D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 56 Citations 10,526 230 World Ranking 923 National Ranking 95

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Thermodynamics
  • Mathematical analysis

His primary areas of investigation include Mechanics, Mathematical optimization, Porous medium, Ensemble Kalman filter and Permeability. His Mathematical optimization research is multidisciplinary, relying on both Stochastic modelling, Inverse problem, Markov chain Monte Carlo, Random field and Applied mathematics. In his study, Monte Carlo method and State is strongly linked to Stochastic process, which falls under the umbrella field of Applied mathematics.

His research in Porous medium intersects with topics in Statistical physics and Boundary value problem. His Ensemble Kalman filter research is multidisciplinary, incorporating elements of Meteorology, Data assimilation, Simulation and Nonlinear system. His Permeability research incorporates themes from Carbon sequestration, Mineralogy, Geomechanics and Finite volume method.

His most cited work include:

  • Stochastic Methods for Flow in Porous Media: Coping with Uncertainties (319 citations)
  • An efficient, high-order perturbation approach for flow in random porous media via Karhunen-Loève and polynomial expansions (268 citations)
  • Data assimilation for transient flow in geologic formations via ensemble Kalman filter (268 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Mathematical optimization, Monte Carlo method, Mechanics, Porous medium and Flow. His Mathematical optimization research includes themes of Random variable, Uncertainty quantification, Polynomial chaos, Ensemble Kalman filter and Applied mathematics. Dongxiao Zhang usually deals with Monte Carlo method and limits it to topics linked to Covariance and Mathematical analysis.

His Mechanics research focuses on Permeability and how it connects with Porosity, Soil science, Fluid dynamics and Carbon sequestration. His study looks at the intersection of Porous medium and topics like Lattice Boltzmann methods with Mineralogy. He has included themes like Hydraulic conductivity, Stochastic process and Stochastic modelling in his Flow study.

He most often published in these fields:

  • Mathematical optimization (22.70%)
  • Monte Carlo method (19.94%)
  • Mechanics (16.87%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (8.28%)
  • Artificial neural network (6.44%)
  • Deep learning (4.91%)

In recent papers he was focusing on the following fields of study:

Dongxiao Zhang spends much of his time researching Artificial intelligence, Artificial neural network, Deep learning, Partial differential equation and Algorithm. His Artificial intelligence study combines topics in areas such as Machine learning, Subsurface flow and Pattern recognition. The Artificial neural network study combines topics in areas such as Well logging, Training set, Mathematical optimization and Boundary value problem.

His Partial differential equation research includes elements of Dynamical systems theory, Conservation law, Domain decomposition methods and Groundwater flow equation. His study in Domain decomposition methods is interdisciplinary in nature, drawing from both Discontinuity and Applied mathematics. His work is dedicated to discovering how Algorithm, Genetic algorithm are connected with Parametric statistics and other disciplines.

Between 2018 and 2021, his most popular works were:

  • Laboratory characterisation of fracture compressibility for coal and shale gas reservoir rocks: A review (35 citations)
  • Deep learning of subsurface flow via theory-guided neural network (30 citations)
  • Air-Sea Fluxes With a Focus on Heat and Momentum (28 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Thermodynamics
  • Mathematical analysis

Dongxiao Zhang mostly deals with Oil shale, Artificial neural network, Artificial intelligence, Petroleum engineering and Partial differential equation. His Oil shale study combines topics from a wide range of disciplines, such as Mineralogy, Methane and Thermodynamics. While the research belongs to areas of Mineralogy, Dongxiao Zhang spends his time largely on the problem of Lead, intersecting his research to questions surrounding Anisotropy.

His Artificial neural network study integrates concerns from other disciplines, such as Boundary value problem, Deep learning, Mathematical optimization, Porous medium and Monte Carlo method. Dongxiao Zhang interconnects Sedimentary rock and Phase in the investigation of issues within Petroleum engineering. His Partial differential equation research integrates issues from Dynamical systems theory, Data assimilation and Groundwater flow equation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Stochastic Methods for Flow in Porous Media: Coping with Uncertainties

Dongxiao Zhang.
(2001)

673 Citations

Stochastic Methods for Flow in Porous Media

Dongxiao Zhang.
(2007)

398 Citations

Efficient Ensemble-Based Closed-Loop Production Optimization

Yan Chen;Dean S. Oliver;Dongxiao Zhang.
Spe Journal (2009)

394 Citations

An efficient, high-order perturbation approach for flow in random porous media via Karhunen-Loève and polynomial expansions

Dongxiao Zhang;Zhiming Lu.
Journal of Computational Physics (2004)

341 Citations

Data assimilation for transient flow in geologic formations via ensemble Kalman filter

Yan Chen;Dongxiao Zhang.
Advances in Water Resources (2006)

341 Citations

Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods

Heng Li;Heng Li;Dongxiao Zhang;Dongxiao Zhang.
Water Resources Research (2007)

286 Citations

Lattice Boltzmann pore-scale model for multicomponent reactive transport in porous media

Qinjun Kang;Peter C. Lichtner;Dongxiao Zhang.
Journal of Geophysical Research (2006)

284 Citations

Pore scale study of flow in porous media: Scale dependency, REV, and statistical REV

Dongxiao Zhang;Raoyang Zhang;Shiyi Chen;Wendy E. Soll.
Geophysical Research Letters (2000)

273 Citations

Displacement of a two-dimensional immiscible droplet in a channel

Qinjun Kang;Dongxiao Zhang;Shiyi Chen.
Physics of Fluids (2002)

273 Citations

Lattice Boltzmann simulation of chemical dissolution in porous media.

Qinjun Kang;Qinjun Kang;Dongxiao Zhang;Shiyi Chen;Shiyi Chen;Xiaoyi He.
Physical Review E (2002)

267 Citations

Best Scientists Citing Dongxiao Zhang

Qinjun Kang

Qinjun Kang

Los Alamos National Laboratory

Publications: 59

Alberto Guadagnini

Alberto Guadagnini

Politecnico di Milano

Publications: 58

Li Chen

Li Chen

Xi'an Jiaotong University

Publications: 44

Wolfgang Nowak

Wolfgang Nowak

University of Stuttgart

Publications: 34

Jichun Wu

Jichun Wu

Nanjing University

Publications: 32

Shlomo P. Neuman

Shlomo P. Neuman

University of Arizona

Publications: 32

Jun Yao

Jun Yao

China University of Petroleum, Beijing

Publications: 31

Harrie-Jan Hendricks Franssen

Harrie-Jan Hendricks Franssen

Forschungszentrum Jülich

Publications: 30

Jan Dirk Jansen

Jan Dirk Jansen

Delft University of Technology

Publications: 30

Wen-Quan Tao

Wen-Quan Tao

Xi'an Jiaotong University

Publications: 29

Zhenxue Dai

Zhenxue Dai

Los Alamos National Laboratory

Publications: 27

Ya-Ling He

Ya-Ling He

Xi'an Jiaotong University

Publications: 27

Albert C. Reynolds

Albert C. Reynolds

University of Tulsa

Publications: 25

Laosheng Wu

Laosheng Wu

University of California, Riverside

Publications: 23

Moran Wang

Moran Wang

Tsinghua University

Publications: 22

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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