This study reports on microstructure evolution and mechanical properties of weld joints of two ASTM A335 P92 steels with varying chromium and tungsten content influenced by heat treatment. Physical simulation samples for fine-grain and intercritical heat-affected zones were done using the Gleeble® 3500 equipment. A peak temperature of 900°C (intercritical zone) and 950°C (fine-grained zone) simulated different heat-affected zones. After physical simulation, the test samples underwent two heat treatment schedules: post-weld heat treatment (PWHT) and normalisation, followed by tempering. The results show that the two steels had similar martensite microstructure. The microstructure further exhibited the presence of M23C6 carbides along the grain and lath boundaries. The P92-B steel had the highest hardness values after heat treatment except at FGHAZ + PWHT condition, which had a lower hardness value (271.9 ± 5.0 HV0.5). In this condition (FGHAZ + PWHT), P92-B steel had a higher Charpy toughness value (180J), slightly higher than the base metal (178J) due to fully formed martensite microstructure. ICHAZ + heat treatment, P92-B steel had the lowest toughness values (74J for r-PWHT and 83J for PWHT), but these values were higher than the minimum toughness value of 47J of the weld joint required for hydro-testing of the vessels. The study revealed no marked significant differences between the two steels. The heat treatment method (r-PWHT) is applicable in the industry for Type IV crack mitigation of the weld joint.

The article reports on the workability of two P92 steels having a chromium content of 8.29 and 9.48 wt%. Constitutive equations were used to calculate material parameters describing the hot deformation flow stress. Hot deformation tests were conducted using the Gleeble® 3500 thermomechanical facility. Test conditions were: temperature of 850-1000°C and strain rate of 0.1-10s-1 to a strain of 0.5. The flow stress curve results show that dynamic recovery was the only softening mechanism. A comparative study of the two steels revealed that Cr content had a marginal significance on the flow stress behaviour. Constitutive analysis results of the material parameters were: a stress exponent of 9.0 (P92-A), and 11.0 (P92-B), while the activation energy was 369 kJmol-1 (P92-A), and 472 kJmol-1 (P92-B). A brief explanation of the material parameter results is in this article. A flow stress model was developed to predict the flow stress behaviour of the two P92 steels investigated. The results show that the model accurately predicts the flow stress at all the deformation conditions applied. The statistical parameters showed a good correlation between the predicted and the experimental data. Therefore, this model can be used to develop metal forming schedules for industrial applications.

This study reports the flow stress behavior of three P92 steels with different compositions. Uniaxial compression tests were conducted in the deformation temperature range of 575 °C to 650 °C and strain rate range of 0.001-0.5 s-1 using a Gleeble® 3500 thermo-mechanical simulator. A simple physically-based constitutive model was used to analyse the effects of deformation conditions (temperature and strain rate) on the metal flow stress behavior during the deformation process. The method accounts for the temperature dependence of Young’s modulus and the lattice self-diffusion coefficient of Fe in the ferrite. Constitutive equations describing the flow stress behavior of the three P92 steels were developed. From the results, the stress exponent n of 26.13(steel A), 21.61(steel B) and 27.55 (steel C) were obtained using the self-diffusion activation energy in the physically-based constitutive equation. From the results, the three steels had variation in the stress exponent values, which was attributed to differences in elemental content, such as chromium and tungsten. The developed constitutive equations were verified using statistical parameters: Pearson’s correlation coefficient (R) and average absolute relative errors (AARE). Statistical analysis showed that the three steels had the same R of 0.98, while AARE was: 1.68 (steel A), 1.72 (steel B), and 1.82 (steel C). The constitutive equations developed showed a good correlation between the experimental and predicted flow stress data. Hence, the method is applicable in describing flow stress behavior in the metalworking process in the industry.