Spatial variation of melt pool geometry, peak temperature and solidification parameters during laser assisted additive manufacturing process

Manvatkar, V.; De, A.; DebRoy, T.

doi:10.1179/1743284714y.0000000701

Cited by 234 publications

(94 citation statements)

References 29 publications

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“…For common autogenous weld conditions, melt pools are roughly ellipsoidal in shape. 19 Prior experimental investigations have shown at low scan velocities, the surface tension of the liquid interface is minimized, and the melt pool has a symmetric, near-hemispherical shape. As velocities increase, an elongated tail develops behind the melt pool and the overall shape becomes more ''comet-like.''…”

Section: Experimental Process Parameters As Model Inputsmentioning

confidence: 99%

Predicting Mesoscale Microstructural Evolution in Electron Beam Welding

Rodgers

Madison

Tikare

et al. 2016

JOM

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Section: Experimental Process Parameters As Model Inputsmentioning

confidence: 99%

Predicting Mesoscale Microstructural Evolution in Electron Beam Welding

Rodgers

Madison

Tikare

et al. 2016

JOM

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“…The temperature rise and the Fourier number are both calculated using a well-tested heat transfer and fluid flow model [3,4]. The model solves the equations of conservations of mass, momentum and energy to provide three dimensional transient temperature and velocity fields as well as the shape and size of the molten pool [3,4]. Since the model and its applications are described in detail in the literature [3][4][5], they are not repeated here.…”

mentioning

confidence: 99%

“…Fourier number is the ratio of the heat dissipation rate to heat storage rate. The temperature rise and the Fourier number are both calculated using a well-tested heat transfer and fluid flow model [3,4]. The model solves the equations of conservations of mass, momentum and energy to provide three dimensional transient temperature and velocity fields as well as the shape and size of the molten pool [3,4].…”

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Mitigation of thermal distortion during additive manufacturing

et al. 2017

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Additively manufactured parts are often distorted because of spatially variable heating and cooling. Currently there is no practical way to select process variables based on scientific principles to alleviate distortion. Here we develop a roadmap to mitigate distortion during additive manufacturing using a strain parameter and a well-tested, three-dimensional, numerical heat transfer and fluid flow model. The computed results uncover the effects of both the key process variables such as power, scanning speed, and important non-dimensional parameters such as Marangoni and Fourier numbers and non-dimensional peak temperature on thermal strain. Recommendations are provided to mitigate distortion based on the results.Laser assisted additive manufacturing (AM) process produces 'near net shape' parts from a stream of alloy powders in a layer-by-layer manner for use in medical, aerospace, automotive and other industries [1,2]. The parts undergo repeated spatially variable heating, melting, solidification and cooling during AM [3,4]. Due to the transient heating and cooling, the fabricated parts exhibit thermal distortion [5-10]. Thermal distortion results in dimensional inaccuracy and adversely affects performance of the fabricated parts [11]. Previous work has shown that increase in net heat input [7] and reduction in dwell time [8] between deposition of successive layers can increase thermal distortion. It is also known that the alloy properties, the deposit and substrate dimensions, the laser scanning pathway, the hatch spacing between layers and the heating and cooling conditions significantly affect thermal distortion [9,12,13].The existing AM literature does not provide any guidance for selecting process variables to minimize thermal distortion. A quantitative understanding of the effects of process variables on thermal distortion and a practical means to mitigate this problem based on scientific principles are needed but not generally available.Here, we show for the first time how thermal distortion during AM can be minimized by back of the envelope calculations. The procedure involves evaluation of the effects of common process variables such as laser power and scanning speed on thermal strain. In addition, the non-dimensional parameters that are important for heat transfer and fluid flow phenomena in AM such as Fourier number, Marangoni number and non-dimensional temperature are correlated with thermal strain. Based on these results we provide recommendations to minimize distortion of the additively manufactured parts.We have recently shown that thermal distortion is related to a strain parameter, ε* [5]:where β is the volumetric coefficient of thermal expansion, ΔT is the maximum rise in temperature during the process, E is the elastic modulus and I is the moment of inertia of the substrate, the product, EI, is the flexural rigidity of the structure, t is the characteristic time, H is the heat input per unit length, F is the Fourier number and ρ is the density of the alloy powder. Fourier number is the ratio o...

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“…To address this challenge, high-performance computing (HPC) tools are being developed to deal with unique features, including A (1) localized melting with heat transfer in granular powder media, 45 (2) heat and mass transfer with steep temperature gradients 46 and high liquid-solid interface velocities, 47 (3) microstructure evolution, 48 and (4) thermomechanics. 49 Here, as a representative example, we describe the use of HPC simulations of heat and mass transfer for predicting the spatial and temporal variation of the melt-pool shape during electronbeam AM of Ti-6Al-4V alloys.…”

Section: Approachmentioning

confidence: 99%

Additive manufacturing of materials: Opportunities and challenges

et al. 2015

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Figure 1. Development stages of big-area additive manufacturing (BAAM). (a) Gantrystyle robotic automation system, without any heating environment, was developed and integrated with a single-screw extrusion nozzle. (b) Initial material trials led to extensive distortion with acrylonitrile butadiene styrene (ABS) pellets, whereas use of pellets with ABS and carbon fi ber (CF) reduced the distortion. (c) Aerial view of the industrial-scale BAAM system developed by Local Motors. (d) The industrial-scale system was verifi ed by printing out a chassis of a small car, which was then integrated with an electric drive train. (e) The same technology was coupled with traditional manufacturing to produce a prototype similar to the Ford Shelby Cobra, which was also powered by an electric drive train. (f) The same technology has also been used to make molds for use in prototyping during traditional metal-forming processes. Reproduced with permission from Reference 10.

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Spatial variation of melt pool geometry, peak temperature and solidification parameters during laser assisted additive manufacturing process

Cited by 234 publications

References 29 publications

Predicting Mesoscale Microstructural Evolution in Electron Beam Welding

Predicting Mesoscale Microstructural Evolution in Electron Beam Welding

Mitigation of thermal distortion during additive manufacturing

Additive manufacturing of materials: Opportunities and challenges

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