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Thermal transient problems, essential for modeling applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensive, thus limiting their applications, for example for model parameter estimation or online process control. Model order reduction, a solution to preserve the accuracy while reducing the computation time, is explored. This article addresses challenges in developing reduced order models using the proper generalized decomposition (PGD) for transient thermal problems with a specific treatment of the moving heat source within the reduced model. Factors affecting accuracy, convergence, and computational cost, such as discretization methods (finite element and finite difference), a dimensionless formulation, the size of the heat source, and the inclusion of material parameters as additional PGD variables are examined across progressively complex examples. The results demonstrate the influence of these factors on the PGD model’s performance and emphasize the importance of their consideration when implementing such models. For thermal example, it is demonstrated that a PGD model with a finite difference discretization in time, a dimensionless representation, a mapping for a moving heat source, and a spatial domain non-separation yields the best approximation to the full order model.
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a beadon-plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is developed, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control, and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the temperature.
The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.
Additive manufacturing (AM) of alkali-activated materials is a promising method for producing ceramic precursors, construction elements and other parts. A recently introduced AM process is laser-induced slip casting of lithium aluminate/microsilica slurries, which yields parts with excellent mechanical strengths. To clarify the underlying mechanisms, μ-Raman spectroscopy was applied to parts produced by the process, and the dissolution and hydration of lithium aluminate was studied inter alia using conventional and in-situ X-ray diffraction. The results show that significant dissolution of lithium aluminate occurs, particularly at increased temperatures during laser interaction, which leads to an increase of pH and precipitation of an akopovaite-like Li-Al-CO3 layered double hydroxide. The increase of the pH is likely to induce dissolution of the microsilica and possibly formation of a hydrous lithium aluminosilicate gel. These observations explain the strength evolution of the studied parts and can also aid the development and improvement of related AM methods.
Often 3D‐printing and additive manufacturing are mentioned as the 3rd industrial revolution. In this conjunction this book provides a brief overview on additively manufactured metal pieces.
This book fulfills its intension to serve as an educational guide, providing a holistic picture encompassing science, technology and applications for the real‐life use of Metal Additive Manufacturing.
This paper investigates fast and inexpensive measurement methods for defect detection in parts produced by Additive Manufacturing (AM) with special focus on lattice parts made of ceramics. By Lithography-based Ceramic Manufacturing, parts were built both without defects and with typical defects intentionally introduced. These defects were investigated and confirmed by industrial X-ray Computed Tomography. Alternative inexpensive methods were applied afterwards on the parts such as weighing, volume determination by Archimedes method and gas permeability measurement. The results showed, that defects resulting in around 20% of change in volume and mass could be separated from parts free of defects by determination of mass or volume. Minor defects were not detectable as they were in the range of process-related fluctuations. Permeability measurement did not allow to safely identify parts with defects. The measurement methods investigated can be easily integrated in AM process chains to support quality control.
Additively manufactured test specimens made of polyamide 12 (PA 12) by Laser Sintering as well as of acrylonitrile butadiene styrene (ABS) by Fused Layer Modelling, were characterised with active thermography directly after manufacturing and after artificial weathering. For this, two different excitation methods (flash and pulse heating) were used and compared, regarding their suitability for the detection of constructed and imprinted defects inside the test specimens. To increase the quality of the thermograms, data processing methods like thermal signal reconstruction (TSR) and Fourier Transformation after TSR were applied. To further investigate the long-term stability of the additively manufactured test specimens towards environmental stress, like UV radiation, heat, humidity, water contact and frost with active thermography, an artificial weathering test over 2000 hours (~3 months) was applied to the specimens. The monitoring of the changes in the optical properties of the weathered plastics was supplemented by spectral reflectance and UV/VIS spectroscopy.
Additive manufacturing of alkali-activated materials currently attracts a lot of attention, because of the possibility to produce customized high-performance elements for a range of applications, potentially being more resource-efficient than conventionally produced parts. Here, we describe a new additive manufacturing process for alkali-activated materials that is based on selective laser-heating of lithium aluminate/microsilica slurries. The new process-material combination allows to manufacture elements with complex geometries at high building rates and high accuracy. The process is versatile and transferrable to structures of sizes differing by orders of magnitude. The mechanical strength of the obtained materials was in the range of values reported for conventional metakaolin-based geopolymers, and superior to what has been hitherto reported for alkali-activated materials produced by additive manufacturing. This mechanical performance was obtained despite the fact that the degree of reaction of the lithium aluminate and the microsilica was low, suggesting that significant reactions took place only at the surface of the microsilica particles.