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Neural networks in computational mechanics
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Outgoing claims: the papers this work cites, builds on, or argues with.
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FINITE ELEMENT SOLUTIONS WITH FEEDBACK NETWORK MECHANISM THROUGH DIRECT MINIMIZATION OF ENERGY FUNCTIONALS
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Are fem solutions of incompressible flows really incompressible? (or how simple flows can cause headaches!)
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First version of a data flow procedure language
inferredcites →https://doi.org/10.1007/978-1-4615-3344-3_87openalex-snapshot
Graphite Epoxy Defect Classification of Ultrasonic Signatures Using Statistical and Neural Network Techniques
inferredcites →https://doi.org/10.1007/978-1-4615-3344-3_90openalex-snapshot
Neural Network for Crack-Depth Determination from Ultrasonic Backscattering Data
inferredcites →https://doi.org/10.1007/978-1-4615-3344-3_91openalex-snapshot
A Neural Network Approach for Solving Inverse Problems in NDE
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Fast Learning Algorithms for Neural Networks
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Identification of Crack Shape Hidden in Solid by Means of Neural Network and Computational Mechanics
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Expert Aids to Finite Element System Applications
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Applications of Artificial Neural Nets in Structural Mechanics
inferredcites →https://doi.org/10.1007/bf00280752openalex-snapshot
A conjugate-residual-FEM for incompressible viscous flow analysis
inferredcites →https://doi.org/10.1007/bf00339943openalex-snapshot
“Neural” computation of decisions in optimization problems
inferredcites →https://doi.org/10.1007/bf01759922openalex-snapshot
Applications of artificial neural nets in structural mechanics
inferredcites →https://doi.org/10.1016/0045-7825(82)90054-8openalex-snapshot
Finite element solution of the unsteady Navier-Stokes equations by a fractional step method
inferredcites →https://doi.org/10.1016/0045-7949(92)90132-jopenalex-snapshot
Use of neural networks in detection of structural damage
inferredcites →https://doi.org/10.1016/0308-0161(94)00040-popenalex-snapshot
Neural network approach to estimate stable crack growth in welded specimens
inferredcites →https://doi.org/10.1016/0308-9126(90)90883-popenalex-snapshot
Eddy current defect characterization using neural networks
inferredcites →https://doi.org/10.1016/0893-6080(93)90013-mopenalex-snapshot
A universal theorem on learning curves
inferredcites →https://doi.org/10.1016/0963-8695(90)90293-ropenalex-snapshot
Review of progress in quantitative nondestructive evaluation
inferredcites →https://doi.org/10.1016/0963-8695(92)90010-eopenalex-snapshot
Classification of ultrasonic defect signatures using an artificial neural network
inferredcites →https://doi.org/10.1016/0963-8695(92)90018-copenalex-snapshot
Application of neural network to classification of defects: basic study of weights
inferredcites →https://doi.org/10.1016/0963-8695(92)90019-dopenalex-snapshot
Depth determination of surface-breaking cracks by a neural network
inferredcites →https://doi.org/10.1016/0963-8695(92)90020-hopenalex-snapshot
Ultrasonic flaw classification in weldments using neural networks
inferredcites →https://doi.org/10.1016/0963-8695(92)90021-8openalex-snapshot
A complex multi-layer neural network for defect detection and characterization
inferredcites →https://doi.org/10.1016/0963-8695(92)90099-3openalex-snapshot
Eddy current defect characterization using neural networks
inferredcites →https://doi.org/10.1016/s0168-2024(08)x7003-1openalex-snapshot
Augmented Lagrangian Methods: Applications to the Numerical Solution of Boundary-Value Problems
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A learning algorithm for multilayered neural networks based on linear least squares problems
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Learning representations by back-propagating errors
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Knowledge‐Based Modeling of Material Behavior with Neural Networks
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A hybrid neural network model for solving optimization problems
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Theory and applications of neural networks for industrial control systems
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30 years of adaptive neural networks: perceptron, Madaline, and backpropagation
inferredcites →https://doi.org/10.1109/72.165590openalex-snapshot
Massively parallel architectures for large scale neural network simulations
inferredcites →https://doi.org/10.1109/72.165600openalex-snapshot
Improving generalization performance using double backpropagation
inferredcites →https://doi.org/10.1109/72.165602openalex-snapshot
A two-phase optimization neural network
inferredcites →https://doi.org/10.1109/72.165605openalex-snapshot
Second-order neural nets for constrained optimization
