•The laser shock peening of Rene-80 Ni-based superalloy was performed using a high-power Nd:YAG pulsed laser.•Effects of power density on microstructure characterization and fatigue behavior are ...investigated on Rene-80.•Microstructural evolution of Rene-80 Ni-based superalloy before and after LSP is assessed.
The microstructure plays a crucial role in determining the mechanical properties and performance of materials, particularly in high-strength alloys such as Rene-80. This study focuses on the microstructure characterization of Rene-80 nickel-based superalloy after undergoing Laser Shock Peening (LSP), an advanced surface treatment technique imparting beneficial residual stresses and improving fatigue life. The primary objective of this research is to investigate how varying power densities during the LSP process affect the microstructure of the Rene-80 superalloy. The power density in LSP is a critical parameter that influences the intensity of shock waves imparted onto the material’s surface, consequently impacting the microstructure. Through advanced microscopy techniques and analysis, the study explores the resulting microstructural changes, including surface roughness, dislocation density, and the presence of defects like dislocations and dislocation cells. These alterations are vital indicators of the material’s mechanical properties, such as tensile and fatigue strength. LSP samples were characterized using various techniques, including field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), and X-ray diffraction (XRD) analysis. Additionally, the mechanical performance of the samples was assessed through low-cycle fatigue tests and tensile tests, both conducted before and after LSP treatment. The optimal power density for Laser Shock Peening is determined to be 2.5 HEL. At this power density, the shock wave generated does not create a molten layer on the surface but accumulates defects, resulting in maximum compressive residual stress at the surface. LSP induces intense plastic deformation in the sample, distorting γ’ precipitates. Higher power densities lead to the formation of cross-linked sets of slip bands, highlighting defect slip as the main mechanism of plastic deformation in the LSP process. Understanding these effects is essential for optimizing the LSP process parameters to achieve desired mechanical properties and enhance the performance and longevity of components made from Rene-80 nickel-based superalloy in high-stress applications. It was found that the fatigue life of the samples increased by 500% and optimizing the effect of power density on the LSP process led to an improvement in the fatigue life of the Rene 80 samples.
•The approach optimizes the laser cladding model by considering both temperature characteristics and residual stress distribution during thermo-mechanical coupling.•Model accuracy is validated with ...experimental data, showing close agreement with melt pool characteristics and residual stresses.•Longitudinal residual stresses show a "tension first, compression later" pattern, with tensile stresses near the clad layer.•The method predicts residual stresses in titanium alloy laser cladding, offering insights to improve quality and performance.
Laser cladding is a cutting-edge technology widely used in additive manufacturing and surface modification. This process entails rapid melting and solidification driven by laser heating, which induces residual stress within the material. This study presents a data-driven approach to refine the numerical model of laser cladding, simultaneously emphasizing both the temperature characteristics and residual stress distribution within the thermomechanical coupling process. After integrating the residual stress distribution data obtained through the contour method with the molten pool morphology shaped by the thermal effects of laser cladding, a Levenberg-Marquardt optimization algorithm based finite element model updating scheme is proposed to efficiently identify the parameters of double ellipsoid heat source model, which employs parallel computing to reduce the computational time for iterations. The effectiveness of the proposed method is validated using experimental data. Moreover, this approach is adaptable, unaffected by the specimen size and shape, and can accurately predict the residual stress distribution characteristics. Therefore, it offers a robust framework for simulating the mechanisms of residual stress generation in titanium alloy laser cladding.
•A novel FEM-ANN coupling dynamic prediction method is proposed.•FEM calculations of LSP-induced residual stress agree with experiment result.•ANN predictions correlated with the dynamic prediction ...accuracy are obtained.•Laser power density plays a significant role in LSP-induced residual stress.
Laser shock peening (LSP) has been frequently used in the aerospace industry for improving the fatigue performance of the load-bearing components by introducing the beneficial compressive residual stresses into the structural materials. By taking the advantages of finite element method (FEM) and artificial neural network (ANN), the FEM-ANN coupling dynamic prediction method is proposed to evaluate the in-depth residual stresses induced by LSP of TC4 titanium alloy. The Python program-based three-dimensional parametric modellings for the repeated LSP associated with the circular-shape laser spot and the multiple LSP associated with the square-shape laser spot are carried out, respectively. The LSP parameters are randomly generated within the given ranges and are treated as the input layer of ANN model, and the in-depth residual stresses induced by LSP are regarded as the output layer. The raw data resulting from FEM calculations are employed to train, test and validate ANN model. Once the test or validation for ANN model fails, the raw data in the test set or validation set would be transferred into the training set for further training the networks. As a result, the prediction accuracy of ANN model could become increasingly higher with the increase of the raw data in the training set. The FEM-ANN coupling dynamic predictions correlated with the dynamic prediction accuracy are well consistent with the FEM calculations as well as the experimental data, indicating that the FEM-ANN coupling dynamic prediction method is feasible and effective to evaluate the LSP-induced residual stresses. It therefore provides a new way to predict the LSP-induced residual stresses with high efficiency and low cost.
