Flow Stress Research Articles

Normalization of hot deformation parameters for activation energy analysis in metallic alloys

Abstract Depending on melting point of a given alloy, the temperature range for
hot deformation of alloys varies widely. Consequently, the apparent activation energy
of hot deformation, Q, is greatly influenced by the temperature range as well as strain
rate applied during hot deformation. The purpose of this investigation is to normalize
hot deformation parameters – temperature and strain rate – to study their effects on
activation energy. Seventy published hot-deformation data sets were used to investigate
the effects of normalized hot-deformation variables on Arrhenius-type constitutive
model parameters. Flow stress, strain rate, and temperature from sample datasets
were normalized to the range [0, 1] and fitted with an Arrhenius-type model. The
results showed that, for normalized parameters, the activation energy has exponential
relationships with a partial derivative of flow stress with strain rate and temperature.

Insights into Machining Techniques for Additively Manufactured Ti6Al4V Alloy: A Comprehensive Review

Investigation into the post-processing machinability of Ti6Al4V alloy is increasingly crucial in the manufacturing industry, particularly in the machining of additively manufactured (AM) Ti6Al4V alloy to ensure effective machining parameters. This review article summarizes various AM techniques and machining processes for Ti6Al4V alloy. It focuses on powder-based fusion AM techniques such as electron beam melting (EBM), selected laser melting (SLM), and direct metal deposition (DMD). The review addresses key aspects of machining Ti6Al4V alloy, including machining parameters, residual stress effects, hardness, microstructural changes, and surface defects introduced during the additive manufacturing (AM) process. Additionally, it covers the qualification process for machined components and the optimization of cutting parameters. It also examines the application of finite element analysis (FEA) in post-processing methods for Ti6Al4V alloy. The review reveals a scarcity of articles addressing the significance of post-processing methods and the qualification process for machined parts of Ti6Al4V alloy fabricated using such AM techniques. Consequently, this article focuses on the AM-based techniques for Ti6Al4V alloy parts to evaluate and understand the performance of the Johnson–Cook (J–C) model in predicting flow stress and cutting forces during machining of the alloy.

Mechanical properties of (Ni, Fe)Cr2O4 polycrystal spinels studied by molecular dynamics simulations.

The elastic moduli and mechanical properties at the onset of crack in nanocrystalline and nanoporous (Ni, Fe)Cr2O4 compounds with a spinel structure are investigated by molecular dynamics simulations. The polycrystalline structures generated contain nanograins from 2.5 to 30nm in diameter. These structures are representative of the internal corrosion layer in nickel-based alloys. These simulations enabled us to establish the evolution of elastic moduli as a function of the composition, porosity, and grain size of the polycrystals. From this evolution, the initial database for the elastic properties of corrosion layers based on von Bertalanffy growth functions was determined. The onset of crack in polycrystals is also investigated via uniaxial tensile and shear deformation. Under shear deformation, flow stress as a function of grain size follows normal and inverse Hall-Petch regimes. The regime change occurs for grain sizes around 10nm. For grain sizes under this threshold, shear banding involving collective translation and rotation of nanograins dominates the plastic deformation. For grain sizes greater than 10nm, phase transition inside grains from a spinel to a post-spinel-like structure is observed as well. In that case, phase transition dominates the plastic deformation. Under uniaxial tensile deformation, intergranular decohesion occurs. The general law as a function of grain size for toughness, which is the material's capacity to absorb elastic and plastic energy prior to failure, is also established.

A thermodynamic based constitutive model considering the mutual influence of multiple physical fields

In multiple physical fields, the mutual influence among these fields can significantly impact material elastoplasticity. This paper proposes a thermodynamic-based constitutive model that incorporates the mutual influence of multiple physical fields. Rather than treating physical field characteristics as adjustable “parameters” affecting material coefficients, the proposed model employs a thermodynamic dissipation potential derived from the Onsager reciprocity relations, accounting for thermodynamic forces coupling. This dissipation potential ensures that the thermodynamic flow in the stress field is influenced by both stress field and other physical fields thermodynamic forces, which describes the plastic flow under multiple physical fields, while preserving thermodynamic duality. The paper begins with the formulation of a generalized thermodynamic model applicable to diverse materials and types of coupled fields, which is then degraded to a specific model for AA5182-O AlMg alloy under the influence of temperature and strain rate fields coupling. Given the universal applicability of the generalized model, such degradation provides a structured approach framework for developing thermodynamics-based constitutive models. For different materials encountered in practical engineering, new thermodynamic forces can be introduced to describe their unique mechanical properties while preserving the overarching thermodynamics-based model framework, thereby facilitating model scalability. The paper concludes with a validation example, showing that within the Portevin-Le Chatelie (PLC) regime, the plastic flow stress of AA5182-O AlMg alloy decreases with increasing strain rate at low temperatures but increases at high temperatures. The accurate simulation of these distinct strain rate effects crucially relies on integrating the mutual influence of temperature field and strain rate field.

