Research
This page contains the peer-reviewed scientific publications that back up the models and theories implemented in our AM-DT platform.
2026 · International Journal of Advanced Manufacturing Technology
Understanding spatial variability in mechanical properties of laser powder-bed fusion parts under material uncertainty
The paper develops a multiscale uncertainty-propagation framework for PBF-L, tracking how uncertain thermal conductivity, heat capacity, and density affect powder-scale and part-scale predictions. It quantifies spatial variability in mechanical properties and shows how build orientation and baseplate contact influence uncertainty.
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2025 · International Journal of Computer Integrated Manufacturing
Understanding and control of gas porosity in metal laser powder-bed fusion additive manufacturing
This study couples melt-pool fluid dynamics, ray tracing, and phase-field/interface tracking to explain gas-pore formation in LPBF. It identifies low scan speeds and stripe turning points as critical pore sources, then demonstrates how laser power modulation can reduce pore emission.
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2024 · Computational Materials Science
Phase field study of heat treatment and strengthening in maraging steels
The abstract presents a phase-field model for martensite decomposition during heat treatment of maraging steels, including precipitate growth, reverted austenite, and transformation-induced deformation. The simulations connect ageing temperature and time to strength trends and clarify the role of reversed austenite.
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2024 · International Journal of Computer Integrated Manufacturing
The role of tool path on microstructure uniformity in large-format additive manufacturing
The paper introduces an integrated thermo-metallurgical-mechanical model for directed energy deposition that reads the robot toolpath and component geometry directly. It links toolpath choices to temperature, phase distribution, residual stress, and distortion in large-format metal AM.
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2024 · International Journal of Computer Integrated Manufacturing
Data-driven surrogate modelling of residual stresses in Laser Powder-Bed Fusion
The study evaluates fast surrogate models for LPBF residual-stress prediction using simulation-generated data from two families of part geometries. It compares neural-network and interpolation strategies as practical alternatives to expensive multiphysics simulations for optimization, control, and digital twinning.
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2023 · Journal of Intelligent Manufacturing
Development of a surrogate model for high-fidelity laser powder-bed fusion using tensor train and Gaussian process regression
The paper proposes a tensor-train and Gaussian-process surrogate for a high-fidelity LPBF powder-scale model. It predicts thermal histories and melt-pool geometry for new laser powers in less than one second, achieving large speedups while preserving useful accuracy.
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2022 · Powder Technology
Discrete element simulation of powder flow in revolution powder analyser
Using DEM simulations of a revolution powder analyser, the paper studies how powder size distribution, non-sphericity, friction, filling degree, rotation speed, and adhesion affect packing density and avalanche flow. It also extracts intrinsic powder friction and adhesion parameters from measurements.
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2022 · Journal of Materials Processing Technology
A part-scale, feature-based surrogate model for residual stresses in the laser powder bed fusion process
This work trains a 3D U-Net convolutional neural network on feature-based LPBF simulations to predict part-scale residual stress. It demonstrates good accuracy for designed feature families and substantial runtime reduction for practical design-stage stress estimation.
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2022 · Additive Manufacturing
Concurrent modeling of porosity and microstructure in multilayer 3D simulations of INCONEL 718 powder-bed fusion
The paper presents a coupled phase-field and lattice-Boltzmann framework that explicitly models porosity and grain microstructure across multiple LPBF layers in 3D. After calibration, it predicts porosity and microstructure trends across process-parameter combinations.
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2022 · Materials & Design
Design guidelines for suppressing distortion and buckling in metallic thin-wall structures built by powder-bed fusion
This paper combines simulations and LPBF experiments to study distortion in thin-wall IN718 structures. It shows that rounded corners reduce distortion, part width is more influential than height, and geometry design can suppress buckling during printing.
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2022 · Additive Manufacturing
Quantitative study on the dynamics of melt pool and keyhole and their controlling factors in metal laser melting
The paper couples ray tracing, phase field, and lattice-Boltzmann methods to reproduce experimentally observed laser-melting regimes in Ti-6Al-4V. It identifies keyhole and melt-pool oscillation modes and links keyhole-tip instability to bubble spill-over.
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2021 · Journal of Alloys and Compounds
Phase field model for multiphase alloys under arbitrary thermal history: an application to IN718 super-alloy
This work builds a phase-field framework for precipitate evolution under arbitrary thermal histories, parameterized with thermodynamics, kinetics, and TTT data. Applied to IN718, it predicts how rapid AM-like thermal cycling changes gamma prime, gamma double-prime, and delta precipitation.
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2021 · Materials & Design
Modelling the influence of process parameters on precipitate formation in powder-bed fusion additive manufacturing of IN718
The paper develops a two-scale finite-element and phase-field workflow for IN718 powder-bed fusion. Stripe-resolved thermal histories are passed into phase-field RVEs to predict precipitate formation and show how process parameters such as stripe width and chamber temperature affect as-built microstructure.
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