scholarly journals Analysis of Sluice Foundation Seepage Using Monitoring Data and Numerical Simulation

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Fan Xuefeng ◽  
Zhenyu Wu ◽  
Liu Lijun ◽  
Yanfeng Wen ◽  
Shu Yu ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Response Surface ◽  
Water Levels ◽  
Monitoring Data ◽  
Seepage Analysis ◽  
Seepage Pressure ◽  
Permeability Coefficients ◽  
Flood Season ◽  
Surface Method ◽  
Periodical Variation

For sluices built on soil foundations, seepage safety of the foundation is one of the most concerns during operation of sluices. Monitoring data could reflect the real seepage behavior in the foundation, but of which the shortcoming is that generally only the local seepage states can be measured. The seepage field in the whole foundation can be analyzed by numerical simulation. The permeability coefficients of the foundation materials significantly affect the numerical simulation results; however, it is difficult to accurately determine the values of permeability coefficients. In this paper, an approach based on response surface method (RSM) for calibration of permeability coefficients was proposed, and the efficiency of parameter calibration is improved by constructing the response surface equation instead of time-consuming finite element calculation of foundation seepage. The seepage in a sluice foundation was analyzed using monitoring data and numerical simulation. The monitoring data showed that the seepage pressure in the foundation periodically varies with high value in flood season and low value in dry season. After calibration of the permeability coefficients of the foundation materials using the measured seepage pressure, the seepage fields in the foundation for different water levels were numerically simulated to investigate the cause for the periodical variation of the seepage pressure and the seepage safety of the foundation was assessed with the calculated seepage gradients. The methods adopted in this study could be applied to seepage analysis for sluice foundations with similar geologic conditions and antiseepage measures.

An optimized design of compression sportswear fabric using numerical simulation and the response surface method

2011 ◽  
Vol 82 (2) ◽  
pp. 108-116 ◽  
Author(s):  
Yinglei Lin ◽  
Ka-fai Choi ◽  
Ming Zhang ◽  
Yi Li ◽  
Ameersing Luximon ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Response Surface ◽  
Response Surface Method ◽  
Optimized Design ◽  
Surface Method

scholarly journals Controlling Flow Instability in Straight Spur Gear Forging Using Numerical Simulation and Response Surface Method

2017 ◽  
Vol 31 (1) ◽  
pp. 82-96 ◽  
Author(s):  
Zhao-Yang Jin ◽  
Nan-Nan Li ◽  
Kai Yan ◽  
Jing-Xin Chen ◽  
Dong-Lai Wei ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Response Surface ◽  
Response Surface Method ◽  
Flow Instability ◽  
Spur Gear ◽  
Surface Method

Reliability Research of Building Fire Based on Numerical Simulation and Uniform Design

2011 ◽  
Vol 368-373 ◽  
pp. 665-672
Author(s):  
Su Fen Huang ◽  
Zhi Gang Song ◽  
Bin Li
Keyword(s):  
Numerical Simulation ◽  
Response Surface ◽  
Response Surface Method ◽  
Reliability Index ◽  
Limit State ◽  
Uniform Design ◽  
State Function ◽  
Limit State Function ◽  
Building Fire ◽  
Surface Method

Existing safety study of building fire is mainly based on the ISO834 temperature-time curve, which is a theoretical curve and not fully reflect the influencing factors of fire such as the distribution of fuel and ventilation of the building. Secondly, the reliability analysis of building fire lacks explicit limit state function, especially when the reliability calculation considers the internal force redistribution of the structure. Direct Monte Carlo simulation has no requirement of explicit limit state function, but it needs huge calculation efforts. To solve these two problems, the response surface method is proposed from the view point of numerical simulation and experiment design. Using the fire modeling software CFAST the actual result of temperature and thickness of smoke layer can be obtained. On this basis, the reliability index can be calculated with the response surface method，which can solve the problem of lacking explicit limit state function by regressing multi-variable function based on the inputs and outputs. Uniform design (UD) method can allocate more parameters without greatly increasing the calculation efforts. Using a case the calculation process is explained with. The results show that this method can quickly obtain the reliability index in the premise of less calculation.

Plane Truss Reliability Numerical Simulation Based on MATLAB

2012 ◽  
Vol 256-259 ◽  
pp. 1091-1096
Author(s):  
Yuan Ying Li ◽  
De Sheng Zhang
Keyword(s):  
Numerical Simulation ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Response Surface ◽  
Vertical Displacement ◽  
Basic Principles ◽  
Structure Reliability ◽  
Surface Method ◽  
Direct Sampling ◽  
Simulation Based

Based on the basic principles of structure reliability numerical analysis, the numerical simulation of the displacement and stress reliability of plane truss under vertical load was programmed with MATLAB. The failure probability of the most unfavorable structural vertical displacement and stress and reliable indicators were obtained through direct sampling Monte Carlo method, response surface method, response surface-Monte Carlo method and response surface-important sampling Monte Carlo method. It is found that calculation lasts longer since there are so many samples with Monte-Carlo method, higher accuracy and less calculation time can be achieved through response surface-Monte Carlo method and response surface-important sampling Monte Carlo method with fewer samples. The results of different numerical simulation calculations are almost identical and reliable, providing references to reliability analysis of complex structures.

A Proposal of PSO with Presumption Function of the Solution Landscape by Response Surface Method

2014 ◽  
Vol 134 (9) ◽  
pp. 1293-1298
Author(s):  
Toshiya Kaihara ◽  
Nobutada Fuji ◽  
Tomomi Nonaka ◽  
Yuma Tomoi
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Surface Method
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