Microstructure-based simulation of constitutive behaviors in friction stir additive manufacturing

The Complex reheating phenomenon during friction stir additive manufacturing (FSAM) has a significant impact on the microstructural evolution. This, in turn, affects its mechanical properties. A flow stress model including the precipitate, solid solution and dislocation density evolution was proposed to reveal the relationship between the microstructure and constitutive behavior in FSAM of Al-Mg-Si alloys. The microstructure and mechanical properties of single-layer and multi-layer FSAM were investigated using experimental and numerical simulation methods. The results revealed that during the first reheating process, the precipitates exhibited dissolution and coarsening behavior in the heating stage. In the third reheating process, precipitates were generated during the heating stage because of the lower temperature. The multiple reheating process in FSAM promoted the generation of precipitates in the stirring zone. This phenomenon increased the yield strength from 183.46 MPa to 189.95 MPa. Meanwhile, the precipitate nucleation and growth during reheating process depleted the concentrations of Si and Mg in the matrix. A comparison of the stress-strain curves before and after the reheating process, revealed that the reheating process reduces the net flow stress in the plastic deformation stage. A decrease in the concentration of solid solution elements caused a decrease in the statistically stored dislocation density, and thereby, decreased the net flow stress.

Research on predicting the thermocompression deformation behavior of Mg-Li matrix composite using machine learning and traditional techniques

Artificial intelligence and machine learning (ML) technologies have emerged as powerful tools for analyzing the thermal compression deformation behavior of metal matrix composites, offering significant potential to optimize their plastic deformation processing techniques. In this study, the Al3La/LAZ532 composite based on in-situ self-reaction technology was successfully prepared by adding La2O3 particles. Then, the thermal compression flow behavior of the as-cast composite was comparatively researched using a traditional Arrhenius model and advanced machine learning methods (Linear Regression, AdaBoost, Random Forest, and XGBoost). The flow stresses were predicted under various thermal operating conditions, and the performance of all models was assessed using root mean square error (RMSE), coefficient of determination (R2) and mean absolute error (MAE). Analysis shows that the Random Forest model outperforms traditional models and other ML methods in predictive accuracy, achieving an R2 of 0.97, an MAE of 5.8, and an RMSE of 7.07. Additionally, the stable hot working zone for the composite at 300 °C and a strain rate of 0.001∼0.01 s⁻1 can be identified by combining the microscopic structure with the macroscopic hot working map. This zone is characterized by a uniformly distributed, fine-grained structure with high levels of dynamic recrystallization (DRX). The texture with the <0001> axis of the grains aligned parallel to the compression direction (CD) is formed in the thermally deformed microstructure, and the DRX mechanism is discontinuous dynamic recrystallization (DDRX).

Hot deformation behavior and process parameters optimization of GH4738 nickel-based superalloy

The GH4738 nickel-based superalloy exhibits exceptional overall performance at high temperatures. However, its high deformation resistance, narrow hot working window, and complex microstructural evolution pose significant challenges to plastic deformation of the alloy. Hot compression experiments were conducted on the GH4738 nickel-based superalloy using a Gleeble 3800-GTC thermal–mechanical physical simulation system. The hot deformation behavior of the alloy was systematically investigated across deformation temperatures ranging from 950 to 1150 °C and strain rates from 0.01 to 10 s⁻1. The analysis of the true stress–strain curves revealed the effect of deformation parameters on the flow stress of the alloy. The flow stress was highly sensitive to both strain rate and deformation temperature, increasing with higher strain rates or lower deformation temperatures. Based on the experimental data, a high-precision peak stress prediction model and an Arrhenius constitutive model considering strain compensation were established. In addition, processing maps for the alloy were constructed based on the dynamic materials model (DMM) and Prasad's instability criterion. Coupled with microstructural observations and validation, the flow instability of the alloy was manifested as flow localization and adiabatic shear bands (ASBs), while the deformation mechanism in the safe region was characterized by discontinuous dynamic recrystallization (DDRX). Ultimately, the optimal hot working process windows for the alloy were determined to be 1010–1075 °C/0.01–1 s−1 and 1075–1150 °C/0.03–1 s−1.

