Search Results (79)

The aim of this study was to analyse in detail the effect of varying the parameters of the Johnson–Cook (JC) material model on the results of a numerical simulation of the orthogonal turning process of the Ti6Al4V titanium alloy. The first step involved an experimental study, including the recording of cutting force components and temperature, as well as the measurement of chip geometry, which was used to validate the FEM simulation. This was followed by a sensitivity analysis of the JC model with respect to five parameters, namely A, B, C, m, and n, each modified independently by ±20%. The effects of these changes on cutting forces, cutting zone temperature, stresses, and chip geometry were evaluated. The results showed that parameters A, B, and m had the greatest influence on the physical quantities analysed, while C and n are of secondary importance. The analysis highlighted the need for precise calibration of the JC model parameters, especially when modelling machining processes involving difficult-to-machine materials. The results provided practical guidance for optimising the selection of constitutive parameters in machining simulations. Full article

This study investigates the effects of Laser Shock Peening (LSP) on residual stress distribution and surface deformation using a Finite Element Method (FEM) model. LSP is a surface treatment process that generates compressive residual stress by applying high-energy laser pulses over nanosecond timescales. The study aims to analyze the impact of key parameters, specifically laser spot overlap rate and power density, on the induced residual stress and surface deformation. A Design of Experiment (DOE) approach was used to systematically vary these parameters. These simulations were performed using the ANSYS Explicit Dynamics FEM with a Johnson–Cook material model to capture the nonlinear constitutive behavior. The research analyzes the distribution of residual stress and surface deformation caused by LSP. Increasing laser spot overlap and power density leads to higher compressive residual stress and surface deformation, revealing two distinct behavioral outcomes: either deep compressive stress with minimal deformation or a transition from compressive to tensile stress followed by significant surface deformation and a subsequent return to compressive stress. The results demonstrate strong agreement with existing experimental data presented in the literature. This study contributes novel insights into the interaction between LSP parameters and their effects on material properties, with implications for understanding LSP techniques in practical applications. The triangular pulse model and dual-overlap analysis offer a novel simulation strategy for optimizing LSP parameters in stainless steel. Full article

The development and validation of constitutive models for high-temperature deformation are critical for bridging microstructure evolution with macroscopic mechanical behavior in materials. In this study, we systematically analyzed the hot deformation behavior of Fe-Mn-Cr-based alloys, compared the modeling processes of physical, phenomenological, and data-driven approaches in detail, and optimized their structural and predictive properties. First, the advantages, disadvantages, and applicability of three traditional models, namely the physical Arrhenius model, the phenomenological Johnson–Cook model, and the artificial neural network (ANN) model, are compared for flow stress prediction. Subsequently, traditional mathematical derivations and numerical optimization methods are evaluated. The parameters and architecture of the ANN model are then systematically optimized using optimization algorithms to enhance training efficiency and prediction accuracy. Finally, sensitivity analysis integrated with Bayesian posterior probability density functions enables the calibration of physical model parameters and uncertainty quantification. The results demonstrate that the ANN with optimized parameters and architecture achieves superior prediction accuracy (R² = 0.9985, AARE = 3.01%) compared to traditional methods. Bayesian inference-based quantification of parameter uncertainty significantly enhances the reliability and interpretability of constitutive model parameters. This study not only reveals the strain–temperature coupling effects in the hot deformation behavior of Fe-Mn-Cr-based alloys but also provides systematic methodological support for constitutive modeling of high-performance alloys and a theoretical foundation for material processing technology design. Full article

In the context of Al-Kharj city, which is steadily advancing as an industrial and manufacturing hub within Saudi Arabia, this study has significant relevance. The city’s focus on metal forming, fabrication, and materials engineering makes it crucial to optimize processes such as hot deformation of metallic alloys for various sectors, including aerospace, automotive, oil and gas, and structural applications. By assessing and comparing phenomenological and physical material models for nickel, aluminum, titanium, and iron-based alloys, this study aids Al-Kharj industries in advancing their process simulation and predictive performance. Thus, this study aims to evaluate the proposed phenomenological and physically based constitutive models for Ni-, Al-, Ti-, and Fe-based alloys to enhance the accuracy of high-temperature deformation simulations. Phenomenological models investigated include the Johnson–Cook (JC), Fields and Backofen (FB), and Khan–Huang–Liang (KHL) formulations, while the Zerilli–Armstrong (ZA) model represents the physical category. Additionally, various modifications to these models are explored. Model parameters are calibrated using the Levenberg–Marquardt algorithm to minimize mean square error. Performance is assessed through key statistical metrics, including the correlation coefficient (R), average absolute relative error (AARE), and root mean square error (RMSE). Of the 32 models analyzed, a modified version of the JC model delivers the highest accuracy across all alloys. Furthermore, four other modifications, one each for the JC and ZA models and two for the FB model, exhibit superior predictive capability for specific alloys. This makes this study valuable not just academically, but also as a practical resource to boost Al-Kharj’s industrial competitiveness and innovation capacity. Full article

