Periodic Reporting for period 2 - MA.D.AM (Modelling Assisted Solid State Materials Development and Additive Manufacturing)
Periodo di rendicontazione: 2022-12-01 al 2024-05-31
The rapid development of additive manufacturing (AM) as a high-potential and flexible manufacturing technology has opened the possibility of producing parts with customized performance. To utilize the full potential of AM, value-added materials with the desired customized chemistry and properties are demanded, in particular for aerospace applications. Ideally, the subsequent AM process should maintain the customized or tailored properties of the materials, i.e. without losses of alloying elements due to volatilization or phase segregation. Rather, the deposition process should further improve the properties of the final AM product.
The MA.D.AM project aims to establish novel scientific knowledge for the fabrication of customized aluminum wires and their application for AM via a fully solid-state based processing route, allowing the production of AM parts with customized mechanical properties, providing at the same time sustainable solution for lightweight design. For this purpose, innovative solid-state materials development and AM processes are utilized to obtain alloys beyond known borders. The solid-state Friction Extrusion process allows for generating phases via thermo-mechanical processing, i.e. severe plastic deformation and elevated temperature, leading to so far unexplored microstructural states, enabling the production of high-performance wire material with tailored properties. To avoid microstructural deterioration and to preserve or even improve the properties of the designed rods, Solid State Layer Deposition, i.e. Friction Surfacing is employed as AM process. To exploit the full capabilities of these processes, the underlying physical relationships along the complete manufacturing chain will be explored via physical models to assist in the experimental alloy and process development. Concepts of machine learning will be employed to establish a digital twin of the process chain.
Therefore, the overarching objective of this project is to establish this experimental reality paired with numerical approaches, leading to a digital twin of the full process chain to ensure its translation to different alloys and AM strategies and to obtain a so far unavailable decryption of the composition-process-(micro)structure-property relationships.
The MA.D.AM project aims to establish novel scientific knowledge for the fabrication of customized aluminum wires and their application for AM via a fully solid-state based processing route, allowing the production of AM parts with customized mechanical properties, providing at the same time sustainable solution for lightweight design. For this purpose, innovative solid-state materials development and AM processes are utilized to obtain alloys beyond known borders. The solid-state Friction Extrusion process allows for generating phases via thermo-mechanical processing, i.e. severe plastic deformation and elevated temperature, leading to so far unexplored microstructural states, enabling the production of high-performance wire material with tailored properties. To avoid microstructural deterioration and to preserve or even improve the properties of the designed rods, Solid State Layer Deposition, i.e. Friction Surfacing is employed as AM process. To exploit the full capabilities of these processes, the underlying physical relationships along the complete manufacturing chain will be explored via physical models to assist in the experimental alloy and process development. Concepts of machine learning will be employed to establish a digital twin of the process chain.
Therefore, the overarching objective of this project is to establish this experimental reality paired with numerical approaches, leading to a digital twin of the full process chain to ensure its translation to different alloys and AM strategies and to obtain a so far unavailable decryption of the composition-process-(micro)structure-property relationships.
Friction extrusion experiments were performed to study the process characteristics and microstructural evolution of aluminium alloys. Two fundamentally distinct extrusion types have been identified, one leading to a fully homogenous recrystallized fine-grained wire material. A novel material flow model has been proposed for this case, illustrating a layer-by-layer pattern in terms of material flow. To investigate the precipitation kinetics in-depth, the first friction extrusion set-up for in-situ synchrotron measurements has been developed. Furthermore, the effect of different feedstock materials was investigated, identifying the characteristics and different requirements for performing the friction extrusion process efficiently. Friction consolidation has shown the potential to enhance the properties of the extruded wires and might serve as a pre-processing step.
In terms of solid-state AM, the friction surfacing process was studied, gaining an in-depth understanding for single and multi-layer structures. Next to analyses of the temperature evolution and process efficiency, the effect of pre- and post-processing techniques in terms of consolidating volumetric defects was successfully investigated, allowing the fabrication of large-scale structures. Based on in-depth microstructure analyses of the deposited material, a periodic variation in the average grain size along the build direction could be proven. This is attributed to the complex material flow, resulting in varying strain and temperature conditions along the height of each individual layer during deposition, representing a characteristic feature of the process independent of the specific alloy.