A finite element–based thermomechanical modeling approach is developed in this study to provide a prediction of the mesoscale melt pool behavior and part-scale properties for AlSi10Mg alloy. On the ...mesoscale, the widely adopted Goldak heat source model is used to predict melt pool formed by laser during powder bed fusion process. This requires the determination of certain parameters as they control temperature distribution and, hence, melt pool boundaries. A systematic parametric approach is proposed to determine parameters, i.e., absorption coefficient and transient temperature evolution. The simulation results are compared in terms of morphology of melt pool with the literature results. Considering the part-scale domain, there is increasing demand for predicting geometric distortions and analyzing underlying residual stresses, which are highly influenced by the mesh size and initial temperature setup. This study aims to propose a strategy for evaluating the correlation between the mesh size and the initial temperature to provide correct residual stresses when increasing the scale of the model for efficiency. The outcomes revealed that the predicted melt pool error produced by optimal Goldak function parameters is between 5 and 12%. On the part-scale, the finite element model is less sensitive to mesh size for distortion prediction, and layer-lumping can be used to increase the speed of simulation. The effect of large time increments and layer lumping can be compensated by appropriate initial temperature value for AlSi10Mg. The study aids practitioners and researchers to establish and validate design for additive manufacturing within the scope of desired part quality metrics.
Additive manufacturing (AM) is a unique manufacturing process that disrupted completely the way which components are made, since this process is capable of producing complex parts layer after layer. ...As a matter of fact, one of its distinct technologies is metal laser beam powder bed fusion (mLB-PBF), also known as selective laser melting (SLM) or direct metal laser sintering (DMLS), which creates metallic parts with the aid of a high-energy laser beam. One of the most employed superalloys in this technology is the Inconel 718 (IN718), a precipitation-hardened alloy that is used in the marine, nuclear power plants, gas turbines, and aerospace field due to its capacity of retaining good mechanical properties at high temperatures. The research novelty of this review manuscript is the compilation of all kinds of information from the last 15 years of investigation about IN718 parts produced via mLB-PBF, namely, information related to distinct heat treatments and the influence they have in increasing mechanical properties of the manufactured components, as well as reducing residual stresses (RS) and part porosity. Throughout the review, it can be seen that the expected microstructure in the as-built state is characterized by fine columnar grains and a saturated
γ
matrix with the presence of the Laves phase and carbides. However, distinct heat treatments can be employed which lead to the dissolution of the undesired phases (Laves and carbides), the precipitation of the strengthening phases (γ’ and γ”), and the porosity decrease. Furthermore, it was also shown that heat treatments as well as optimized process parameters can be held accountable for lowering the RS of the IN718 manufactured parts. Nevertheless, there are still some problems to overcome, namely, the mechanical properties variability when subjecting IN718 powder to different process parameters. Moreover, the RS evolution under different heat treatments needs to be further investigated.
Residual stresses are inevitably generated during the welding process of steel structures, which can have a negative impact on the structure’s normal use and fatigue performance. With the continuous ...advancements in intelligent manufacturing technology and modular construction of steel structures, there is a growing need for accurate prediction of residual stresses. This paper presents a visualization procedure using Python language and ABAQUS commercial software to predict the full-field residual stress of butt welds in cast steel nodes. The procedure takes into account the geometry and welding parameters of the girth butt weld as input data and provides the post-weld residual stress field as output. Instead of using the traditional thermodynamic coupling finite element calculation method, this procedure develops a parameter function form that uniformly describes the residual stress field. A radial basis function network, trained by a genetic algorithm, is employed to establish a nonlinear relationship between the input and output data. The dataset is generated through finite element simulation, and a visualization interface is created within the ABAQUS software. Experimental results validate the speed and accuracy of the proposed method. This procedure can serve as a valuable reference for quickly determining residual stress fields and optimizing welding parameters during the construction process of steel structures.