Owing to potential inaccuracies in the current stress–strain curve used for constructing the Johnson–Cook (JC) constitutive model of amorphous alloys, the parameters of the JC constitutive equation were derived using Oxley’s cutting theory, negative chamfer theoretical mechanics modelling, and the particle swarm optimisation algorithm. A two-dimensional finite element cutting model was subsequently established using AdvantEdge software. The optimised constitutive model was used to simulate the main cutting force (Fz) and the backward force (Fy), which resulted in average errors of 12.461% and 9.161%, respectively. Based on the optimised constitutive model in which the JC constitutive equation parameters were derived using Oxley’s method, the variations in temperature, strain rate, and stress in the deformation zone during the cutting process were analysed. The chip microstructures revealed the transformation of lamellar chips into serrated chips resulting from a combination of plastic deformation, adiabatic shear, and shear slip. Full article

Fused deposition modelling (FDM) technology provides a flexible and cost-effective solution for the manufacture of polymer components, enabling the precise design of structures and the incorporation of a variety of composite materials. Its development is confirmed by numerous studies on fibre reinforcements (e.g., GFRP and CF) and thermosetting resin modifications, resulting in improved impact strength and fracture toughness and increased thermal stability of products. The final mechanical properties are significantly influenced by processing parameters (e.g., fill density, layer height, and printing speed) and internal geometry (e.g., lattice structures), which can be further optimised by numerical analyses using constitutive models such as the Johnson–Cook model. The focus of the study presented here is on the fabrication of composites from FDM dies filled with F8 polyurethane resin. Filaments, including PETG carbon and PETG, were tested for potential applications with the resin. A static compression test, supported by numerical analysis using the Johnson–Cook model, was carried out to identify key mechanical characteristics and to predict the material’s behaviour under different loading conditions. The results indicate that these structures exhibit numerous potential delamination planes and voids between filament paths, leading to relatively low maximum stress values (σ_m ≈ 2.5–3 MPa). However, the impregnation with polyurethane resin significantly enhances these properties by bonding the layers and filling the pores, resulting in a more homogeneous and stronger composite. Additionally, numerical simulations effectively captured key aspects of structural behaviour, identifying critical stress concentration areas, particularly along the side walls and in regions forming triangular stress zones. These findings provide valuable insights into the potential of resin-filled FDM structures in engineering applications, demonstrating their improved performance over purely printed samples. Full article

To acquire Johnson–Cook (J-C) constitutive parameters that accurately depict the mechanical behavior of powder liner under conditions of high pressure, elevated temperature, and large deformation, as well as Holmquist–Johnson–Cook (HJC) constitutive parameters that precisely describe the dynamic damage of hard rock and make them suitable for numerical simulations for hard rock perforation, the present study introduces a constitutive parameter inversion method based on finite element simulation. Firstly, based on the experiments of perforating steel targets and underground perforating hard rock targets, a dynamic simulation of the perforating process of a shaped charge perforating target was carried out using ANSYS/LS-DYNA, and the influence law of each constitutive parameter on perforating depth and perforating aperture was systematically analyzed. Subsequently, the key parameters of the J-C constitutive model for powder liner and the HJC constitutive model for hard rock were optimized and determined using a response surface method, multi-genetic algorithm, and experimental data. A numerical simulation of the perforating process was finally conducted using the retrieved constitutive parameters of powder liner and hard rock, which were then compared with the experimental results. The results demonstrated that the discrepancy between the experimental and simulated data was within 5%, indicating that the constitutive parameters obtained through this inversion method could more reliably reflect the mechanical behavior of the powder mold and hard rock used in this study during perforation. Full article

