Flow Stress Research Articles

A unified constitutive model and microstructure evolution of a solution treated 7075 aluminum alloys under warm forming condition

The warm flow characteristics and microstructural evolution features in a solution-treated 7075 aluminum alloy are revealed. An elastic-visco-plastic constitutive model is developed to capture the flow stress behavior of 7075 aluminum alloy under warm deformation. The variations of microstructure features, including grain and subgrain size, are also analyzed under warm deformation, and are further incorporated in the proposed unified constitutive model. The results indicate that the dynamic recovery (DRV), related to dislocation annihilation and formation/growth of sub-grains, is the domain softening mechanism. The DRV behavior is enhanced at higher temperatures or lower strain rates. Warm external temperature field assists the plastic deformation by means of activating and accelerating the dynamic softening, while the reduced strain rate also gives sufficient time for the softening. Through experimental validation, the proposed constitutive model successfully captures the grain/subgrain features and flow behavior of the studied 7075 aluminum alloy during warm deformation. The predicted result is in a great agreement with the experimental stress-strain data, demonstrating the excellent predictive performance of the model. Moreover, the proposed model also successfully predicts the average grain/subgrain size.

Prediction of Flow Stress and Characterizing the Deformation Mechanism of As‐Extruded 7005 Aluminum Alloy

This study explores isothermal hot compression of the as‐extruded 7005 aluminum alloy within a temperature range of 573–823 K, with strain rates from 0.001 to 1 s−1 and a strain of 1.2. Three constitutive equations, employing hyperbolic sine, power law, and exponential functions, were formulated and compared to predict rheological peak stress accuracy and applicability. The results indicate that the hyperbolic sine function is suitable across all stress levels, the power law function for low stress (<56 MPa), and the exponential function for high stress (>56 MPa). Introducing a strain compensation function enhances hyperbolic sine function accuracy. The stress exponent (n) and activation energy (Q) decrease with increased deformation, indicating a transition in the deformation mechanism from early‐stage dislocation climb to later‐stage dislocation glide. At 773 K with strain >0.6, the presence of precipitates maintains the n value at approximately 4. Solute atoms (Zn, Mg, and Zr) and precipitates (MgZn2 and Al3Zr) impede diffusion and dislocation motion, resulting in deformation activation energies surpassing pure aluminum. Additionally, kernel average misorientation maps demonstrate that higher deformation temperatures and lower strain rates reduce internal residual stresses.

A machine learning constitutive model for plasticity and strain hardening of polycrystalline metals based on data from micromechanical simulations

Machine learning (ML) methods have emerged as promising tools for generating constitutive models directly from mechanical data. Constitutive models are fundamental in describing and predicting the mechanical behavior of materials under arbitrary loading conditions. In recent approaches, the yield function, central to constitutive models, has been formulated in a data-oriented manner using ML. Many ML approaches have primarily focused on initial yielding, and the effect of strain hardening has not been widely considered. However, taking strain hardening into account is crucial for accurately describing the deformation behavior of polycrystalline metals. To address this problem, the present study introduces an ML-based yield function formulated as a support vector classification model, which encompasses strain hardening. This function was trained using a 12-dimensional feature vector that includes stress and plastic strain components resulting from crystal plasticity finite element method (CPFEM) simulations on a 3-dimensional RVE with 343 grains with a random crystallographic texture. These simulations were carried out to mimic multi-axial mechanical testing of the polycrystal under proportional loading in 300 different directions, which were selected to ensure proper coverage of the full stress space. The training data were directly taken from the stress–strain results obtained for the 300 multi-axial load cases. It is shown that the ML yield function trained on these data describes not only the initial yield behavior but also the flow stresses in the plastic regime with a very high accuracy and robustness. The workflow introduced in this work to generate synthetic mechanical data based on realistic CPFEM simulations and to train an ML yield function, including strain hardening, will open new possibilities in microstructure-sensitive materials modeling and thus pave the way for obtaining digital material twins.

