What is he best known for?
The fields of study he is best known for:
- Finite element method
- Composite material
- Geometry
The scientist’s investigation covers issues in Finite element method, Smoothed finite element method, Smoothing, Mathematical analysis and Stiffness matrix. His studies in Finite element method integrate themes in fields like Vibration, Upper and lower bounds and Numerical analysis. His research links Meshfree methods with Smoothed finite element method.
In his research, Solid mechanics and Penalty method is intimately related to Geometry, which falls under the overarching field of Stiffness matrix. In his study, Discrete element method is inextricably linked to Extended finite element method, which falls within the broad field of Mixed finite element method. Many of his research projects under Structural engineering are closely connected to Isotropy and Simple with Isotropy and Simple, tying the diverse disciplines of science together.
His most cited work include:
- An edge-based smoothed finite element method (ES-FEM) for static, free and forced vibration analyses of solids (490 citations)
- A node-based smoothed finite element method (NS-FEM) for upper bound solutions to solid mechanics problems (415 citations)
- A software framework for probabilistic sensitivity analysis for computationally expensive models (321 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Finite element method, Structural engineering, Vibration, Smoothed finite element method and Mathematical analysis. His Finite element method research includes themes of Smoothing, Geometry and Numerical analysis. His Smoothing research is multidisciplinary, incorporating elements of Upper and lower bounds, Mathematical optimization and Edge.
His study looks at the relationship between Structural engineering and topics such as Composite number, which overlap with Deformation theory and Carbon nanotube. His Vibration study combines topics in areas such as Shear, Composite material, Material properties and Stiffness. His Smoothed finite element method course of study focuses on Extended finite element method and Discrete element method.
He most often published in these fields:
- Finite element method (62.22%)
- Structural engineering (43.11%)
- Vibration (37.78%)
What were the highlights of his more recent work (between 2019-2021)?
- Vibration (37.78%)
- Algorithm (9.33%)
- Mathematical analysis (31.11%)
In recent papers he was focusing on the following fields of study:
Trung Nguyen-Thoi mostly deals with Vibration, Algorithm, Mathematical analysis, Finite element method and Artificial neural network. His work carried out in the field of Vibration brings together such families of science as Smoothed finite element method, Harmonic, Porosity and Interpolation. The study incorporates disciplines such as Shear and Composite number in addition to Smoothed finite element method.
His Mathematical analysis research is multidisciplinary, relying on both Natural frequency, Material properties and Galerkin method. His Finite element method study combines topics from a wide range of disciplines, such as Piezoelectricity, Shear and Magneto. His Buckling study is focused on Structural engineering in general.
Between 2019 and 2021, his most popular works were:
- Solidification inside a clean energy storage unit utilizing phase change material with copper oxide nanoparticles (97 citations)
- Numerical study for nanofluid behavior inside a storage finned enclosure involving melting process (37 citations)
- Prediction of slope failure in open-pit mines using a novel hybrid artificial intelligence model based on decision tree and evolution algorithm. (21 citations)
In his most recent research, the most cited papers focused on:
- Composite material
- Statistics
- Finite element method
His scientific interests lie mostly in Artificial intelligence, Finite element method, Artificial neural network, Composite material and Nanofluid. His Finite element method study combines topics in areas such as Modal, Mathematical analysis and Edge. His Mathematical analysis research is multidisciplinary, incorporating perspectives in Piezoelectricity, Parametric statistics and Magneto.
His Artificial neural network study also includes fields such as
- Support vector machine which connect with Rock mass rating, Structural engineering, Cohesion, Compressive strength and Shear strength,
- Mean squared error that intertwine with fields like Feature selection, Monte Carlo method and Extreme learning machine,
- Algorithm which is related to area like Flexibility method. His Nanofluid study incorporates themes from Nusselt number, Pitch ratio and Forced convection. His Open-pit mining study integrates concerns from other disciplines, such as Vibration and Random forest.
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