Friction has a significant impact on chip formation, so modeling it accurately is crucial in numerical cutting simulations. However, there is still controversy regarding the application scope and effectiveness of various friction models. A two-dimensional orthogonal cutting thermomechanical coupled finite element model is established. Critical strain values, recrystallization temperature, and recrystallization flow stress are introduced, and a power-law-modified softening coefficient is used to modify the standard Johnson–Cook constitutive model to simulate material mechanical properties. Zorev’s friction model, velocity-dependent friction model, and temperature-dependent friction model are separately employed to describe the friction behavior between the tool and workpiece. The contact and friction characteristics between the workpiece and tool, material damage, and temperature field are evaluated. Predicted cutting forces are compared and analyzed with experimental values. The friction coefficient can adjust the contact length between the tool and chip, the high-temperature range on the tool surface, and the fluctuation of temperature throughout the entire cutting process. The friction coefficient is more sensitive to sliding velocity, and the temperature distribution is more sensitive to the friction model than to different working conditions. Whether by modifying the friction coefficient or maximum friction shear stress, and regardless of whether adding parameters affected by velocity or temperature changes the fluctuation range, period, and local peaks of the cutting force prediction curve, improving the accuracy of predictions within certain working condition ranges to some extent. However, the overall trend of error fluctuations obtained from these friction models is similar, and the accuracy of predictions from these friction models tends to become more inaccurate with increasing cutting thickness. Full article

Titanium alloys, such as Ti-6Al-4V, are crucial for aeroengine structural integrity, especially during high-energy events like turbine blade-out scenarios. However, accurately predicting their behavior under such conditions requires the precise calibration of constitutive models. This study presents a comprehensive sensitivity analysis of the Johnson-Cook plasticity and progressive damage model parameters for Ti-6Al-4V in blade containment simulations. Using finite element models, key plasticity parameters (yield strength (A), strain-hardening constant (B), strain-rate sensitivity (C), thermal softening coefficient (m), and strain-hardening exponent (n)) and damage-related parameters (d1, d2, d3, d4, and d5) were systematically varied by ±5% to assess their influence on stress distribution, plastic deformation, and damage indices. The results indicate that the thermal softening coefficient (m) and the strain rate hardening coefficient (C) exhibit the most significant influence on the predicted casing damage, highlighting the importance of accurately characterizing these parameters. Variations in yield strength (A) and strain hardening exponent (n) also notably affect stress distribution and plastic deformation. While the damage evolution parameters (d1–d5) influence the overall damage progression, their individual sensitivities vary, with d1 and d4 showing more pronounced effects compared to others. These findings provide crucial guidance for calibrating the Johnson-Cook model to enhance aeroengine structural integrity assessments. Full article

Titanium alloys are widely used in the manufacture of gas turbines’ compressor blades. Elucidating their mechanical behavior and strength under damaged conditions is the key to evaluating the equipment’s reliability. However, the conventional Johnson-Cook (J-C) constitutive model has limitations in describing the dynamic response of titanium alloy materials under the impact of a high strain rate. In order to solve this problem, the mechanical behavior of a TC4 titanium alloy under high strain rate and different temperature conditions was analyzed by combining experiments and numerical simulations. In this study, the parameters of the J-C model were analyzed in detail, and an improved J-C constitutive model is proposed, based on the new mechanism of the strain rate strengthening effect and the temperature softening effect, which improves the accuracy of the description of strain sensitivity and temperature dependence. Finally, the VUMAT subroutine of ABAQUS software was used for numerical simulation, and the predictive ability of the improved model was verified. The simulation results showed that the maximum prediction error of the traditional J-C model was 23.6%, while the maximum error of the improved model was reduced to 5.6%. This indicates that the improved J-C constitutive model can more accurately predict the mechanical response of a titanium alloy under an impact load and provides a theoretical basis for the study of the mechanical properties of titanium alloy blades under subsequent conditions of foreign object damage. Full article

Numerical simulations of the cutting process play a key role in manufacturing and cost optimization. Inherent in finite element analysis (FEA) simulations is the correct description of material behavior during machining. For this purpose, various material models are used to describe the behavior of the material in the range of high deformation, high temperature values, and high strain rates. Very often the Johnson–Cook (JC) material model is used for this purpose; however, the correct determination of the material constants of this model is a key aspect. Therefore, this paper presents a procedure for determining the material constants of the JC model using an analytical method based on normalized tensile and compression testing of the material for different strain rates over a wide temperature range. After determining the material constants, the authors conducted numerical simulations of the orthogonal turning of Ti6Al4V titanium alloy using the obtained constants. Validation of the obtained results with those obtained in experimental studies was also carried out. The outcomes demonstrated that the difference between FEM simulation and experimental tests did not exceed 0.02 mm (14%) in the case of chip thickness,. Much smaller differences were obtained for the temperature in the cutting zone, where the maximum difference was about 45 °C (4%). Comparing the components of the cutting force, we found that, in the case of the main cutting force, in most cases, the differences did not exceed 70 N (8%). After the verification of the obtained results, it was also found that the determined material constants of the Johnson–Cook model can be successfully used in FEM modeling of the cutting process of Ti6Al4V titanium alloy for the adopted range of values of technological parameters. Full article

