Additive Manufacturing

The contact person for this project is Stefan Kollmannsberger (This email address is being protected from spambots. You need JavaScript enabled to view it.).

Additive Manufacturing:

Additive Manufacturing, also called 3D printing, is a general term for the production of artifacts by successively adding material in a layerwise fashion. There are numerous processes such as fused deposition modelling, stereolithography and laser power bed fusion. We focus on modelling the process of laser power bed fusion. In this process, a highly focused laser selectively melts powder. Thereby the local state of the material changes from powder to liquid to solid. Once one layer of powder has been treated selectively, a new layer of powder is added. The process is repeated until the final artifact emerges. An example of the process and selected artifacts is given below

The process

A showcase product and an enginnering application: a heat exchanger These pictures were taken at our cooperation partner the Institute of Photonic Technologies https://www.lpt.tf.fau.de/

We are working on the simulation of the processes and products generated by additive manufacturing. Aspects of the simulation of products of additive manufacturing are discussed here. For the simulation of the process we use a set of coupled differential equations describing the transient thermo-elasto-plastic process. For the discretization we developed a special variant of the finite cell method [1]. Herein we embed the physical domain into a fictitious domain. We track the evolution of the fictitious domain as well as its state (powder, liquid or solid) in time and space using fast octree-like discretizations. The diffusive temperature field is computed in the sense of the finite cell method on a separate grid equipped with high-order finite elements. This grid refines adaptively towards the impact zone of the laser beam and de-refines in regions where the heat has already dissipated.

Computational Setting

Example Computation

We are also working on the computation of residual stresses which are inherent to this process. This computational analysis forms the basis for the optimization of the process on the scale of the melt pool as well as on the macroscopic scale.

Conferences:

We have organized the first ECCOMAS conference on the Simulation for Additive Manufacturing in 2017 @TUM.

We are also heavily involved in the organization of the follow up ECCOMAS conference on Simulation for Additive Manufacturing 2019 in Pavia, Italy.

Publications



• Paolini, A.; Kollmannsberger, S.; Rank, E. Show abstract Additive manufacturing in construction: A review on processes, applications, and digital planning methods
  Additive Manufacturing, 2019
  DOI: 10.1016/j.addma.2019.100894 - Status: Postprint / reviewed
  
  
  
  The application of additive manufacturing (AM) in construction has been increasingly studied in recent years. Large robotic arm- and gantry-systems have been created to print building parts using aggregate-based materials, metals, or polymers. Significant benefits of AM are the automation of the production process, a high degree of design freedom, and the resulting potential for optimization. However, the building components and 3D-printing processes need to be modeled appropriately. In this paper, the current state of AM in construction is reviewed. AM processes and systems as well as their application in research and construction projects are presented. Moreover, digital methods for planning 3D-printed building parts and AM processes are described.
  
  
  
• Kollmannsberger, S.; Özcan, A.; Carraturo, M.; Zander, N.; Rank, E. Show abstract A hierarchical computational model for moving thermal loads and phase changes with applications to Selective Laser Melting
  Computers & Mathematics with Applications 75 (5), pp. 1483-1497, 2018
  DOI: 10.1016/j.camwa.2017.11.014 - Status: Verlagsversion / published
  
  
  
  Computational heat transfer analysis often involves moving fluxes which induce traveling fronts of phase change coupled to one or more field variables. Examples are the transient simulation of melting, welding or of additive manufacturing processes, where material changes its state and the controlling fields are temperature and structural deformation. One of the challenges for a numerical computation of these processes is their multi-scale nature with a highly localized zone of phase transition which may travel over a large domain of a body. Here, a transient local adaptation of the approximation, with not only a refinement at the phase front, but also a de-refinement in regions, where the front has past is of advantage because the de-refinement can assure a bounded number of degrees of freedom which is independent from the traveling length of the front. We present a computational model of this process which involves three novelties: a) a very low number of degrees of freedom which yet yields a comparatively high accuracy. The number of degrees of freedom is, additionally, kept practically constant throughout the duration of the simulation. This is achieved by means of the multi-level hp-finite element method. Its exponential convergence is verified for the first time against a semi-analytic, three-dimensional transient linear thermal benchmark with a traveling source term which models a laser beam. b) A hierarchical treatment of the state variables. To this end, the state of the material is managed on a separate, octree-like grid. This material grid may refine or coarsen independently of the discretization used for the temperature field. This methodology is verified against an analytic benchmark of a melting bar computed in three dimensions in which phase changes of the material occur on a rapidly advancing front. c) The combination of these technologies to demonstrate its potential for the computational modeling of selective laser melting processes. To this end, the computational methodology is extended by the finite cell method which allows for accurate simulations in an embedded domain setting. This opens the new modeling possibility that neither a scan vectors no a layer of material needs to conform to the discretization of the finite element mesh but can form only a fraction within the discretization of the field and state variables.
  
  
  
• Özcan, A.; Kollmannsberger, S.; Jomo, J; De Lorenzis, L.; Rank, E. Residual stresses in metal deposition modeling: discretizations of higher order
  Computers and Mathematics with Applications, 2018 - Status: Postprint / reviewed