Residual stress characterization of single and triple-pass autogenously welded stainless steel pipes

Using neutron diffraction the components of the residual stress field have been determined in the region near a mid-length groove in two identical austenitic stainless pipes in which weld beads had been laid down. One pipe sample had a single pass, and the second a triple pass, autogenous weld deposited around the groove circumference. The results show the effect on the stress field of the additional weld deposited and are compared to the results of Finite Element Modelling. The hoop stress component is found to be generally tensile, and greater in the triple pass weldment than in the single pass weldment. The hoop stresses reach peak values of around 400 MPa in tension. X-ray measurements of the residual stress components on the near inner surface of the pipe weldments are also presented, and show tensile stresses in both pipes, with a higher magnitude in the three-pass weldment

Prediction of residual stresses in girth welded pipes using an artificial neural network approach

Management of operating nuclear power plants greatly relies on structural integrity assessments for safety critical pressure vessels and piping components. In the present work, residual stress profiles of girth welded austenitic stainless steel pipes are characterised using an artificial neural network approach. The network has been trained using residual stress data acquired from experimental measurements found in literature. The neural network predictions are validated using experimental measurements undertaken using neutron diffraction and the contour method. The approach can be used to predict through-wall distribution of residual stresses over a wide range of pipe geometries and welding parameters thereby finding potential applications in structural integrity assessment of austenitic stainless steel girth welds

Mitigating Cutting-Induced Plasticity Errors in the Determination of Residual Stress at Cold Expanded Holes Using the Contour Method

Background The split sleeve cold expansion process is widely used to improve the fatigue life of fastener holes in the civil and military aircraft industry. The process introduces beneficial compressive residual stresses around the processed hole, but uncertainties remain about the character of the stress field immediately adjacent to the bore of the hole.ObjectiveThe primary objective of this study was to implement the contour method with minimising error associated with cutting-induced plasticity to provide detailed and reliable characterisation of the residual stress introduced by the split sleeve cold expansion process.MethodsA systematic FE study of plasticity effects by simulating different contour cutting strategies (a single cut, two sequential cuts and a 6-cut sequence) for a cold expanded hole in an aluminium alloy coupon was conducted. The identified ‘optimum’ cutting strategy was then applied experimentally on coupons containing a hole that had been processed to 3.16% applied expansion. ResultsThe FE study of different cutting simulations show that the locations of the stress error is consistent with the location where cutting-induced plasticity accumulated and that the magnitude and locations of stress re-distribution plasticity can be controlled by an optimised cutting strategy. In order to validate this hypothesis a high quality contour measurement was performed, showing that accurate near bore stress results can be achieved by the proposed 6-cut approach that controls cutting induced plasticity.ConclusionsThe present work has demonstrated that detailed FE simulation analysis can be a very effective tool in supporting the development of an optimum cutting sequence and in making correct choices of boundary conditions. Through optimizing these key aspects of the cutting sequence one is much more likely to have a successful, low error contour residual stress result

Measurement of the residual stress tensor in a compact tension weld specimen

Neutron diffraction measurements have been performed to determine the full residual stress tensor along the expected crack path in an austenitic stainless steel (Esshete 1250) compact tension weld specimen. A destructive slitting method was then implemented on the same specimen to measure the stress intensity factor profile associated with the residual stress field as a function of crack length. Finally deformations of the cut surfaces were measured to determine a contour map of the residual stresses in the specimen prior to the cut. The distributions of transverse residual stress measured by the three techniques are in close agreement. A peak tensile stress in excess of 600 MPa was found to be associated with an electron beam weld used to attach an extension piece to the test sample, which had been extracted from a pipe manual metal arc butt weld. The neutron diffraction measurements show that exceptionally high residual stress triaxiality is present at crack depths likely to be used for creep crack growth testing and where a peak stress intensity factor of 35 MPa√m was measured (crack depth of 21 mm). The neutron diffraction measurements identified maximum values of shear stress in the order of 50 MPa and showed that the principal stress directions were aligned to within ~20° of the specimen orthogonal axes. Furthermore it was confirmed that measurement of strains by neutron diffraction in just the three specimen orthogonal directions would have been sufficient to provide a reasonably accurate characterisation of the stress state in welded CT specimens

Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of ‘innate scatter’ and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated

The UK Transforming the Foundation Industries Research and Innovation Hub (TransFIRe)

Transforming Foundation Industries Research and Innovation hub (TransFIRe) was developed in response to the UK Government Industrial Strategy Challenge Fund call to transform the Foundation Industries: Chemicals, Cement, Ceramics, Glass, Metals, and Paper. These industries produce 75% of all materials in the UK economy and are vital for the UK’s manufacturing and construction industries. Together, the Foundation Industries are worth £52 Bn to the UK economy and produce 28 Mt of materials per year, accounting for about 10% of the UK’s total CO2 emissions. TransFIRe is a consortium of 20 investigators from 12 institutions, more than 50 companies, and 14 NGO, and government organisations related to the sectors, with expertise across the FIs as well as material flows and energy mapping, life cycle sustainability, circular economy, industrial symbiosis, computer science, AI and digital manufacturing, management, social science, and technology transfer. This paper will introduce the Foundation Industries, present the three work streams through which transformative change will be enabled, and initial plans for including a diversity of stakeholders