Process Maps for Predicting Residual Stress and Melt Pool Size in the Laser-Based Fabrication of Thin-Walled Structures

2006 ◽  
Vol 129 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Aditad Vasinonta ◽  
Jack L. Beuth ◽  
Michelle Griffith
Keyword(s):  
Residual Stress ◽  
Residual Stresses ◽  
Pool Size ◽  
Thermal Gradients ◽  
Manufacturing Strategy ◽  
Process Maps ◽  
Thin Walled Structures ◽  
Melt Pool ◽  
Thin Walled ◽  
Melt Pool Size

Thermomechanical models are presented for the building of thin-walled structures by laser-based solid freeform fabrication (SFF) processes. Thermal simulations are used to develop quasi-non-dimensional plots (termed process maps) that quantify the effects of changes in wall height, laser power, deposition speed, and part preheating on thermal gradients, with the goal of limiting residual stresses in manufactured components. Mechanical simulations are used to demonstrate the link between thermal gradients and maximum final residual stresses. The approach taken is analogous to that taken in previous research by the authors in developing process maps for melt pool length, for maintaining an optimal melt pool size during component fabrication. Process maps are tailored for application to the laser engineered net shaping process; however, the general approach, insights, and conclusions are applicable to most SFF processes involving a moving heat source, and to other laser-based fusion processes. Results from the residual stress simulations identify two mechanisms for reducing residual stresses and quantify maximum stress reductions achievable through manipulation of all process variables. Results from thermal gradient and melt pool length process maps are used to identify a manufacturing strategy for obtaining a consistent melt pool size while limiting residual stress in a thin-walled part.

Research on Machining Distortion due to Residual Stresses of Large Monolithic Beam

2012 ◽  
Vol 433-440 ◽  
pp. 530-537
Author(s):  
Yun Qiao Wang ◽  
Zhong Yi Mei ◽  
Yu Qing Fan
Keyword(s):  
Residual Stress ◽  
Residual Stresses ◽  
Manufacturing Industry ◽  
Field Analysis ◽  
Internal Stresses ◽  
Machining Performance ◽  
Thin Walled Structures ◽  
Aircraft Manufacturing ◽  
Machining Distortion ◽  
Thin Walled

Machining-induced distortion of large monolithic parts with thin walled structures creates problems in aircraft manufacturing industry. Typical monolithic beams of airframe are machined by NC machine and machining distortions are recorded. Thin walled structures are prone to distortions and dimensional instabilities due to internal stresses; therefore, stress-relieved vibration method is applied to reduce the internal stresses in blank material and results in better machining performance and dimension stability. But vibration stress-relief method doesn’t work always due to unknown reasons. Machining simulations in ANSYS are performed to predict the residual stress-induced machining distortion and simulation result is compared with the machining measurements to validate the simulation process. Cutting simulations have been executed by the element deactivation technique after developing the initial residual stresses via sequential coupled field analysis. The possibility of residual stress being relieved more reasonably and less distortion by optimized machining sequence through simulation is discussed.

Analysis of circumferentially welded thin-walled cylinders to study the effects of tack weld orientations and joint root opening on residual stress fields

2009 ◽  
Vol 223 (5) ◽  
pp. 1037-1049 ◽  
Author(s):  
N U Dar ◽  
E M Qureshi ◽  
A M Malik ◽  
M M I Hammouda ◽  
R A Azeem
Keyword(s):  
Residual Stress ◽  
Residual Stresses ◽  
Arc Welding ◽  
Operating Conditions ◽  
Stress Fields ◽  
Welded Structures ◽  
Prime Concern ◽  
Thin Walled ◽  
Tack Weld ◽  
Welding Processes

In recent years, the demand for resilient welded structures with excellent in-service load-bearing capacity has been growing rapidly. The operating conditions (thermal and/or structural loads) are becoming more stringent, putting immense pressure on welding engineers to secure excellent quality welded structures. The local, non-uniform heating and subsequent cooling during the welding processes cause complex thermal stress—strain fields to develop, which finally leads to residual stresses, distortions, and their adverse consequences. Residual stresses are of prime concern to industries producing weld-integrated structures around the globe because of their obvious potential to cause dimensional instability in welded structures, and contribute to premature fracture/failure along with significant reduction in fatigue strength and in-service performance of welded structures. Arc welding with single or multiple weld runs is an appropriate and cost-effective joining method to produce high-strength structures in these industries. Multi-field interaction in arc welding makes it a complex manufacturing process. A number of geometric and process parameters contribute significant stress levels in arc-welded structures. In the present analysis, parametric studies have been conducted for the effects of a critical geometric parameter (i.e. tack weld) on the corresponding residual stress fields in circumferentially welded thin-walled cylinders. Tack weld offers considerable resistance to the shrinkage, and the orientation and size of tacks can altogether alter stress patterns within the weldments. Hence, a critical analysis for the effects of tack weld orientation is desirable.

