TEM Studies of High Temperature Corrosion Behaviour of TiAl Intermetallics with Surface Modifications

The oxidation/sulphidation behaviour of a Ti‐46.7Al‐1.9W‐0.5Si alloy with a TiAl₃ diffusion coating was studied in an environment of H₂/H₂S/H₂O at 850^oC. The kinetic results demonstrate that the TiAl₃ coating significantly increased the high temperature corrosion resistance of Ti‐46.7Al‐1.9W‐0.5Si. The SEM, EDX, XRD and TEM analysis reveals that the formation of an Al₂O₃ scale on the surface of the TiAl₃‐coated sample was responsible for the enhancement of the corroison resistance. The Ti‐46.7Al‐1.9W‐0.5Si alloy was also modified by Nb ion implantation. The Nb ion implanted and as received sampels were subjected to cyclic oxidation in an open air at 800^oC. The Nb ion implantation not only increased the oxidation resistance but also substantially improved the adhesion of scale to the substrate.     

On optimal sequential prediction for general processes

This paper considers several aspects of the sequential prediction problem for unbounded, nonstationary processes under pth power loss /spl lscr//sub p/(u,v)=|u-v|/sup p/, 1相似文献   

Small–Capacity Modular Units. Experience in Startup and Management

A series of small–capacity units has recently been constructed in regions of oil field development and crude oil and gas condensate production to satisfy the requirements for such petroleum products as naphtha, diesel fuel, kerosene, and boiler fuel and to reduce costs for delivery of these products. There are almost no data in the technical literature, particularly in periodicals, on the construction and operation of small–capacity units. We attempt to generalize the experience of Orgeneftekhimzavody Trust in this area. We hope that this experience will be useful to specialists in the development and management of small–capacity plants.     

Using the magneto-optical Kerr effect to study magnetization processes in two-dimensional magnonic crystals based on YIG thin films

The magneto-optical Kerr effect for red (628 nm) and green (532 nm) light is used to study magnetization processes in 2D magnonic crystals obtained by etching pits with the diameter D ≈ 32 μm to a depth of t ≤ 2 μm in a 16.1-μm-thick film of yttrium iron garnet (YIG). Hysteresis loops obtained in the case of the inplane crystal magnetization at 628 nm are characterized by lower saturation fields H _s and higher remanent magnetizations than those obtained at 532 nm, a result that is attributed to different absorption coefficients of the YIG film at these wavelengths. This difference between the magnetization curves reflects the fact that the magnonic-crystal surface probed with the green light makes a greater contribution to the magneto-optical Kerr effect. Therefore, the green light is more sensitive to the demagnetizing fields, which govern magnetization processes in the magnonic crystals.     

Synthesis of Rice Processing Plants. I. Development of Simplified Models

This article, the first of three articles on the synthesis of rice processing plants, focuses on the development of simplified mathematical models necessary for use in optimizing rice processing plants. The second concentrates on the optimal synthesis of a rice plant and the third on the sensitivity of the optimization to uncertainty in model parameters. Existing models for rice processing unit operations are not suitable for flowsheet optimization and new models need to be developed to overcome numerical difficulties that occur in optimization applications, specifically in mixed integer nonlinear programming (MINLP) applications. Simplified models of the drying, cooling, and tempering units are developed. In addition head rice yield models, used as a quality indicator, energy consumption, and economic models were also developed. Naturally, the new models exhibit some mismatch with respect to the existing models from which they were developed. However, a sensitivity analysis, presented in Part III, has shown that the optimal flowsheet structure was not sensitive to a lack of fit between the simplified and complex models. The simplified models were found adequate to be appropriate for use at the synthesis stage.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

A VQ-based blind image restoration algorithm

Learning-based algorithms for image restoration and blind image restoration are proposed. Such algorithms deviate from the traditional approaches in this area, by utilizing priors that are learned from similar images. Original images and their degraded versions by the known degradation operator (restoration problem) are utilized for designing the VQ codebooks. The codevectors are designed using the blurred images. For each such vector, the high frequency information obtained from the original images is also available. During restoration, the high frequency information of a given degraded image is estimated from its low frequency information based on the codebooks. For the blind restoration problem, a number of codebooks are designed corresponding to various versions of the blurring function. Given a noisy and blurred image, one of the codebooks is chosen based on a similarity measure, therefore providing the identification of the blur. To make the restoration process computationally efficient, the principal component analysis (PCA) and VQ-nearest neighbor approaches are utilized. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.