A thermal-mechanical finite element workflow for directed energy deposition additive manufacturing process modeling

Stender, Michael E.; Beghini, Lauren L.; Sugar, Joshua D.; Veilleux, Michael; Subia, Samuel R.; Smith, Thale R.; Marchi, Chris San; Brown, Arthur A.; Dagel, Daryl

doi:10.1016/j.addma.2018.04.012

Cited by 56 publications

(26 citation statements)

References 29 publications

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“…DED processes can be conducted in a controlled atmosphere or in the air. Since the feedstock is jetted via nozzles, DED consumes more powder to fabricate a specific part compared to SLM [53]. Figure 3 represents a schematic layout of an SLM mechanism and apparatus.…”

Section: Different Types Of Ammentioning

confidence: 99%

The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review

et al. 2019

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Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations.

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Section: Different Types Of Ammentioning

confidence: 99%

The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review

et al. 2019

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“…A fixed displacement boundary condition was applied at the bottom edge of the base plate to replicate the experiment condition. A detailed explanation of the coupled thermo-mechanical procedure was reported in [ 22 , 23 ]. A numerical simulation was conducted in the computer powered by Intel i7 six-core processor (3.20 GHz) with 32 GB Random Access Memory (RAM).…”

Section: Methodsmentioning

confidence: 99%

Numerical Simulation Development and Computational Optimization for Directed Energy Deposition Additive Manufacturing Process

et al. 2020

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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.

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“…The quality and the failure of the deposited part by the DED process are significantly influenced by thermo-mechanical characteristics, including temperature and residual stress distributions, in the vicinity of the irradiated region by the heat source during deposition of the material on the substrate [ 17 , 18 , 19 , 20 , 21 ]. To prevent the occurrence of defects in the fabricated part by the DED process, it is necessary to examine the thermo-mechanical behavior of the boundary region between the deposited region and the substrate through analytical and experimental approaches [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…To prevent the occurrence of defects in the fabricated part by the DED process, it is necessary to examine the thermo-mechanical behavior of the boundary region between the deposited region and the substrate through analytical and experimental approaches [ 18 , 19 ]. Stender et al proposed thermal-mechanical finite element (FE) flow for LENS process modeling [ 20 ]. They validated the FE model by comparing estimated temperature distributions by FEAs and measured temperature distributions by a forward-looking infrared (FLIR) camera.…”

Section: Introductionmentioning

confidence: 99%

Effects of Deposition Strategy and Preheating Temperature on Thermo-Mechanical Characteristics of Inconel 718 Super-Alloy Deposited on AISI 1045 Substrate Using a DED Process

et al. 2021

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Thermomechanical characteristics are highly dependent on the deposition strategy of the directed energy deposition (DED) process, including the deposition path, the interpass time, the deposition volume, etc., as well as the preheating condition of the substrate. This paper aims to investigate the effects of the deposition strategy and the preheating temperature on thermomechanical characteristics of Inconel 718 super-alloy deposited on an AISI 1045 substrate using a DED process via finite element analyses (FEAs). FE models for different deposition strategies and preheating temperatures are created to examine the thermomechanical behavior. Sixteen deposition strategies are adopted to perform FEAs. The heat sink coefficient is estimated from a comparison of temperature histories of experiments and those of FEAs to obtain appropriate FE models. The influence of deposition strategies on residual stress distributions in the designed model for a small volume deposition is examined to determine feasible deposition strategies. In addition, the effects of the deposition strategy and the preheating temperature on residual stress distributions of the designed part for large volume deposition are investigated to predict a suitable deposition strategy of the DED head and appropriate preheating temperature of the substrate.

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A thermal-mechanical finite element workflow for directed energy deposition additive manufacturing process modeling

Cited by 56 publications

References 29 publications

The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review

The Potential of Additive Manufacturing in the Smart Factory Industrial 4.0: A Review

Numerical Simulation Development and Computational Optimization for Directed Energy Deposition Additive Manufacturing Process

Effects of Deposition Strategy and Preheating Temperature on Thermo-Mechanical Characteristics of Inconel 718 Super-Alloy Deposited on AISI 1045 Substrate Using a DED Process

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