Research graph
References from Integrating machine learning with DEM for effective calibration of bonded-particle structures. Local targets link to admitted publications; unresolved targets remain external evidence.
An extended arbitrary Lagrangian–Eulerian finite element method for large deformation of solid mechanics
10.1016/j.finel.2007.12.005 · 2008 · External reference
Discrete element modeling of the machining processes of brittle materials: recent development and future prospective
10.1007/s00170-020-05792-y · 2020 · External reference
Wire-feed additive manufacturing of metal components: technologies, developments and future interests
10.1007/s00170-015-7077-3 · 2015 · External reference
Coupled CFD-DEM simulation of interfacial fluid–particle interaction during binder jet 3D printing
10.1016/j.cma.2024.116747 · 2024 · External reference
A strain energy-based elastic parameter calibration method for lattice/bonded particle modelling of solid materials
2022 · External reference
A scale-invariant bonded particle model for simulating large deformation and failure of continua
10.1016/j.compgeo.2020.103735 · 2020 · External reference
Discrete element method using cohesive plastic beam for modeling elasto-plastic deformation of ductile materials
10.1007/s40571-020-00343-4 · 2021 · External reference
Grain growth in sintering: A discrete element model on large packings
10.1016/j.actamat.2021.117182 · 2021 · External reference
Microstructure evolution during sintering: Discrete element method approach
10.1111/jace.19131 · 2023 · External reference
A bonded-particle model for rock
10.1016/j.ijrmms.2004.09.011 · 2004 · External reference
A rheometry based calibration of a first-order DEM model to generate virtual avatars of metal Additive Manufacturing (AM) powders
10.1016/j.powtec.2018.09.047 · 2019 · External reference
Simulating fractures with bonded discrete element method
10.1109/tvcg.2021.3106738 · 2021 · External reference
Analytic laws for direct calibration of discrete element modeling of brittle elastic media using cohesive beam model
10.1007/s40571-018-00221-0 · 2019 · External reference
Linearization-based methods for the calibration of bonded-particle models
10.1007/s40571-020-00348-z · 2021 · External reference
A study of abrasive wear on high speed steel surface in hot rolling by Discrete Element Method
10.1016/j.triboint.2017.01.034 · 2017 · External reference
Deep learning-based analysis of true triaxial DEM simulations: Role of fabric and particle aspect ratio
10.1016/j.compgeo.2024.106529 · 2024 · External reference
DEM simulations of agglomerates impact breakage using Timoshenko beam bond model
10.1007/s10035-022-01231-9 · 2022 · External reference
Modelling third body flows with a discrete element method-a tool for understanding wear with adhesive particles
10.1016/j.triboint.2006.02.056 · 2007 · External reference
Discrete element method, a tool to investigate complex thermo mechanical behaviour: application to friction stir welding
10.1007/s12289-009-0433-9 · 2009 · External reference
Numerical analysis of FSW employing discrete element method
2017 · External reference
A 3D distinct lattice spring model for elasticity and dynamic failure
10.1002/nag.930 · 2011 · External reference
Discrete element method to simulate continuous material by using the cohesive beam model
10.1016/j.cma.2011.12.002 · 2012 · External reference
3DRSP: Matlab-based random sphere packing code in three dimensions
10.1016/j.softx.2022.101051 · 2022 · External reference
An improved specimen generation method for DEM based on local Delaunay tessellation and distance function
10.1002/nag.1088 · 2012 · External reference
An efficient algorithm to generate random sphere packs in arbitrary domains
10.1016/j.camwa.2016.02.032 · 2016 · External reference
Unresolved reference
2012 · External reference
3D discrete solid-element method for elastoplastic problems of continuity
10.1061/(asce)em.1943-7889.0001459 · 2018 · External reference
Modelling of elastic continua using a grillage of structural elements based on discrete element concepts
10.1002/nme.99 · 2001 · External reference
Estimating DEM microparameters for uniaxial compression simulation with genetic programming
10.1016/j.ijrmms.2019.03.024 · 2019 · External reference
Parameter calibration method of clustered-particle logic concrete DEM model using BP neural network-particle swarm optimisation algorithm (BP-PSO) inversion method
2023 · External reference
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation
10.1016/j.powtec.2020.02.077 · 2020 · External reference
