Prediction Of Residual Stresses Research Articles

Residual stress prediction in shot blasted cobalt–chromium biomedical cast components

ASTM F75 implants distort due to residual stress released after finishing machining operations, causing implants to fail quality requirements. Previous work has shown that a shot blasting cleaning process could be the source of this distortion. Finite element analysis (FEA) is conducted to predict stress and Almen strip arc heights for experimental comparison. 2D and 3D single impact models and 3D multiple impact models are created. 3D multiple impact models with plastically deforming shot are shown to accurately predict the stress state and distortion. For shot with hardness similar to the implants, distortion creating stress magnitudes are induced, with the greatest fluctuations in stress coming from shot velocity. The depth of the predicted compressive stress layer ranges from 0.23 to 0.6 mm.

Numerical Prediction and Experimental Investigation of Temperature, Residual Stress and Mechanical Properties of Dissimilar Friction-Stir Welded AA5083 and AZ31 Alloys

Numerical Prediction and Experimental Investigation of Temperature, Residual Stress and Mechanical Properties of Dissimilar Friction-Stir Welded AA5083 and AZ31 Alloys

Comparative Study of Residual Stress Prediction Methods in Additive Manufacturing Processes

The additive manufacturing (AM) of products involves various processes, such as raising the temperature of a work-piece (part) and substrate to the melting point and subsequent solidification, using a movable source of heat. The work piece is subjected to repeated cycles of heating and cooling. The main objective of this work was to present an overview of the various methods used for prediction of the residual stresses and how their contributions can be used to improve current additive manufacturing methods. These novel methods of manufacturing have several merits, compared to conventional methods. Some of these merits include the lower costs, higher precision and accuracy of manufacturing, faster processing time and more eco-friendly approaches to processes involved.

Numerical and experimental investigation on thermo-mechanically induced residual stress in high-speed milling of Ti-6Al-4V alloy

The machining-induced residual stress, which significantly influences the machined part's service performance and geometrical stability, is considered an essential indicator of surface integrity. The intermittent cutting process and the consequences of thermo-mechanical and microstructural phenomenon accompanying white layer formation, which directly influences residual stress distribution of the workpiece, make the milling process different from turning process. Therefore, a comprehensive understanding of residual stress distribution mechanism within the milled part is essential. The current study presents a numerical and experimental approach for in-depth residual stress prediction in the milled part of Ti-6Al-4V alloy. First, a simplified milling model was proposed based on J-C constitutive model and J-C failure criterion. Secondly, the proposed model was verified regarding cutting forces, cutting temperature, and chip morphological characteristics. An excellent correlation was obtained between the simulated and experimental results for given analogous milling conditions. Thirdly, the workpiece was allowed to cool down to room temperature for stress-strain relaxation. Finally, the effect of the white layer on residual stress distribution and the relationship between nano-hardness and residual stress were analyzed and discussed. It was found that residual stress was tensile when no white layer was detected on the machined surface, and the nature of residual stress becomes compressive with the formation of a white layer. This study can provide an in-depth understanding of residual stress distribution within the milled part and the fatigue life of the component's services performance.

Finite element analysis, prediction, and optimization of residual stresses in multi-pass arc welding with experimental evaluation

Prediction and reduction of unwanted tensile Residual Stress of welded stainless-steel plates is presented in this paper. Validated finite element analysis and Artificial Neural Network (ANN) is employed to simulate and mathematically model the process, respectively. Taguchi design of experiments tool is utilized to generate input data for finite element analyses and also to choose the most accurate ANN structures. RSs are minimized using three methods: Taguchi suggestion, Comprehensive factorial search, and Particle Swarm Optimization, whose accuracy and response pace increases and decreases respectively in this order. Furthermore, adding and removing extra weld lines was proposed to reduce unwanted residual stresses by up to 50%. Finally, the shapes and amounts of results are experimentally verified using contour method and proposed novel application of roughness testing. Micro-grain structures of the welded samples were also investigated, and RSs were discussed considering metallography images.

