Enriched analytical solutions for additive manufacturing modeling and simulation

Steuben, John C.; Birnbaum, Andrew J.; Michopoulos, John G.; Iliopoulos, Athanasios

doi:10.1016/j.addma.2018.10.017

Cited by 32 publications

(20 citation statements)

References 46 publications

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“…This flexible method leads to a reduction in computational time and costs, and simulated microstructures were consistent with experimental data (Figure 6b). An enriched analytic solution model (EASM) was developed by Steuben et al [ 98 ] for AM simulation. The results of EASM were equivalent to those of FEA, whereas the computational efficiency was roughly six orders of magnitude faster.…”

Section: Design Concepts For Fgmammentioning

confidence: 99%

A Review on Functionally Graded Materials and Structures via Additive Manufacturing: From Multi‐Scale Design to Versatile Functional Properties

Yan

Feng

Liu

et al. 2020

Adv Materials Technologies

297

116

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Functionally graded materials (FGMs) and functionally graded structures (FGSs) are special types of advanced composites with peculiar features and advantages. This article reviews the design criteria of functionally graded additive manufacturing (FGAM), which is capable of fabricating gradient components with versatile functional properties. Conventional geometrical‐based design concepts have limited potential for FGAM and multi‐scale design concepts (from geometrical patterning to microstructural design) are needed to develop gradient components with specific graded properties at different locations. FGMs and FGSs are of great interest to a larger range of industrial sectors and applications including aerospace, automotive, biomedical implants, optoelectronic devices, energy absorbing structures, geological models, and heat exchangers. This review presents an overview of various fabrication ideas and suggestions for future research in terms of design and creation of FGMs and FGSs, benefiting a wide variety of scientific fields.

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Section: Design Concepts For Fgmammentioning

confidence: 99%

A Review on Functionally Graded Materials and Structures via Additive Manufacturing: From Multi‐Scale Design to Versatile Functional Properties

Yan

Feng

Liu

et al. 2020

Adv Materials Technologies

297

116

View full text Add to dashboard Cite

show abstract

“…For example, Yang studied the influence of process parameters, such as laser power and scanning speed, on the vertical surface roughness of the AlSi10Mg parts fabricated by LPBF process [9]. Steuben et al 2019 discussed the use of a computational enriched analytical solution method (EASM) for AM modeling and simulation in order to predict the influence of process parameters on the properties and associated functional performance of the LPBF parts [10]. Understanding the influence of main LPBF processing parameters on the surface roughness of AM components can be used for additional process optimization [11].…”

Section: Introduction 1additive Manufacturingmentioning

confidence: 99%

Gold, Silver, and Electrum Electroless Plating on Additively Manufactured Laser Powder-Bed Fusion AlSi10Mg Parts: A Review

et al. 2021

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Additive manufacturing (AM) revolutionary technologies open new opportunities and challenges. They allow low-cost manufacturing of parts with complex geometries and short time-to-market of products that can be exclusively customized. Additive manufactured parts often need post-printing surface modification. This study aims to review novel environmental-friendly surface finishing process of 3D-printed AlSi10Mg parts by electroless deposition of gold, silver, and gold–silver alloy (e.g., electrum) and to propose a full process methodology suitable for effective metallization. This deposition technique is simple and low cost method, allowing the metallization of both conductive and insulating materials. The AlSi10Mg parts were produced by the additive manufacturing laser powder bed fusion (AM-LPBF) process. Gold, silver, and their alloys were chosen as coatings due to their esthetic appearance, good corrosion resistance, and excellent electrical and thermal conductivity. The metals were deposited on 3D-printed disk-shaped specimens at 80 and 90 °C using a dedicated surface activation method where special functionalization of the printed AlSi10Mg was performed to assure a uniform catalytic surface yielding a good adhesion of the deposited metal to the substrate. Various methods were used to examine the coating quality, including light microscopy, optical profilometry, XRD, X-ray fluorescence, SEM–energy-dispersive spectroscopy (EDS), focused ion beam (FIB)-SEM, and XPS analyses. The results indicate that the developed coatings yield satisfactory quality, and the suggested surface finishing process can be used for many AM products and applications.

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“…Bruna-Rosso et al (2018) applied a FEM model to conduct the thermal analysis of SLM and further applied the results to predict the lack-of-fusion defects. Steuben et al (2018) developed a promising semi-analytical solution approach for AM processes and claimed that the results are comparable to those of the FEM approach.…”

Section: Introductionmentioning

confidence: 99%

On efficiency and effectiveness of finite volume method for thermal analysis of selective laser melting

Wang

Shi

2020

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Purpose Selective laser melting (SLM) is a major additive manufacturing (AM) process in which laser beams are used as the heat source to melt and deposit metals in a layerwise fashion to enable the construction of components of arbitrary complexity. The purpose of this paper is to develop a framework for accurate and fast prediction of the temperature distribution during the SLM process. Design/methodology/approach A fast computation tool is proposed for thermal analysis of the SLM process. It is based on the finite volume method (FVM) and the quiet element method to allow the development of customized functionalities at the source level. The results obtained from the proposed FVM approach are compared against those obtained from the finite element method (FEM) using a well-established commercial software, in terms of accuracy and efficiency. Findings The results show that for simulating the SLM deposition of a cubic block with 81,000, 189,000 and 297,000 cells, the computation takes about 767, 3,041 and 7,054 min, respectively, with the FEM approach; while 174, 679 and 1,630 min with the FVM code. This represents a speedup of around 4.4x. Meanwhile, the average temperature difference between the two is below 6%, indicating good agreement between them. Originality/value The thermal field for the multi-track and multi-layer SLM process is for the first time computed by the FVM approach. This pioneering work on comparing FVM and FEM for SLM applications implies that a fast and simple computing tool for thermal analysis of the SLM process is within the reach, and it delivers comparable accuracy with significantly higher computational efficiency. The research results lay the foundation for a potentially cost-effective tool for investigating the fundamental microstructure evolution, and also optimizing the process parameters in the SLM process.

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Enriched analytical solutions for additive manufacturing modeling and simulation

Cited by 32 publications

References 46 publications

A Review on Functionally Graded Materials and Structures via Additive Manufacturing: From Multi‐Scale Design to Versatile Functional Properties

A Review on Functionally Graded Materials and Structures via Additive Manufacturing: From Multi‐Scale Design to Versatile Functional Properties

Gold, Silver, and Electrum Electroless Plating on Additively Manufactured Laser Powder-Bed Fusion AlSi10Mg Parts: A Review

On efficiency and effectiveness of finite volume method for thermal analysis of selective laser melting

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