English
Related papers

Related papers: Surrogate Modeling of Melt Pool Thermal Field usin…

200 papers

We present a data-driven, differentiable neural network model designed to learn the temperature field, its gradient, and the cooling rate, while implicitly representing the melt pool boundary as a level set in laser powder bed fusion. The…

Insufficient overlap between the melt pools produced during Laser Powder Bed Fusion (L-PBF) can lead to lack-of-fusion defects and deteriorated mechanical and fatigue performance. In-situ monitoring of the melt pool subsurface morphology…

Powder-based additive manufacturing techniques provide tools to construct intricate structures that are difficult to manufacture using conventional methods. In Laser Powder Bed Fusion, components are built by selectively melting specific…

Signal Processing · Electrical Eng. & Systems 2021-02-08 Francis Ogoke , Amir Barati Farimani

Defects in laser powder bed fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. For instance, the melt pool can directly contribute to the formation of undesirable…

While multiple sensors are used for real-time monitoring in additive manufacturing, not all provide practical or reliable process insights. For example, high-speed X-ray imaging offers valuable spatial information about subsurface melt pool…

Machine Learning · Computer Science 2025-09-04 Satyajit Mojumder , Pallock Halder , Tiana Tonge

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and…

Computational Engineering, Finance, and Science · Computer Science 2025-07-18 Nicholas Kirschbaum , Nathaniel Wood , Chang-Eun Kim , Thejaswi U. Tumkur , Chinedum Okwudire

Laser powder bed fusion (LPBF) has shown promise for wide range of applications due to its ability to fabricate freeform geometries and generate a controlled microstructure. However, components generated by LPBF still possess sub-optimal…

Machine Learning · Computer Science 2025-01-16 Olabode T. Ajenifujah , Francis Ogoke , Florian Wirth , Jack Beuth , Amir Barati Farimani

Modeling plays a critical role in additive manufacturing (AM), enabling a deeper understanding of underlying processes. Parametric solutions for such models are of great importance, enabling the optimization of production processes and…

Computational Engineering, Finance, and Science · Computer Science 2025-02-05 Hesameddin Safari , Henning Wessels

Wire-feed laser additive manufacturing (WLAM) is gaining wide interest due to its high level of automation, high deposition rates, and good quality of printed parts. In-process monitoring and feedback controls that would reduce the…

Materials Science · Physics 2021-03-23 Noopur Jamnikar , Sen Liu , Craig Brice , Xiaoli Zhang

Laser Powder Bed Fusion (L-PBF) is a widely adopted additive manufacturing process for fabricating complex metallic parts layer by layer. Effective thermal management is essential to ensure part quality and structural integrity, as thermal…

Systems and Control · Electrical Eng. & Systems 2025-09-22 Yukta Pareek , Abdul Malik Al Mardhouf Al Saadi , Amrita Basak , Satadru Dey

The usefulness of semi-analytical thermal models for predicting the connection between process, microstructure and properties in powder bed fusion has been well illustrated in recent years. Such an approach provides the promise of accuracy…

Materials Science · Physics 2024-04-05 Shaun R. Cooke , Chadwick W. Sinclair , Daan M. Maijer

Additive manufacturing processes are flexible and efficient technologies for producing complex geometries. However, ensuring reliability and repeatability is challenging due to the complex physics and various sources of uncertainty in the…

Systems and Control · Electrical Eng. & Systems 2024-09-18 Dominic Liao-McPherson , Efe C. Balta , Mohamadreza Afrasiabi , Alisa Rupenyan , Markus Bambach , John Lygeros

Metal Laser Powder Bed Fusion (PBF-LB/M) is a leading additive manufacturing technique in which part quality and grain morphology are highly dependent on process parameters. Numerous studies of process variations, such as laser power, scan…

Additive Manufacturing presents a great application area for Machine Learning because of the vast volume of data generated and the potential to mine this data to control outcomes. In this paper we present preliminary work on classifying…

Machine Learning · Computer Science 2020-10-05 Vivek Mahato , Muhannad Ahmed Obeidi , Dermot Brabazon , Padraig Cunningham

High-fidelity simulations of laser welding capture complex thermo-fluid phenomena, including phase change, free-surface deformation, and keyhole dynamics, however their computational cost limits large-scale process exploration and real-time…

Machine Learning · Computer Science 2026-04-01 Alix Benoit , Toni Ivas , Mateusz Papierz , Asel Sagingalieva , Alexey Melnikov , Elia Iseli

Thermal multi-phase flow simulations are indispensable to understanding the multi-scale and multi-physics phenomena in metal additive manufacturing (AM) processes, yet accurate and robust predictions remain challenging. This book chapter…

Computational Engineering, Finance, and Science · Computer Science 2022-06-13 Jinhui Yan , Qiming Zhu , Ze Zhao

Phase change process plays a critical role in thermal management systems, yet quantitative characterization of multiphase heat transfer remains limited by the challenges of measuring temperature fields in chaotic, rapidly evolving flow…

Machine Learning · Computer Science 2026-02-03 Qianxi Fu , Youngjoon Suh , Xiaojing Zhang , Sanghyeon Chang , Yoonjin Won

Laser Powder Bed Fusion (LPBF) additive manufacturing has revolutionized industries with its capability to create intricate and customized components. The LPBF process uses moving heat sources to melt and solidify metal powders. The fast…

Computational Engineering, Finance, and Science · Computer Science 2024-07-10 Xin Liu , Xingchen Liu , Paul Witherell

Multi-fidelity (MF) modeling is a powerful statistical approach that can intelligently blend data from varied fidelity sources. This approach finds a compelling application in predicting melt pool geometry for laser-directed energy…

Machine Learning · Computer Science 2024-03-21 Nandana Menon , Amrita Basak

Laser powder bed fusion (LPBF) is a widely used metal additive manufacturing technology. However, the accumulation of internal residual stress during printing can cause significant distortion and potential failure. Although various scan…

Computational Engineering, Finance, and Science · Computer Science 2024-04-12 Mian Qin , Junhao Ding , Shuo Qu , Xu Song , Charlie C. L. Wang , Wei-Hsin Liao
‹ Prev 1 2 3 10 Next ›