A Line Heat Input Model for Additive Manufacturing

Author(s):  
Jeff Irwin ◽  
P. Michaleris

A line input model has been developed which makes the accurate modeling of powder bed processes more computationally efficient. Goldak’s ellipsoidal model has been used extensively to model heat sources in additive manufacturing, including lasers and electron beams. To accurately model the motion of the heat source, the simulation time increments must be small enough such that the source moves a distance smaller than its radius over the course of each increment. When the source radius is small and its velocity is large, a strict condition is imposed on the size of time increments regardless of any stability criteria. In powder bed systems, where radii of 0.1 mm and velocities of 500 mm/s are typical, a significant computational burden can result. The line heat input model relieves this burden by averaging the heat source over its path. This model allows the simulation of an entire heat source scan in just one time increment. However, such large time increments can lead to inaccurate results. Instead, the scan is broken up into several linear segments, each of which is applied in one increment. In this work, time increments are found that yield accurate results (less than 10 % displacement error) and require less than 1/10 of the CPU time required by Goldak’s moving source model. A dimensionless correlation is given that can be used to determine the necessary time increment size that will greatly decrease the computational time required for any powder bed simulation while maintaining accuracy.

Author(s):  
Jeff Irwin ◽  
P. Michaleris

A line input (LI) model has been developed, which makes the accurate modeling of powder bed processes more computationally efficient. Goldak's ellipsoidal model has been used extensively to model heat sources in additive manufacturing (AM), including lasers and electron beams. To accurately model the motion of the heat source, the simulation time increments must be small enough such that the source moves a distance smaller than its radius over the course of each increment. When the source radius is small and its velocity is large, a strict condition is imposed on the size of time increments regardless of any stability criteria. In powder bed systems, where radii of 0.1 mm and velocities of 500 mm/s are typical, a significant computational burden can result. The line heat input model relieves this burden by averaging the heat source over its path. This model allows the simulation of an entire heat source scan in just one time increment. However, such large time increments can lead to inaccurate results. Instead, the scan is broken up into several linear segments, each of which is applied in one increment. In this work, time increments are found that yield accurate results (less than 10% displacement error) and require less than 1/10 of the central processing unit (CPU) time required by Goldak's moving source model. A dimensionless correlation is given that can be used to determine the necessary time increment size that will greatly decrease the computational time required for any powder bed simulation while maintaining accuracy.


2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Shijie Dai ◽  
Miao Gong ◽  
Liwen Wang ◽  
Tao Wang

Heat input is a crucial factor affecting the quality in blade additive manufacturing repairing. First, a moving heat source model was established, and through numerical analysis and experimental comparison, the optimal geometric parameters of the heat source model for ultrathin blade repair were obtained. Second, a heat transfer model is established based on the optimal heat source model. By analyzing the thermophysical properties of different alloys, the heat input range of the blade was calculated. By heat transfer calculation under different heat inputs, the heat transfer model of blade repair was optimized. Then, a mathematical model of additive height is established. The optimized heat transfer model is used to solve the temperature distribution of the additive section with time under different wire feeding speeds through numerical analysis, which further reduced the heat input range. Third, the experiments are carried out based on the results of numerical analysis. The evolution law of the microstructure and heat input rate of the additive manufacturing zone was revealed, and the optimal heat input parameters were obtained. Under the optimal parameters, the segregation zone disappeared; hence, the test data were close to the base metal, and the additive manufacturing zone achieved better quality. The results and methods are of great guiding significance for the optimization design in additive manufacturing repair of the aero blades. The study also contributes to carrying out a series of research on heat transfer of ultrathin nickel-based alloy welding.


2020 ◽  
Vol 106 (7-8) ◽  
pp. 3367-3379 ◽  
Author(s):  
Shahriar Imani Shahabad ◽  
Zhidong Zhang ◽  
Ali Keshavarzkermani ◽  
Usman Ali ◽  
Yahya Mahmoodkhani ◽  
...  

Author(s):  
Reza Alizadeh ◽  
Liangyue Jia ◽  
Anand Balu Nellippallil ◽  
Guoxin Wang ◽  
Jia Hao ◽  
...  

AbstractIn engineering design, surrogate models are often used instead of costly computer simulations. Typically, a single surrogate model is selected based on the previous experience. We observe, based on an analysis of the published literature, that fitting an ensemble of surrogates (EoS) based on cross-validation errors is more accurate but requires more computational time. In this paper, we propose a method to build an EoS that is both accurate and less computationally expensive. In the proposed method, the EoS is a weighted average surrogate of response surface models, kriging, and radial basis functions based on overall cross-validation error. We demonstrate that created EoS is accurate than individual surrogates even when fewer data points are used, so computationally efficient with relatively insensitive predictions. We demonstrate the use of an EoS using hot rod rolling as an example. Finally, we include a rule-based template which can be used for other problems with similar requirements, for example, the computational time, required accuracy, and the size of the data.


Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2666 ◽  
Author(s):  
Abhilash Kiran ◽  
Josef Hodek ◽  
Jaroslav Vavřík ◽  
Miroslav Urbánek ◽  
Jan Džugan

The rapid growth of Additive Manufacturing (AM) in the past decade has demonstrated a significant potential in cost-effective production with a superior quality product. A numerical simulation is a steep way to learn and improve the product quality, life cycle, and production cost. To cope with the growing AM field, researchers are exploring different techniques, methods, models to simulate the AM process efficiently. The goal is to develop a thermo-mechanical weld model for the Directed Energy Deposition (DED) process for 316L stainless steel at an efficient computational cost targeting to model large AM parts in residual stress calculation. To adapt the weld model to the DED simulation, single and multi-track thermal simulations were carried out. Numerical results were validated by the DED experiment. A good agreement was found between predicted temperature trends for numerical simulation and experimental results. A large number of weld tracks in the 3D solid AM parts make the finite element process simulation challenging in terms of computational time and large amounts of data management. The method of activating elements layer by layer and introducing heat in a cyclic manner called a thermal cycle heat input was applied. Thermal cycle heat input reduces the computational time considerably. The numerical results were compared to the experimental data for thermal and residual stress analyses. A lumping of layers strategy was implemented to reduce further computational time. The different number of lumping layers was analyzed to define the limit of lumping to retain accuracy in the residual stress calculation. The lumped layers residual stress calculation was validated by the contour cut method in the deposited sample. Thermal behavior and residual stress prediction for the different numbers of a lumped layer were examined and reported computational time reduction.


Proceedings ◽  
2019 ◽  
Vol 27 (1) ◽  
pp. 24
Author(s):  
D’Accardi ◽  
Altenburg ◽  
Maierhofer ◽  
Palumbo ◽  
Galietti

One of the most advanced technologies of Metal Additive Manufacturing (AM) is the Laser Powder Bed Fusion process (L-PBF), also known as Selective Laser Melting (SLM). This process involves the deposition and fusion, layer by layer, of very fine metal powders and structure and quality of the final component strongly depends on several processing parameters, for example the laser parameters. Due to the complexity of the process it is necessary to assure the absence of defects in the final component, in order to accept or discard it. Thermography is a very fast non-destructive testing (NDT) technique. Its applicability for defect detection in AM produced parts would significantly reduce costs and time required for NDT, making it versatile and very competitive.


Author(s):  
M Shafiqur Rahman ◽  
Paul J. Schilling ◽  
Paul D. Herrington ◽  
Uttam K. Chakravarty

Electron beam additive manufacturing (EBAM) is a powder-bed fusion additive manufacturing (AM) technology that can make full density metallic components using a layer-by-layer fabrication method. To build each layer, the EBAM process includes powder spreading, preheating, melting, and solidification. The quality of the build part, process reliability, and energy efficiency depends typically on the thermal behavior, material properties, and heat source parameters involved in the EBAM process. Therefore, characterizing those properties and understanding the correlations among the process parameters are essential to evaluate the performance of the EBAM process. In this study, a three-dimensional computational fluid dynamics (CFD) model with Ti-6Al-4V powder was developed incorporating the temperature-dependent thermal properties and a moving conical volumetric heat source with Gaussian distribution to conduct the simulations of the EBAM process. The melt pool dynamics and its thermal behavior were investigated numerically, and results for temperature profile, melt pool geometry, cooling rate and variation in density, thermal conductivity, specific heat capacity, and enthalpy were obtained for several sets of electron beam specifications. Validation of the model was performed by comparing the simulation results with the experimental results for the size of the melt pool.


Author(s):  
Samuel Lorin ◽  
Julia Madrid ◽  
Rikard Söderberg ◽  
Kristina Wärmefjord

Abstract Laser welding is a common technique for joining metals in many manufacturing industries. Due to the heat input and the resulting melting and solidification, the parts deform causing residual distortion and residual stresses. To assure the geometrical and functional quality of the product, Computational Welding Mechanics (CWM) is often employed in the design phase to predict the outcome of different design proposals. Furthermore, CWM can be used to design the welding process with the objective of assuring the quality of the weld. However, welding is a complex multi-physical process and in a design process it is typically not feasible, for example, to employ fluid simulation of the weld pool in order to predict deformation, especially if a set of design proposals is under investigation. Instead, what is used is a heat source that emulates the heat input from the melt pool. However, standard heat sources are typically not flexible enough to capture the fusion zone for deep keyhole mode laser welding. In this paper, a new heat source model for keyhole mode laser welding is presented. In an industrial case study, a number of bead on plate welds have been employed to compare standard weld heat sources and develop the new heat source model. The proposed heat source is based on a combination of standard heat sources. From the study, it was concluded that the standard heat sources could not predict the observed melted zone for certain industrial application while the new heat source was able to do so.


Author(s):  
Zhonghai Jin ◽  
Andrew Lacis

AbstractA computationally efficient method is presented to account for the horizontal cloud inhomogeneity by using a radiatively equivalent plane parallel homogeneous (PPH) cloud. The algorithm can accurately match the calculations of the reference (rPPH) independent column approximation (ICA) results, but use only the same computational time required for a single plane parallel computation. The effective optical depth of this synthetic sPPH cloud is derived by exactly matching the direct transmission to that of the inhomogeneous ICA cloud. The effective scattering asymmetry factor is found from a pre-calculated albedo inverse look-up-table that is allowed to vary over the range from -1.0 to 1.0. In the special cases of conservative scattering and total absorption, the synthetic method is exactly equivalent to the ICA, with only a small bias (about 0.2% in flux) relative to ICA due to imperfect interpolation in using the look-up tables. In principlel, the ICA albedo can be approximated accurately regardless of cloud inhomogeneity. For a more complete comparison, the broadband shortwave albedo and transmission calculated from the synthetic sPPH cloud and averaged over all incident directions, have the RMS biases of 0.26% and 0.76%, respectively, for inhomogeneous clouds over a wide variation of particle size. The advantages of the synthetic PPH method are that (1) it is not required that all the cloud subcolumns have uniform microphysical characteristic, (2) it is applicable to any 1D radiative transfer scheme, and (3) it can handle arbitrary cloud optical depth distributions and an arbitrary number of cloud subcolumns with uniform computational efficiency.


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