Dynamic Recrystallization Nucleation Mechanism and Precipitation Behavior of Homogeneous Al-Zn-Mg-Cu Alloy during Hot Deformation

The hot deformation behavior of Al-Zn-Mg-Cu alloy was investigated by flow stress curves in isothermal hot compression experiments with deformation temperatures of 350–450 °C and strain rates of 0.01 s−1 to 1 s−1, and the constitutive equation of homogeneous alloy was obtained. At the same time, the dynamic recrystallization and precipitation behavior during hot deformation and the relationship between them and the Z parameters were studied by using EBSD and TEM. DRV is the main mechanism of dynamic softening. With the decrease in Z parameter, the softening mechanism changes from dynamic recovery to discontinuous dynamic recrystallization or continuous dynamic recrystallization. At a higher Z parameter, the dislocation density and precipitated phase density are also higher because the high dislocation density provides heterogeneous nucleation sites of the precipitated phase. A large number of precipitates in the alloy also inhibit the nucleation and growth of dynamic recrystallization by hindering dislocation movement and grain boundary migration.

Prediction of Tensile Properties in Inconel 625 Superalloy Fabricated by Wire Arc Additive Manufacturing Using Improved Artificial Neural Network

This study exhibits the possibility of using an artificial neural network (ANN) to model the mechanical behavior of wire arc additive manufacturing (WAAM) for Inconel 625. For this reason, tensile tests of Inconel 625 superalloy as-built (AB) samples and samples after heat treatment at 1200 °C (HT-1200) by WAAM were performed. For the HT-1200 samples, the yield stress decreased, and the elongation increased significantly due to grain refinement and the formation of annealed twins. A new hybrid model combining a swarm intelligence optimization algorithm with a back propagation neural network (BPNN) was developed to simulate the flow behavior of the superalloy. Compared with other hybrid BPNN models that have been reported, the proposed BPNN model is in better agreement with the experimental data and provides a better description of the flow stress of the Inconel 625 superalloy. The excellent predictive ability of the model may be attributed to the optimization of the weights and thresholds of the BPNN, which obtains the optimal global solution in the search space more efficiently.

Hot deformation characteristics and dynamic recrystallization behavior of Cr5 die casting mold steel

Hot compression experiment was conducted on Gleeble-3800 thermal simulation testing machine to investigate the hot deformation behavior of Cr5 die casting mold steel, with deformation temperatures of 1100–1300 °C and strain rates of 0.01−10s−1. The experimental results indicated that deformation temperature and strain rate have significant impacts on dynamic recrystallization(DRX) of Cr5 die casting mold steel, the critical strain of DRX decreased as deformation temperature increased and strain rate decreased. According to the Arrhenius model, the activation energy for deformation was 427.85 kJ/mol, and the constitutive equation of hot deformation was derived. Validation of high temperature flow stress model showed that the fitted model emerged appreciable accuracy and reliability. The processing map was constructed based on DMM theory, which was concluded that the unstable region is mainly concentrated around the deformation condition of 1300 °C/10s−1. Cr5 die casting mold steel exhibits the best hot processing performance under the deformation condition of 1250 °C/0.1s−1, with an excellent efficiency of power dissipation(η = 0.36) and a lower value of Kernel average misorientation(KAM average = 1.675°). Discontinuous dynamic recrystallization (DDRX) is the main mechanism for recrystallization nucleation and growth during hot deformation of Cr5 die casting mold steel.

Flow behavior and dynamic recrystallization mechanism of a new near-alpha titanium alloy Ti-0.3Mo-0.8Ni-2Al-1.5Zr

A new near-α titanium alloy Ti-0.3Mo-0.8Ni-2Al-1.5Zr was designed based on Ti-0.3Mo-0.8Ni (TA10). The hot compression tests were carried out at temperatures of 800–970 °C and strain rates of 0.01–5 s−1. The results show that the flow softening phenomenon in the α + β phase region is more distinct than that in the single β phase region. The Arrhenius constitutive models based on strain compensation in the α+β phase region and β phase region were established respectively, and the correlation coefficient between the predicted flow peak stress values and the experimental values reached 0.99365. The hot processing map of the alloy was established, the processing parameters of the peak efficiency: 800 ≤ T ≤ 818 °C, 0.01 ≤ ε˙ ≤ 0.0235 s−1, and 960 ≤ T ≤ 970 °C, 0.01 ≤ ε˙ ≤ 0.0213 s−1. The microstructure evolution and deformation mechanism of the compressed specimens were researched by electron backscatter diffraction (EBSD) technique. There were two nucleation mechanisms for dynamic recrystallization (DRX): sub-grains growth nucleation and high angle grain boundaries (HAGBs) bulging nucleation, the former was continuous dynamic recrystallization (CDRX), and the latter was discontinuous dynamic recrystallization (DDRX). The flow stress in the α+β phase region was softened by CDRX and dynamic recovery (DRV), while the principal deformation mechanisms in the β phase region are DRV and DDRX. The dislocation strain energy and recrystallization ability at different temperatures were quantitatively analyzed by the kernel average misorientation (KAM) and the geometrically necessary dislocation (GND), and the results showed that more complete recrystallization occurred at lower temperature in the α + β phase region. The HCP slip was principally completed by prismatic ⟨a⟩ and pyramidal ⟨c+a⟩ slip systems during the hot compression, while BCC was a mixed mode of {110}, {112} and {113} multiple slips.