Inverse design of short-range order arrangement via neural network

Short-range order (SRO) plays a critical role in the mechanical behavior of metallic alloys. The arrangement of atoms at short ranges significantly impacts how the material responds to external forces. Nevertheless, the mechanics of these phenomena remain poorly understood. The identification of SRO in experiments is constrained by the low resolution of intensity distribution and the limitations associated with the direct observation of atomic arrangements in the lattice within the SRO domains. On the other hand, modeling the mechanical properties of short-range-ordered alloys is challenged by computationally expensive density functional theory (DFT)-based Monte Carlo (MC) simulations required to achieve the SRO structure dictated by energy minimization. This study aims to replace these expensive simulations with a trained machine learning (ML) model that yields accurate energy values for a given atomic structure. Further, we train an inverse model to determine the atomic configuration corresponding to the given SRO parameter. We propose a data-driven approach to map out the SRO directly to the atomic arrangements, combining ab initio calculations and a Neural Network (NN) model. We perform DFT-based MC simulations for Ni-V alloys in a wide range of solute compositions. Then, forward and inverse NN models are trained to map the SRO parameters into atomic arrangements or vice-versa. We predict the critical resolved shear stress (CRSS) for slip for all the studied configurations encompassing random and SRO structures and discuss the effect of SRO on the flow stress. The proposed ML methodology provides atomic arrangements from target order parameters with high accuracy, thereby eliminating the need for expensive simulations, and it advances the understanding of SRO at the atomistic scale.

The isolated effect of yield stress in viscoplastic turbulent flow

Turbulent flows of viscoplastic fluids are present in several industrial and natural applications. The effects of yield stress on this problem have always been studied as a part of a larger physical context, because real viscoplastic materials have many properties that cannot be easily isolated. Direct numerical simulations have recently emerged as a viable tool for investigating non-Newtonian fluid flow in turbulent regimes. In the present work, we solve the turbulent flow of an ideal Bingham fluid, focusing on the isolated effect of yield stress. A numerical scheme for viscoplastic flows was implemented based on the lattice Boltzmann method. An outstanding characteristic of this scheme is the possibility of representing infinite viscosity by setting the relaxation frequency to zero, enabling the representation of the Bingham constitutive equation without artifacts, and producing a more accurate representation of the yield surfaces. In the turbulent channel flow simulations, the friction Reynolds number was fixed at 180, while the Bingham number varied from 0 (Newtonian) to 0.15. It is shown that unyielded portions of material travel along with the flow near the centerline. These unyielded spots do not disappear quickly, but rather have a significant lifetime. Another interesting outcome is that the yield stress increases the turbulence anisotropy, by lowering the spanwise and normal velocity fluctuations, while the streamwise component becomes higher. Reynolds stresses and budgets of turbulent kinetic energy have been analyzed regarding the increased bulk velocities that were found by increasing the yield stress.

Wake characteristics of near-wall submerged bluff bodies with varying streamwise length

This study aims to investigate the effect of streamwise length on the wake characteristics of submerged sharp-edged bluff bodies in the presence of an underbody gap using large eddy simulation. To this end, three bodies with identical width (W) and height (h), but varying only in their streamwise lengths (L) were employed resulting in streamwise elongation ratios of L/h = 1, 2, and 3, respectively. The underbody gap between the bottom face of the body and the wall was fixed at 0.14 h for all cases. A fully developed turbulent boundary layer with a thickness of 3.6 h was used as the approaching flow. It was noted that the mean flow and turbulent stresses were significantly affected by the streamwise length. Premultiplied frequency spectra of the velocity fluctuations were utilized to examine the fluctuating properties of the wake. A single dominant vortex shedding frequency was observed for L/h = 1 and 3, whereas dual mode vortex shedding was noted for L/h = 2. The latter case exhibited an intermittent reattachment on the top surface of the body. The fluid structures evaluated using the λ2 criterion, indicated that they were strongly influenced by L/h. Interestingly, even with the presence of a gap, a weak horseshoe vortex which occurred intermittently was captured close to the bed for the three cases.

