Recent Developments of the Multiphysics Discrete Element Method for Additive Manufacturing Modeling and Simulation

2017 ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Additive Manufacturing ◽  
Discrete Element Method ◽  
Discrete Element ◽  
Additive Manufacture ◽  
Computational Tools ◽  
Computational Performance ◽  
Macro Scale ◽  
Recent Developments ◽  
Am Processes ◽  
Element Method

Recent years have seen a sharp increase in the development and usage of Additive Manufacturing (AM) technologies for a broad range of scientific and industrial purposes. The drastic microstructural differences between materials produced via AM and conventional methods has motivated the development of computational tools that model and simulate AM processes in order to facilitate their control for the purpose of optimizing the desired outcomes. This paper discusses recent advances in the continuing development of the Multiphysics Discrete Element Method (MDEM) for the simulation of AM processes. This particle-based method elegantly encapsulates the relevant physics of powder-based AM processes. In particular, the enrichment of the underlying constitutive behaviors to include thermoplasticity is discussed, as are methodologies for modeling the melting and re-solidification of the feedstock materials. Algorithmic improvements that increase computational performance are also discussed. The MDEM is demonstrated to enable the simulation of the additive manufacture of macro-scale components. Concluding remarks are given on the tasks required for the future development of the MDEM, and the topic of experimental validation is also discussed.

scholarly journals Discrete Element Method Analysis of the Spreading Mechanism and Its Influence on Powder Bed Characteristics in Additive Manufacturing

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 392
Author(s):  
Valerio Lampitella ◽  
Marco Trofa ◽  
Antonello Astarita ◽  
Gaetano D’Avino
Keyword(s):  
Additive Manufacturing ◽  
Discrete Element Method ◽  
Ad Hoc ◽  
Low Cost ◽  
Discrete Element ◽  
Spreading Process ◽  
Powder Bed ◽  
Physical Phenomena ◽  
Element Method

Laser powder bed fusion additive manufacturing is among the most used industrial processes, allowing for the production of customizable and geometrically complex parts at relatively low cost. Although different aspects of the powder spreading process have been investigated, questions remain on the process repeatability on the actual beam–powder bed interaction. Given the influence of the formed bed on the quality of the final part, understanding the spreading mechanism is crucial for process optimization. In this work, a Discrete Element Method (DEM) model of the spreading process is adopted to investigate the spreading process and underline the physical phenomena occurring. With parameters validated through ad hoc experiments, two spreading velocities, accounting for two different flow regimes, are simulated. The powder distribution in both the accumulation and deposition zone is investigated. Attention is placed on how density, effective layer thickness, and particle size distribution vary throughout the powder bed. The physical mechanism leading to the observed characteristics is discussed, effectively defining the window for the process parameters.

Characterization of powder bed generation in electron beam additive manufacturing by discrete element method (DEM)

2017 ◽  
Vol 4 (11) ◽  
pp. 11437-11440 ◽  
Author(s):  
Yufan Zhao ◽  
Yuichiro Koizumi ◽  
Kenta Aoyagi ◽  
Kenta Yamanaka ◽  
Akihiko Chiba
Keyword(s):  
Electron Beam ◽  
Additive Manufacturing ◽  
Discrete Element Method ◽  
Discrete Element ◽  
Powder Bed ◽  
Element Method

scholarly journals Load-Balancing Strategies in Discrete Element Method Simulations

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 79
Author(s):  
Shahab Golshan ◽  
Bruno Blais
Keyword(s):  
Load Balancing ◽  
Discrete Element Method ◽  
Large Scale ◽  
Discrete Element ◽  
Single Step ◽  
Rotating Drum ◽  
Optimum Load ◽  
Computational Performance ◽  
A Cell ◽  
Element Method

In this research, we investigate the influence of a load-balancing strategy and parametrization on the speed-up of discrete element method simulations using Lethe-DEM. Lethe-DEM is an open-source DEM code which uses a cell-based load-balancing strategy. We compare the computational performance of different cell-weighing strategies based on the number of particles per cell (linear and quadratic). We observe two minimums for particle to cell weights (at 3, 40 for quadratic, and 15, 50 for linear) in both linear and quadratic strategies. The first and second minimums are attributed to the suitable distribution of cell-based and particle-based functions, respectively. We use four benchmark simulations (packing, rotating drum, silo, and V blender) to investigate the computational performances of different load-balancing schemes (namely, single-step, frequent and dynamic). These benchmarks are chosen to demonstrate different scenarios that may occur in a DEM simulation. In a large-scale rotating drum simulation, which shows the systems in which particles occupy a constant region after reaching steady-state, single-step load-balancing shows the best performance. In a silo and V blender, where particles move in one direction or have a reciprocating motion, frequent and dynamic schemes are preferred. We propose an automatic load-balancing scheme (dynamic) that finds the best load-balancing steps according to the imbalance of computational load between the processes. Furthermore, we show the high computational performance of Lethe-DEM in the simulation of the packing of 108 particles on 4800 processes. We show that simulations with optimum load-balancing need ≈40% less time compared to the simulations with no load-balancing.

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