Hydrogen permeation resistance in the welded region of 06Cr18Ni11Ti steel is relatively weak due to surface defects, which need high integrity surface machining. The parameters of the welding material for 06Cr18Ni11Ti steel are currently unavailable, which causes some inconvenience for simulation studies. To fill the lack of 06Cr18Ni11Ti steel weld material parameters in the relevant literature at the present stage, the quasi-static tensile test at different strain rates and notch specimen tensile tests were conducted in this paper and determined the Johnson–Cook (J-C) constitutive model parameters and Johnson–Cook failure model parameters. Subsequently, a multi-grain grinding simulation model was built based on W-M fractal dimension theory by using the determined material parameters. The influence of processing parameters on grinding heat was analyzed. Grinding experiments were conducted to analyze the influence of processing parameters on grinding heat and grinding force. By comparing the simulation and experimental results, it is revealed that the average error is 9.37%, indicating relatively small discrepancy. It is demonstrated that the grinding simulation model built in this paper could efficiently simulate the grinding process, and the determined weld material parameters of 06Cr18Ni11Ti steel have been verified to possess high accuracy and reliability. Full article

The chip compression ratio is the most important characteristic of various machining processes with chip generation. This characteristic enables the determination of kinetic and other energy loads on the tool and the machined material. This provides an overall evaluation of the machining process and the possibility of its subsequent optimization. This paper presents the results of determining this cutting characteristic by experimental method, analytical calculation, and numerical modeling. For the analytical calculation of the chip compression ratio, an analytical cutting model developed based on the variational principle of the minimum potential energy was used. A finite element model of orthogonal cutting was used for the numerical simulation of the above process characteristic. Experimentally, the chip compression ratio was determined by the ratio of the chip thickness to the cutting depth (undeformed cutting thickness). The chip thickness was determined by direct measurement using chip slices obtained during the cutting process. The Johnson–Cook constitutive equation was used as the machined material model and the Coulomb model was used as the friction model. The generalized parameters’ determination of the constitutive equation was performed through a DOE (Design of Experiment) sensitivity analysis. The variation range of these parameters was chosen based on the analysis of the effect of individual parameters of the constitutive equation on the chip compression ratio value. The largest deviations between the experimental and analytically calculated values of the chip compression ratio did not exceed 21%. At the same time, the largest deviations of simulated values of the indicated cutting characteristic and its experimental values did not exceed 20%. When comparing the experimental values of the chip compression ratio with the corresponding calculated and simulated values, the deviations were within 22%. Full article

A precise Johnson-Cook (J–C) constitutive model is the foundation for precise calculation of finite-element simulation. In order to obtain the J–C constitutive model accurately for a new cast and forged alloy GH4198, an inverse identification of J–C constitutive model was proposed based on a genetic–particle swarm algorithm. Firstly, a quasi-static tensile test at different strain rates was conducted to determine the initial yield strength A, strain hardening coefficient B, and work hardening exponent n for the material’s J–C model. Secondly, a new method for orthogonal cutting model was constructed based on the unequal division shear theory and considering the influence of tool edge radius. In order to obtain the strain-rate strengthening coefficient C and thermal softening coefficient m, an orthogonal cutting experiment was conducted. Finally, in order to validate the precision of the constitutive model, an orthogonal cutting thermo-mechanical coupling simulation model was established. Meanwhile, the sensitivity of J–C constitutive model parameters on simulation results was analyzed. The results indicate that the parameter m significantly affects chip morphology, and that the parameter C has a notable impact on the cutting force. This study addressed the issue of missing constitutive parameters for GH4198 and provided a theoretical reference for the optimization and identification of constitutive models for other aerospace materials. Full article

Metals manufactured by selective laser melting (SLM) with different directions exhibit different mechanical properties. This study conducted dynamic and static mechanical tests using a universal testing machine and split-Hopkinson bar (SHPB). The mechanical properties of 18Ni300 with 0° and 90° build directions manufactured by SLM were compared, and the micro-structure properties of the two build directions were analysed by metallographic tests. The Johnson–Cook (J-C) constitutive model was fitted according to the experimental results, and the obtained constitutive parameters were verified by numerical simulations. The results revealed that the constitutive model could predict the mechanical properties of 18Ni300 in a dynamic state. The build direction had little influence on the mechanical properties in a static state, but there was a significant difference in the dynamic state. The difference in the dynamic compressive yield strength of the 18Ni300 material manufactured by SLM with two build directions was 9.8%. The SLM process can be improved to produce 18Ni300 with uniform mechanical properties by studying the reasons for this difference. Full article