Numerical modelling of heat transfer and experimental validation in powder-bed fusion with the virtual domain approximation

Neiva, Eric; Chiumenti, Michele; Cervera, Miguel; Salsi, Emilio; Piscopo, Gabriele; Badia, Santiago; Martı́n, Alberto F.; Chen, Zhuoer; Lee, Caroline; Davies, Chris

doi:10.1016/j.finel.2019.103343

Cited by 34 publications

(36 citation statements)

References 29 publications

(51 reference statements)

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“…As described in Section 1 , examples of such features are acute overhangs and thin connections. Nevertheless, it is found that the findings based on this one-dimensional model are in agreement with the experimental observations reported by Davies [ 28 ] where thermocouples embedded inside an overhanging part recorded temperatures during the build. It is shown that the part temperatures remain in the range of 100–400

C at different locations below the topmost layer when the pre-heated baseplate temperature is at 100

C. This suggests that the one-dimensional insights can be extended to real parts.…”

Section: Thermal Modeling Simplifications and Comparison Metricssupporting

confidence: 91%

“…It is based on the thermal model previously presented by Chiumenti et al [ 27 ] for simulating material deposition in the laser material deposition (LMD) process. The same concept was later used for LPBF modeling in several publications [ 24 , 28 , 29 ]. The experimental validation of the model has been presented in Davies [ 24 ] where simulation results were compared with temperatures empirically recorded using in situ thermocouples placed inside the part during the LPBF process.…”

Section: Reference Thermal Lpbf Process Modelmentioning

confidence: 99%

“…As mentioned earlier, the modeling principles presented by Davies [ 24 ] and Davies [ 28 ] are used here which provides a basis for setting simulation parameters

and

. The two key ideas presented by Davies [ 24 ] and Davies [ 28 ] are as follows: Heating time

for a layer with area A equals the time that the laser would take for scanning that entire layer, i.e.,

where h is hatch spacing and v is laser scan velocity. Please note that by using this definition,

is calculated for each super layer and it depends on the local part geometry through layer scan areas.…”

Section: Reference Thermal Lpbf Process Modelmentioning

confidence: 99%

“…This ensures that the input energy is automatically scaled when using thicker lumped layers. It is demonstrated by Davies [ 24 ] and Davies [ 28 ] that the described simulation scheme is capable of predicting the real physical temperatures recorded during the process as captured using the thermocouples located as close as

mm away from the topmost layer.…”

Section: Reference Thermal Lpbf Process Modelmentioning

confidence: 99%

“…Nevertheless, available data from the literature can be used to make an estimate. For example, empirical observations from Davies [ 28 ] reported a temperature difference

C between the topmost point of the melt zone and a point located

mm below it, i.e.,

mm. Putting these values in Equation ( 10 ) gives |

.…”

Section: Thermal Modeling Simplifications and Comparison Metricsmentioning

confidence: 99%

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Fast Detection of Heat Accumulation in Powder Bed Fusion Using Computationally Efficient Thermal Models

et al. 2020

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The powder bed fusion (PBF) process is a type of Additive Manufacturing (AM) technique which enables fabrication of highly complex geometries with unprecedented design freedom. However, PBF still suffers from manufacturing constraints which, if overlooked, can cause various types of defects in the final part. One such constraint is the local accumulation of heat which leads to surface defects such as melt ball and dross formation. Moreover, slow cooling rates due to local heat accumulation can adversely affect resulting microstructures. In this paper, first a layer-by-layer PBF thermal process model, well established in the literature, is used to predict zones of local heat accumulation in a given part geometry. However, due to the transient nature of the analysis and the continuously growing domain size, the associated computational cost is high which prohibits part-scale applications. Therefore, to reduce the overall computational burden, various simplifications and their associated effects on the accuracy of detecting overheating are analyzed. In this context, three novel physics-based simplifications are introduced motivated by the analytical solution of the one-dimensional heat equation. It is shown that these novel simplifications provide unprecedented computational benefits while still allowing correct prediction of the zones of heat accumulation. The most far-reaching simplification uses the steady-state thermal response of the part for predicting its heat accumulation behavior with a speedup of 600 times as compared to a conventional analysis. The proposed simplified thermal models are capable of fast detection of problematic part features. This allows for quick design evaluations and opens up the possibility of integrating simplified models with design optimization algorithms.