The interplay of plasticity and elasticity in elastoviscoplastic flows in wavy channels

Elastoviscoplastic (EVP) fluids, which exhibit both solid-like and liquid-like behaviors depending on the applied stress, are critical in industrial processes involving complex geometries such as porous media and wavy channels. In this study, we investigate how flow characteristics and channel design affect EVP fluid flow through a wavy channel, using numerical simulations supported by microfluidic experiments. Our results reveal that elasticity significantly influences flow dynamics, reducing pressure drops and expanding unyielded regions. Notably, we find that even minimal elasticity can shift the flow from steady to time-dependent regimes, a transition less pronounced in viscoelastic fluids. Additionally, we show that the development of stagnation regions can be prevented when using a modified EVP fluid with enhanced elasticity, thus providing a full global yielding of the material. This study elucidates the role of elasticity in modifying flow patterns and stress distribution within EVP fluids, offering insights into the optimization of industrial applications, such as the displacement of yield stress fluids in enhanced oil recovery, gas extraction, cementing, and other processes where flow efficiency is critical.

Evaluation of fatigue behavior of a casting aluminum knuckle considering influences of inhomogeneous microstructure

Until now the fatigue behavior of casting aluminum components is usually evaluated in the safety analysis without considering the inhomogeneity of local properties. It can result in an underestimation of damage risk or an oversizing of the components. The purpose of the work is to quantify and to predict the influence of the inhomogeneity of microstructure and the corresponding local properties on the overall behavior of the selected casting aluminum knuckle under cyclic loading. Since no shrinkage pores are observed in the knuckle produced by the counter pressure casting process, influences of porosity on fatigue property are not taken into account in this study. Tensile specimens are extracted from different positions in the knuckle and tested under quasistatic and cyclic loading. The dependences of the flow stress, the fracture strain, and the S-N curve on position for specimen extraction are evaluated. Metallographic investigations are performed to reveal the relations between microstructure and the mentioned properties. A relationship between the S-N curves and the secondary dendrite arm spacing (SDAS) is derived from the experimental results. The corresponding parameters of the new fatigue damage model are determined and used to simulate the specimens and component tests. The distribution of SDAS in the component is determined by casting simulations and transferred to the FE-model for the fatigue analysis. The standard fatigue tests on knuckles are performed and the damage behavior is analyzed in view of the influence of microstructure. The simulations of the knuckle fatigue tests are performed with SDAS-dependent material parameters. The prediction of the fatigue behavior of the knuckles agrees with the experimental results well.

Research on hot deformation behavior and microstructure characterization of the NiTi alloy fabricated by wire arc additive manufacturing

This study investigates the hot deformation behavior and microstructural evolution of wire arc additive manufactured (WAAMed) NiTi alloy. Hot deformation tests were conducted within a temperature range of 750–900 °C and a strain rate range of 0.01–5 s−1, achieving a height reduction of up to 50%. The Strain-Compensated Arrhenius-Type (SCAT) model and deformation processing maps were developed. The microstructures of compression specimens at strain rates of 0.01 s−1 and temperatures of 750–900 °C were characterized. The results demonstrate that the flow stress of WAAMed NiTi alloys increases with increasing strain rate and decreases with increasing deformation temperature. The calculated values from the SCAT model align closely with the experimental values, indicating a reliable analysis with high prediction accuracy. Flow instability region expands as the degree of deformation increases, and the optimal processing windows for the studied alloy are concentrated within the range of 800–900 °C and 0.01–0.05 s−1. In the deformed WAAMed NiTi alloys, the proportion of low-angle grain boundaries is around 70% and the recrystallized grain fraction remains below 15%. This is attributed to the predominance of dynamic recovery behavior in the softening mechanism. Discontinuous dynamic recrystallization and continuous dynamic recrystallization as auxiliary softening mechanisms are also involved in the softening of NiTi alloys, leading to a steady state of flow behavior.

