scholarly journals Uncertain natural frequency analysis of composite plates including effect of noise – A polynomial neural network approach

2016 ◽  
Vol 143 ◽  
pp. 130-142 ◽  
Author(s):  
S. Dey ◽  
S. Naskar ◽  
T. Mukhopadhyay ◽  
U. Gohs ◽  
A. Spickenheuer ◽  
...  
Keyword(s):  
Neural Network ◽  
Natural Frequency ◽  
Frequency Analysis ◽  
Composite Plates ◽  
Network Approach ◽  
Neural Network Approach ◽  
Polynomial Neural Network ◽  
Natural Frequency Analysis

An accurate full-dimensional potential energy surface for the reaction OH + SO → H + SO2

2021 ◽  
Vol 23 (1) ◽  
pp. 487-497
Author(s):  
Jie Qin ◽  
Jun Li
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Invariant Polynomial ◽  
Network Approach ◽  
Neural Network Approach ◽  
Polynomial Neural Network

An accurate full-dimensional PES for the OH + SO ↔ H + SO2 reaction is developed by the permutation invariant polynomial-neural network approach.

scholarly journals Stochastic Natural Frequency Analysis of Composite Structures Based on Micro-Scale and Meso-Scale Uncertainty

2019 ◽  
Vol 9 (13) ◽  
pp. 2603 ◽  
Author(s):  
Shufeng Zhang ◽  
Xun Chen
Keyword(s):  
Natural Frequency ◽  
Frequency Analysis ◽  
Composite Structures ◽  
Great Influence ◽  
Composite Plates ◽  
Statistical Correlation ◽  
Micro Scale ◽  
Scale Uncertainty ◽  
Natural Frequency Analysis ◽  
Meso Scale

Composite structure often shows undesirably significant uncertainty in its mechanical properties, which may consequently result into large stochastic variation of its natural frequency. This study provides stochastic natural frequency analysis of typical composite structures based on micro-scale (constituent-scale) and meso-scale (ply-scale) uncertainty. Uncertainty propagation across micro-scale and meso-scale is investigated. Response surface method (RSM) based on finite element modeling is employed to obtain approximate natural frequency of structures with complex shape or boundary conditions, and mean value and standard deviation of natural frequency of composite plate and cylindrical shell are derived. Differences in natural frequency statistics of composite plates and cylindrical shells derived by considering uncertainty at different scales are quantified and discussed. Significant statistical correlation between ply elastic properties and ply density is observed, and the statistical correlation is demonstrated to lay great influence on the statistics of structure natural frequency.

scholarly journals Uncertainty Quantification in Natural Frequency of Composite Plates - An Artificial Neural Network Based Approach

2016 ◽  
Vol 25 (2) ◽  
pp. 096369351602500 ◽  
Author(s):  
Sudip Dey ◽  
Tanmoy Mukhopadhyay ◽  
Axel Spickenheuer ◽  
Uwe Gohs ◽  
S. Adhikari
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Uncertainty Quantification ◽  
Natural Frequency ◽  
Composite Plates ◽  
Ann Model ◽  
Artificial Neural ◽  
Natural Frequency Analysis

This paper presents the stochastic natural frequency for laminated composite plates by using artificial neural network (ANN) model. The ANN model is employed as a surrogate and is trained by using Latin hypercube sampling. Subsequently the stochastic first two natural frequencies are quantified with ANN based uncertainty quantification algorithm. The convergence of the proposed algorithm for stochastic natural frequency analysis of composite plates is verified and validated with original finite element method (FEM) in conjunction with Monte Carlo simulation. Both individual and combined variation of stochastic input parameters are considered to address the influence on the output of interest. The sample size and computational cost are reduced by employing the present approach compared to traditional Monte Carlo simulation.

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