A Physics-Informed Two-Level Machine Learning Model for Predicting Melt-Pool Size in Laser Powder Bed Fusion

2021 ◽  
Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris
Keyword(s):  
Machine Learning ◽  
Initial Temperature ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Input Feature ◽  
Melt Pool Size ◽  
Melt Pool Characteristics

Abstract Laser powder bed fusion (L-PBF) additive manufacturing (AM) is one type of metal-based AM process that is capable of producing high-value complex components with a fine geometric resolution. As melt-pool characteristics such as melt-pool size and dimensions are highly correlated with porosity and defects in the fabricated parts, it is crucial to predict how process parameters would affect the melt-pool size and dimensions during the build process to ensure the build quality. This paper presents a two-level machine learning (ML) model to predict the melt-pool size during the scanning of a multi-track build. To account for the effect of thermal history on melt-pool size, a so-called (pre-scan) initial temperature is predicted at the lower-level of the modeling architecture, and then used as a physics-informed input feature at the upper-level for the prediction of melt-pool size. Simulated data sets generated from the Autodesk's Netfabb Simulation are used for model training and validation. Through numerical simulations, the proposed two-level ML model has demonstrated a high prediction performance and its prediction accuracy improves significantly compared to a naive one-level ML without using the initial temperature as an input feature.

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D Is Driving Speed, Scale, and Efficiency

2020 ◽  
Author(s):  
Brian T. Gibson ◽  
Paritosh Mhatre ◽  
Michael C. Borish ◽  
Justin L. West ◽  
Emma D. Betters ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Large Scale ◽  
Closed Loop ◽  
Size Control ◽  
Pool Size ◽  
Large Format ◽  
Layer Height ◽  
Melt Pool ◽  
The Impact ◽  
Melt Pool Size

Abstract This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

On Process Temperature in Powder-Bed Electron Beam Additive Manufacturing: Model Development and Validation

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Bo Cheng ◽  
Steven Price ◽  
James Lydon ◽  
Kenneth Cooper ◽  
Kevin Chou
Keyword(s):  
Thermal Conductivity ◽  
Electron Beam ◽  
Additive Manufacturing ◽  
Thermal Characteristics ◽  
Pool Size ◽  
Process Temperature ◽  
Thermal Imager ◽  
Powder Bed ◽  
Melt Pool ◽  
Melt Pool Size

Powder-bed beam-based metal additive manufacturing (AM) such as electron beam additive manufacturing (EBAM) has a potential to offer innovative solutions to many challenges and difficulties faced in the manufacturing industry. However, the complex process physics of EBAM has not been fully understood, nor has process metrology such as temperatures been thoroughly studied, hindering part quality consistency, efficient process development and process optimizations, etc., for effective EBAM usage. In this study, numerical and experimental approaches were combined to research the process temperatures and other thermal characteristics in EBAM using Ti–6Al–4V powder. The objective of this study was to develop a comprehensive thermal model, using a finite element (FE) method, to predict temperature distributions and history in the EBAM process. On the other hand, a near infrared (NIR) thermal imager, with a spectral range of 0.78 μm–1.08 μm, was employed to acquire build surface temperatures in EBAM, with subsequent data processing for temperature profile and melt pool size analysis. The major results are summarized as follows. The thermal conductivity of Ti–6Al–4V powder is porosity dependent and is one of critical factors for temperature predictions. The measured thermal conductivity of preheated powder (of 50% porosity) is 2.44 W/m K versus 10.17 W/m K for solid Ti–6Al–4V at 750 °C. For temperature measurements in EBAM by NIR thermography, a method was developed to compensate temperature profiles due to transmission loss and unknown emissivity of liquid Ti–6Al–4V. At a beam speed of about 680 mm/s, a beam current of about 7.0 mA and a diameter of 0.55 mm, the peak process temperature is on the order around 2700 °C, and the melt pools have dimensions of about 2.94 mm, 1.09 mm, and 0.12 mm, in length, width, and depth, respectively. In general, the simulations are in reasonable agreement with the experimental results with an average error of 32% for the melt pool sizes. From the simulations, the powder porosity is found critical to the thermal characteristics in EBAM. Increasing the powder porosity will elevate the peak process temperature and increase the melt pool size.