A study on hot deformation behaviors and microstructures of 10 vol% SiCP/Al-Cu-Mg-Ag composite prepared by spray co-deposition and extrusion

Isothermal compression test is used to investigate the hot deformation behavior of spray co-deposited and extruded 10 vol% SiCP/Al-Cu-Mg-Ag composite. In this study, an accurate strain-compensated model based on Arrhenius constitutive equation is constructed with the corresponding R value of 0.9965 and AARE of 4.05%. The experimental results are in high agreement with the predicted flow stress. Hot deformation activation energy of the SiCP/Al composite (161.685 kJ/mol) is notably higher than that of Al-Cu-Mg-Ag alloy, which is attributed to the dislocations introduced by SiC reinforcement. The microstructure evolution of compressed specimens is characterized using EBSD and TEM. DRX, including CDRX and DDRX, is the main softening mechanism under the hot deformation conditions of high temperature, low strain rate and high strain. The softening mechanism transition from DRV to DRX is due to the subgrains consuming dislocations and then transforming into DRX grains. Comparing the microstructure under different hot deformation parameters, the recrystallization degree is significantly influenced by temperature, followed by strain rate and strain. In addition, the recrystallization process is impeded by the primary Al2Cu phases, T phases and SiC particles in the composite through hindering the migration of dislocations.

Influence of Gas Oven Temperature on the Microstructure and Extrudability of Al-Mg-Si Aluminium Alloys

The microstructure of Al-Mg-Si aluminium alloys is well characterised when it comes to the initial state of the cast billet or the artificially aged profile. Typically, a gas oven coupled with an induction oven is used to preheat the billets before extrusion. Preheating reduces the flow stress of the aluminium and dissolves the phases that have precipitated during cooling after homogenisation. In this paper, the influence of the gas oven temperature on the partial or complete dissolution of the precipitated phases will be shown. In addition, the negative effect of a wrong choice of parameters on the volume content of the MgSi phases will be shown.

The deformation behavior and mechanism modeling of a corrosion-resistant Ni-Cr-Mo alloy with nanoscale precipitates at room and elevated temperatures

Ni-Cr-Mo alloys are widely-used materials in various critical applications owing to their excellent balance of strength and ductility. The precipitates play a significant role in the exceptional mechanical properties of these alloys, yet the precise microscopic mechanisms underpinning the enhanced properties are still open. Here, the atomistic simulation based on molecular dynamics (MD) was employed to investigate the deformation behavior and mechanism of the precipitation-strengthened single crystal Ni-Cr-Mo alloy under uniaxial loading at temperatures of 300 K, 500 K, 700 K, and 900 K. The results revealed high temperature-induced softening under both tension and compression. Furthermore, the tension-compression asymmetry in ultimate strength is influenced by the disparity in Schmid factor of leading Shockley partial dislocations. By monitoring the evolution of microscopic defects during deformation, the Shockley partial dislocation slip was identified as the primary deformation mechanism in the plastic regime at 300 K, 500 K, 700 K, and 900 K. Based on that, a flow stress representation model was proposed. Moreover, the investigation on the nanoscale Ni2(Cr, Mo) precipitates revealed the transition from the Orowan bypass mechanism to the shearing mechanism under uniaxial loading, accompanied by the formation of dislocation tangles. The dislocation tangles impeded dislocation slip, enhancing the mechanical properties of the alloy. The precipitate can significantly promote the formation of the lamellar dislocation structure under compression at 900 K.

Modeling of elastic plastic deformation of near-surface layers of materials

According to the results of strain measurements, a kinematically hardening body model is used to describe the process of elastic-plastic deformation of 1X18H9T steel. Special attention is paid to the processes occurring in the surface layers. The model takes into account the increasing tightness of shear deformations deep into the material. The increase in the stress of the plastic flow in depth is described by a second-order polynomial. The main parameters of the surface effect were determined experimentally and by calculations using the method of reduction coefficients in the process of successive approximations: depth, coefficient of hardening of the material, stresses of plastic flow on the surface and inside the material. It is shown that in order to study the near-surface effect by the strain gauge method, it is necessary to give preference to bending tests of samples rather than stretching. The presence of the surface effect explains the following facts: the destruction of the sample during the tensile test does not begin from the surface, but from the inside, the origin of fatigue cracks occurs under the surface, the surface effect practically does not affect the deformed state of the elastic body, but very strongly affects the stress state at the surface.