Depth-resolved X-ray residual stress analysis in PVD (Ti, Cr) N hard coatings

Abstract Physical vapour deposition (PVD) of thin hard coatings on TiN basis is usually performed at rather low temperatures (T D < 500 °C) far from thermal equilibrium, which leads to high intrinsic residual stresses in the growing film. In contrast to the extrinsic thermal residual stresses which can easily be estimated from the difference of the coefficients of thermal expansion between the substrate and the coating, a theoretical prediction of the intrinsic residual stresses is difficult, because their amount as well as their distribution within the film depend in a very complex way on the deposition kinetics. By the example of strongly fibre-textured PVD (Ti, Cr)N coatings which have been prepared under defined variation of the deposition parameters in order to adjust the residual stress distribution within the coatings, the paper compares different X-ray diffraction techniques with respect to their applicability for detecting residual stresses which are non-uniform over the coating thickness.

Numerical prediction and experimental investigation of residual stresses in sequential milling of GH4169 considering initial stress effect

Residual stresses affect the service life and cause the deformation of machined parts. Therefore, the study on the development of residual stresses during machining operation is very important. For this, analytical and numerical models have been developed to predict the residual stresses for single-step machining operation. However, the parts are usually machined with a serial of production processes. A numerical model for predicting residual stress in sequential side milling GH4169, considering initial stress, was proposed in this research. The initial residual stress distribution due to previous-step milling was considered in the proposed model. It was assumed that this initial residual stress value changed with the depth from the machined surface, while the residual stress on the identical horizontal plane was assumed with uniform distribution. The proposed numerical simulation model could predict the stress value of the machined surface, the stress value of the compression valley, and the residual stress distribution in the depth direction beneath the machined surface with high accuracy. Experimental investigations of sequential side milling GH4169 were conducted and the generated residual stresses were measured. The distribution trend and influence rule of residual stress between two sequential milling steps were analyzed. The residual stress distribution beneath the surface showed a spoon-shaped pattern. The thickness of the residual stress influence layer (RSIL) after the current milling step was affected by the depth of cut and the RSIL thickness of the previous milling step. The numerical model could predict the thickness of RSIL and optimize the depth of cut in sequential side milling.

Prediction of residual stress induced by high-frequency mechanical impact treatment

Prediction of residual stress induced by high-frequency mechanical impact treatment

Coupled Modeling Approach for Laser Shock Peening of AA2198-T3: From Plasma and Shock Wave Simulation to Residual Stress Prediction

Laser shock peening (LSP) is a surface modification technique to improve the mechanical properties of metals and alloys, where physical phenomena are difficult to investigate, due to short time scales and extreme physical values. In this regard, simulations can significantly contribute to understand the underlying physics. In this paper, a coupled simulation approach for LSP is presented. A global model of laser–matter–plasma interaction is applied to determine the plasma pressure, which is used as surface loading in finite element (FE) simulations in order to predict residual stress (RS) profiles in the target material. The coupled model is applied to the LSP of AA2198-T3 with water confinement, 3×3mm2 square focus and 20 ns laser pulse duration. This investigation considers the variation in laser pulse energy (3 J and 5 J) and different protective coatings (none, aluminum and steel foil). A sensitivity analysis is conducted to evaluate the impact of parameter inaccuracies of the global model on the resulting RS. Adjustment of the global model to different laser pulse energies and coating materials allows us to compute the temporal pressure distributions to predict RS with FE simulations, which are in good agreement with the measurements.

Assessment of the cartesian and layered tetrahedral mesh strategies in the thermomechanical simulation of the selective laser melting process

Selective Laser Melting (SLM) is an Additive Manufacturing (AM) process aimed for the fabrication of complex metallic parts. Due to the inherent to the process rapid thermal cycles and the developed high temperature gradients, residual stresses are formed which result to part distortion and may lead to preliminary failure during its building. Current thermomechanical modelling methods of the SLM process aim at the prediction of residual stress and strain fields in an efficient manner. Meshing schemes such as uniform or adaptive cartesian and layered tetrahedral meshing have been utilized in thermomechanical modelling but their accuracy has not been evaluated yet. The present study quantitively assess the meshing strategies in the simulation of SLM process with the focus placed on the characteristics of layered tetrahedral meshing. Although it is shown both meshing strategies lead to accurate results for a relatively small element size, layered tetrahedral meshing strategy can achieve convergence with relative coarse mesh and better discretization of curvature regions.