Distributed Temperature Control in Laser-Based Manufacturing

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Chengjian Zheng ◽  
John T. Wen ◽  
Mamadou Diagne
Keyword(s):  
Temperature Field ◽  
Steady State ◽  
Cooling Rate ◽  
Temperature Control ◽  
Heat Dissipation ◽  
Pool Size ◽  
Scanning Laser ◽  
Measured Temperature ◽  
Melt Pool ◽  
Melt Pool Size

Abstract Temperature control is essential for regulating material properties in laser-based manufacturing. Motion and power of the scanning laser affect local temperature evolution, which in turn determines the a posteriori microstructure. This paper addresses the problem of adjusting the laser speed and power to achieve the desired values of key process parameters: cooling rate and melt pool size. The dynamics of a scanning laser system is modeled by a one-dimensional (1D) heat conduction equation, with laser power as the heat input and heat dissipation to the ambient. Since the model is 1D, length and size are essentially the same. We pose the problem as a regulation problem in the (moving) laser frame. The first step is to obtain the steady-state temperature distribution and the corresponding input based on the desired cooling rate and melt pool size. The controller adjusts the input around the steady-state feedforward based on the deviation of the measured temperature field from the steady-state distribution. We show that with suitably defined outputs, the system is strictly passive from the laser motion and power. To avoid over-reliance on the model, the steady-state laser speed and power are adaptively updated, resulting in an integral-like update law for the feedforward. Moreover, the heat transfer coefficient to the ambient may be uncertain, and can also be adaptively updated. The final form of the control law combines passive error temperature field feedback with adaptive feedforward and parameter estimation. The closed-loop asymptotical stability is shown using the Lyapunov arguments, and the controller performance is demonstrated in a simulation.

Ultrasonic Frequency Effects on the Melt Pool Formation, Porosity, and Thermal-Dependent Property of Inconel 718 Fabricated by Ultrasonic Vibration-Assisted Directed Energy Deposition

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Fuda Ning ◽  
Dayue Jiang ◽  
Zhichao Liu ◽  
Hui Wang ◽  
Weilong Cong
Keyword(s):  
Ultrasonic Vibration ◽  
Inconel 718 ◽  
Energy Deposition ◽  
Pool Size ◽  
Peak Temperature ◽  
Ultrasonic Frequency ◽  
Melt Pool ◽  
Directed Energy ◽  
Pool Formation ◽  
Melt Pool Size

Abstract Ultrasonic vibration-assisted (UV-A) directed energy deposition (DED) has become a promising technology to improve the as-built quality and mechanical performance of metal parts. Ultrasonic frequency, a critical parameter of the ultrasonic vibration, can remarkably affect the ultrasonic vibration behaviors in assisting DED processes. However, leveraging varied ultrasonic frequencies in UV-A DED attracts little attention, and the effects of ultrasonic frequency have been thus overlooked. Linking ultrasonic frequency and part performance emphasizes the need for an understanding of the underlying thermodynamics in the melt pool due to the key role of thermal history in the DED process. In this work, we fabricated Inconel 718 (IN718) parts using the UV-A DED process under different levels of ultrasonic vibration frequency (including 0, 25 kHz, 33 kHz, and 41 kHz). For the first time, melt pool size, temperature distribution, and peak temperature within the melt pool, as well as the peak temperature fluctuation within a layer deposition, were studied. Porosity and thermal-dependent properties including grain size and microhardness were also investigated. The results indicated that the increase in ultrasonic frequency led to an increase in both melt pool size and peak temperature. Moreover, the lowest porosity was obtained at an ultrasonic frequency of 25 kHz, while grain refinement and microhardness enhancement were achieved at the highest frequency of 41 kHz. This investigation provides great insights into the link among ultrasonic frequency, melt pool formation, temperature field, porosity, and thermal-dependent properties in the UV-A DED-built IN718 parts.

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