A relationship between tensile strength and loading stress governing the onset of mode I crack propagation obtained via numerical investigations using a bonded particle model
10.1002/nag.2710 · 2017 · External reference
Effect of micromechanical parameters of microstructure on compressive and tensile failure process of rock
10.1016/j.ijrmms.2013.08.016 · 2013 · External reference
Combination of discrete element method and artificial neural network for predicting porosity of gravel-bed river
10.3390/w11071461 · 2019 · External reference
Machine learning-based intelligent prediction of elastic modulus of rocks at thar coalfield
10.3390/su14063689 · 2022 · External reference
Predicting liner wear of ball mills using discrete element method and artificial neural network
10.1016/j.cherd.2022.04.013 · 2022 · External reference
Use of machine learning for unraveling hidden correlations between particle size distributions and the mechanical behavior of granular materials
10.1007/s11440-021-01420-5 · 2022 · External reference
A discrete element modeling of rock and soil material based on the machine learning
2021 · External reference
Machine learning accelerated discrete element modeling of granular flows
10.1016/j.ces.2021.116832 · 2021 · External reference
A novel machine learning framework for efficient calibration of complex DEM model: A case study of a conglomerate sample
2023 · External reference
Calibration of the microparameters of rock specimens by using various machine learning algorithms
10.1061/(asce)gm.1943-5622.0001977 · 2021 · External reference
Machine learning-assisted distinct element model calibration: ANFIS, SVM, GPR, and MARS approaches
10.1007/s11440-021-01303-9 · 2022 · External reference
PFC model parameter calibration using uniform experimental design and a deep learning network
10.1088/1755-1315/304/3/032062 · 2019 · External reference
Modeling continuous solid structure with discrete particles
10.1016/j.powtec.2026.122394 · 2026 · External reference
Euler-Bernoulli beam theory
10.1007/978-90-481-2516-6_5 · 2009 · External reference
Unresolved reference
2011 · External reference
Dynamic particle packing to generate complex geometries
10.1016/j.cma.2025.117802 · 2025 · External reference
Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
10.1016/s0951-8320(03)00058-9 · 2003 · External reference
Mechanical characterization of 304L-VAR stainless steel in tension with a full coverage of low, intermediate, and high strain rates
10.1016/j.mechmat.2020.103654 · 2021 · External reference
Unresolved reference
2002 · External reference
Energy absorption of square tubes with perforations in dynamic axial crush
10.1007/s12541-020-00456-z · 2021 · External reference
An improved specimen generation method for DEM based on local Delaunay tessellation and distance function
10.1002/nag.1088 · ExternalCitation · doi-reference
A relationship between tensile strength and loading stress governing the onset of mode I crack propagation obtained via numerical investigations using a bonded particle model
10.1002/nag.2710 · ExternalCitation · doi-reference
A 3D distinct lattice spring model for elasticity and dynamic failure
10.1002/nag.930 · ExternalCitation · doi-reference
Modelling of elastic continua using a grillage of structural elements based on discrete element concepts
10.1002/nme.99 · ExternalCitation · doi-reference
Euler-Bernoulli beam theory
10.1007/978-90-481-2516-6_5 · ExternalCitation · doi-reference
Wire-feed additive manufacturing of metal components: technologies, developments and future interests
10.1007/s00170-015-7077-3 · ExternalCitation · doi-reference
Discrete element modeling of the machining processes of brittle materials: recent development and future prospective
10.1007/s00170-020-05792-y · ExternalCitation · doi-reference
DEM simulations of agglomerates impact breakage using Timoshenko beam bond model
10.1007/s10035-022-01231-9 · ExternalCitation · doi-reference
Machine learning-assisted distinct element model calibration: ANFIS, SVM, GPR, and MARS approaches
10.1007/s11440-021-01303-9 · ExternalCitation · doi-reference
Use of machine learning for unraveling hidden correlations between particle size distributions and the mechanical behavior of granular materials
10.1007/s11440-021-01420-5 · ExternalCitation · doi-reference
Discrete element method, a tool to investigate complex thermo mechanical behaviour: application to friction stir welding
10.1007/s12289-009-0433-9 · ExternalCitation · doi-reference
Energy absorption of square tubes with perforations in dynamic axial crush
10.1007/s12541-020-00456-z · ExternalCitation · doi-reference