Efficient thermomechanical modelling of Laser Powder Bed Fusion additive manufacturing process with emphasis on parts residual stress fields

<abstract> <p>Laser Powder Bed Fusion (LPBF) process is one of the advanced Additive Manufacturing (AM) processes, which is employed for the fabrication of complex metallic components. One of the major drawbacks of the LPBF is the development of residual stresses due to the high temperature gradients developed during the process thermal cycles. Reliable models for the prediction of residual strain and stress at part scale are required to support the LPBF process optimization. Due to the computational cost of the LPBF simulation, the current modelling methodology utilizes assumptions to make feasible the prediction of residual stresses at parts or component level. To this scope, a thermomechanical modelling approach for the simulation of LPBF process is presented with focus to residual stress and strain prediction. The modelling efficiency of the proposed approach was tested on a series on cases for which experimental data were available. The good comparison between the predicted and experimental data validated the modelling method. The efficiency of the thermomechanical modelling method is demonstrated by the reduced computational time required.</p> </abstract>

Empirical modeling of residual stress profiles in Ti6Al4V after face-milling

Titanium represents a large part of critical structural and engine components on aircrafts. Surface residual stresses generated during machining are highly relevant regarding the fatigue behavior of these components. Nevertheless, the complex nature of the residual stress generation process prevents considering them during part and machining process design phases. In this work, an empirical model based on an exponential decay cosine function for surface residual stresses prediction is presented. Modeling data was obtained by X-ray diffraction from face-milled surfaces on Ti6Al4V. The model was validated with further experimental data, showing its capability to provide a powerful residual stress prediction tool.

Studies on Residual Stress and Distortion Prediction of Lattice Structures in Powder Bed Fusion of Alloy 625

Studies on Residual Stress and Distortion Prediction of Lattice Structures in Powder Bed Fusion of Alloy 625

Analysis of chip segmentation frequencies in turning Ti-6Al-4V for the prediction of residual stresses

Machining-induced residual stresses depend on the process parameters and are strongly influenced by the tool wear. The chip segmentation frequency in turning of Ti-6Al-4V can be obtained by processing signals of acoustic emission (AE) caused by the cutting process and used to estimate the tool wear condition. In this work, chip segmentation frequencies during longitudinal turning of Ti-6Al-4V are measured using AE sensors and correlated with the process parameters, abrasive tool wear and residual stresses. The resulting models allow for predition of significant characteristics in the residual stress distribution based on in-process measured chip segmentation frequencies.

Development of a process signature for electrical discharge machining

Electrical discharge machining (EDM) is a versatile unconventional machining process allowing high precision manufacturing. Due to the thermal main active principle, the process-induced heat affected rim zone always needs to be particularly considered regarding its characteristics as the resulting surface integrity has to fulfill the needed functional properties for advanced applications. Today, no deterministic model is available especially for the residual stress prediction. As consequence, current process design is based on experience and heuristic optimization. The paper therefore mechanistically links the material modification and the process-induced load. Inversion of the according process signature component finally allows model-based process design.

3D Numerical modelling of turning-induced residual stresses in 316L stainless steel

This paper lies in the framework of turning-induced residual stress prediction by presenting an up-dated method based on a two-scale approach. Previous works aimed at building a 3D hybrid method consisting in modelling the turning consequences through equivalent thermo-mechanical loadings combining a finite element model with experimental tests. The new proposed global hybrid strategy keeps the same concept but has the advantage to define the thermo-mechanical shapes more accurately thanks to local 2D orthogonal cutting models. After carefully detailing each step of the numerical method, a validation case study concerning a longitudinal turning operation on a 316L austenitic stainless steel is proposed. By comparing numerical results with experimental residual stresses coming from X-Ray diffraction, the new numerical method shows its superiority to predict, within few hours, much more accurately the residual stress state induced by a real longitudinal turning operation.

