Advances in computational modeling for laser powder bed fusion additive manufacturing: A comprehensive review of finite element techniques and strategies

D Sarkar, A Kapil, A Sharma - Additive Manufacturing, 2024 - Elsevier
The laser powder bed fusion process, a prominent additive manufacturing method, involves
intricate thermal dynamics and stress distribution. Despite the mature knowledge base in …

[HTML][HTML] An overview of additive manufacturing technologies—a review to technical synthesis in numerical study of selective laser melting

A Razavykia, E Brusa, C Delprete, R Yavari - Materials, 2020 - mdpi.com
Additive Manufacturing (AM) processes enable their deployment in broad applications from
aerospace to art, design, and architecture. Part quality and performance are the main …

Digitally twinned additive manufacturing: Detecting flaws in laser powder bed fusion by combining thermal simulations with in-situ meltpool sensor data

R Yavari, A Riensche, E Tekerek, L Jacquemetton… - Materials & Design, 2021 - Elsevier
The goal of this research is the in-situ detection of flaw formation in metal parts made using
the laser powder bed fusion (LPBF) additive manufacturing process. This is an important …

Feedforward control of thermal history in laser powder bed fusion: Toward physics-based optimization of processing parameters

A Riensche, BD Bevans, Z Smoqi, R Yavari… - Materials & Design, 2022 - Elsevier
We developed and applied a model-driven feedforward control approach to mitigate thermal-
induced flaw formation in laser powder bed fusion (LPBF) additive manufacturing process …

Part-scale thermal simulation of laser powder bed fusion using graph theory: Effect of thermal history on porosity, microstructure evolution, and recoater crash

R Yavari, Z Smoqi, A Riensche, B Bevans, H Kobir… - Materials & Design, 2021 - Elsevier
Flaw formation in laser powder bed fusion (LPBF) is influenced by the spatiotemporal
temperature distribution–thermal history–of the part during the process. Therefore, to prevent …

[HTML][HTML] Predicting meltpool depth and primary dendritic arm spacing in laser powder bed fusion additive manufacturing using physics-based machine learning

AR Riensche, BD Bevans, G King, A Krishnan… - Materials & Design, 2024 - Elsevier
The long-term goal of this work is to predict and control the microstructure evolution in metal
additive manufacturing processes. In pursuit of this goal, we developed and applied an …

Digital twins for rapid in-situ qualification of part quality in laser powder bed fusion additive manufacturing

BD Bevans, A Carrington, A Riensche, A Tenequer… - Additive …, 2024 - Elsevier
This work concerns the laser powder bed fusion (LPBF) additive manufacturing process.
Currently, LPBF parts are inspected post-process using such techniques as X-ray computed …

Thermal modeling in metal additive manufacturing using graph theory–Application to laser powder bed fusion of a large volume impeller

R Yavari, R Williams, A Riensche, PA Hooper… - Additive …, 2021 - Elsevier
Despite its potential to overcome the design and processing barriers of traditional
subtractive and formative manufacturing techniques, the use of laser powder bed fusion …

Thermal modeling in metal additive manufacturing using graph theory

MR Yavari, KD Cole, P Rao - Journal of …, 2019 - asmedigitalcollection.asme.org
The goal of this work is to predict the effect of part geometry and process parameters on the
instantaneous spatiotemporal distribution of temperature, also called the thermal field or …

Prediction of recoater crash in laser powder bed fusion additive manufacturing using graph theory thermomechanical modeling

MH Kobir, R Yavari, AR Riensche, BD Bevans… - Progress in Additive …, 2023 - Springer
The objective of this work is to predict a type of thermal-induced process failure called
recoater crash that occurs frequently during laser powder bed fusion (LPBF) additive …