The rapid manufacturing technology selective laser melting (SLM) is among others employed to build individually designed bone implants out of the bioresorbable composite material polylactide/β-tricalcium phosphate (PDLLA/β-TCP). Degradation of PDLLA, which commences at temperatures >215 °C and results in unwanted changes in resorption kinetics, has to be avoided. This is achieved by keeping the process temperatures as low as possible while still producing dense parts. Processing strategies are investigated using a thermal model of the SLM process solved with finite element analysis. A mesh refinement algorithm is implemented, reducing the computation time by a factor of approximately 5, making the full three-dimensional modeling of the SLM process possible. The thermal and optical properties of PDLLA/β-TCP are measured focusing on the absorption of laser radiation during the process. The model predicts the lowest degradation when a top hat beam profile in combination with a reduced layer thickness and the respective laser power are used. The results of the theoretical investigation are used to fabricate dense parts (density >98%) out of the material PLDLA/β-TCP.

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Scale-resolving simulations, such as large eddy simulations, have become affordable tools to investigate the flow in turbomachinery components. The resulting time-resolved flow field is typically analyzed using first- and second-order statistical moments. However, two sources of uncertainty are present when recording statistical moments from scale-resolving simulations: the influence of initial transients and statistical errors due to the finite number of samples. In this paper, both are systematically analyzed for several quantities of engineering interest using time series from a long-time large eddy simulation of the low-pressure turbine cascade T106C. A set of statistical tools to either remove or quantify these sources of uncertainty is assessed. First, the Marginal Standard Error Rule is used to detect the end of the initial transient. The method is validated for integral and local quantities and guidelines on how to handle spatially varying initial transients are formulated. With the initial transient reliably removed, the statistical error is estimated based on standard error relations considering correlations in the time series. The resulting confidence intervals are carefully verified for quantities of engineering interest utilizing cumulative and simple moving averages. Furthermore, the influence of periodic content from large scale vortex shedding on the error estimation is studied. Based on the confidence intervals, the required averaging interval to reduce the statistical uncertainty to a specific level is indicated for each considered quantity.