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Numerical Investigation of Laser Surface Hardening of AISI 4340 Using 3D FEM Model for Thermal Analysis of Different Laser Scanning Patterns
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作者 baha tarchoun Abderrazak El Ouafi Ahmed Chebak 《Modeling and Numerical Simulation of Material Science》 2020年第3期31-54,共24页
<span style="font-family:Verdana;">Laser surface hardening is becoming one of the most successful heat treatment processes for improving wear and fatigue properties of steel parts. In this process, the... <span style="font-family:Verdana;">Laser surface hardening is becoming one of the most successful heat treatment processes for improving wear and fatigue properties of steel parts. In this process, the heating system parameters and the material properties have important effects on the achieved hardened surface characteristics. The control of these variables using predictive modeling strategies leads to the desired surface properties without following the fastidious trial and error method. However, when the dimensions of the surface to be treated are larger than the cross section of the laser beam, various laser scanning patterns can be used. Due to their effects on the hardened surface properties, the attributes of the selected scanning patterns become significant variables in the process. This paper presents numerical and experimental investigations of four scanning patterns for laser surface hardening of AISI 4340 steel. The investigations are based on exhaustive modelling and simulation efforts carried out using a 3D finite element thermal analysis and structured experimental study according to Taguchi method. The temperature distribution and the hardness profile attributes are used to evaluate the effects of heating parameters and patterns design parameters on the hardened surface characteristics. This is very useful for integrating the scanning patterns</span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">’</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> features in an efficient predictive modeling approach. A structured experimental design combined to improved statistical analysis tools </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> used</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> to</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> assess the 3D model performance. The experiments are performed on a 3 kW Nd:Yag laser system. The modeling results exhibit a great agreement between the predicted and measured values for the hardened surface characteristics. The model evaluation reveal</span></span></span><span><span><span>s </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">also its ability to provide not only accurate and robust predictions of the temperature distribution and the hardness profile as well an in-depth analysis of the effects of the process parameters.</span></span></span> 展开更多
关键词 Laser Surface Hardening 3D Thermal Analysis Finite Element Modelling AISI 4340 Steel Laser Scanning Patterns Taguchi Method ANOVA Nd:Yag Laser Source
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Experimental Investigation of Laser Surface Hardening of AISI 4340 Steel Using Different Laser Scanning Patterns 被引量:1
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作者 baha tarchoun Abderrazak El Ouafi Ahmed Chebak 《Journal of Minerals and Materials Characterization and Engineering》 2020年第2期9-26,共18页
Laser surface transformation hardening becomes one of the most modern processes used to improve fatigue and wear properties of steel surfaces. In this process, the material properties and the heating parameters are th... Laser surface transformation hardening becomes one of the most modern processes used to improve fatigue and wear properties of steel surfaces. In this process, the material properties and the heating parameters are the factors that present the most significant effects on the hardened surface attributes. The control of these factors using predictive modeling approaches to achieve desired surface properties leads to conclusive results. However, when the dimensions of the surface to be treated are larger than the cross-section of the laser beam, various laser-scanning patterns are involved. This paper presents an experimental investigation of laser surface hardening of AISI 4340 steel using different laser scanning patterns. This investigation is based on a structured experimental design using the Taguchi method and improved statistical analysis tools. Experiments are carried out using a 3 kW Nd: YAG laser source in order to evaluate the effects of the heating parameters and patterns design parameters on the physical and geometrical characteristics of the hardened surface. Laser power, scanning speed and scanning patterns (linear, sinusoidal, triangular and trochoid) are the factors used to evaluate the hardened depth and the hardened width variations and to identify the possible relationship between these factors and the hardened zone attributes. Various statistical tools such as ANOVA, correlations analysis and response surfaces are applied in order to examine the effects of the experimental factors on the hardened surface characteristics. The results reveal that the scanning patterns do not modify the nature of the laser parameters’ effects on the hardened depth and the hardened width. But they can accentuate or reduce these effects depending on the type of the considered pattern. The results show also that the sinusoidal and the triangular patterns are relevant when a maximum hardened width with an acceptable hardened depth is desired. 展开更多
关键词 LASER Surface HARDENING Process Experimental Investigation LASER Scanning PATTERNS AISI 4340 STEEL Hardness Profile Hardened Depth Hardened WIDTH Design of Experiment Analysis of Variance
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