OOIR: Observatory of International Research

Papers

(The H4-Index of Computer Methods in Applied Mechanics and Engineering is 64. 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 2020-04-01 to 2024-04-01.)

Article	Citations
The Arithmetic Optimization Algorithm	1520
An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications	801
Dwarf Mongoose Optimization Algorithm	417
Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data	397
Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications	387
Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems	361
A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics	345
PPINN: Parareal physics-informed neural network for time-dependent PDEs	228
hp-VPINNs: Variational physics-informed neural networks with domain decomposition	213
SciANN: A Keras/TensorFlow wrapper for scientific computations and physics-informed deep learning using artificial neural networks	178
Physics-informed multi-LSTM networks for metamodeling of nonlinear structures	168
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems	149
A framework to model the fatigue behavior of brittle materials based on a variational phase-field approach	148
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks	146
Starling murmuration optimizer: A novel bio-inspired algorithm for global and engineering optimization	146
Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization	132
Deep generative modeling for mechanistic-based learning and design of metamaterial systems	116
Designing phononic crystal with anticipated band gap through a deep learning based data-driven method	110
Geometric deep learning for computational mechanics Part I: anisotropic hyperelasticity	106
Hybrid FEM and peridynamic simulation of hydraulic fracture propagation in saturated porous media	101
A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths	99
A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials	99
Modified couple stress-based geometrically nonlinear oscillations of porous functionally graded microplates using NURBS-based isogeometric approach	98
A machine learning based plasticity model using proper orthogonal decomposition	95
Parametric deep energy approach for elasticity accounting for strain gradient effects	95

POD-DL-ROM: Enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition	94
Multi-level convolutional autoencoder networks for parametric prediction of spatio-temporal dynamics	93
A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data	92
Smart constitutive laws: Inelastic homogenization through machine learning	91
Hybrid enhanced Monte Carlo simulation coupled with advanced machine learning approach for accurate and efficient structural reliability analysis	85
Novel probabilistic model for searching most probable point in structural reliability analysis	84
Acoustic topology optimization of sound absorbing materials directly from subdivision surfaces with isogeometric boundary element methods	82
Non-invasive inference of thrombus material properties with physics-informed neural networks	82
Sobolev training of thermodynamic-informed neural networks for interpretable elasto-plasticity models with level set hardening	81
A higher order nonlocal operator method for solving partial differential equations	80
Unsupervised discovery of interpretable hyperelastic constitutive laws	79
Thermal field prediction for laser scanning paths in laser aided additive manufacturing by physics-based machine learning	78
Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy	77
Hierarchical Deep Learning Neural Network (HiDeNN): An artificial intelligence (AI) framework for computational science and engineering	76
New efficient and robust method for structural reliability analysis and its application in reliability-based design optimization	74
A ductile phase-field model based on degrading the fracture toughness: Theory and implementation at small strain	73
A self-adaptive deep learning algorithm for accelerating multi-component flash calculation	73
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks	72
A phase-field model for mixed-mode fracture based on a unified tensile fracture criterion	72
SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials	72
MOMPA: Multi-objective marine predator algorithm	72
A sequential calibration and validation framework for model uncertainty quantification and reduction	71
New hybrid reliability-based topology optimization method combining fuzzy and probabilistic models for handling epistemic and aleatory uncertainties	71
Fracture of thermo-elastic solids: Phase-field modeling and new results with an efficient monolithic solver	71
An enhanced hybrid arithmetic optimization algorithm for engineering applications	71
The neural particle method – An updated Lagrangian physics informed neural network for computational fluid dynamics	69
A new Lagrange multiplier approach for gradient flows	69
Data-driven fracture mechanics	69
Adaptive fourth-order phase field analysis for brittle fracture	69
An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning	68
De-homogenization of optimal multi-scale 3D topologies	67
An adaptive global–local approach for phase-field modeling of anisotropic brittle fracture	67
Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture	67
Phase-field modeling of porous-ductile fracture in non-linear thermo-elasto-plastic solids	66
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	66
Data-driven multiscale finite element method: From concurrence to separation	65
Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks	65
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems	65
Deep-learning-based surrogate flow modeling and geological parameterization for data assimilation in 3D subsurface flow	64