Scalable Thermal Simulation of Powder Bed Fusion

2021 ◽  
pp. 1-17
Author(s):  
Yaqi Zhang ◽  
Vadim Shapiro ◽  
Paul Witherell
Keyword(s):  
Spatial Data ◽  
Manufacturing Process ◽  
Thermal Simulation ◽  
Powder Bed Fusion ◽  
Time Step ◽  
Powder Bed ◽  
Melt Pool ◽  
Scan Path ◽  
History Of ◽  
Metallic Parts

Abstract Powder bed fusion (PBF) has become a widely used additive manufacturing technology to produce metallic parts. In PBF, thermal field evolution during the manufacturing process plays an important role in determining both geometric and mechanical properties of the fabricated parts. Thermal simulation of the PBF process is computationally challenging due to the geometric complexity of the manufacturing process and the inherent computational complexity that requires a numerical solution at every time increment of the process. We propose a new thermal simulation of the PBF process based on the laser scan path. Our approach is unique in that it simulates the thermal history of the process on the discretization of the geometry implied by the process plan, as opposed to voxelization or meshing of the design geometry. The discretization is based on the laser scan path, and the thermal model is formulated directly in terms of the manufacturing primitives. An element growth mechanism is introduced to simulate the evolution of the melt pool during the manufacturing process. A spatial data structure, called contact graph, is used to represent the discretized domain and capture all thermal interactions. The simulation is localized through exploiting spatial and temporal locality. This limits the need to update to at most a constant number of elements at each time step, which implies that the proposed simulation not only scales to handle 3D components of arbitrary complexity but also can achieve real-time performance. The simulation is fully implemented and validated against experimental data and other simulation results.

Scalable Thermal Simulation of Powder Bed Fusion

2020 ◽  
Author(s):  
Yaqi Zhang ◽  
Vadim Shapiro ◽  
Paul Witherell
Keyword(s):  
Spatial Data ◽  
Manufacturing Process ◽  
Thermal Field ◽  
Three Dimensional ◽  
Thermal Simulation ◽  
Powder Bed Fusion ◽  
Time Step ◽  
Powder Bed ◽  
Field Evolution ◽  
Scan Path

Abstract Powder bed fusion (PBF) has become a widely used additive manufacturing (AM) technology to produce metallic parts. Since the PBF process is driven by a moving heat source, consistency in part production, particularly when varying geometries, has proven difficult. Thermal field evolution during the manufacturing process determines both geometric and mechanical properties of the fabricated components. Simulations of the thermal field evolution can provide insight into desired process parameter selection for a given material and geometry. Thermal simulation of the PBF process is computationally challenging due to the geometric complexity of the manufacturing process and the inherent computational complexity that requires a numerical solution at every time increment of the process. We propose a new thermal simulation of the PBF process based on the laser scan path. Our approach is unique in that it does not restrict itself to simulations on the part design geometry, but instead simulates the formation of the geometry based on the process plan of a part. The implication of this distinction is that the simulations are in tune with the as-manufactured geometry, meaning that calculations are more aligned with the process than the design, and thus could be argued is a more realistic abstraction of real-world behavior. The discretization is based on the laser scan path, and the thermal model is formulated directly in terms of the manufacturing primitives. An element growth mechanism is introduced to simulate the evolution of a melt pool during the manufacturing process. A spatial data structure, called contact graph, is used to represent the discretized domain and capture all thermal interactions during the simulation. The simulation is localized through exploiting spatial and temporal locality, which is based on known empirical data. This limits the need to update to at most a constant number of elements at each time step. This implies that the proposed simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. The simulation is fully implemented and validated against experimental data and other simulation results.