Effects of intermediate aging on the microstructure, strength and texture evolution of the Cu–Cr–Zr-Hf alloys

Cu-0.4Cr-0.2Zr-0.2Hf (wt%) alloy plates were prepared by cryogenic rolling and intermediate aging process. The effects of intermediate aging and cryogenic rolling on the microstructural, mechanical and textural evolutions were studied by X-ray diffraction, electron backscatter diffraction and transmission electron microscopy. The results show that the combination of cryogenic rolling and intermediate aging resulted in the formation of high-density dislocations, nanoscale deformation twins, deformation bands, and nano-precipitates in the Cu–Cr–Zr-Hf alloys. The nano-precipitates formed during the intermediate aging effectively increase the flow stress, and promote the formation of the nano-twins. Besides, the combination process can both reduce the fraction of the remnant grains and refine the width of remnant grains, promoting the homogeneous deformation of the Cu–Cr–Zr-Hf alloys. The reduction of the remnant grains decreases the Brass component, and increases the S component. The profuse nano-twins and Brass-type shear band contribute to the increase in the Y component.

Study of flow stress in Mg-Gd-Y-Nd-Zr alloys based on IWOA-BPNN model

This study investigates the compression deformation behavior of an Mg-Gd-Y-Nd-Zr alloy at temperatures ranging from 293 K to 573 K and strain rates ranging from 293K to 573K and strain rates ranging from 1000 s−1 to 2100 s−1 using a split Hopkinson pressure bar. A modified Johnson-Cook (JC) constitutive model and a backpropagation neural network (BPNN) model based on the improved whale optimization algorithm (IWOA) are established. Four statistical metrics, including correlation coefficient (R), mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE), are employed to evaluate the predictive accuracy of the two models. The findings indicate that the flow stress of the alloy is sensitive to strain, strain rate, and temperature. Increasing strain and strain rate or decreasing deformation temperature results in higher flow stress. Error calculations revealed that the modified Johnson-Cook constitutive model has an R of 0.98731, a MAPE of 7.3653%, a MAE of 19.6305 MPa, and a RMSE of 26.5704 MPa. In contrast, the model established using the IWOA-BPNN has an R of 0.99996, a MAPE of 0.58894%, a MAE of 1.2671 MPa, and a RMSE of 1.7709 MPa. The IWOA-BPNN model demonstrates higher accuracy and accurately predicts the flow stress of the alloy.

Effect of cooling rate and Nb addition on the strengthening in eutectic CoCr1.3FeMnNi0.7Nbx (0 ≤ x ≤ 0.45) high entropy alloys comprising of low stacking fault energy FCC phase

The CoCr1.3FeNi0.7MnNbx (0.3 ≤ x ≤ 0.45) eutectic high entropy alloy (EHEA) comprising of ultrafine lamellae of low stacking fault energy (SFE = 11 mJ/m2) face centered cubic (FCC) and Laves phase are synthesized at cooling rates of 2.5–10 K/s (arc melted ingots, AMIs) and 4.2 × 102 K/s (suction cast bars, SCBs). The microstructural investigation suggests that secondary dendritic arm spacing (SDAS) and interlamellar spacing are refined in SCBs due to a higher cooling rate than the AMIs. Whereas, deformation twins evolve in FCC phase due to its low SFE. The EHEAs exhibit a high yield strength of 1327 MPa for x = 0.367 SCB and a large fracture strain of 20% for x = 0.3 AMI under compression. Systematic investigation on the influence of Nb addition, microstructure refinement, and evolution of deformation twins during straining on the strengthening mechanisms reveals that the phase interface strengthening, solid solution strengthening, and twin boundary strengthening play critical roles in providing the high flow stress. The post-deformation analysis and the presence of multiple positive slopes in work hardening curves confirms that the concurrent effect of the evolution of dislocations, deformation twins, and their mutual interactions are solely responsible for the severe strain hardening at multiple stages during plastic deformation. The low values of strain rate sensitivity (0.0106–0.0111) and the activation volume (28b3-41b3) suggest that the deformation kinetics is governed by the dislocation interactions with the ultrafine lamellae interface and twin boundaries.