In terms of modelling, a primary thermodynamic assessment of the unary systems of the considered aluminium alloys was performed via the CALPHAD method. A phase-field formalism for describing precipitation and the grain size evolution has been implemented. In terms of process simulation, a thermo-mechanical process simulation of friction extrusion has been validated against experimental data. A heat transfer model for friction surfacing has been developed, which has been employed to build a data-enhanced hybrid surrogate model, based on limited available experimental data. Shapley Additive Explanation values were used to evaluate the built machine learning model and most particular findings were confirmed by existing knowledge in literature, thereby allowing for an extension of this knowledge.
In terms of solid-state AM, the friction surfacing process was studied, gaining an in-depth understanding for single and multi-layer structures. Next to analyses of the temperature evolution and process efficiency, the effect of pre- and post-processing techniques in terms of consolidating volumetric defects was successfully investigated, allowing the fabrication of large-scale structures. Based on in-depth microstructure analyses of the deposited material, a periodic variation in the average grain size along the build direction could be proven. This is attributed to the complex material flow, resulting in varying strain and temperature conditions along the height of each individual layer during deposition, representing a characteristic feature of the process independent of the specific alloy.
In terms of modelling, a primary thermodynamic assessment of the unary systems of the considered aluminium alloys was performed via the CALPHAD method. A phase-field formalism for describing precipitation and the grain size evolution has been implemented. In terms of process simulation, a thermo-mechanical process simulation of friction extrusion has been validated against experimental data. A heat transfer model for friction surfacing has been developed, which has been employed to build a data-enhanced hybrid surrogate model, based on limited available experimental data. Shapley Additive Explanation values were used to evaluate the built machine learning model and most particular findings were confirmed by existing knowledge in literature, thereby allowing for an extension of this knowledge.
The project investigates and exploits the unique intrinsic potentials offered by the friction extrusion process. It will be shown that friction extrusion can produce value-added metallic materials with customized chemical composition and microstructures under the present thermo-mechanical processing conditions. Furthermore, it will be demonstrated that the following solid-state AM process will maintain or even improve the original high-performance properties of the wire. To assist the experimental developments, new modelling approaches and concepts will be employed at different length scales.
Until now, two fundamentally different extrusion types were identified during friction extrusion for the first time, one leading to a fully recrystallized wire material. This is related to established sticking friction condition at the interface between the extrusion die and charge material. Under these friction conditions, the material flow follows a layer-by-layer pattern, for which a novel material flow model has been proposed. It has been shown for the first time that the deposited aluminium alloys via friction surfacing show a characteristic periodic pattern in terms of grain size distribution across the building direction, which is related to the thermo-mechanical loading condition during the deposition process, independent of the specific alloy system. The process-characteristic phenomenon observed is expected to be in direct relation with the material flow during FS layer deposition, which is aspect of ongoing research. Furthermore, fundamental knowledge and understanding have been gained with perspective to the mechanical properties of multi-layer friction surfacing structures, especially with regard to the role of layer interfaces. For the first time, a data-enhanced hybrid surrogate model for the friction surfacing process has been established, requiring much less data compared to a fully experimentally based machine learning model.
Until now, two fundamentally different extrusion types were identified during friction extrusion for the first time, one leading to a fully recrystallized wire material. This is related to established sticking friction condition at the interface between the extrusion die and charge material. Under these friction conditions, the material flow follows a layer-by-layer pattern, for which a novel material flow model has been proposed. It has been shown for the first time that the deposited aluminium alloys via friction surfacing show a characteristic periodic pattern in terms of grain size distribution across the building direction, which is related to the thermo-mechanical loading condition during the deposition process, independent of the specific alloy system. The process-characteristic phenomenon observed is expected to be in direct relation with the material flow during FS layer deposition, which is aspect of ongoing research. Furthermore, fundamental knowledge and understanding have been gained with perspective to the mechanical properties of multi-layer friction surfacing structures, especially with regard to the role of layer interfaces. For the first time, a data-enhanced hybrid surrogate model for the friction surfacing process has been established, requiring much less data compared to a fully experimentally based machine learning model.