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Laser Powder Bed Fusion (PBF-LB/M) of AISI 316L stainless steel has gained popularity due to its exceptional capacity to produce complex geometries and hierarchical microstructures, which can increase the yield strength while maintaining good ductility. Nevertheless, owing to high thermal gradients encountered during the process, the as printed 316L stainless steel often exhibit microstructural heterogeneities and residual stresses, which can limit its performance in demanding environments. Hence, employing heat treatments which balance the reduction of residual stresses while retaining improved static strength may be beneficial in various scenarios and applications. This study investigates the impact of post-processing heat treatments on the microstructure of 316L stainless steel manufactured via PBF-LB/M, along with its correlation with micro-hardness properties. To this end, 6 different heat treatments, i.e., 450 °C for 4h, 700 °C for 1h, 700 °C for 3h, 800 °C for 1h, 800 °C for 3h, and 900 °C for 1h, were applied to different specimens and Vickers hardness measurements (HV1) were performed in all states. At 800 °C, although the cellular structure appears to be retained, there is an observable increase in cellular size. However, while treatments exceeding 900 °C indicate no significant grain growth compared to other conditions, the cellular structure is entirely dissolved, which leads to a reduced Vickers hardness. The effect of the heat treatments on other microstructural features such as grain size and morphology, melt pool boundaries (MPB), crystallographic texture, chemical segregation, dispersoids and phase stability are also discussed in the present work
The general term additive manufacturing (AM) encompasses processes that enable the production of parts in a single manufacturing step. Among these, laser powder bed fusion (PBF-LB) is one of the most commonly used to produce metal components. In essence, a laser locally melts powder particles in a powder bed layer-by-layer to incrementally build a part. As a result, this process offers immense manufacturing flexibility and superior geometric design capabilities compared to conventional processes. However, these advantages come at a cost: the localized processing inevitably induces large thermal gradients, resulting in the formation of large thermal stress during manufacturing. In the best case, residual stress remains in the final parts produced as a footprint of this thermal stress. Since residual stress is well known to exacerbate the structural integrity of components, their assessment is important in two respects. First, to optimize process parameter to minimize residual stress magnitudes. Second, to study their effect on the structural integrity of components (e.g., validation of numerical models). Therefore, a reliable experimental assessment of residual stress is an important factor for the successful application of PBF-LB. In this context, diffraction-based techniques allow the non-destructive characterization of the residual stress. In essence, lattice strain is calculated from interplanar distances by application of Braggs law. From the known lattice strain, macroscopic stress can be determined using Hooke’s law. To allow the accurate assessment of the residual stress distribution by such methods, a couple of challenges in regard of the characteristic PBF-LB microstructures need to be overcome.
This presentation highlights some of the challenges regarding the accurate assessment of residual stress in PBF-LB on the example of the Nickel-based alloy Inconel 718. The most significant influencing factors are the use of the correct diffraction elastic constants, the choice of the stress-free reference, and the consideration of the crystallographic texture. Further, it is shown that laboratory X-ray diffraction methods characterizing residual stress at the surface are biased by the inherent surface roughness. Overall, the impact of the characteristic microstructure is most significant for the selection of the correct diffraction elastic constants. In view of the localized melting and solidification, no significant gradients of the stress-free reference are observed, even though the cell-like solidification sub-structure is known to be heterogeneous on the micro-scale.
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
Laser powder bed fusion (PBF-LB/M) of metallic alloys is a layer-wise additive manufacturing process that provides significant scope for more efficient designs of components, benefiting performance and weight, leading to efficiency improvements for various sectors of industry. However, to benefit from these design freedoms, knowledge of the high produced induced residual stress and mechanical property anisotropy associated with the unique microstructures is critical. X-ray and neutron diffraction are considered the benchmark for non-destructive characterization of surface and bulk internal residual stress. The latter, characterized by the high penetration power in most engineering alloys, allows for the use of a diffraction angle close to 90° enabling a near cubic sampling volume to be specified. However, the complex microstructures of columnar growth with inherent crystallographic texture typically produced during PBF-LB/M of metallics present significant challenges to the assumptions typically required for time efficient determination of residual stress. These challenges include the selection of an appropriate set of diffraction elastic constants and a representative lattice plane suitable for residual stress analysis. In this contribution, the selection of a suitable lattice plane family for residual stress analysis is explored. Furthermore, the determination of an appropriate set of diffraction and single-crystal elastic constants depending on the underlying microstructure is addressed.
