Smoothed Particle Hydrodynamics Modeling of the Multi-layer Laser Powder Bed Fusion Process

Afrasiabi, Mohamadreza; Lüthi, C.; Bambach, Markus; Wegener, Konrad

doi:10.1016/j.procir.2022.04.045

Cited by 7 publications

(5 citation statements)

References 21 publications

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“…The melt pool dynamics at the point where the laser interacts with the material is of crucial importance for the mechanical properties of the finished part. We use the high-fidelity numerical simulations of an SLM process presented in [21] to model the melt pool length output as a function of the laser power input and extract a 5 dimensional discrete-time linear time invariant single input single output model…”

Section: Numerical Demonstrationmentioning

confidence: 99%

Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch

Balta

Iannelli

Smith

et al. 2022

2022 IEEE 61st Conference on Decision and Control (CDC)

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In Iterative Learning Control (ILC), a sequence of feedforward control actions is generated at each iteration on the basis of partial model knowledge and past measurements with the goal of steering the system toward a desired reference trajectory. This is framed here as an online learning task, where the decision-maker takes sequential decisions by solving a sequence of optimization problems having only partial knowledge of the cost functions. Having established this connection, the performance of an online gradient descent-based scheme using inexact gradient information is analyzed in the setting of static and dynamic regret, standard measures in online learning. Fundamental limitations of the scheme and its integration with adaptation mechanisms are further investigated, followed by numerical simulations on a benchmark ILC problem.

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Section: Numerical Demonstrationmentioning

confidence: 99%

Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch

Balta

Iannelli

Smith

et al. 2022

2022 IEEE 61st Conference on Decision and Control (CDC)

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“…To model the multi-layer LPBF process with a high degree of fidelity, our numerical simulation framework needs to solve the coupled thermo-fluid dynamics equations (including phase transitions) to capture the dynamic behaviour of the melt pool and model the recoating step (powder deposition and cooling between layers). We use an efficient meshfree modeling approach based on the SPH (smoothed particle hydrodynamics) method, developed by Afrasiabi et al [39]. We make the following assumptions:…”

Section: High-fidelity Multi-layer Lpbf Process Modelmentioning

confidence: 99%

“…1) Simulation domain is 2D 2) Heat source is volumetric and obeys the Beer-Lambert law 3) Laser moves with a constant speed 4) Flow of the molten material is incompressible 5) Gas phase and evaporation are not considered 6) All powder grains are spherical (i.e., circular in 2D) A brief description of the process simulator's main melt pool simulation and powder layer generation modules is presented next. A detailed description of the predictive capabilities and experimental validation of our SPH-based LPBF model for 2D and 3D single-track applications is available in [37], [39], [40].…”

Section: High-fidelity Multi-layer Lpbf Process Modelmentioning

confidence: 99%

“…where ⃗ f i denotes the collision force contribution of particle i computed from the non-linear Hertzian elastic contact formulation (including the repulsive and damping components) and ⃗ r iM is the distance vector to the grain's center of mass. See [39], [43] for more detailed derivation and implementation procedures.…”

Section: A Powder Layer Generation Modulementioning

confidence: 99%

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In-layer Thermal Control of a Multi-layer Selective Laser Melting Process

Liao‐McPherson¹,

Balta²,

Wüest³

et al. 2022

2022 European Control Conference (ECC)

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Selective Laser Melting (SLM) is an additive manufacturing technology that builds three dimensional parts by melting layers of metal powder together with a laser that traces out a desired geometry. SLM is popular in industry, however the inherent melting and re-solidification of the metal during the process can, if left uncontrolled, cause excessive residual stress, porosity, and other defects in the final printed parts. This paper presents a control-oriented thermal model of a multilayer SLM process and proposes a structured model reduction methodology with an associated reduced order model based in-layer controller to track temperature references. Simulation studies demonstrate that the controller is able to prevent layerto-layer heat buildup and that good closed-loop performance is possible using relatively low-order models.

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“…This Lagrangian method has demonstrated its ability to simulate different physical problems involving large material deformation and mold filling encountered in highpressure die casting [23][24][25], low-pressure vacuum molding [26], and gravity permanent mold casting [27,28], metal forging [29], additive manufacturing [30][31][32][33], cold spray [34,35], thermal spray [36,37], machining [38,39], as well as in high-pressure plastic [40][41][42] or composite injection molding [43]. Despite its promising range of applications, SPH still suffers from key issues that need to be addressed in order to improve its readiness level in order to facilitate its percolation towards other industrial applications.…”

Section: Introductionmentioning

confidence: 99%

Smoothed Particle Hydrodynamics Approach for Simulation of Non-Newtonian Flow of Feedstocks Used in Powder Injection Molding

Meiabadi,

Demers,

Dufresne

2023

Metals

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The present work aims to explore the ability to simulate flow patterns and the velocity field in the powder injection molding (PIM) process using the smoothed particle hydrodynamics (SPH) method. Numerical simulations were performed using the DualSPHysics platform. A feedstock formulated from 17-4 PH stainless steel powder (60 vol. % of powder) and a wax-based binder system was prepared to experimentally obtain its rheological properties that were implemented in DualSPHysics using two different viscosity models. The numerical simulations were calibrated, and then validated with real-scale injections using a laboratory injection press. During the calibration step, the feedstock flow momentum equation in the DualSPHysics code was modified and boundary friction coefficients at different injection rates were adjusted to create a frictional effect. During the validation step, these calibrated conditions were used to simulate the flow behavior into a more complex shape, which was compared with experimental measurements. Using an appropriate boundary friction factor, both the frictional effect of the boundaries and the stability of the numerical solution were taken into account to successfully demonstrate the ability of this meshless SPH method. The flow front length and feedstock velocity obtained in a complex cavity were satisfactorily predicted with relative differences of less than 15%.

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Smoothed Particle Hydrodynamics Modeling of the Multi-layer Laser Powder Bed Fusion Process

Cited by 7 publications

References 21 publications

Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch

Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch

In-layer Thermal Control of a Multi-layer Selective Laser Melting Process

Smoothed Particle Hydrodynamics Approach for Simulation of Non-Newtonian Flow of Feedstocks Used in Powder Injection Molding

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