The load-bearing performance of train bodies under complex service conditions requires accurate evaluation, necessitating substantial analysis of the damage and fracture behavior of thin-walled structures with heterogeneous materials under complex stress states. To address this requirement, this study focuses on MIG-welded thin-walled 6005A-T6 aluminum alloy and proposes a parameter identification method based on the bilevel parallel optimization principle. The welding regions were characterized through metallographic and microhardness tests, and specimens were designed with pre-crack tips located in various welding regions. This enabled the calibration of material parameters from the elastic to the fracture stages for each welding region. By smoothing the material properties at the boundaries of the welding regions based on surface interpolation principles, the complex fracture behaviors, such as slant fractures and V-shaped fractures, were successfully represented. The predicted load–displacement curves closely matched the experimental results, with a relative error in peak force prediction within 8%. The proposed damage characterization method effectively captures material deformation behavior and accurately predicts fracture performance, offering potential refinements to current standards for welding crack propagation tests.

This study addresses the limitations of current parametric equations and artificial neural networks (ANNs) in accurately predicting the stress concentration factor (SCF) of fillet welded joints stemming from the simplification of their real weld profiles. To improve the accuracy, this study introduces bagged trees for estimating local stresses. The dataset used as the foundation for training the bagged trees is extracted from the actual weld geometry of T-shaped joints. It is created via a digitalization process involving the extraction of actual geometric parameters from the joints, which are transformed into finite element models (FEMs). These models are then employed to determine the ratio between the simulated sectional stress and the nominal stress (σsec/∆σnom) under an axial loading condition. A comprehensive comparison is carried out among existing parametric equations, ANNs, and the proposed bagged trees. The results emphasize the inadequacy of idealized geometry models in accurately determining local stresses for real weld profiles. In contrast, bagged trees are a promising method for accurately computing sectional weld stresses (σsec) within real weld geometry.

Plate thickness influences the fatigue performance of welded components. In fatigue design standards and recommendations, the thickness effect and fatigue strength reduction have been considered by modifying the S–N curve for plates thicker than a reference thickness. However, increasing fatigue strength due to the thinness effect is often disregarded. The current study focuses on the size effect in fatigue of butt welded and non-load carrying cruciform welded joints under constant amplitude tension load. Literature data is evaluated using the effective notch stress method with a reference radius of 1 mm, which is used for all finite element models to ensure that FAT-value corresponding to a 1 mm notch radius remains constant across all models. A probabilistic assessment of the results using the weakest-link theory is applied to improve the prediction accuracy of thinner members outside the recommended thickness range of the used radius. The method reduces the S–N data scatter in comparison to the variation of test data and shows applicability also for thinner members. A comparison of the size effect for the current method with extrapolated values from standards and recommendations shows a difference in the size effect for thinner members.

A probabilistic framework is developed utilizing a two-scale modeling approach to efficiently consider the material variability that is typical for composite materials. The modeling integrates a macro-scale model with effective elastic properties extracted from micro-mechanical simulations. Using a weakest link modeling approach for fatigue assessment the combined effects of defects on fatigue strength in a Carbon Fiber Reinforced Polymer (CFRP) material can be investigated. A full fatigue test program is presented and is used to calibrate the probabilistic fatigue model. By including material variability in the numerical model, the calibrated probabilistic model improves the fatigue life prediction.

The study presents a two-scale modeling approach allowing for an efficient fatigue strength evaluation on a macro scale considering a micro-mechanical defect characterization of a Carbon Fiber Reinforced Polymer (CFRP) material. The modeling approach integrates a macro model with the effective elastic properties from micro-mechanical simulations considering voids. This enables the analysis of defects’ influence on material fatigue strength using a probabilistic weakest link approach. A CFRP laminate with a cross-ply layup was investigated. Two simulation case studies demonstrate the effect of void content and size on the characteristic fatigue strength. An experimental investigation was conducted testing the laminates in tension–tension fatigue verifying the predicted numerical behavior. The numerical models identify a difference in the characteristic fatigue strength consistent with the fatigue test results. It is numerically concluded that the investigated CFRP material's fatigue strength is affected by the presence of voids and even with only a slight difference in the global void volume fraction a scatter in fatigue strength is identified.

