Solidification and crystal growth phenomena

Derniers papiers

• A mesh-free multiresolution deep energy method with phase-field modeling of brittle fracture

  Han Zhang, Mehrisadat Makki Alamdari, Babak Shahbodagh, Mohammad Vahab, Cosmin Anitescu, Timon Rabczuk, Elena Atroshchenko · 26 août 2026

  Phase-field modeling of brittle fracture removes the need to track cracks explicitly by recasting their evolution as the minimization of an energy functional. In return it requires a discretization dense enough to resolve a localization band whose width is set by a regularization length and whose pa…

• Multiphase-Diff: Diffusion-Based Generative Modeling for High-Contrast Multiphase Physical Systems with Sharp Interfaces

  Yining Huang, Zhenyu Liang · 17 août 2026

  Physics-constrained diffusion for high-contrast, sharp-interface multiphase fields faces three coupled difficulties. At coefficient jumps, expanded pointwise strong-form PDE residuals contain singular gradient terms that can penalize physical interfaces. Under extreme contrast, low-magnitude phases …

• A Smooth Phase-Separation Model for Weak-Boundary Segmentation of Homogeneous Structures

  Zihan Li, Jiebao Sun, Fanghui Song, Zhichang Guo · 27 juillet 2026

  Segmentation of adjacent structures with similar intensity distributions remains a challenging problem in image analysis, particularly when object boundaries are weak or ambiguous. Under such conditions, classical variational models may suffer from degenerated image-driven forces, leading to boundar…

• Extended pseudo-spectral physics-informed neural networks for phase-field models

  Callum Marsh, Radek Erban, Andreas Munch · 24 juin 2026

  Phase-field models play a central role in the continuum description of phase separation, in which the bulk free-energy density and the interfacial thickness parameter determine pattern formation and microstructural evolution. In practice, these constitutive quantities are rarely known a priori and m…

• DeepRitzSplit Neural Operator for Phase-Field Models via Energy Splitting

  Chih-Kang Huang, Ludovick Gagnon, Miha Zalo\v{z}nik, Beno\^it Appolaire · 21 avril 2026

  The multi-scale and non-linear nature of phase-field models of solidification requires fine spatial and temporal discretization, leading to long computation times. This could be overcome with artificial-intelligence approaches. Surrogate models based on neural operators could have a lower computatio…

• AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulation

  Sukriti Manna, Henry Chan, Subramanian K. R. S. Sankaranarayanan · 24 mars 2026

  Multiphysics simulation frameworks such as MOOSE provide rigorous engines for phase-field materials modeling, yet adoption is constrained by the expertise required to construct valid input files, coordinate parameter sweeps, diagnose failures, and extract quantitative results. We introduce AutoMOOSE…

• Adaptive Uncertainty-Guided Surrogates for Efficient phase field Modeling of Dendritic Solidification

  Eider Garate-Perez, Kerman L\'opez de Calle-Etxabe, Oihana Garcia, Borja Calvo, Meritxell G\'omez-Omella, Jon Lambarri · 3 mars 2026

  The high computational cost of phase field simulations remains a major limitation for predicting dendritic solidification in metals, particularly in additive manufacturing, where microstructural control is critical. This work presents a surrogate model for dendritic solidification that employs uncer…

• Three-dimensional narrow volume reconstruction method with unconditional stability based on a phase-field Lagrange multiplier approach

  Renjun Gao, Xiangjie Kong, Dongting Cai, Boyi Fu, Junxiang Yang · 4 novembre 2025

  Reconstruction of an object from points cloud is essential in prosthetics, medical imaging, computer vision, etc. We present an effective algorithm for an Allen--Cahn-type model of reconstruction, employing the Lagrange multiplier approach. Utilizing scattered data points from an object, we reconstr…