The presented research aims to examine local fatigue failure modes of Glass Fiber-polymer Composite (a.k.a. GFRP), particularly how the bending of the Web-to-Flange Junctions (WFJ) and tensile loading of the material affects the composite's fatigue resistance. By conducting experimental analyses, the study investigates GFRP's efficacy both as a material and as a component element, drawing parallels with Eurocode standards for steel and concrete. The coupon tests under static and fatigue loading conditions provided an empirical data on the Ultimate Limit State (ULS) and fatigue resistance of the GFRP composites, including a better understanding of the effects of variation in the facing’s thicknesses in the web-core composite on the fatigue response. Subsequent three-point bending tests on the WFJ provided the insights into the strength of WFJ with the first indications on the governing failure mechanisms in the WFJ.@en

In this paper, for the first time, a three-step approach for the optimal design of stiffened panels accounting for the ultimate limit state due to welding residual stress is developed. First, authors rely on state-of-the-art analytical approaches coupled with recently data-driven nonlinear finite element methods surrogates characterized by functional which are computationally expensive to build but computationally inexpensive to use. Then, surrogates are used within a design optimization loop to find new optimal designs since nonlinear finite element methods are too computationally demanding for this purpose. Finally, the new designs are reassessed with the original nonlinear finite element methods to verify that substituting them with their surrogates in the optimization loop actually leads to better designs. Results obtained optimizing a series of parameters of a commonly used stiffened panel geometry under different scenarios will support the authors’ novel approach.

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This study presents a numerical approach for modelling the Corrosion Fatigue Crack Growth (CFCG) in conventional casting and additively manufactured Ti6Al4V alloys. The proposed numerical model, based on Peridynamics (PD), combines the PD Fatigue Crack Growth (FCG) model and PD diffusion model in order to couple the mechanical and diffusion fields existing in the material due to the impact of environmental fatigue. The mechanical field is responsible for the characterisation of the changes to the structure due to the fatigue loading conditions. The diffusion field is based on the modelling of the adsorbed-hydrogen Stress Corrosion Cracking (SCC), in particular, the Hydrogen Embrittlement (HE) model is considered. The proposed approach has been validated using experimental data available in the literature showing the capability of the tool to predict the CFCG rates.

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Additive Manufacturing (AM) has gained a lot of interest due to the freedom to produce complex metal geometries directly from the designed digital model. Despite the high potential of AM, the process induced imperfections, like pores and the microstructural changes due to the layer-by-layer manufacturing, made a significant impact on the fatigue resistance and crack growth behaviour. Consequently, this work aims to evaluate the effect of microstructure and existence of pores in additively manufactured Ti6Al4V on Fatigue Crack Growth (FCG) utilizing bond-based Peridynamics (PD) fatigue model. Employing the columnar granularity and different levels of porosities indicated a substantial impact on FCG rates.@en

This study presents a numerical approach to predict the influence of the residual stresses on Fatigue Crack
Growth Rates (FCGR). The main focus is on the additively manufactured titanium alloy Ti6Al4V with resultant
high residual stresses in the samples due to the layer by layer manufacturing. A parabolic temperature profile has
been applied to represent the effect of the pre-tension or pre-compression of the sample to account for the ex-
istence of the initial residual stresses. The proposed approach has been validated using experimental data
available in the literature showing the capability of the tool to predict the FCGR.@en

Additive manufacturing (AM) has enabled the fabrication of complex geometries directly from the design data and gained a lot of interest. However, AM products can contain pores, which can significantly reduce fatigue life. The main focus of this work is to evaluate the effect of the pores in Ti6Al4V dog-bone samples, produced by AM, and propose a methodology to estimate the fatigue life reduction due to the internal pores. The bond-based Peridynamics (PD) fatigue model was utilised to analyse the fatigue life of the defect-free sample with the calibrated PD parameters. Moreover, a numerical model is developed to investigate two types of porosities in a system. The application of the PD model showed a capability of crack nucleation prediction for the titanium alloy samples under cycling loading. The predicted results are compared with experimental data using the stress-life (S-N) curve. Furthermore, this paper presents a numerical approach to assess the influence of the pore location and size on the fatigue life of Ti6Al4V. The PD predictions indicated the critical pore characteristics and the applicability of the developed PD model on samples with low porosity for high cycle fatigue-loaded applications.@en