Analytical modeling of residual stress in end-milling with minimum quantity lubrication

Milling with minimum quantity lubrication (MQL) is now a commonly used machining technique in industry. This paper proposed an analytical model for residual stress prediction in milling with MQL based on chip formation orthogonal cutting model and boundary lubrication effect. The effect of lubrication is considered to the change of friction coefficients and the heat loss at the flank surface, which would further affect the prediction of the cutting force and temperature. The proposed model is validated with experimental data done to AZ61A magnesium alloy and obtained a reasonable validation result. The predictive results show at the case investigated, neither feed per tooth nor depth of cut has a significant influence to the general trend of residual stress, where at the surface the residual stress is highly tensile and come to compressive at deeper depth. However, the application of MQL is shown to be able to significantly reduce the average magnitude of the residual stress.

Prediction of residual stresses in high-strength S690 cold-formed square hollow sections using integrated numerical simulations

In general, residual stresses are induced in structural members during various fabrication processes, such as welding, bending, press-braking, folding, flame cutting and punching. The presence of those residual stresses in cold-formed square hollow sections (CFSHS) primarily caused by i) transverse bending (or cold-forming), and ii) longitudinal welding, is widely considered to have modified both initial stress and strain conditions of these steel members significantly. Hence, these residual stresses are widely considered to have significant adverse effects onto the structural performance of these CFSHS under various actions.In order to examine and quantify both magnitudes and distributions of these residual stresses in S690 CFSHS, an investigation is undertaken to measure residual stresses due to transverse bending and longitudinal welding. Moreover, an approach of integrated numerical simulations is adopted in which a total of three co-ordinated finite element models are established together with various element types and block data transfers to generate compatible meshes for the following three analyses: i) two-dimensional plane-strain bending analyses with large plastic deformations and springback, ii) three-dimensional heat transfer analyses for transient temperature distributions under a heat source, and iii) three-dimensional thermomechanical analyses for welding-induced residual stresses.The predicted results of these three analyses have been carefully calibrated against various experimental data, such as surface temperatures during welding, and residual stresses and strains after welding. Good comparisons between the measured and the predicted data of these S690 CFSHS are demonstrated. The complete residual stress distributions within typical S690 CFSHS due to transverse bending and longitudinal welding are illustrated in three-dimensional plots while simplified residual stress patterns of these sections with specific values and parameters are also provided for subsequent advanced structural analyses and design.The proposed modelling technique for transverse bending and longitudinal welding with compatible meshes of two-dimensional and three-dimensional models with various element types and block data transfers is demonstrated to be highly effective. The technique is readily applicable to simulate residual stresses of all fabricated sections manufactured with transverse bending and longitudinal welding, and, thus, the simulated residual stresses can be employed in subsequent structural analyses of all fabricated members.

Process modeling and characterization of thermoset composites for residual stress prediction

A computational process modeling framework is presented to predict performance-altering residual stress generation at the microscale. A comprehensive material characterization effort is carried out as a function of the resin temperature and curing state, resulting in a novel material database. For a prescribed cure cycle, in-situ elastic modulus evolution, chemical and thermal strains, and random fiber distribution are shown to significantly influence residual stress generation. The results also show that a full process modeling analysis that includes the complete cure cycle (instead of the standard approach of just considering post-processing cool-down) is necessary to accurately predict manufacturing-induced residual stresses.

Predicting part deformation based on deformation force data using Physics-informed Latent Variable Model

Part deformation prediction and control is a crucial issue for obtaining tight dimensional accuracy so as to ensure product quality with high performance, and deformation prediction is the fundamental of the deformation control. However, existing machining deformation prediction methods are based on the prediction or measurement of residual stress and suffering from two challenges: (i) the measurement accuracy of residual stress field is limited by physical principle and (ii) low prediction in accuracy. In order to address these issues, this paper presents a method for predicting part machining deformation based on deformation force using the proposed Physics-informed Latent Variable Model involved physics knowledge. Deformation force is introduced to represent the inner unbalanced residual stress state of the workpiece, and it is a much easier and more accurate signal compared with residual stress. Machining deformation is predicted by fusing the data-driven method and the prior knowledge of deformation mechanical relationship by taking advantage of the latent variable. The proposed method was verified both in simulation and actual machining environment, and accurate machining deformation prediction has been achieved. The proposed method can be readily extended to the prediction problems involved with difficult-to-measure physical quantities.