Reliability analysis of mid-plane symmetric laminated plates using direct simulation method

1998 ◽  
Vol 43 (1) ◽  
pp. 1-13 ◽  
Author(s):  
H.K. Jeong ◽  
R.A. Shenoi
Keyword(s):  
Reliability Analysis ◽  
Simulation Method ◽  
Laminated Plates ◽  
Direct Simulation ◽  
Plane Symmetric

A direct simulation method for flows with suspended paramagnetic particles

2008 ◽  
Vol 227 (9) ◽  
pp. 4441-4458 ◽  
Author(s):  
Tae Gon Kang ◽  
Martien A. Hulsen ◽  
Jaap M.J. den Toonder ◽  
Patrick D. Anderson ◽  
Han E.H. Meijer
Keyword(s):  
Simulation Method ◽  
Direct Simulation

scholarly journals Semi-Supervised Deep Learning for High-Dimensional Uncertainty Quantification

2020 ◽  
Author(s):  
Zequn Wang ◽  
Mingyang Li
Keyword(s):  
Uncertainty Quantification ◽  
Reliability Analysis ◽  
Supervised Learning ◽  
Dimensional Space ◽  
Limit State ◽  
Failure Surface ◽  
Simulation Method ◽  
High Dimensional ◽  
State Function ◽  
Latent Space

Abstract Conventional uncertainty quantification methods usually lacks the capability of dealing with high-dimensional problems due to the curse of dimensionality. This paper presents a semi-supervised learning framework for dimension reduction and reliability analysis. An autoencoder is first adopted for mapping the high-dimensional space into a low-dimensional latent space, which contains a distinguishable failure surface. Then a deep feedforward neural network (DFN) is utilized to learn the mapping relationship and reconstruct the latent space, while the Gaussian process (GP) modeling technique is used to build the surrogate model of the transformed limit state function. During the training process of the DFN, the discrepancy between the actual and reconstructed latent space is minimized through semi-supervised learning for ensuring the accuracy. Both labeled and unlabeled samples are utilized for defining the loss function of the DFN. Evolutionary algorithm is adopted to train the DFN, then the Monte Carlo simulation method is used for uncertainty quantification and reliability analysis based on the proposed framework. The effectiveness is demonstrated through a mathematical example.

A Direct Simulation Method for Subsonic, Microscale Gas Flows

2002 ◽  
Vol 179 (2) ◽  
pp. 400-425 ◽  
Author(s):  
Quanhua Sun ◽  
Iain D. Boyd
Keyword(s):  
Simulation Method ◽  
Gas Flows ◽  
Direct Simulation

SAFETY AND RELIABILITY OF BREAKWATERS

1984 ◽  
Vol 1 (19) ◽  
pp. 164 ◽  
Author(s):  
A. Mol ◽  
R.L. Groeneveld ◽  
A.J. Waanders
Keyword(s):  
Reliability Analysis ◽  
Probability Distributions ◽  
Simulation Method ◽  
Design Parameters ◽  
Suggested Approach ◽  
Design Procedures ◽  
Traditional Design ◽  
Safety And Reliability ◽  
Event Trees ◽  
Rubble Mound Breakwaters

This paper discusses the need to incorporate a reliability analysis in the design procedures for rubble mound breakwaters. Such an analysis is defined and a suggested approach is outlined. Failure mechanisms are analysed and categorized in Damage Event Trees. The probability of failure is computed using a level III simulation method to include time and cumulative effects and to account for skewed probability distributions. Typical outputs of the computer program are shown and compared with results according to traditional design approaches. The paper concludes that there is a definite need to include reliability analysis in the design procedures for larger breakwaters and such an analysis must consider the accuracy of design parameters and methods.

Reliability Analysis of Composite Structure Using ANSYS Software

2014 ◽  
Vol 945-949 ◽  
pp. 1155-1158
Author(s):  
Wei Tao Zhao ◽  
Feng Guo ◽  
Xiao Li
Keyword(s):  
Reliability Analysis ◽  
Composite Structures ◽  
Fiber Composite ◽  
Laminated Plates ◽  
Ansys Software ◽  
Geometric Tolerances ◽  
Surface Method ◽  
Practical Engineering ◽  
Critical Components ◽  
Fiber Composite Materials

ANSYS software has provided complete and accurate solutions for composite laminate analysis and provided a set of special elements for different composite structures such as laminated plates, beams, solid structures and stiffeners. Fiber composite materials have been widely used to critical components of aircrafts, automobiles, mechanical, and marine structures. Since uncertainties associated with geometric tolerances, material properties, and boundary conditions widely exist in practical engineering problems. The probability approach is the most popular way to quantify uncertain parameters and perform the reliability analysis. The paper researches on the reliability analysis of the composite panels using ANSYS software. The numerical example is given, it is shown that the response surface method (RSM) can reduce the computational efforts comparing with Monte Carlo simulation (MCS).

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