inferredcites →https://doi.org/10.1109/72.182696openalex-snapshot
Disturbance rejection in nonlinear systems using neural networks
inferredcites →https://doi.org/10.1109/72.207617openalex-snapshot
Neural network for quadratic optimization with bound constraints
inferredcites →https://doi.org/10.1109/72.217184openalex-snapshot
A feedforward artificial neural network based on quantum effect vector-matrix multipliers
inferredcites →https://doi.org/10.1109/72.286908openalex-snapshot
Functional approximation by feed-forward networks: a least-squares approach to generalization
inferredcites →https://doi.org/10.1109/72.286912openalex-snapshot
Inverse mapping of continuous functions using local and global information
inferredcites →https://doi.org/10.1109/72.317726openalex-snapshot
On the initialization and optimization of multilayer perceptrons
inferredcites →https://doi.org/10.1109/72.317727openalex-snapshot
Weight smoothing to improve network generalization
inferredcites →https://doi.org/10.1109/72.80209openalex-snapshot
Self-organizing network for optimum supervised learning
inferredcites →https://doi.org/10.1109/72.97932openalex-snapshot
Bounds on the number of samples needed for neural learning
inferredcites →https://doi.org/10.1109/78.157303openalex-snapshot
Enhancement of covariance matrix for array processing
inferredcites →https://doi.org/10.1109/78.175746openalex-snapshot
Optimum block-adaptive learning algorithm for error back-propagation networks
inferredcites →https://doi.org/10.1109/78.218154openalex-snapshot
On the optimal weight vector of a perceptron with Gaussian data and arbitrary nonlinearity
inferredcites →https://doi.org/10.1109/82.160170openalex-snapshot
Fast learning algorithms for neural networks
inferredcites →https://doi.org/10.1109/82.160171openalex-snapshot
Implementation of neural networks on massive memory organizations
inferredcites →https://doi.org/10.1109/icnn.1993.298527openalex-snapshot
Solving search problems with subgoals using an artificial neural network
inferredcites →https://doi.org/10.1109/icnn.1993.298597openalex-snapshot
Unknown parameter identification of parameterized system using multi-layered neural network
inferredcites →https://doi.org/10.1109/icnn.1993.298720openalex-snapshot
A new acceleration technique for the backpropagation algorithm
inferredcites →https://doi.org/10.1109/icnn.1993.298737openalex-snapshot
Hardware implementation of an artificial neural network
inferredcites →https://doi.org/10.1109/icnn.1993.298767openalex-snapshot
A neural network to solve discrete dynamic programming problems
inferredcites →https://doi.org/10.1109/icnn.1993.298802openalex-snapshot
Parallel computation of neural networks in a processor pipeline with partially shared memory
inferredcites →https://doi.org/10.1109/icnn.1993.298814openalex-snapshot
Stone impact damage to automotive paint finishes-a neural net analysis of electrochemical impedance data
inferredcites →https://doi.org/10.1109/icnn.1993.298816openalex-snapshot
Evaluation of the performance of various artificial neural networks to the signal fault diagnosis in nuclear reactor systems
inferredcites →https://doi.org/10.1109/icnn.1993.298817openalex-snapshot
Neural networks as massively parallel automatic test pattern generators
inferredcites →https://doi.org/10.1109/icnn.1993.298860openalex-snapshot
Neural plant inverse control approach to color error reduction for scanner and printer
inferredcites →https://doi.org/10.1109/iscas.1993.394093openalex-snapshot
An efficient tolerance design procedure for yield maximization using optimization techniques and neural network
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An introduction to computing with neural nets
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Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit
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VII INTERNATIONAL CONGRESS ON EXPERIMENTAL MECHANICS
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Three-Dimensional Fully Plastic Solutions for Plates and Cylinders With Through-Wall Cracks
inferredcites →https://doi.org/10.1115/1.3264257openalex-snapshot
On the Plastic and Viscoplastic Constitutive Equations—Part I: Rules Developed With Internal Variable Concept
inferredcites →https://doi.org/10.1115/1.3265669openalex-snapshot
Stable and Unstable Crack Growth of A508 Class 3 Plates Subjected to Combined Force of Thermal Shock and Tension
inferredcites →https://doi.org/10.1115/1.3265670openalex-snapshot
Cleavage and Ductile Thermal Shock Fractures of Corner-Cracked Nozzles
inferredcites →https://doi.org/10.1115/1.3601206openalex-snapshot
A Path Independent Integral and the Approximate Analysis of Strain Concentration by Notches and Cracks
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Technique for Estimation of Elastic Contact Stress Distributions by Neural Network.
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An Application of a Neural Network to CFRP Elastic Coefficient Design.
inferredcites →https://doi.org/10.1299/kikaia.59.489openalex-snapshot
Learning and Generation of BEM adaptive Meshes by Using Neural Network.