The machining residual stress generated on the surface of the machined parts during machining has a crucial influence on the machining accuracy, fatigue strength, and corrosion resistance of the ...parts. Tool wear will aggravate the tool-work friction, and the thermal and mechanical load will change significantly, affecting the residual stress distribution. The distribution of 3D oblique cutting mechanical stress and thermal stress during tool wear is predicted by analyzing the 3D contact state of quick oblique cutting. The incremental thermal-elastic–plastic method is used for stress loading, and the 3D relaxation method is used for stress release to obtain residual stress. An analytical residual stress model considering tool wear is proposed to predict the residual stress distribution in milling, while aluminum alloy 7075-T6 is used as the workpiece in the case study. The results show that with the increase of tool wear, the residual stress of machined surface transfers from compressive stress to tensile stress, the value of sub-surface residual compressive stress increases the peak value of compressive stress moves more resounding, and the thickness of residual stress layer increases significantly. The average error between the predicted and experimental values is about 23.3%, which proves the model’s validity and provides a new idea for controlling the distribution of machining residual stress.
•Investigation of microstructure parameters on the residual stresses of ultrafine-grained sheets.•Microstructure parameters are crystallites size, dislocations density, and lattice ...strain.•Microstructure parameters have a significant effect on macro-residual stresses, and strain is the most effective parameter.•In the UFGed sheets, micro-parameters have a contribution as same as macro-parameters on the macro-residual stresses.
In this research, the influence of microstructure parameters on the residual stresses of ultrafine-grained sheets was investigated. For this purpose, the constrained groove pressing (CGP) process was carried out on the copper sheets with 3 mm thickness, and residual stresses of the CGPed sheets was measured using the contour method. Microstructure of the CGPed specimens was evaluated by the optical microscopy, micro x-ray diffraction (micro-XRD), and transmission electron microscopy (TEM) experiments. Microstructure parameters including crystallites size, dislocations density, and lattice strain were calculated using Williamson-Hall and Williamson-Smallman equations, and the calculated results were validated by the TEM images. The influence of these parameters on the residual stresses was investigated by analysis of variance (ANOVA) method, and two approaches were considered in this way. According to the results, the CGP process can create nanostructures in the CGPed sheets, and with increasing number of CGP passes, grains size, crystallites size, lattice strain, and residual stresses decrease, and density of dislocations increases. Microstructure parameters have a significant effect on the macro-residual stresses, and strain is the most effective parameter. Also, in the ultrafine-grained sheets, micro-parameters have an undeniable contribution, which is the same as that of macro-parameters on the macro-residual stresses.
The combination of technical advantages of high entropy alloys (HEAs) and manufacturing capabilities of thermal spray (TS) offer potential towards new protective coatings to address extreme ...engineering environments. In this research, equi-atomic AlCoCrFeNi HEA coatings were synthesized via atmospheric plasma spray (APS) using mechanically alloyed feedstock, and a correlation between microstructure and mechanical properties in terms of both hardness and wear were established at multiscale levels. In addition, electrochemical performance in sea water and the overall residual stress distribution in the HEA coatings were also assessed. Superimposition of scanning electron micrographs and statistically analysed heat and contour maps using nanoindentation datasets revealed deviations in localized properties within and across individual phases; which were supported by Weibull plots of individual phases. Scanning wear tests revealed superior nanowear resistance of oxide phases developed by in-flight oxidation during APS process. In comparison, the HEA phases in the coating exhibited significant localized plastic deformation. The outcome of macroscale wear testing postulated that plasma sprayed AlCoCrFeNi HEA coatings exhibited superior wear resistance at high temperature (500 °C) than at room temperature, signifying high thermal stability of the coating. Residual stress generated due to plasma spray was measured using neutron diffraction and was tensile in nature. The corrosion resistance of the coating was slightly lower than that of SS316L, however, the anodic and cathodic polarization behaviour of HEA coating were identical to that of SS316L, indicating that the AlCoCrFeNi-based HEAs have prospects as corrosion resistant materials.
•Rietveld analysis revealed increase in FCC phase fraction within coating.•Microstructure-mechanical property mapping evaluates the disparity at nano level.•HEA phase exhibited high nano wear volume loss compared to oxide phases.•Superior wear resistance at elevated temperature implied high thermal stability.•Selective corrosion on coating surface with polarization behaviour alike SS316L.
In this work is presented the analysis of the manufacturing technology of arcuate elastic elements. In the course of the work, the technological problems of the formation of out-of-plane ...microelectromechanical structures with the use of surface micromachining were studied. Internal stresses were controlled by varying the pressure of the working gas during sputtering. The use of this method allowed forming the arcuate profile of the Cr-Cu-Cr film structure.
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