In-situ loading experiments have been performed at the Swiss Spallation Neutron Source with the main scope to study the deformation behaviour of laser powder bed fused Inconel 718. Cylindrical tensile bars have been subjected to an increasing mechanical load. At pre-defined steps, neutron diffraction data has been collected. After reaching the yield limit, unloads have been performed to study the accumulation of intergranular strain among various lattice plane families.
Development of representative test specimens by thermal history transfer in laser powder bed fusion
(2024)
The use of components manufactured by laser powder bed fusion (PBF LB/M) and subjected to fatigue loading is still hampered by the uncertainty about the homogeneity of the process results. Numerous influencing factors including the component’s geometry contribute to the risk of process instability and resulting inhomogeneity of properties. This drastically limits the comparability of different built parts and requires expensive full component testing. The thermal history as the spatiotemporal temperature distribution has been identified as a major cause for flaw formation. Therefore, it can be hypothesized that a similar thermal history between components and test specimens enhances their comparability. Following this assumption, a strategy is developed to transfer the intrinsic preheating temperature as a measure of comparability of thermal histories from a region of interest of a complex component to a simple test specimen. This transfer concept has been successfully proved by the use of FEM-based macroscale thermal simulations, validated by calibrated infrared thermography. An adoption of the specimen manufacturing process by the adjustment of the inter layer times was established to manufacture specimens which are representatives of a specific region of a large-scale component in terms of the thermal history similarity criterion. The concept is schematically illustrated in Figure 1 and was demonstrated using a pressure vessel geometry from the chemical industry.
Direct energy deposition additive manufacturing technologies that utilize an electric arc have great potential for generating large volume metal components. However, selecting process parameters that yield the desired near net shape design and requested mechanical component behavior is not a trivial task due to the complex relationship between all process parameters and material characteristics. This presentation exemplifies the application of a newly developed solid welding wire doped with TiB to enhance grain refinement in the deposited metal for additive manufacturing based on DED-Arc of high-strength precipitation hardening AlMgSi-aluminum alloys. It is worth noting that the solid wire is the result of our preliminary metallurgical studies on grain refinement in aluminum weld metal.
Consequently, research focuses on the correlation between process parameters and component quality to understand the underlying mechanisms. This is crucial for evaluating a robust process parameter space that yields component quality in line with corresponding standards which are mainly taken from welding technology.
Specifically, we examine component quality by analyzing pore size and distribution, as well as grain morphology. To enhance the mechanical properties of the deposited metal, a post-weld heat treatment was conducted, comprising of solution treatment, quenching, and artificial aging. The study also evaluates the effects of various heat treatment strategies on the final mechanical properties of the material.
To demonstrate the applicability of 3D metal printing of high-strength aluminium alloys, a more complex demonstrator was created. It has been shown that DED-Arc can produce high-volume aluminium parts with the same quality as the corresponding subtractive processing strategy.
Additionally, the entire additive manufacturing chain has been digitally integrated, enabling traceability of all relevant process steps, which is essential for reliable subsequent quality assessment.
This paper explores combining a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor and a video camera to create a virtual gas camera for methane leak detection. This provides a low-to-zero-cost extension of typical TDLAS gas tomography systems. A prototype setup mounted on a ground robot is evaluated. Results acquired using a simulated methane leak show the feasibility of the virtual gas camera, accurately detecting methane leaks by overlaying concentrations onto a visual image. While the acquisition time is significantly longer than for traditional gas cameras, potential enhancements are discussed. The study concludes that the virtual gas camera is feasible and useful, despite its longer acquisition time. It serves as a valuable software-only addition to typical TDLAS gas tomography systems, offering quickly-available on-site data augmentation for visual leak assessment at low-to-zero cost.