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Special Issue "Fuzzy/Neural Network Applications to Dynamics and Control of Mechanical Systems". Criterion Acquisition for the Motion Planning of Adaptive Truss. Implementation by Modular Neural Network.
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Estimations on J-Integral and Tearing Modulus T from a Single Specimen Test Record
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Research Trends in Neuromorphic Control
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Engineering approach for elastic-plastic fracture analysis
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Modeling of the Space Shuttle Main Engine Using Feed-forward Neural Networks
inferredcites →https://doi.org/10.2472/jsms.39.476openalex-snapshot
Benchmark project on inelastic deformation and life prediction of 21/4Cr-1Mo steel at high temperature under multiaxial stresses.
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Neural network architectures: an introduction
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Crystal Plasticity Constitutive Modeling and Testing at the Heat Affected Zone of Welded Joint in Steel Bridge
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Computational Mechanics Meets Artificial Intelligence
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Physics-informed deep operator network for predicting martensite evolution in superelastic shape memory alloys through cyclic tensile tests
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Identification of elastic-plastic material parameters from pyramidal indentation of thin films
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Novel anisotropic continuum‐discrete damage model capable of representing localized failure of massive structures
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A Deep Learning Approach Replacing the Finite Difference Method for In Situ Stress Prediction
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Determination of Poisson’s Ratio by Spherical Indentation Using Neural Networks—Part I: Theory
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Reduced-Order Constitutive Modeling of Directionally Solidified Ni-Base Superalloys
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Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle
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Artificial neural network for correction of effects of plasticity in equibiaxial residual stress profiles measured by hole drilling
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Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation
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Predicting and explaining nonlinear material response using deep physically guided neural networks with internal variables
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THE EFFECT OF KINEMATIC HARDENING ON SPHERICAL INDENTATION
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Design of a Short Tensile Coupon for Fiber Reinforced Plastic Using Artificial Neural Networks
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Using Machine Learning to Predict the Stress-strain State of a Ring Plate
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Identification of viscoplastic material parameters from spherical indentation data: Part I. Neural networks
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Deep Learning-Enabled Design and Seismic Performance Evaluation of a Nonlinear Magnetic Vibration Absorber for Structural Control
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BASIC STUDY ON THE FATIGUE LIFE PREDICTION OF STEEL STRUCTURAL MEMBER BASED ON THE CONTINUUM DAMAGE MECHANICS
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Dynamical Response Analysis of Jointed Structures by 2-D/3-D Adjusted Iwan Beam Elements
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Machine Learning Enhanced Boundary Element Method: Prediction of Gaussian Quadrature Points
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Connections Between Topology and Macroscopic Mechanical Properties of Three-Dimensional Open-Pore Materials
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Efficient Exploration of Microstructure-Property Spaces via Active Learning
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Machine Learning in Model-free Mechanical Property Imaging: Novel Integration of Physics With the Constrained Optimization Process
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Feed-Forward Neural Networks for Failure Mechanics Problems
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Comparative Study of Various Neural Network Types for Direct Inverse Material Parameter Identification in Numerical Simulations
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A Nonlinear Free Vibration Analysis of Functionally Graded Beams Using a Mixed Finite Element Method and a Comparative Artificial Neural Network
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Methodology for Neural Network-Based Material Card Calibration Using LS-DYNA MAT_187_SAMP-1 Considering Failure with GISSMO
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Mechanics 4.0 and Mechanical Engineering Education
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Quantifying Mechanical Properties of Automotive Steels with Deep Learning Based Computer Vision Algorithms
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Artificial Neural Networks-Based Material Parameter Identification for Numerical Simulations of Additively Manufactured Parts by Material Extrusion
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A Neural Network Approach for Locating Multiple Defects
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Locating Defects Using Dynamic Strain Analysis and Artificial Neural Networks
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Novel anisotropic continuum-discrete damage model capable of representing localized failure of massive structures. Part II: identification from tests under heterogeneous stress field
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The evolution of in-silico physiological models of bone remodelling: From cell population models to micro-MPA approaches
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New approach to composite materials modeling under extreme mechanical and thermal loads
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PARAMETER IDENTIFICATION AND MODELING OF SUPERELASTIC SHAPE MEMORY ALLOY WIRES SUBJECTED TO DYNAMIC LOADS
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A DIGITAL TWIN OF A FIBER BRAGG GRATING NETWORK IN THE LEADING EDGE OF A ROTATING COMPOSITE FAN BLADE SUBJECTED TO BIRD STRIKE
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