This work investigates the interaction between two competing mechanisms on the fatigue life of 304L stainless steel, martensitic transformation and viscoplastic relaxation, as well as the potential fatigue life enhancement of a single hold time applied prior to cyclic loading. At 300 °C, a tensile load hold time of 15 h applied prior to alternating cyclic loading resulted in an increase in mean fatigue life, exceeding 20 % in the studied low cycle fatigue regime. The observed enhancement is primarily attributed to viscoplastic effects during the hold time, which reduces the maximum stress and fatigue crack growth rate in cyclic loading. At room temperature, the opposite effect was observed. A strain-induced martensitic transformation resulted in a secondary cyclic hardening and a brittle final softening phase. The transformation was enhanced by the hold time, which led to increased brittleness and therefore reduced fatigue life. However, viscoplastic relaxation attenuated the detrimental effect of martensite, as was observed by a 15 % decrease in maximum stress. This study not only demonstrates the positive impact of an extended hold time at elevated temperature on the low cycle fatigue behavior but also analyzes underlying competing mechanisms at room temperature through an in-depth experimental investigation.

This study addresses the critical need for a constitutive model to analyze the cyclic plasticity of additively manufactured 316L stainless steel. The anisotropic behavior at both room temperature and 300 °C is investigated experimentally based on cyclic hysteresis loops performed in different orientations with respect to the build direction. A comprehensive constitutive model is proposed, that integrates the Armstrong-Frederick nonlinear kinematic hardening, Voce nonlinear isotropic hardening and Hill's anisotropic yield criterion within a 3D return mapping algorithm. The model was calibrated to specimens in the 0° and 90° orientations and validated with specimens in the 45° orientation. A single set of hardening parameters successfully represented the elastoplastic response for all orientations at room temperature. The algorithm effectively captured the full cyclic hysteresis loops, including historical effects observed in experimental tests. A consistent trend of reduced hardening was observed at elevated temperature, while the 45° specimen orientation consistently exhibited the highest degree of strain hardening. The applicability of the model was demonstrated by computing energy dissipation for stabilized hysteresis loops, which was combined with fatigue tests to propose an energy-based fatigue life prediction model.

This work investigates the influence of a single tensile preload, applied prior to fatigue testing, on the fatigue strength of 316L stainless steel parts manufactured using laser-based powder bed fusion (PBF-LB) with a porosity of up to 4 %. The specimens were produced in both the horizontal and vertical build directions and were optionally preloaded to 85 % and 110 % of the yield strength before conducting the fatigue tests. The results indicate a clear tendency of improved fatigue life and fatigue limit with increasing overload in both cases. The fatigue limits increased by 25.8 % and 24.6 % for the horizontally and vertically built specimens, respectively. Extensive modelling and experiments confirmed that there was no significant alteration in the shape and size of the porosity before and after preloading. Therefore, the observed enhancement in fatigue performance was primarily attributed to the imposed local compressive residual stresses around the defects.

In this work, we predicted the gradient of the deformational moisture dynamics in a sized commercial paper by observing the curl deformation in response to the one-sided water application. The deformational moisture is a part of the applied liquid which ends up in the fibers causing swelling and subsequent mechanical response of the entire fiber network structure. The adapted approach combines traditional experimental procedures, advanced machine learning techniques and continuum modeling to provide insights into the complex phenomenon relevant to ink-jet digital printing in which the sized and coated paper is often used, meaning that not all the applied moisture will reach the fibers. Key material properties including elasticity, plastic parameters, viscoelasticity, creep, moisture dependent behavior, along with hygroexpansion coefficients are identified through extensive testing, providing vital data for subsequent simulation using a continuum model. Two machine learning models, a Feedforward Neural Network (FNN) and a Recurrent Neural Network (RNN), are probed in this study. Both models are trained using exclusively numerically generated moisture profile histories, showcasing the value of such data in contexts where experimental data acquisition is challenging. These two models are subsequently utilized to predict moisture profile history based on curl experimental measurements, with the RNN demonstrating superior accuracy due to its ability to account for temporal dependencies. The predicted moisture profiles are used as inputs for the continuum model to simulate the associated curl response comparing it to the experiment representing “never seen” data. The result of comparison shows highly predictive capability of the RNN. This study melds traditional experimental methods and innovative machine learning techniques, providing a robust technique for predicting moisture gradient dynamics that can be used for both optimizing the ink solution and paper structure to achieve desirable printing quality with lowest curl propensities during printing.

