OOIR: Observatory of International Research

Papers

(The H4-Index of Computer Methods in Applied Mechanics and Engineering is 62. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)

Article	Citations
The Arithmetic Optimization Algorithm	1568
Dwarf Mongoose Optimization Algorithm	439
Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications	408
Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems	372
A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics	361
PPINN: Parareal physics-informed neural network for time-dependent PDEs	231
hp-VPINNs: Variational physics-informed neural networks with domain decomposition	220
SciANN: A Keras/TensorFlow wrapper for scientific computations and physics-informed deep learning using artificial neural networks	183
Physics-informed multi-LSTM networks for metamodeling of nonlinear structures	172
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks	162
Starling murmuration optimizer: A novel bio-inspired algorithm for global and engineering optimization	160
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems	157
Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization	138
Deep generative modeling for mechanistic-based learning and design of metamaterial systems	121
Geometric deep learning for computational mechanics Part I: anisotropic hyperelasticity	111
A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths	105
A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials	104
A machine learning based plasticity model using proper orthogonal decomposition	102
Hybrid FEM and peridynamic simulation of hydraulic fracture propagation in saturated porous media	102
POD-DL-ROM: Enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition	100
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data	99
Modified couple stress-based geometrically nonlinear oscillations of porous functionally graded microplates using NURBS-based isogeometric approach	99
Parametric deep energy approach for elasticity accounting for strain gradient effects	99
Smart constitutive laws: Inelastic homogenization through machine learning	97
Multi-level convolutional autoencoder networks for parametric prediction of spatio-temporal dynamics	94

Hybrid enhanced Monte Carlo simulation coupled with advanced machine learning approach for accurate and efficient structural reliability analysis	89
Sobolev training of thermodynamic-informed neural networks for interpretable elasto-plasticity models with level set hardening	86
Novel probabilistic model for searching most probable point in structural reliability analysis	84
Non-invasive inference of thrombus material properties with physics-informed neural networks	84
Unsupervised discovery of interpretable hyperelastic constitutive laws	83
A higher order nonlocal operator method for solving partial differential equations	82
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks	80
Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy	80
Hierarchical Deep Learning Neural Network (HiDeNN): An artificial intelligence (AI) framework for computational science and engineering	79
New efficient and robust method for structural reliability analysis and its application in reliability-based design optimization	77
Fracture of thermo-elastic solids: Phase-field modeling and new results with an efficient monolithic solver	76
MOMPA: Multi-objective marine predator algorithm	76
An enhanced hybrid arithmetic optimization algorithm for engineering applications	76
Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks	76
A phase-field model for mixed-mode fracture based on a unified tensile fracture criterion	74
SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials	74
A self-adaptive deep learning algorithm for accelerating multi-component flash calculation	74
A ductile phase-field model based on degrading the fracture toughness: Theory and implementation at small strain	74
An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning	73
New hybrid reliability-based topology optimization method combining fuzzy and probabilistic models for handling epistemic and aleatory uncertainties	73
Data-driven fracture mechanics	71
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems	71
A new Lagrange multiplier approach for gradient flows	71
A sequential calibration and validation framework for model uncertainty quantification and reduction	71
The neural particle method – An updated Lagrangian physics informed neural network for computational fluid dynamics	71
Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture	70
A physics-guided neural network framework for elastic plates: Comparison of governing equations-based and energy-based approaches	69
Physics informed neural networks for continuum micromechanics	68
An open-source Abaqus implementation of the phase-field method to study the effect of plasticity on the instantaneous fracture toughness in dynamic crack propagation	68
Deep-learning-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow	68
De-homogenization of optimal multi-scale 3D topologies	67
Phase field modelling of fracture and fatigue in Shape Memory Alloys	66
Data-driven multiscale finite element method: From concurrence to separation	65
Topology optimization using material-field series expansion and Kriging-based algorithm: An effective non-gradient method	65
An extended finite element solution for hydraulic fracturing with thermo-hydro-elastic–plastic coupling	63
Universal machine learning for topology optimization	63
Double-phase-field formulation for mixed-mode fracture in rocks	62