Multiscale modelling of vascular tumour growth in 3D: the roles of domain size & boundary condition

We investigate a three-dimensional multiscale model of vascular tumour growth, which couples blood flow, angiogenesis, vascular remodelling, nutrient/growth factor transport, movement of, and interactions between, normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. In particular, we determine how the domain size, aspect ratio and initial vascular network influence the tumour's growth dynamics and its long-time composition. We establish whether it is possible to extrapolate simulation results obtained for small domains to larger ones, by constructing a large simulation domain from a number of identical subdomains, each subsystem initially comprising two parallel parent vessels, with associated cells and diffusible substances. We find that the subsystem is not representative of the full domain and conclude that, for this initial vessel geometry, interactions between adjacent subsystems contribute to the overall growth dynamics. We then show that extrapolation of results from a small subdomain to a larger domain can only be made if the subdomain is sufficiently large and is initialised with a sufficiently complex vascular network. Motivated by these results, we perform simulations to investigate the tumour's response to therapy and show that the probability of tumour elimination in a larger domain can be extrapolated from simulation results on a smaller domain. Finally, we demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour

Analysis of melt pool characteristics and process parameters using a coaxial monitoring system during directed energy deposition in additive manufacturing

The growing number of commercially available machines for laser deposition welding show the growing acceptance and importance of this technology for industrial applications. Their increasing usage in research and production requires process stability and user-friendly handling. A commercially available DMG MORI LT 65 3D hybrid machine used in combination with a CCD-based coaxial temperature measurement system was utilized in this work to investigate what information relating to the intensity distribution of melt pool surfaces could be appropriate to draw conclusions about process conditions. In this study it is shown how the minimal required specific energy for a stable process can be determined, and it is indicated that the evolution of a plasma plume depends on thermal energy within the base material. An estimated melt pool area-calculated by the number of pixels (NOP) with intensities larger than a fixed, predefined threshold-builds the main measure in analysing images from the process camera. The melt pool area and its temporal variance can also serve as an indicator for an increased working distance

Image-based algorithm for nozzle adhension detection in powder-fed directed-energy deposition: Paper presented at ICALEO 2019, International Congress on Applications of Lasers and Electro-Optics, October 7-10, 2019, Orlando, Florida

The rapidly growing technological innovation of Directed Energy Deposition (DED) leads to an increase in part complexity as well as quality and mechanical properties of manufacturable components. However, the variety of process parameters and influencing factors still requires skilled operators, who observe the machine tools. For an unobserved use of deposition welding machines, well parametrised and validated monitoring systems have to analyse the process to detect irregularities and finally initiate a machine stop. This study focuses on nozzle adhesions that frequently occur when tool or high-speed steels are processed. This effect leads to decreasing quality or ultimately to a failure of the whole welding process. In this work, we present an algorithm and the corresponding parametrisation to automatically detect nozzle adhesions based on images from a coaxial camera, integrated in the laser head. The algorithm is based on a detailed image analysis from which temporal and spatial patterns are derived. In particular, the algorithm calculates a nozzle adhesion indicator based on the heat intensity distribution in an experimentally derived shaped area on the inner nozzle boundary. It is parametrised in such a way that processcritical adhesions are detected. The algorithm was parametrised using an experimental setup with four materials: Stainless steel (X2CrNiMo17-12-2), tool steel (X35CrMoMn7-2-1), high-speed steel (HS6-5-2C) and the nickel-based alloy NiCr19NbMo