This study explores the acceleration of material design in the concrete industry, focusing on improving carbonation resistance, a key factor in the durability of concrete structures. Traditional tests for carbonation resistance are lengthy, but with the construction industry aiming for sustainable production, finding a balance between carbonation resistance and CO2 footprint is crucial. Our research employs two innovative methods: 1. Applying the Sequential Learning App for Materials Discovery (SLAMD), an AI materials design framework, to an extensive dataset of real-world concrete compositions to selectively test materials that meet market demands: maximum durability, optimal eco-durability, and the best cost-durability trade-off. 2. Investigating 1H Nuclear Magnetic Resonance (NMR) relaxometry as a quick alternative for characterizing carbonation behavior, as it saves time compared to traditional tests and assesses the complete material's pore space. Specific NMR features are then integrated into the material design model, with the model's performance compared against traditional approaches. The results of our study are compelling, demonstrating that materials can be precisely tailored to meet specific requirements with minimal data points. This marks a significant stride in the concrete industry, indicating that NMR-based, low-fidelity surrogate characterizations, combined with a focused, data-driven design approach, can substantially accelerate the development of durable, sustainable concrete mixtures.
In this presentation, the results of the determination of the diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 are presented. The analysis is based on high-energy synchrotron diffraction experiments performed at the Deutsches Elektronen-Synchrotron. It is shown that the characteristic microstructure of laser powder bed fused Inconel 718 impacts the elastic anisotropy and therefore the diffraction and single-crystal elastic constants. Finally, the consequences on the diffraction-based residual stress determination of laser powder bed fused Inconel 718 are discussed.
Ultrasonic guided waves interacting with complex geometrical features are of high interest in the SHM field. For example, investigations into the extent to which a small change in defect geometry affects wave propagation have applications in Probability of Detection and defect reconstruction. These fields have to be supported by numerical tools aiming to retrieve accurate and reliable results and, thus, more realistic modeling.
Due to the short wavelengths of ultrasonic waves and the relatively large domains in which the waves propagate, fine grid resolution for the entire domain is usually not possible due to limited computational resources. One solution is to partition the domain into different subdomains and use a specific, efficient approach for each subdomain.
This contribution shows a combination of methods that aims to study these wave defect interactions in an elastic media. Firstly we introduce high-order 3D meshes that can resolve very fine geometrical details and are based on an Octree discretisation technique that employs special transition shape functions to resolve the hanging nodes that may appear due to the nature of the method. Afterward, the Octree mesh is embedded in a prismatic wave-guide based on the semi-analytical formulation of the SBFEM in 3D. To couple the different domains, we employ the mortar method, which enforces the continuity of the wave field across the internal boundaries of the domains. Examples show the power of the approach especially when it comes to parametric analysis.
For structural health monitoring systems or non-destructive testing, it is crucial to study the interactions of ultrasonic-guided waves with inhomogeneities or damage in structural components. Simulation of these interactions poses a challenge.
After the wave-damage interaction, the numerical model must reproduce features like mode conversion or wave scattering. Mathematically, damages are discontinuities in a computational domain, and each interacts diversely depending on its geometrical features. We propose a quadtree-based meshing in the current contribution to capture these geometrical
characteristics.
This kind of discretisation approach requires special techniques to couple cells of different sizes since, after a quadtree decomposition, the problem of so-called hanging nodes may arise. Transition elements based on high-order transfinite shape functions are used to solve this issue. The advantage is that these elements allow the correct coupling of the cells while retaining a high-order interpolation. Moreover, the reuse of the dynamic stiffness matrices can be exploited based on the similarity of the cells. This procedure renders the approach very efficient.
Examples show the scattering characteristics of different guided wave modes after interacting with inhomogeneities and discontinuities in a plate.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field material characterization by X-ray imaging is presented. The principle of X-ray Computed Tomography (XCT) is explained. The multiple examples of application of quantitative analysis by XCT are reported, such as additive manufacturing, Li-ion battery, concrete research.
