Additive manufacturing (AM) is a quicker and more cost-effective technique to produce complex parts that can perform similar to or better than conventionally manufactured parts. However, due to the dissimilar microstructure compared to conventional parts, there is a lack of understanding in the physical and mechanical response of AM alloys under different loading conditions and strain rates, and thus the suitability of using AM parts is uncertain. Notably, the presence of voids in AM metal alloys is more prevalent. By developing a computational model that can represent plasticity and track fracture initiation at the void sites in AM alloys such as Al-Si10-Mg, the failure response can be predicted. Therefore, the objective of this research is to use in-situ micro-computed tensile testing to identify individual voids or networks of voids that are likely to cause fracture initiation in an AM Al-Si10-Mg alloy.
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Themes: Fatigue and Fracture of Additively Manufactured Materials
FACTORS GOVERNING THE FATIGUE PERFORMANCE OF AM TI-6AL-4V COMPONENTS
Before an additively manufactured component can be safely used in a load bearing application, its mechanical performance must be qualified. Traditional qualification approaches, involving the fabrication and testing of many identical components, negate one of the greatest benefits of additive manufacturing, i.e. the ability to quickly and cheaply fabricate one-off components. Thus, qualification methods that rely less on mechanical testing and more on predictive modeling are of value. This is most true for high cycle fatigue performance, where mechanical testing requires significant resources and produces stochastic results.
High cycle fatigue failure is difficult to predict because it can depend nonlinearly on many parameters, e.g. part geometry, residual stresses, surface characteristics, material defect characteristics, grain and dislocation structures, mechanical and environmental loading characteristics and their history. This has motivated a succession of fatigue models with ever increasing mechanistic fidelity, with some now diving down to the atomic scale. This raises the question of: what level of mechanistic detail is required to sufficiently predict the performance of AM Ti-6Al-4V components? In this talk, I will give my perspective on this question, building from a decade of AM Ti-6Al-4V fatigue modeling and experimentation across scales.
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FINITE ELEMENT MODELLING IN PREDICTING THE EFFECT OF DEFECTS ON STRESS CONCENTRATION AND FATIGUE LIFE OF L-PBF ALSI10MG ALLOY
The elastic-plastic finite element analysis is performed to obtain the stress field around pores and evaluate their resultant effects on fatigue life for L-PBF (Laser Powder Bed Fusion) produced AlSi10Mg alloy. The stress field is calculated for both single and multiple pore models, where stress concentration is evaluated as a function of the pore location and its size. A multi-scale finite element (FE) model is proposed based on the inherent porosity data from Computed Tomography (CT) to predict the overall fatigue life with high (90%) accuracy. The predicted fatigue life (cycles) are calculated using the rainflow counting algorithm in fe-Safe software using the stress-strain data obtained from the proposed FE model developed using the Abaqus software. Using the proposed model, it is possible to generate S-N curves for any loading condition for a given porosity characteristic (porosity density and average pore size).
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IMPACT OF MICRO AND MESOSTRUCTURE ON THE FAILURE RESISTANCE OF LASER POWDER BED FUSION-PROCESSED MATERIALS
Engineering materials processed using additive manufacturing (AM) techniques such as laser powder bed fusion (LPBF) often exhibit unique microstructures and defects that must be controlled to obtain peak performance in mechanical properties and as such a level of damage-tolerance that cannot be achieved in cast alloys. However, our understanding of how processing conditions control micro- and mesostructure and, in turn, mechanical performance, particularly regarding failure resistance, is weak. Furthermore, heat treatments that have been designed to achieve peak performance in cast alloys are often not optimized for alloys that have been processed using AM techniques. Here, we report our work on the effect of processing parameters such as layer thickness, hatch spacing, and scan strategy on crack resistance curve (R-curve) behavior in different orientations of LPBF-processed AlSi10Mg and correlate mechanical performance with meso- and microstructural features such as melt pool arrangement, cell morphology, grain size, grain orientation, and texture. Compared to that we show how heat-treatments impact fracture resistance as well as their anisotropy in two orthogonal orientations in an LPBF-processed 18Ni-300 maraging steel.
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PREDICTING SURFACE ROUGHNESS IN METALLIC ADDITIVELY MANUFACTURED PARTS USING MACHINE LEARNING
A melt pool geometry-based approach is developed to predict surface roughness in metal additively manufactured parts for a range of processing parameters. It is shown that surface roughness on a particular facet can be estimated by stacking melt pools along the facet, extracting their outer contour and applying the necessary transformations. To be able to predict surface quality of various processing parameters in a reasonable time frame, a machine learning framework is developed. This framework is trained over melt pool data generated by high-fidelity FE simulations.