The presence of defects in the structure requires noticeable attention and understanding of fracture mechanisms in brittle materials has to be established. Defects in the form of holes, macro- and micro-cracks are the main interest of this paper. This work investigates the dual role of holes and micro-crack arrays on toughening and degradation mechanisms in concrete structures. An ordinary state-based peridynamics (PD) model is utilized to analyse the fracture problem at the micro-level. The application of PD shows its advantage in crack-hole, macro- and micro-crack interaction problems since PD can accurately predict the contribution of defects on structural behaviour. The study of the three-point bending problem with five types of holes existing in the structure showed the crack arrest phenomena at the hole boundary and the “attraction” of the crack to propagate towards the hole. For the study of the macro- and micro-cracks interaction problem, various cases of the micro-crack distribution and inclination angles are considered and validated with analytical studies. The PD quasi-static simulations show good agreement with analytical solutions. Moreover, PD dynamic solutions show the capability of PD to capture complex crack propagation paths. It is observed that the presence of micro-cracks and holes ahead of the main crack can suppress its further propagation as well as have an influence on the crack propagation direction. The numerical results demonstrate the efficiency of the PD modelling of multiple crack interaction problems.

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This study presents an in-depth investigation of the critical stretch based failure criterion in ordinary state-based peridynamics for both static and dynamic conditions. Seven different cases are investigated to determine the effect of the failure parameter on peridynamic forces between material points and dilatation. Based on crack opening displacement (COD) results from both peridynamics and finite element analysis, it was found that one of the seven cases provides the best agreement between the two approaches. This particular case is further investigated by considering the influence of the discretisation and the horizon sizes on COD and crack propagation speeds. Moreover, PD predictions of COD for PMMA material is analysed with the theory of dynamic fracture mechanics and compared with the fracture experiments. It is shown that the peridynamic model can correctly model, simulate and predict the behaviour of the crack under different loading conditions. Furthermore, the presented PD models capture accurate fracture phenomena, specifically the crack path, branching angles and crack propagation speeds, which are in good agreement with experimental results.@en

The continuous increase of marine traffic and the entry of autonomous ships into the market is urging an improvement in safety measures to guarantee avoidance of collisions between moving objects at sea. This rise in automated maneuverability requires gaining further insight in the vessel’s behavior. The ship design has to ensure that the vessel is controllable and capable of maneuvering securely, even at critical operating conditions. Crash stop maneuvering performance is one of the key indicators of the vessel’s safety properties for designers and shipbuilders. Many factors affect this performance, from the hull design to the environmental conditions; hence, it is non-trivial to assess them accurately during the preliminary design stages. In this paper, the authors focus on predicting accurately and with minimal computational effort the crash stop characteristics of a vessel in the design stage, for the preliminary assessment of safety requirements imposed by the classification societies. The crash stop prediction model of the said vessel can be utilized in combination with collision avoidance algorithms. The authors propose a new data-driven method, based on the popular Random Forests learning algorithm, for predicting the crash stop maneuvering performance. Results from full-scale measured data show the effectiveness of the proposed method.@en

Crash stop maneuvering performance is one of the key indicators of the vessel safety properties for a shipbuilding company. Many different factors affect these performances, from the vessel design to the environmental conditions, hence it is not trivial to assess them accurately during the preliminary design stages. Several first principal equation methods are available to estimate the crash stop maneuvering performance, but unfortunately, these methods usually are either too costly or not accurate enough. To overcome these limitations, the authors propose a new data-driven method, based on the popular Random Forests learning algorithm, for predicting the crash stopping maneuvering performance. Results on real-world data provided by the DAMEN Shipyards show the effectiveness of the proposal.

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