NEURAL NETWORK ANALYSIS FOR DEPOSITION OF NICKEL-ALUMINIDE COATINGS ON STEEL BY PLASMA SPRAYING
Nickel-aluminides are used in thermal spray applications mostly as bond-coat materials, where their function is two-fold: to minimize the thermo-mechanical stresses at the substrate-coating interface arising out of thermal expansion mismatch of the metal substrate and ceramic top layer and secondly to promote coating adhesion. This paper describes the deposition of nickel aluminide coatings on mild steel substrates. A computational technique (ANN analysis) is used to predict the rate of coating deposition under various operational conditions. Prediction of deposition efficiency is significant as it gives an idea about the effectiveness of the spraying technique as well as about the coatability of the material under investigation. This technique involves database training to predict property parameter evolutions in process having large number of interdependent variables such as in the case of plasma spray coating deposition. This paper presents the database construction, implementation protocol and also the set of predicted results related to the deposition efficiency of nickel-aluminide coating. It is seen that the deposition rate depends largely on the plasma arc current, arc voltage etc. The neural network analysis gives an oversight on the parameter inter-dependencies and of the effect of the individual process variable on the efficiency of coating deposition.
Plasma-Spray Coating: Principles and Applications
I. Scope and Introduction Coatings in the Industrial Environment Surface Coating Techniques Brief History of Thermal Spraying Synergistic Nature of Coatings Applications of Thermally Sprayed Coatings II. Principles of Thermal Spraying Characterization of Flame versus Plasma Spraying Concept of Energy Transfer Processes Unique Features of the Plasma Spray Process III. The First Energy Transfer Process: Electron-Gas Interaction The Plasma State Plasma Generation Design of Plasmatrons Plasma Diagnostics: Temperature, Enthalpy, and Velocity Measurements IV. The Second Energy Transfer Process: Plasma-Particle Interaction Injection of Powders Feed Material Characteristics Momentum Transfer Heat Transfer Particle Diagnostics: Velocity, Temperature, and Number Densities V. The Third Energy Transfer Process: Particle-Substrate Interaction Basic Considerations Estimation of Particle Number Density Momentum Transfer from Particles to Substrate Heat Transfer from Particles to Substrate Coating Diagnostics: Microstructure, Porosity, Adhesion, and Residual Stresses VI. Modeling and Numerical Simulation Plasma Properties Plasma-Particle Interactions Plasma-Substrate Interactions VII. Solutions to Industrial Problems (1): Structural Coatings Carbide Coatings Nitride Coatings Oxide Coatings Metallic Coatings Diamond Coatings VIII. Solutions to Industrial Problems (2): Functional Coatings Thermal and Chemical Barrier Coatings Conducting and Superconducting Coatings Dielectric Coatings Electro- and Photocatalytic Coatings IX. Solution to Medical Problems: Bioceramic Coatings Essential Properties of Bioconductive Coatings Structure and Crystal Chemistry of Hydroxyapatite Melting, Decomposition, and Solidification of Hydroxyapatite Bioinert Bond Coats In Vitro and In Vivo Performance of Coatings X. Quality Control and Assurance Procedures XI. Design of Novel Coatings XII. Future Developments and Outlook Appendices
On grain boundaries in nickel-rich Ni3Al
Etude par microscopie electronique a transmission et diffraction electronique des joints de grains apres recuit dans l'alliage Ni 3 Al contenant ou non 0,35% at. de bore. Observation dans l'alliage non dope d'une phase desordonnee (jusqu'a 20 nm de large) le long de certains joints de grains. En presence de bore, cette phase couvre tous les joints