Prediction of the hardness profile of an AISI 4340 steel cylinder heat-treated by laser - 3D and artificial neural networks modelling and experimental validation

2017 ◽  
Vol 31 (2) ◽  
pp. 615-623 ◽  
Author(s):  
Mahdi Hadhri ◽  
Abderazzak El Ouafi ◽  
Noureddine Barka
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Experimental Validation ◽  
Hardness Profile ◽  
Steel Cylinder ◽  
Aisi 4340 Steel ◽  
4340 Steel ◽  
Heat Treated ◽  
Artificial Neural ◽  
Aisi 4340

scholarly journals The use of classical methods and neural networks in deformation studies of hydrotechnical objects

2020 ◽  
Vol 12 (1) ◽  
pp. 718-725
Author(s):  
Maria Mrówczyńska ◽  
Jacek Sztubecki ◽  
Małgorzata Sztubecka ◽  
Izabela Skrzypczak
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Cylinder Surface ◽  
Building Structures ◽  
Steel Cylinder ◽  
Factors Affecting ◽  
Initial Stage ◽  
Artificial Neural ◽  
Set Of Points

Abstract Objects’ measurements often boil down to the determination of changes due to external factors affecting on their structure. The estimation of changes in a tested object, in addition to proper measuring equipment, requires the use of appropriate measuring methods and experimental data result processing methods. This study presents a statement of results of geometrical measurements of a steel cylinder that constitutes the main structural component of the historical weir Czersko Polskie in Bydgoszcz. In the initial stage, the estimation of reliable changes taking place in the cylinder structure involved the selection of measuring points essential for mapping its geometry. Due to the continuous operation of the weir, the points covered only about one-third of the cylinder area. The set of points allowed us to determine the position of the cylinder axis as well as skews and deformations of the cylinder surface. In the next stage, the use of methods based on artificial neural networks allowed us to predict the changes in the tested object. Artificial neural networks have proved to be useful in determining displacements of building structures, particularly hydro-technical objects. The above-mentioned methods supplement classical measurements that create the opportunity for carrying out additional analyses of changes in a spatial position of such structures. The purpose of the tests is to confirm the suitability of artificial neural networks for predicting displacements of building structures, particularly hydro-technical objects.

Artificial Neural Networks Approach for Hardness Prediction of Copper Cold Spray Laser Heat Treated Coatings

2022 ◽  
Author(s):  
Maryam Razavipour ◽  
Jean-Gabriel Legoux ◽  
Dominique Poirier ◽  
Bruno Guerreiro ◽  
Jason D. Giallonardo ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Cold Spray ◽  
Laser Heat ◽  
Heat Treated ◽  
Hardness Prediction ◽  
Artificial Neural

Polarization of Strained AISI 4340 Steel in Oxygenated NaCl Solutions

CORROSION ◽  
1966 ◽  
Vol 22 (8) ◽  
pp. 229-237 ◽  
Author(s):  
S. M. TOY
Keyword(s):  
Tensile Load ◽  
Corrosion Current ◽  
Cell System ◽  
Cathodic Polarization Curve ◽  
Aisi 4340 Steel ◽  
Sodium Chloride Solutions ◽  
4340 Steel ◽  
Heat Treated ◽  
Heat Treated Condition ◽  
Aisi 4340

Abstract Electrode reactions involved in the stress corrosion of AISI 4340 steel in sodium chloride solutions were studied by pulse galvanostatic and potentiostatic experiments. The redox cell system involves two principal cathodic reactions and one anodic reaction. These electrochemical reactions are affected by the application of stress, by change in pH, by oxygen content and the heat-treated condition of the materials. The effect of stress is to shift the cathodic polarization curve in an electropositive direction with increasing tensile load. It is equivalent to cathodic control for the conditions investigated and is described by the electrochemical interpretation, based on the coupling of the redox branches which produce the largest corrosion current.

Plasma Nitriding of Hard Chromium Electroplated Low Alloy AISI 4340 Steel in Pure Nitrogen Gas Atmosphere

2020 ◽  
Vol 65 ◽  
pp. 135-144
Author(s):  
Soheib Mokhtara ◽  
Mosbah Zidani ◽  
Mohamed Mounis Alim ◽  
Said Mechachti
Keyword(s):  
Plasma Nitriding ◽  
Morphological Properties ◽  
Nanoindentation Test ◽  
Hardness Profile ◽  
Nitrogen Gas ◽  
Pure Nitrogen ◽  
Aisi 4340 Steel ◽  
Hard Chromium ◽  
4340 Steel ◽  
Aisi 4340

Duplex treatments are surface modification techniques used to enhance the surface properties of steels. In this study, hard chromium electroplated AISI 4340 steel was plasma nitrided in pure nitrogen gas at 600°C for 90 min. The structural and morphological properties were analysed by an X-ray diffractometer and a scanning electron microscope (SEM), respectively. The hardness profile was obtained by a multicycle nanoindentation test and the tribological properties by a ball-on-disk test at room temperature. The results showed that the duplex layer was composed mainly of Cr2N and it had a rough surface morphology with a network of micro-cracks. The highest values of hardness were registered in the nitrogen diffusion layer beneath the outer porous thin layer. The friction coefficient and the specific wear rate after plasma nitriding were reduced by 3 and 5 factors, respectively.

Analysis of the Mechanical Behavior of AISI 4340 Steel Cylindrical Specimens Heat Treated with Fiber Laser

2020 ◽  
Vol 55 ◽  
pp. 41-56
Author(s):  
Rachid Fakir ◽  
Noureddine Barka ◽  
Jean Brousseau ◽  
Gabriel Caron-Guillemette
Keyword(s):  
Mechanical Behavior ◽  
Fiber Laser ◽  
Aisi 4340 Steel ◽  
4340 Steel ◽  
Heat Treated ◽  
Aisi 4340
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