Modelling the complex evaporated gas flow and its impact on particle spattering during laser powder bed fusion

The additive manufacturing (AM) of metals is becoming an increasingly important production process with the potential to replace traditional techniques such as casting. Laser Powder Bed Fusion (LPBF) is used in many applications to print metal parts from powder. The metal powder is heated locally with sufficient laser radiation that the liquid melt easily reaches its boiling temperature, which leads to a metallic vapour jet that can entrain both powder bed particles and molten droplets. The small size of laser-matter interaction site makes a detailed experimental analysis of the process challenging. Synchrotron X-ray imaging experiments are one of the few methods which can capture the dynamic melting and solidification processes. Comparing such experiments with computer simulations of the process is an important approach in order to better understand the manufacturing process and to analyse the influence of process parameters on the evaporated gas jet and the subsequent impact on particle ejection, leading to potentially reduced AM component quality. The melting and solidification of the metal powder is simulated using an Eulerian multiphase approach based on a control volume discretization of powder bed and substrate and a volume of liquid separation from melt and gas phase. The gas phase modelled as an ideal gas reaches velocities up to 100 m/s. Lagrangian particle tracking in the simulation demonstrates that the velocity fields calculated by the Eulerian multi-phase approach in combination with a standard drag-force model lead to particle accelerations in good agreement with those measured experimentally. In order to avoid numerical laborious Lagrangian calculations, a direct method to compare an Eulerian multiphase simulation with synchrotron X-ray experiments was introduced and validated. This approach is used to analyse the influence of process parameters including laser power and laser speed on the maximal acceleration of particles from the melt pool area. While the particle acceleration increases linearly with line energy in the conduction mode, a linear decrease of the acceleration with increasing line energy can be found in the transition mode before the acceleration increases again with line energy in the keyhole mode

Supporting Engineering Processes Utilizing Service-Oriented Grid Technology

Speeding up knowledge-intensive core processes in engineering and increas-ing the quality of their results is becoming more and more decisive, since economic pressure from national and international competitors and customers is rising. In particular, these demands exceed the organizational and infrastructural capacities of small and medium-sized enterprises (SME) by far. Hence, combining complementary core competencies across organizational boundaries is crucial for an enterprise's continuing success. Efficient and economically reasonable support of knowledge-intensive core processes in virtual organisations is therefore a predominant requirement for future IT infrastructures. The paradigm shift to service-orientation in Grid middleware opens the possibility to provide such support along the product lifecycle by employing a flexible software development approach, namely to compose applications from standard components, promising easier development and modification of Grid applications. In this paper, a service-oriented Grid computing approach is presented which aims at supporting distributed business processes in industry (see section 2 for industrial scenarios) from top level modelling, workflow design and exe-cution to actual Grid service code (presented in section 3). Parts of this gap between processes and code can be bridged by semi-automatically generated Grid service code. Orchestration of these Grid services is also automated by using a Grid-enabled workflow engine (see section 3). The feasibility of the proposed approach is demonstrated by presenting an exemplary process chain from the casting industry (see full paper)

Efficient Silicon Device Simulation with the Local Iterative Monte Carlo Method

The Local Iterative Monte Carlo technique (LIMO) is used for an effective simulation of hot electron distributions in silicon MOSFETs. This new Monte Carlo approach yields an efficient use of the computational resources due to a different iteration scheme. In addition the necessary computation time can be further reduced by a reuse of the computational expensive MC step simulation results in the iteration process. The later possibility is investigated in detail in this work. Results for short channel MOSFETs demonstrates that correct two-dimensional hot electron distributions can be calculated by LIMO within I hour on a standard work station

Influence of Electron-Electron Interaction on Electron Distributions in Short Si-MOSFETs Analysed Using the Local Iterative Monte Carlo Technique

The effects of electron–electron interaction on the electron distribution in n-channel metal-oxide-semiconductor field-effect transistors (MOSFETs) are studied using the Local Iterative Monte Carlo (LIMO) technique. This work demonstrates that electron–electron scattering can be efficiently treated within this technique. The simulation results of a 90 nm Si-MOSFET are presented. We observe an increase of the high energy tail of the electron distribution at the transition from channel to drain