A Scalable Framework for Process-Aware Thermal Simulation of Additive Manufacturing Processes

2021 ◽  
pp. 1-16
Author(s):  
Yaqi Zhang ◽  
Vadim Shapiro ◽  
Paul Witherell
Keyword(s):  
Additive Manufacturing ◽  
Heat Source ◽  
Spatial Data ◽  
Manufacturing Process ◽  
Thermal Simulation ◽  
Physical Parameters ◽  
Moving Heat Source ◽  
Time Step ◽  
Fused Deposition ◽  
Am Processes

Abstract Many additive manufacturing (AM) processes are driven by a moving heat source. Thermal field evolution during the manufacturing process plays an important role in determining both geometric and mechanical properties of the fabricated parts. Thermal simulation of AM processes is challenging due to the geometric complexity of the manufacturing process and inherent computational complexity that requires a numerical solution at every time increment of the process. We propose a new general computational framework that supports scalable thermal simulation at path scale of any AM process driven by a moving heat source. The proposed framework has three novel ingredients. First, the path-level discretization is process-aware, which is based on the manufacturing primitives described by the scan path and the thermal model is formulated directly in terms of manufacturing primitives. Second, a spatial data structure, called contact graph, is used to represent the discretized domain and capture all possible thermal interactions during the simulation. Finally, the simulation is localized based on specific physical parameters of the manufacturing process, requiring at most a constant number of updates at each time step. The latter implies that the constructed simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. To demonstrate the efficacy and generality of the framework, it has been successfully applied to build thermal simulations of two different AM processes, fused deposition modeling (FDM) and powder bed fusion (PBF).

Towards Thermal Simulation of Powder Bed Fusion on Path Level

2019 ◽  
Author(s):  
Yaqi Zhang ◽  
Vadim Shapiro ◽  
Paul Witherell
Keyword(s):  
Manufacturing Process ◽  
Thermal Simulation ◽  
Experimental Results ◽  
Intermediate Step ◽  
Valuable Insight ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Thermal Simulations ◽  
Element Method

Abstract Powder bed fusion (PBF) is a widely used additive manufacturing (AM) technology to produce metallic parts. Understanding the relationships between process parameter settings and the quality of finished parts remains a critical research question. Developing this understating involves an intermediate step: Process parameters, such as laser power and scan speed, influence the ongoing process characteristics, which then affect the final quality of the finished parts. Conventional approaches to addressing those challenges such as powder-based simulations (e.g., discrete element method (DEM)) and voxel-based simulations (e.g., finite element method (FEM)) can provide valuable insight into process physics. Those types of simulations, however, are not well-suited to handle realistic manufacturing plans due to their high computational complexity. Thermal simulations of the PBF process have the potential to implement that intermediate step. Developing accurate thermal simulations, however, is difficult due to the physical and geometric complexities of the manufacturing process. We propose a new, meso-scale, thermal-simulation, which is built on the path-level interactions described by a typical process plan. Since our model is rooted in manufactured geometry, it has the ability to produce scalable, thermal simulations for evaluating realistic process plans. The proof-of-concept simulation result is validated against experimental results in the literature and experimental results from National Institute of Standards and Technology (NIST). In our model, the laser-scan path is discretized into elements, and each element represents the newly melted material. An element-growth mechanism is introduced to simulate the evolution of the melt pool and its thermal characteristics during the manufacturing process. The proposed simulation reduces computational demands by attempting to capture the most important thermal effects developed during the manufacturing process. Those effects include laser-energy absorption, thermal interaction between adjacent elements and elements within the underneath substrate, thermal convection and radiation, and powder melting.

scholarly journals Finite Element Modeling of Melt Pool Dynamics in Laser Powder Bed Fusion of 316L Stainless Steel

2021 ◽  
Author(s):  
Juan Trejos-Taborda ◽  
Luis Reyes-Osorio ◽  
Carlos Garza ◽  
Patricia del Carmen Zambrano-Robledo ◽  
Omar Eduardo Lopez-Botello
Keyword(s):  
Numerical Model ◽  
Relative Error ◽  
Laser Scanning ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
History Of ◽  
Dynamics Stability