Predicting the strain hardening behavior and constructing processing maps of a lightweight Fe–Mn–Al–C steel through phenomenological modelling

This research deals with predicting the strain hardening behavior and constructing the processing maps of a lightweight steel over a wide range of temperature. To achieve this, the tensile tests were conducted at temperatures of 100 °C–1100 °C under strain rates of 0.001, 0.01, and 0.1s−1 up to fracture. In order to predict the deformation behavior of the lightweight steel, strain compensated Arrhenius-type models were employed. Considering the wide temperature range under investigation, the activation energies and strain rate sensitivity coefficients substantially varied, therefore, three different temperature ranges of 25–200 °C, 300–600 °C, and 700–1000 °C were considered for the prediction of the flow stress level. To evaluate the accuracy of the applied models, the (i) root mean square error (RMSE), (ii) average absolute relative error (AARE), and (iii) correlation coefficient (R), were calculated as well-known statistical parameters. A good agreement was observed between the predicted and actual flow stress. Employing the predicted data, the strain hardening curves were plotted and power dissipation/instability maps were constructed at various strain levels and temperature ranges. The rapid hardening regions, the regions with high efficiency and instability regions were identified which would be valuable for industrialization of the experimented material.

In-Situ synchrotron investigation of elastic and tensile properties of oxide dispersion strengthened EUROFER97 steel for advanced fusion reactors

The augmentation of mechanical properties of reduced activation ferritic martensitic steels through the introduction of creep resistant nano-oxide particles produces a class of oxide dispersion strengthened steels, which have attracted significant interest as candidates for first wall supporting structural materials in future nuclear fusion reactors. In the present work, the effect of temperature on the elastic properties and micro-mechanics of 0.3 wt% Y2O3 oxide dispersion strengthened steel EUROFER97 is investigated using synchrotron high energy X-ray diffraction in-situ tensile testing at elevated temperatures, alongside the non-oxide strengthened base steel as a point of comparison. The single crystal elastic constants of both steels are experimentally determined through analysis of the diffraction peaks corresponding to specific grain families in the polycrystalline samples investigated. The effect of temperature on the evolving dislocation density and character in both materials is interrogated, providing insight into deformation mechanisms. Finally, a constitutive flow stress model is used to evaluate the factors affecting yield strength, allowing the strengthening contribution of the oxide particles to be assessed, and correlation between the thermally driven microstructural behaviour and macroscopic mechanical response to be determined.

Ti6Al4V-0.72H on the Establishment of Flow Behavior and the Analysis of Hot Processing Maps

Significant columnar grains usually occur in the metallurgical microstructure of laser additive manufacturing, and plastic deformation introduced into additive manufacturing can significantly refine grain size. Due to the high deformation resistance and difficult deformation of titanium alloys, reducing the high-temperature deformation resistance of additive manufacturing titanium alloys is essential to facilitating the implementation of online rolling processes. High-temperature compression of titanium alloys was performed on a Gleeble-3800. It was found that the flow stress of the alloy decreased when the strain of the alloy decreased or the deformation temperature increased. The flow behavior of titanium alloys at high temperatures was investigated with the help of a Z-parameter flow model and multiple linear regression model. A positive correlation was found between the experimental and predicted values of the alloy under the multiple linear regression model, with a correlation coefficient of 0.98 and its error of 13.5%, which could better predict the flow stress values. In addition, hot processing maps were established, and the optimal deformation conditions were determined to provide some theoretical guidance for subsequent experiments.

