23 citations · 31 across the 9 of their papers we have counts for
9 papers
A hybrid s-version isogeometric strategy for dynamic crack propagation in 2D and 3D problems
Tianyu He, Kosei Kurosaki, Naoki Morita +2
A hybrid s-version of isogeometric analysis (hS-IGA) strategy is proposed for accurate and efficient evaluation of near-crack fracture quantities in dynamic crack propagation analy…
A generalized vertical coordinate transformation based on SPH(2) for efficient free surface flow simulations
Shujiro Fujioka, Kumpei Tsuji, Naoto Mitsume +1
We propose three new particle methods that improve computational efficiency by introducing a generalized Vertical Coordinate Transformation (VCT) for free surface flow problems wit…
Metagraph-Based Domain-Decomposed Galerkin Reduced-Order Model
Kyohei Shintate, Naoki Morita, Shigeki Kaneko +2
This study proposes a metagraph-based domain-decomposed Galerkin reduced-order model (MBDD-G-ROM) for distributed-memory parallel reduced-order analysis of large-scale problems. Th…
Domain-decomposed parallelization of B-spline based s-version of the finite element method via generalized graph abstraction
Nozomi Magome, Naoki Morita, Shigeki Kaneko +1
The s-version of the finite element method (SFEM) enables locally high-resolution analysis by superimposing independently defined finite element meshes. However, domain-decomposed…
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance
Masanobu Horie, Naoto Mitsume
Utilizing machine learning to address partial differential equations (PDEs) presents significant challenges due to the diversity of spatial domains and their corresponding state co…
2D Slice-driven Physics-based 3D Motion Estimation Framework for Pancreatic Radiotherapy
Yuki Hara, Noriyuki Kadoya, Naoto Mitsume +4
Pancreatic diseases are difficult to treat with high doses of radiation, as they often present both periodic and aperiodic deformations. Nevertheless, we expect that these difficul…
Higher-continuity s-version of finite element method with B-spline functions
Nozomi Magome, Naoki Morita, Shigeki Kaneko +1
This paper proposes a strategy to solve the problems of the conventional s-version of finite element method (SFEM) fundamentally. Because SFEM can reasonably model an analytical do…
Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions
Masanobu Horie, Naoto Mitsume
Graph neural network (GNN) is a promising approach to learning and predicting physical phenomena described in boundary value problems, such as partial differential equations (PDEs)…
Isometric Transformation Invariant and Equivariant Graph Convolutional Networks
Masanobu Horie, Naoki Morita, Toshiaki Hishinuma +2
Graphs are one of the most important data structures for representing pairwise relations between objects. Specifically, a graph embedded in a Euclidean space is essential to solvin…