Abstract In Laser Powder Bed Fusion (LPBF), melt pool dynamics stability determines the overall quality of a manufactured component. In this work, a numerical model of the LPBF process was developed in order to study and fully understand the behavior of the melt pool dynamics. The numerical model takes into account most of the manufacturing parameters, thermophysical properties, an enhanced thermal conductivity approach and a volumetric heat source in order to precisely mimic LPBF. This research assumes that the energy emitted by the laser interacts with the metal powder with an absorptivity gradient through the layer thickness in order to calculate the thermal history of the process and the evolution of the melt pool dimensions. The obtained results determined that melt pool dimensions follow a thermal pattern, which is caused by the laser scanning strategy of the LPBF process. A new effective width criterion was proposed in the present research in order to accurately relate both calculated and measured dimensions of the melt pool, reducing the relative error of the model and obtaining data scattering with a standard deviation of ±7.21 µm and a relative error of 2.92%.

scholarly journals Process characterization and analysis of ceramic powder bed fusion

2021 ◽  
Author(s):  
Kevin Florio ◽  
Dario Puccio ◽  
Giorgio Viganò ◽  
Stefan Pfeiffer ◽  
Fabrizio Verga ◽  
...  
Keyword(s):  
High Speed ◽  
Ceramic Powder ◽  
Integrating Sphere ◽  
Alumina Powder ◽  
Powder Bed Fusion ◽  
Single Track ◽  
Ceramic Powders ◽  
Pure Alumina ◽  
Powder Bed ◽  
Melt Pool

AbstractPowder bed fusion (PBF) of ceramics is often limited because of the low absorptance of ceramic powders and lack of process understanding. These challenges have been addressed through a co-development of customized ceramic powders and laser process capabilities. The starting powder is made of a mix of pure alumina powder and alumina granules, to which a metal oxide dopant is added to increase absorptance. The performance of different granules and process parameters depends on a large number of influencing factors. In this study, two methods for characterizing and analyzing the PBF process are presented and used to assess which dopant is the most suitable for the process. The first method allows one to analyze the absorptance of the laser during the melting of a single track using an integrating sphere. The second one relies on in-situ video imaging using a high-speed camera and an external laser illumination. The absorption behavior of the laser power during the melting of both single tracks and full layers is proven to be a non-linear and extremely dynamic process. While for a single track, the manganese oxide doped powder delivers higher and more stable absorptance. When a full layer is analyzed, iron oxide-doped powder is leading to higher absorptance and a larger melt pool. Both dopants allow the generation of a stable melt-pool, which would be impossible with granules made of pure alumina. In addition, the present study sheds light on several phenomena related to powder and melt-pool dynamics, such as the change of melt-pool shape and dimension over time and powder denudation effects.

scholarly journals Optimization of Laser Powder Bed Fusion Processing Using a Combination of Melt Pool Modeling and Design of Experiment Approaches: Density Control

2019 ◽  
Vol 3 (1) ◽  
pp. 21 ◽  
Author(s):  
Morgan Letenneur ◽  
Alena Kreitcberg ◽  
Vladimir Brailovski
Keyword(s):  
Scanning Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Density Prediction ◽  
Melt Pool ◽  
Density Control ◽  
Pool Model ◽  
Conventional Material ◽  
Prediction Approach

A simplified analytical model of the laser powder bed fusion (LPBF) process was used to develop a novel density prediction approach that can be adapted for any given powder feedstock and LPBF system. First, calibration coupons were built using IN625, Ti64 and Fe powders and a specific LPBF system. These coupons were manufactured using the predetermined ranges of laser power, scanning speed, hatching space, and layer thickness, and their densities were measured using conventional material characterization techniques. Next, a simplified melt pool model was used to calculate the melt pool dimensions for the selected sets of printing parameters. Both sets of data were then combined to predict the density of printed parts. This approach was additionally validated using the literature data on AlSi10Mg and 316L alloys, thus demonstrating that it can reliably be used to optimize the laser powder bed metal fusion process.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

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