Influence of disturbed blood flow on endothelial function in people living with HIV

Abstract Introduction People infected with human immunodeficiency virus (HIV) are more susceptible to endothelial dysfunction due to the virus itself, side effects of the antiretroviral therapy and classical risk factors. Endothelial damage is most prominent at the locations where laminar blood flow is disturbed and oscillatory shear stress with retrograde blood flow is dominating. Purpose The goal of this study was to assess the endothelial function in people with HIV, and to determine whether their endothelium is more susceptible to a short-term increase in retrograde blood flow in comparison to healthy individuals. Methods The study included 62 people with HIV infection and 38 people without HIV infection, in whom endothelial function was assessed using flow-mediated dilatation, which was presented in absolute (FMD) and relative (FMD%) values. The intervention produced oscillatory shear stress and retrograde blood flow during 20 minutes, after which the endothelial function assessment was repeated. Results Baseline FMD (0.30±0.07 vs. 0.36±0.07 mm; p&amp;lt;0.05) and FMD% (6.84±1.57 vs. 7.89±1.19 %, p&amp;lt;0.05) were lower in the HIV group in compare to controls. FMD and FMD% decreased in the HIV group by 0.03 mm and 0.7% (p&amp;lt;0.05), while in the control group they decreased by 0.09 mm and 2.0% (p&amp;lt;0.05). The post-intervention FMD and FMD% were not different between the groups (p&amp;gt;0.05). Conclusion People with HIV infection express worse endothelial function in compare to healthy individuals. Retrograde blood flow and oscillatory shear stress deteriorate endothelial function in both HIV patients and healthy controls, although this decline is more pronounced in healthy individuals.

Hot deformation behavior of an ignition resistance Mg–6Zn-0.6Zr-1.2Ca magnesium alloy

The addition of Ca could enhance the ignition point of magnesium alloys but impairing their workability, so it is essential to study the hot deformation behavior of new Ca-containing ignition resistance magnesium alloys. The hot deformation behavior of a new ignition resistance Mg–6Zn-0.6Zr-1.2Ca alloy was investigated by compression experiment in the temperature range of 240 °C–360 °C, strain rates of 10−3 s−1-1 s−1 and height reduction of 10%–60%. The true stress-strain curves show that flow stress decreases as the deformation temperature increases or the strain rate decreases. Microstructure analysis shows that higher temperatures and lower strain rates are favorable for DRX, while higher strain rates promote the fragmentation of the Ca2Mg6Zn3 phase. Meanwhile, the existence of Ca2Mg6Zn3 phase make the DRX process be dominated by the particle-induced subgrain nucleation mechanism. By superposition of the power dissipation map and the instability map, a hot processing map of true strain of 0.6 is generated. According to analyses on the processing map and microstructure evolution, the instability of processing map can be attributed to the greater dislocation motion resistances, insufficient DRX, and Ca2Mg6Zn3 phase with low-melting point. Conversely, the optimal processing parameters for the alloy were determined as 280–360 °C/0.001–0.01 s−1 in safe zone with a high η above 0.3, which can be due to the apparent DRX and good deformation coordination.

Leveraging machine learning to minimize experimental trials and predict hot deformation behaviour in dual phase high entropy alloys

In recent time, high entropy alloys (HEAs) are widely used due to their wide design space and remarkable properties allowing a vast range of property variations with myriads of possible combinations of constituent elements. This research utilizes machine learning techniques, including Random Forest (RF), K-Nearest Neighbors (KNN), XGBoost (XGB), Decision Tree (DT), and Support Vector Regressor (SVR), to predict the flow stress behavior of the dual FCC phase CoCrCu1.2FeNi high entropy alloy (HEA) at new temperature and strain rates to reduce the experiments dependency. The RF and KNN models were identified as top performers, with R² values of 0.987 and 0.986, respectively. These models successfully predicted flow stresses, aligning closely with actual measurements. A new flow stress-strain curve was generated at new temperature of 1123 K, demonstrating good performance metrics for RF and KNN. with R² values of 0.97 and 0.958 respectively. This approach has the potential to significantly reduce the need for extensive experimental work in determining the mechanical behaviour of HEA, offering substantial savings in time, cost, and energy, and marks a significant advancement in the development of such alloys.