typically seen in multi-phase pumping and in trans-critical and supercritical CO2 compression systems, na m el y, risks due to phase change, two-phase compression inefficiencies, rotordynamic instabilities and sealing challenges etc. In this design the entrance and exit flow angles impart momentum to the rotor and the rotor achieves a self-sustained rotation without external power. The rotational speed dictates the volumetric efficiency, travel distance of the liquid piston within the ducts and the zero-mixing effectiveness of the design. This creates a very efficient pumping/compression system with just one moving part and three stationary parts, which can handle very high pressures and temperatures typical of supercritical CO2 turbomachines and also mitigates some of the rotordynamic stability challenges typically seen in MW-scale sCO2 turbomachinery designs. Ability of the pressure exchanger to dynamically maintain micro-scale gaps between rotor and stators through intelligent pressure balancing features relaxes the need to have complex dynamic seals. In this paper, use of this novel pump for multi-phase CO2 pumping application is explored through an advanced 3D multi-scale multi-phase flow model. The model captures the phase transport, compressibility, advection & diffusion of one phase into the other using a hybrid Eulerian-Lagrangian algorithm. Using these advanced models, performance curves are developed and results for key performance parameters including phase mixing, compressibility losses, effect of inlet gas volume fractions etc. are presented. A detailed transient evolution of two-phase fluid piston interface in the rotor ducts that captures acoustic wave propagation and reflection is presented. This new technology has promise to solve challenges typically seen in multi-phase pumping/ compression, transcritical and supercritical CO2 compression systems or in applications where the traditional pumps face steep challenges like phase change, erosive/ corrosive fluids, particle laden flows with high particle loading or flows with high gas volume fractions. This technology renders itself useful to several applications including supercritical CO2 turbomachines, waste pressure recovery, applications in oil & gas extraction and carbon sequestration etc.


2006 ◽  
Vol 251-252 ◽  
pp. 123-126 ◽  
Author(s):  
Yuriy S. Nechaev

Urgent open questions and their solution ways are considered of the thermodynamic stimuli and mechanisms of the enhanced Fickian diffusion mass-transport providing the unusual structuralphase transformations in metallic materials undergoing the intensive cold deformation, those can not be described in the framework of the conventional phase diagrams.


2017 ◽  
Vol 9 (12) ◽  
pp. 168781401773766 ◽  
Author(s):  
Xiaobing Liu ◽  
Quanyou Hu ◽  
Guangtai Shi ◽  
Yongzhong Zeng ◽  
Huiyan Wang

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