This study presents a thermodynamically consistent continuum damage model for fiber-based materials that combines elastoplasticity and damage mechanisms to simulate the nonlinear mechanical behavior under in-plane loading. The anisotropic plastic response is characterized by a non-quadratic yield surface composed of six sub-surfaces, providing flexibility in defining plastic properties and accuracy in reproducing material response. The damage response is modeled based on detailed uniaxial monotonic and cyclic tension-loaded experiments conducted on specimens extracted from a paper sheet in various directions. To account for anisotropic damage, we propose a criterion consisting of three sub-surfaces representing tension damage in the in-plane material principal directions and shear direction, where the damage onset is determined through cyclic loading tests. The damage evolution employs a normalized fracture energy concept based on experimental observation, which accommodates an arbitrary uniaxial loading direction. To obtain a mesh-independent numerical solution, the model is regularized using the implicit gradient enhancement by utilizing the linear heat equation solver available in commercial finite-element software. The study provides insights into the damage behavior of fiber-based materials, which can exhibit a range of failure modes from brittle-like to ductile, and establishes relationships between different length measurements.

This paper develops a hybrid experimental/simulation method for the first time to assess the thermal stresses generated during electron beam melting (EBM) at high temperatures. The bending and rupture of trusses supporting Inconel 625 alloy panels at similar to 1050 degrees C are experimentally measured for various scanning strategies. The generated thermal stresses and strains are thereafter simulated using the Finite-Element Method (FEM). It is shown that the thermal stresses on the trusses may reach the material UTS without causing failure. Failure is only reached after the part experiences a certain magnitude of plastic strain (similar to 0.33 +/- 0.01 here). As the most influential factor, the plastic strain increases with the scanning length. In addition, it is shown that continuous scanning is necessary since the interrupted chessboard strategy induces cracking at the overlapping regions. Therefore, the associated thermal deformation is to be minimized using a proper layer rotation according to the part length. Although this is similar to the literature reported for selective laser melting (SLM), the effect of scanning pattern is found to differ, as no significant difference in thermal stresses/strains is observed between bidirectional and unidirectional patterns from EBM.

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.

The anisotropic properties and pressure sensitivity are intrinsic features of the constitutive response of fiber network materials. Although advanced models have been developed to simulate the complex response of fibrous materials, the lack of comparative studies may lead to a dubiety regarding the selection of a suitable method. In this study, the pressure-sensitive Hoffman yield criterion and the Xia model are implemented for the plane stress case to simulate the mechanical response under a bi-axial loading state. The performance of both models is experimentally assessed by comparison to bi-axial tests on cruciform-shaped specimens loaded in different directions with respect to the material principal directions. The comparison with the experimentally measured forces shows the ability of the Hoffman model as well as the Xia model with shape parameter k≤2 to adequately predict the material response. However, this study demonstrates that the Xia model consistently presents a stiffer bi-axial response when k≥3 compared to the Hoffman model. This result highlights the importance of calibrating the shape parameter k for the Xia model using a bi-axial test, which can be a cumbersome task. Also, for the same tension-compression response, the Hill criterion as a special case of the Hoffman model presents a good ability to simulate the mechanical response of the material for bi-axial conditions. Furthermore, in terms of stability criteria, the Xia model is unconditionally convex while the convexity of the Hoffman model is a function of the orthotropic plastic matrix. This study not only assesses the prediction capabilities of the two models, but also gives an insight into the selection of an appropriate constitutive model for material characterization and simulation of fibrous materials. The UMAT implementations of both models which are not available in commercial software and the calibration tool of the Xia model are shared with open-source along with this work. 

Idealized geometry is typically used in standards for the fatigue life assessment of welded joints. In the presence of stochastic geometrical variations along the weld, the choice of the idealized geometry is however ambiguous. In the notch stress (NS) method with a fictitious notch radius rref = 1 mm, the FAT 225 curve is derived for welds with relatively good quality in toe profiles. In the NS method with rref = ractual + 1 mm, a lower FAT 200 curve is recommended. Both approaches neglect the stochastic variability in toe radius, toe angle and leg length along the weld. The aim of this paper is two-fold. First, a numerical comparison between both approaches in terms of their predicted fatigue life is performed for a non-load carrying fillet cruciform joints. The results show that the NS method with rref = 1 mm and FAT 225 is substantially more conservative. Second, these methods are enhanced by replacing the deterministic stress concentration factor by a probability distribution computed using Monte Carlo simulation. It is shown that NS with rref = 1 mm and FAT 225 does not predict any substantial influence of the stochastic variability in process parameters since the actual toe radius is not included in the analysis. However, the NS method with rref = ractual + 1 mm and FAT 200 predicts a decrease in fatigue life when uncertainties in geometrical parameters is included. This numerical study paves the way for an experimental validation of the predicted influence of stochastic variability of geometrical parameters based on the stochastic notch stress analysis.