Data-driven prediction of the high-dimensional thermal history in directed energy deposition processes via recurrent neural networks

2018 ◽  
Vol 18 ◽  
pp. 35-39 ◽  
Author(s):  
Mojtaba Mozaffar ◽  
Arindam Paul ◽  
Reda Al-Bahrani ◽  
Sarah Wolff ◽  
Alok Choudhary ◽  
...  
Author(s):  
Jianyi Li ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris

In modeling and simulating thermo-mechanical behavior in a directed energy deposition process, it often needs to compute the temperature field evolved in the deposition process since thermal history in the deposition process would affect part geometry as well as microstructure, material properties, residual stress, and distortion of the final part. This paper presents an analytical computation of temperature field evolved in a directed energy deposition process, using a single-bead wall as an illustrating example. Essentially, the temperature field is computed by superposition of the temperature fields generated by the laser source as well as induced from each of the past beads, where the transient solution to a moving heat source in a semi-infinite body is applied to describe each individual temperature field. For better characterization of cooling effect (temperature contribution from a past bead), a pair of positive and negative virtual heat sources is assigned for each past bead. In addition, mirrored heat sources through a reflexion technique are introduced to define the adiabatic boundaries of the part being built and to account for the substrate thickness. In the end, three depositions of Ti-6AL-4V walls with different geometries and inter-layer dwell times on an Optomec® laser engineered net shaping (LENS) system are used to validate the proposed analytical computation, where predicted temperatures at several locations of the depositions show reasonable agreement with the in situ temperature measurements, with the average prediction error less than 15%. The proposed analytical computation for temperature field in directed energy deposition could be potentially used in model-based feedback control for thermal history in the deposition, which could affect microstructure evolution and other properties of the final part.


Author(s):  
Tobias Hauser ◽  
Raven T. Reisch ◽  
Tobias Kamps ◽  
Alexander F. H. Kaplan ◽  
Joerg Volpp

AbstractAcoustic emissions in directed energy deposition processes such as wire arc additive manufacturing and directed energy deposition with laser beam/metal are investigated within this work, as many insights about the process can be gained from this. In both processes, experienced operators can hear whether a process is running stable or not. Therefore, different experiments for stable and unstable processes with common process anomalies were carried out, and the acoustic emissions as well as process camera images were captured. Thereby, it was found that stable processes show a consistent mean intensity in the acoustic emissions for both processes. For wire arc additive manufacturing, it was found that by the Mel spectrum, a specific spectrum adapted to human hearing, the occurrence of different process anomalies can be detected. The main acoustic source in wire arc additive manufacturing is the plasma expansion of the arc. The acoustic emissions and the occurring process anomalies are mainly correlating with the size of the arc because that is essentially the ionized volume leading to the air pressure which causes the acoustic emissions. For directed energy deposition with laser beam/metal, it was found that by the Mel spectrum, the occurrence of an unstable process can also be detected. The main acoustic emissions are created by the interaction between the powder and the laser beam because the powder particles create an air pressure through the expansion of the particles from the solid state to the liquid state when these particles are melted. These findings can be used to achieve an in situ quality assurance by an in-process analysis of the acoustic emissions.


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