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C at different locations below the topmost layer when the pre-heated baseplate temperature is at 100

C. This suggests that the one-dimensional insights can be extended to real parts.…”

Section: Thermal Modeling Simplifications and Comparison Metricssupporting

confidence: 91%

Section: Reference Thermal Lpbf Process Modelmentioning

confidence: 99%

“…As mentioned earlier, the modeling principles presented by Davies [ 24 ] and Davies [ 28 ] are used here which provides a basis for setting simulation parameters

and

. The two key ideas presented by Davies [ 24 ] and Davies [ 28 ] are as follows: Heating time

for a layer with area A equals the time that the laser would take for scanning that entire layer, i.e.,

where h is hatch spacing and v is laser scan velocity. Please note that by using this definition,

is calculated for each super layer and it depends on the local part geometry through layer scan areas.…”

Section: Reference Thermal Lpbf Process Modelmentioning

confidence: 99%

mm away from the topmost layer.…”

Section: Reference Thermal Lpbf Process Modelmentioning

confidence: 99%

“…Nevertheless, available data from the literature can be used to make an estimate. For example, empirical observations from Davies [ 28 ] reported a temperature difference

C between the topmost point of the melt zone and a point located

mm below it, i.e.,

mm. Putting these values in Equation ( 10 ) gives |

.…”

Section: Thermal Modeling Simplifications and Comparison Metricsmentioning

confidence: 99%

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Fast Detection of Heat Accumulation in Powder Bed Fusion Using Computationally Efficient Thermal Models

et al. 2020

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A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing

Neiva

Badia

Martı́n

et al. 2019

Numerical Meth Engineering

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Summary This work introduces an innovative parallel fully‐distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well known that virtual part design and qualification in additive manufacturing requires highly accurate multiscale and multiphysics analyses. Only high performance computing tools are able to handle such complexity in time frames compatible with time‐to‐market. However, efficiency, without loss of accuracy, has rarely held the centre stage in the numerical community. Here, in contrast, the framework is designed to adequately exploit the resources of high‐end distributed‐memory machines. It is grounded on three building blocks: (1) hierarchical adaptive mesh refinement with octree‐based meshes; (2) a parallel strategy to model the growth of the geometry; and (3) state‐of‐the‐art parallel iterative linear solvers. Computational experiments consider the heat transfer analysis at the part scale of the printing process by powder‐bed technologies. After verification against a three‐dimensional (3D) benchmark, a strong‐scaling analysis assesses performance and identifies major sources of parallel overhead. A third numerical example examines the efficiency and robustness of (2) in a curved 3D shape. Unprecedented parallelism and scalability were achieved in this work. Hence, this framework contributes to take on higher complexity and/or accuracy, not only of part‐scale simulations of metal or polymer additive manufacturing but also in welding, sedimentation, atherosclerosis, or any other physical problem where the physical domain of interest grows in time.

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Mitigation of residual stresses and microstructure homogenization in directed energy deposition processes

Chiumenti

Cervera

et al. 2022

Engineering with Computers

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In additive manufacturing (AM), residual stresses and microstructural inhomogeneity are detrimental to the mechanical properties of as-built AM components. In previous studies the reduction of the residual stresses and the optimization of the microstructure have been treated separately. Nevertheless, the ability to control both them at the same time is mandatory for improving the final quality of AM parts. This is the main goal of this paper. Thus, a thermo-mechanical finite element model is firstly calibrated by simulating a multi-track 40-layer Ti-6Al-4V block fabricated by Directed Energy Deposition (DED). Next, the numerical tool is used to study the effect of the baseplate dimensions and the energy density on both residual stresses and microstructure evolution. On the one hand, the results indicate that the large baseplate causes higher residual stresses but produces more uniform microstructures, and contrariwise for the smaller baseplate. On the other hand, increasing the energy density favors stress relief, but its effect fails to prevent the stress concentration at the built basement. Based on these results, two approaches are proposed to control both the stress accumulation and the metallurgical evolution during the DED processes: (i) the use of a forced cooling suitable for small baseplates and, (ii) the adoption of grooves when large baseplates are used.The numerical predictions demonstrated the effectiveness of the proposed manufacturing strategies.

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Numerical modelling of heat transfer and experimental validation in powder-bed fusion with the virtual domain approximation

Cited by 34 publications

References 29 publications

Fast Detection of Heat Accumulation in Powder Bed Fusion Using Computationally Efficient Thermal Models

Fast Detection of Heat Accumulation in Powder Bed Fusion Using Computationally Efficient Thermal Models

A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing

Mitigation of residual stresses and microstructure homogenization in directed energy deposition processes

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