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ANALYSIS OF FATIGUE CRACK GROWTH WITH OVERLOAD EFFECTS THROUGH T-STRESS
Fatigue crack is a major concern to all industries for safety reasons. Fatigue life predictions for structural components such as railways or turbine disks are based on fracture mechanics analysis. Such components are inevitably submitted to underloads or overloads. The aim of this paper is to provide a DIC-BASED experimental analysis of overload 2D fatigue cracks using higher order terms in the Williams’ series expansion.
The prediction of the fatigue life of these components is often based on crack propagation calculations. However, overloads and underloads perturb steady state fatigue crack growth conditions and affect the growth rates by retarding or accelerating growth. The application of overloads generates complex effects on the crack behavior which induce delays that are difficult to predict. The mechanisms that have been proposed to explain retardation after tensile overload include, e.g. residual stress, crack closure and plasticity ahead of the crack tip.
In this work, based on DIC we use full-field measurements to obtain LEFM crack tip features (Stress Intensity Factor and T-stress). Therefore, with these crack tip features, we propose to analyze the T-stress effect on the crack growth propagation.
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FATIGUE LIFE OF LASER POWDER BED FUSION (L-PBF) ALSI10MG ALLOY: EFFECTS OF SURFACE ROUGHNESS AND POROSITY
The fatigue life of components manufactured by the laser powder bed fusion (L-PBF) process is dominated by the presence of defects, such as surface roughness and internal porosity. The present study focuses on the relative effect of surface roughness and porosity in determining the fatigue properties of AlSi10Mg alloy produced by L-PBF built in the Z direction for as-built (ASB), machined (M) and machined & polished (M&P) conditions. As-built L-PBF samples possess higher surface roughness (1.5-2 µm) compared to the machined (0.8-1.0 µm) or polished ones (0.3-0.75 µm). For ASB samples, surface roughness was found to be the dominant factor affecting fatigue life. However, for M or M&P samples with relatively low surface roughness, the subsurface porosity becomes the dominant factor affecting fatigue failure rather than variations in the surface roughness. The pore size and location effects are analysed using linear elastic fracture mechanics theory, and the critical stress intensity factors (SIF) for L-PBF AlSi10Mg alloy samples are estimated.
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HIGH CYCLE FATIGUE OF AM PRODUCED HOT WORK TOOL STEEL
Additive manufacturing as a mean to produce near net shape components of metal alloys has evolved in many commercial applications during the last decade. Still, development of additive processes and alloy grades requires new research knowledge. In the present study focus is on advanced high strength martensitic steels and fatigue properties. They are used in demanding tooling and high performance applications where high strength and toughness, both static and dynamic, are required. Fatigue strength and failure defect distributions of one AISI H13 AM grade and one corresponding ingot cast and forged grade have been characterized and modelled.
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PREDICTING MICROSTRUCTURE-SENSITIVE FRACTURE BEHAVIOR IN AM IN625 USING A DAMAGE-ENABLED ELASTO-VISCOPLASTIC FFT FRAMEWORK
In this work, we use a large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) code enhanced with a continuum damage mechanics model to predict failure response of a subcontinuum mesoscale tensile specimen in the context of the National Institute of Standards and Technology (NIST) 2022 Additive Manufacturing Benchmark (AM-Bench) Challenge. In the Challenge, participants were provided with data from X-ray computed tomography and electron backscattered diffraction (EBSD) for an AM IN625 sample and asked to predict stress and strain response and locations of necking and fracture. To account for uncertainty in the subsurface microstructure, we instantiated 10 semi-synthetic microstructures using a Potts model in a modified version of the open-source software SPPARKS. While all 10 models maintain identical surface grain structure, surface roughness, and internal porosity, their subsurface grain structures vary due to randomness in the microstructure-generation procedure. Results from the blind predictions using the LS-EVPFFT framework are compared to the experimental results. Lessons learned are discussed.
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ON THE MECHANISTIC ORIGINS OF THE INCREASED HYDROGEN ENVIRONMENT-ASSISTED CRACKING SUSCEPTIBILITY OF AM 17-4PH STEEL
Literature results indicate that the hydrogen environment-assisted cracking susceptibility of additively manufactured (AM) 17-4PH steel fabricated using laser powder bed fusion is increased relative to comparable wrought 17-4PH. This study seeks to understand the mechanistic origins of this increased susceptibility through a detailed examination of near-crack deformation, alloy microstructure, and hydrogen-metal interactions. Based on these data, it is determined that sub-micrometer porosity present in the AM material provides a primary contribution to the degradation in HEAC resistance. The mechanistic basis for the influence of porosity is considered in the context of an existing model for HEAC. The implications of these findings on the broader AM community are then discussed.
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