Analytic laws for direct calibration of discrete element modeling of brittle elastic media using cohesive beam model
10.1007/s40571-018-00221-0 · ExternalCitation · doi-reference
Discrete element method using cohesive plastic beam for modeling elasto-plastic deformation of ductile materials
10.1007/s40571-020-00343-4 · ExternalCitation · doi-reference
Linearization-based methods for the calibration of bonded-particle models
10.1007/s40571-020-00348-z · ExternalCitation · doi-reference
Grain growth in sintering: A discrete element model on large packings
10.1016/j.actamat.2021.117182 · ExternalCitation · doi-reference
An efficient algorithm to generate random sphere packs in arbitrary domains
10.1016/j.camwa.2016.02.032 · ExternalCitation · doi-reference
Machine learning accelerated discrete element modeling of granular flows
10.1016/j.ces.2021.116832 · ExternalCitation · doi-reference
Predicting liner wear of ball mills using discrete element method and artificial neural network
10.1016/j.cherd.2022.04.013 · ExternalCitation · doi-reference
Discrete element method to simulate continuous material by using the cohesive beam model
10.1016/j.cma.2011.12.002 · ExternalCitation · doi-reference
Coupled CFD-DEM simulation of interfacial fluid–particle interaction during binder jet 3D printing
10.1016/j.cma.2024.116747 · ExternalCitation · doi-reference
Dynamic particle packing to generate complex geometries
10.1016/j.cma.2025.117802 · ExternalCitation · doi-reference
A scale-invariant bonded particle model for simulating large deformation and failure of continua
10.1016/j.compgeo.2020.103735 · ExternalCitation · doi-reference
Deep learning-based analysis of true triaxial DEM simulations: Role of fabric and particle aspect ratio
10.1016/j.compgeo.2024.106529 · ExternalCitation · doi-reference
An extended arbitrary Lagrangian–Eulerian finite element method for large deformation of solid mechanics
10.1016/j.finel.2007.12.005 · ExternalCitation · doi-reference
A bonded-particle model for rock
10.1016/j.ijrmms.2004.09.011 · ExternalCitation · doi-reference
Effect of micromechanical parameters of microstructure on compressive and tensile failure process of rock
10.1016/j.ijrmms.2013.08.016 · ExternalCitation · doi-reference
Estimating DEM microparameters for uniaxial compression simulation with genetic programming
10.1016/j.ijrmms.2019.03.024 · ExternalCitation · doi-reference
Mechanical characterization of 304L-VAR stainless steel in tension with a full coverage of low, intermediate, and high strain rates
10.1016/j.mechmat.2020.103654 · ExternalCitation · doi-reference
A rheometry based calibration of a first-order DEM model to generate virtual avatars of metal Additive Manufacturing (AM) powders
10.1016/j.powtec.2018.09.047 · ExternalCitation · doi-reference
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation
10.1016/j.powtec.2020.02.077 · ExternalCitation · doi-reference
Modeling continuous solid structure with discrete particles
10.1016/j.powtec.2026.122394 · ExternalCitation · doi-reference
3DRSP: Matlab-based random sphere packing code in three dimensions
10.1016/j.softx.2022.101051 · ExternalCitation · doi-reference
Modelling third body flows with a discrete element method-a tool for understanding wear with adhesive particles
10.1016/j.triboint.2006.02.056 · ExternalCitation · doi-reference
A study of abrasive wear on high speed steel surface in hot rolling by Discrete Element Method
10.1016/j.triboint.2017.01.034 · ExternalCitation · doi-reference
Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
10.1016/s0951-8320(03)00058-9 · ExternalCitation · doi-reference
3D discrete solid-element method for elastoplastic problems of continuity
10.1061/(asce)em.1943-7889.0001459 · ExternalCitation · doi-reference
Calibration of the microparameters of rock specimens by using various machine learning algorithms
10.1061/(asce)gm.1943-5622.0001977 · ExternalCitation · doi-reference
PFC model parameter calibration using uniform experimental design and a deep learning network
10.1088/1755-1315/304/3/032062 · ExternalCitation · doi-reference
Simulating fractures with bonded discrete element method
10.1109/tvcg.2021.3106738 · ExternalCitation · doi-reference
Microstructure evolution during sintering: Discrete element method approach
10.1111/jace.19131 · ExternalCitation · doi-reference
Machine learning-based intelligent prediction of elastic modulus of rocks at thar coalfield
10.3390/su14063689 · ExternalCitation · doi-reference
Combination of discrete element method and artificial neural network for predicting porosity of gravel-bed river
10.3390/w11071461 · ExternalCitation · doi-reference