Modification of extended Oxley’s predictive machining theory and determination of Johnson-Cook material model constants by inverse approach

The Johnson-Cook (J-C) flow stress model, renowned for its consideration of the combined effect of strain, strain-rate, and temperature on material property, forms the cornerstone of this research. Its simplicity and applicability in numerical simulation render it widely popular. The study addresses two primary objectives: first, to modify extended Oxley’s predictive machining theory by eliminating the iterative loop for calculating the tool-chip interface temperature, and second, to utilize an inverse approach for determining J-C material model constants specific to medium carbon steel. The modified approach successfully eliminates the iterative loop, thereby streamlining the determination process and effectively reducing calculation time by 25%–40%, thereby enhancing overall efficiency. Concurrently, the study employs an inverse approach to accurately determine the J-C constants (A, B, n, C, and m). Notably, the research avoids the need for expensive and time-consuming Split Hopkinson Pressure Bar (SHPB) tests, instead opting for low-cost axial tensile tests and numerical optimization techniques to obtain the J-C constants. Thus, this study provides a practical method for determining J-C constants, pivotal for accurate material representation in numerical simulations and metal cutting applications. Standard materials and machines are employed, ensuring ease of understanding for a wider audience. The predicted values for the J-C constants are in proximity to the experimental values obtained by using SHPB test. Validated findings, achieved with precision under specified metal cutting conditions, highlight the effectiveness and applicability of the proposed approach, providing valuable insights for optimizing machining processes and improving efficiency.

Droplet evaporation on curved surfaces: transients of internal and external transport phenomena

We explore the transient evolution of thermo-fluid-dynamics of evaporating sessile droplets over curved substrates in the liquid and gaseous domains. A computational model using the Arbitrary Lagrangian-Eulerian framework is adopted. The governing equations in both liquid and gaseous domains are solved in a fully coupled manner, considering coupled effects of evaporative cooling and heat advection due to bulk fluid motion. This bulk motion in the liquid domain is caused by natural advection due to thermal actuations such as thermal Marangoni flow and buoyancy-driven convection. For the gaseous domain, the additional effects of solutal convection (due to vapour-concentration variation), Stefan flow and interfacial viscous stresses are also considered. To depict a generalized role of substrate curvature, both concave and convex surfaces with curvatures over a wide range are studied. The surface wettability effects are also explored by varying the true contact angle of the droplets. Computational predictions on evaporation rate and internal flow field are validated against experimental results from literature. The interplay of wetting state and substrate curvature is noted to substantially affect the evaporation process and its thermo-fluidics. The convex curvature significantly augments internal advection while the same is weakened over concave substrates due to altered mass loss rate. Consequently, the duration of multi-vortex Marangoni flows in the development stages of evaporation and the advection in the external gaseous domain is markedly different for different curvatures. Further, on superhydrophobic curved surfaces, the effects of re-distributed evaporative fluxes play a major role. In such cases, the reduced mass flux over a large interfacial area near the periphery expedites the stable state Marangoni and external flow features.

An Improvised Modulation and Control Approach for Dual Active Bridge DC–DC Converter System

Aimed at the control and modulation of dual active bridge bi-directional dc (DAB-BIDC) converter, an unconventional approach is applied to explore its effect in symmetrical wave-based isolated dc-dc converters. The existing control schemes of DAB-BIDC converter with unified or optimal phase shift (UPS/OPS) modulation have the constraints like complex control schemes, light load efficiency, current stress, and reactive power. Since a 50 Hz, grid-connected conventional converter system uses the sinusoidal pulse width modulation method to minimize the requirement for passive filters. Similarly, this work investigates the same analogy for the high-frequency (HF) symmetrical wave converters to get effective modulation and control scheme for the DAB-BIDC converter. Furthermore, the proposed sinusoidal pulse width-phase shift (SPW-PS) modulation scheme has been implemented by the optimally derived control parameters using Lagrange's Multiplier Method (LMM) to minimize the reactive power flow and current stress reduction at the HF link. Therefore, the DAB-BIDC converter with the proposed modulation and control approach can be used for EV charging and solid-state transformers applications. Finally, the proposed work is validated using MATLAB simulation and experimental setup having turn ratio 36/12 V, fundamental frequency 5-kHz, and switching frequency 100-kHz for the experimental validation using OPAL-RT.

Understanding the impact of combined hydrodynamic shear and interfacial dilatational stress, on interface-mediated particle formation for monoclonal antibody formulations