To evaluate the durability of new alternative cement compositions, it is important to examine the internal transport of moisture through these materials. For this purpose, mortars were prepared from different types of cement and capillary suction experiments were carried out. The moisture transport was studied with an NMR tomograph and compared with weight easurements. With the tomograph, the total moisture input could be determined, as well as the moisture content within the samples non-destructively and spatially resolved. This allows precise observation of the moisture fronts. The tomograph was also used to determine the capillary transport
coefficient.
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
Residual stresses Analysis in Additively Manufactured alloys using neutron diffraction (L-PBF)
(2023)
An overview of recent progress at BAM of residual stress analysis in additively manufactured, in particular Laser Powder Bed Fusion of metallics materials, using neutron diffraction will be presented. This will cover important topics of the stress-free reference, the diffraction elastic moduli and principal stress determination.
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing.
This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing.
Structural alloys are largely employed in key industrial sectors and their demand is predicted to rise rapidly for the next decades. Most of these materials require a large amount of energy for extraction and manufacturing, which causes the emission of greenhouse gases and other pollutants. Therefore, strategies for improving the sustainability of structural metallic alloys are urgently needed.
Additive Manufacturing (AM), in particular Laser Powder Bed Fusion (PBF-LB/M), aims to be a sustainable manufacturing process, as it allows the build-up of complex geometry in near net-shape from 3D models, while minimizing material waste and the energy required for the process and post-process treatments.
Nevertheless, the application of additively manufactured parts in structural safety-relevant applications is still hindered by the poor fatigue performance. The cause of this has been mainly attributed to the presence of manufacturing defects and surface roughness. Therefore, a huge effort has been made to optimize the process parameters and to introduce post-process treatments to minimize the defect content. However, material flaws cannot be fully eliminated, but these can be considered in a damage tolerance framework for the prediction of the fatigue performance of additively manufactured metallic materials, which is essential for part design and qualification.
This work aims at presenting different modelling strategies for the prediction of the fatigue limit of AM metals. Simple empirical models and more complex models based on fatigue short crack propagation are proposed. The investigated material is an AlSi10Mg alloy fabricated by PBF-LB/M and subjected to two different low-temperature heat-treatments (265°C for 1 h and 300°C for 2h). The results show that the models can provide good approximation of the fatigue limits and help in the interpretation of the scatter of fatigue data.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). Also, two successful research project in collaboration with CAM2, Sweden are presented.
The capability to produce complexly and individually shaped metallic parts is one of the main advantages of the laser powder bed fusion (PBF LB/M) process. Development of material and machine specific process parameters is commonly based on results acquired from small cubic test coupons of about 10 mm edge length. Such cubes are usually used to conduct an optimization of process parameters to produce dense material. The parameters are then taken as the basis for the manufacturing of real part geometries. However, complex geometries go along with complex thermal histories during the manufacturing process, which can significantly differ from thermal conditions prevalent during the production of simply shaped test coupons. This may lead to unexpected and unpredicted local inhomogeneities of the microstructure and defect distribution in the final part and it is a root cause of reservations against the use of additive manufacturing for the production of safety relevant parts. In this study, the influence of changing thermal conditions on the resulting melt pool depth of 316L stainless steel specimens is demonstrated. A variation of thermo-graphically measured intrinsic preheating temperatures was triggered by an alteration of inter layer times and a variation of cross section areas of specimens for three distinct sets of process parameters. Correlations between the preheating temperature, the melt pool depth, and occurring defects were analyzed. The limited expressiveness of the results of small density cubes is revealed throughout the systematic investigation. Finally, a clear recommendation to consider thermal conditions in future process parameter optimizations is given.
In this paper, we demonstrate the value of 1H NMR
relaxometry for studying the hydration of clinker-reduced, more
climate-friendly cementitious binders. The results were obtained
on typical CEM I cements and samples containing two different
reactive agricultural ashes as well as non-reactive biochars as
supplementary cementitious materials. The findings prove that
time-resolved NMR measurements provide valuable additional
information when combined with classical heat flow calorimetry.