What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Mathematical analysis
- Finite element method
Jiun-Shyan Chen spends much of his time researching Mathematical analysis, Galerkin method, Meshfree methods, Applied mathematics and Finite element method.
His Mathematical analysis study incorporates themes from Kernel and Kernel method.
His studies in Galerkin method integrate themes in fields like Smoothing, Pure bending, Stress, Curvature and Rate of convergence.
His Meshfree methods research integrates issues from Regularization, Industrial engineering, Mixed boundary condition, Gradient method and Nonlinear mechanics.
His Applied mathematics study combines topics in areas such as Weak solution, Mathematical optimization, Large deformation and Calculus.
The concepts of his Finite element method study are interwoven with issues in State variable and Kernel.
His most cited work include:
- A stabilized conforming nodal integration for Galerkin mesh-free methods (982 citations)
- Reproducing Kernel Particle Methods for large deformation analysis of non-linear structures (660 citations)
- Overview and applications of the reproducing Kernel Particle methods (231 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Mathematical analysis, Finite element method, Meshfree methods, Applied mathematics and Kernel.
His work in Mathematical analysis addresses issues such as Geometry, which are connected to fields such as Grain boundary.
His studies deal with areas such as Mechanics, Numerical analysis and Classical mechanics as well as Finite element method.
His Meshfree methods study deals with Galerkin method intersecting with Smoothing.
His research in Applied mathematics intersects with topics in Basis and Mathematical optimization.
His Kernel research incorporates themes from Rate of convergence and Partial differential equation.
He most often published in these fields:
- Mathematical analysis (34.05%)
- Finite element method (25.95%)
- Meshfree methods (22.16%)
What were the highlights of his more recent work (between 2017-2021)?
- Applied mathematics (21.62%)
- Kernel (20.54%)
- Discretization (14.05%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Applied mathematics, Kernel, Discretization, Mechanics and Meshfree methods.
His Applied mathematics study combines topics from a wide range of disciplines, such as Stability, Dirichlet boundary condition, Eigenvalues and eigenvectors and Particle method.
His Kernel research includes elements of Particle, Level set method, Topology optimization, Boundary and Algorithm.
His Discretization research incorporates elements of Partial differential equation, Continuum, Residual, Advection and Rate of convergence.
His research investigates the connection between Partial differential equation and topics such as Fracture mechanics that intersect with issues in Finite element method.
His biological study spans a wide range of topics, including Newmark-beta method, Boundary value problem and Relaxation.
Between 2017 and 2021, his most popular works were:
- A physics-constrained data-driven approach based on locally convex reconstruction for noisy database (15 citations)
- Hyperbolic phase field modeling of brittle fracture: Part II—immersed IGA–RKPM coupling for air-blast–structure interaction (15 citations)
- A reproducing kernel enhanced approach for peridynamic solutions (14 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Finite element method
- Mathematical analysis
His primary scientific interests are in Meshfree methods, Discretization, Kernel, Applied mathematics and Node.
His Mathematical analysis research extends to Meshfree methods, which is thematically connected.
His research integrates issues of Compressibility, Partial differential equation, Fracture mechanics, Finite element method and Inertia in his study of Discretization.
His Partial differential equation research focuses on Mechanics and how it connects with Isogeometric analysis.
His Kernel research is multidisciplinary, relying on both Algorithm, Smoothness and Boundary value problem.
His work deals with themes such as Galerkin method and Collocation, which intersect with Applied mathematics.
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