During biomanufacturing, several unit operations expose solutions of biologics to multiple stresses, such as hydrodynamic shear forces due to fluid flow and interfacial dilatational stresses due to mechanical agitation or bubble collapse. When these stresses individually act on proteins adsorbed to interfaces, it results in an increase in protein particles in the bulk solution, a phenomenon referred to as interface-induced protein particle formation. However, an understanding of the dominant cause, when multiple stresses are acting simultaneously or sequentially, on interface-induced protein particle formation is limited. In this work, we established a unique set-up using a peristaltic pump and a Langmuir-Pockels trough to study the impact of hydrodynamic shear stress due to pumping and interfacial dilatational stress, on protein particle formation. Our experimental results together demonstrate that for protein solutions subjected to various combinations of stress (i.e., interfacial and hydrodynamic stress in different sequences), surface pressure values during adsorption and when subjected to compression/dilatational stresses, showed no change, suggesting that the interfacial properties of the protein film are not impacted by pumping. The concentration of protein particles is an order of magnitude higher when interfacial dilatational stress is applied at the air-liquid interface, compared to solutions that are only subjected to pumping. Furthermore, the order in which these stresses are applied, have a significant impact on the concentration of protein particles measured in the bulk solution. Together, these studies conclude that for biologics exposed to multiple stresses throughout bioprocessing and manufacturing, exposure to air-liquid interfacial dilatational stress is the predominant mechanism impacting protein particle formation at the interface and in the bulk solution.

Investigation of friction modeling on numerical Ti6Al4V cutting simulations

Friction significantly influences chip formation, thereby highlighting its modeling critical in numerical cutting simulations. Notably, issues like the underestimation of feed force in simulations are often attributed to inadequate friction models. Nevertheless, diverse conclusions in the literature regarding friction’s behavior complicate the accurate implementation of this input. Additionally, the enormous number of the available friction models and their varied calibration methods introduce further debates over which aspects of friction modeling should receive more focus. These controversies and deficiencies hinder progress in further understanding friction’s role in chip formation through numerical studies. Instead of proposing or calibrating new friction models, the current study, based on Ti6Al4V machining simulations, attempts to readdress the aforementioned controversies in a neutral stance by conducting sensitivity studies using a hybrid Smoothed Particle Hydrodynamics (SPH) - Finite Element Method (FEM) solver with Graphics Processing Units (GPU) acceleration, which is capable of efficiently executing high-resolution computations. The significant impact of friction particularly at the end of the tool-chip contact on the chip formation, physical contact states and process forces are highlighted. The behaviors of physical parameters including normal contact pressure, sliding velocity, and temperature-dependent friction models in the literature are also evaluated. Several aspects such as the shear flow stress limit, the relationship between friction and process forces, and the selection of different models are discussed. In conclusion, pragmatic recommendations for friction modeling and cutting simulation work are provided. On the one hand, the available complex physical parameter dependent friction models could not prove their necessity and should be approached cautiously. Instead, the constant Coulomb friction model without the shear stress limit, despite its simplicity, demonstrates effective and sufficient for a single set of metal cutting simulations. On the other hand, reliable on-site measurement techniques of the coefficient of friction (COF) at the tool-chip sliding contact area should be developed, with consideration of the contact length and the state of material flow. Combined with careful cutting edge preparation and suitable constitutive models, the overall accuracy of numerical cutting simulations including the feed force prediction is expected to be improved.

Deformation-induced HCP phase transformation of CrCoNiSi0.3 medium-entropy alloy under high strain rate tension

The yield strength of a CrCoNiSi0.3 medium-entropy alloy is significantly increased from 450 MPa (quasi-static, 0.001 s−1) to 1600 MPa (at a strain rate of 5000 s−1) under dynamic tension, with a considerable ductility of 60%. The high strain-rate sensitivity (SRS) of strength and work hardening is obtained, and the strength SRS reaches 0.408. The dominant deformation mechanisms are abundant multiple-twinning, increasing fractions of deformation twins and phase transformation from face-centered-cubic to hexagonal-close-packed (HCP) phases with a strain rate. A universal dislocation-hardened constitutive model considering the evolution of the twin and HCP transformation is established to predict the flow stress and microstructure evolution.

Hydrogen contribution to low temperature embrittlement during PWR exposure of an alloy 82 weld metal

The embrittlement of alloy 82 welds exposed to a simulated pressurised water reactor (PWR) environment was analysed and compared with that observed for cathodically hydrogen-precharged specimens. Similarities in mechanical behaviour, i.e. the evolution of the constitutive equations with a decrease in flow stress compared with non-precharged specimens, and in the fracture modes, with brittle zones in the outer layer, enabled us to conclude that the embrittlement observed in simulated PWR environment corresponded to a two-step hydrogen-assisted cracking mechanism. The first step corresponded to hydrogen absorption into the surface layer leading to crack initiation, and the second step to hydrogen localisation ahead of the crack tip promoting crack propagation.