The process temperatures in the friction stir welding of thick polymer plates play a significant role in the joint's quality since the process is characterized by mixed solid and viscous flow states. The heat generation mechanism in each state is fundamentally different, with heat being generated by friction in the solid-state and by viscous shear flow in the viscous state. In this study, the heat generation and dissipation in the friction stir welding of 14 mm thick high-density polyethylene plates were studied numerically through solving the direct heat conduction problem. Two models of heat generation were used in the numerical solution and the effect of the pin rotational speed on the process temperatures was investigated. It was shown that the utilization of a mixed heat generation model consisting of both the solid state and the viscous shear flow considerably improves the numerical model predictions. The temperature predictions were validated through welding experiments and showed a temperature difference of 3 %. Furthermore, it was found that the welding process stabilizes at rotational speeds higher than 800 rpm, where no considerable change occurs in the volume of the viscous flow region and the welding power requirement. The numerical results based on the combined solid-viscous heat model were in good agreement with the experimental thermal histories.

The local weld geometry and its variability can significantly affect the fatigue strength of structures, especially for non-load-carrying welds. Standardised definitions, such as sharp transition radii or undercuts, govern stress-raising effects at the weld toe. High-resolution digital tools can nowadays accurately determine these parameters, allowing for studying the impact of geometry variability on fatigue strength. However, real welds rarely exhibit idealised transitions as multiple radii, undercuts, and ripple lines introduce uncertainty in geometry estimations. Numerical simulations of the actual weld geometry, with all its variations, in combination with probabilistic evaluations, have shown great potential for studying the influence of competing notches in the weld. This study compares probabilistic evaluations of 3D scanned welds with analytical relations for stress concentration factors. Results reveal no clear trend between the analytical expressions and the ratio of simulated sectional stress to nominal stress. This highlights the challenge of directly applying existing analytical equations to idealised measurement data from real welds in their as-welded condition for fatigue strength estimations.

Global Sensitivity Analysis (GSA) is a well-established approach to support simulation-driven design decisions where the dependency between the simulation's output and the model's input is quantifed. However, classical GSA approaches, such as Sobol' indices based on Monte Carlo Simulations (MCS), are not convenient when computationally expensive simulation models such as Representative Volume Elements (RVE) are used as the model to analyze. A simulation framework is developed with a metamodeling-based GSA to overcome the aforementioned cost of the MCS approaches. The developed framework has been applied in a Multi-Scale Modeling (MSM) framework replacing a micromechanical RVE simulation with three different metamodels for performing GSA. The micromechanical model predicts the stiffness of a Carbon Fiber Reinforced Polymer (CFRP) material and the GSA can quantify how the experimental material parameters affect the material properties. The obtained sensitivity analysis demonstrates that void size is the most influential parameter on the outputs of interest, and the metamodel-based GSA is a computationally convenient approach.

Progress in developing digital quality assurance systems for welded joints has made it possible to accurately measure the local geometry and its variation, making it possible to derive new relations between the geometric variations and fatigue. A probabilistic model for the fatigue strength is here presented based on the actual weld geometry. The novelty lies in that representative stresses can be determined for both the complete weld and sections of the weld. Calibration of the model using 105 fatigue-tested specimens shows a reduced variation in SN-diagrams compared with the nominal stress methods when substantial weld geometry variations are present.

Safe design against unstable fractures in load-bearing structures is crucial at sub-zero temperatures where the brittle fracture toughness can be unfavourable, especially for high-stress designs incorporating ultra-high-strength steels. The brittle fracture toughness of surface cracks in structural steel with a minimum yield strength of 1300 MPa is, for this reason, tested in the present study at sub-zero temperatures. The realistic flaws are compared with single-edge notched specimens (SEN(B)) from thicker plates with the same chemical composition, using a representative fracture toughness for a three-dimensional crack front according to the Master Curve method. A novel approach determines the latter without considering the local temperature and constraint variation through empirical relations. The experimental result shows a difference in the reference temperature between the two specimen types, which likely is the natural variation of the manufactured materials and/or a loss of constraint due to the difference in the scaled specimen deformation level.