Parametric Sensitivity Analysis of Long-Span Arch-Truss String Structure

2014 ◽  
Vol 919-921 ◽  
pp. 193-198
Author(s):  
Zheng Xian Bai ◽  
Xi Ming Hou ◽  
Shuai Tian ◽  
Jin Zhi Wu
Keyword(s):  
Sensitivity Analysis ◽  
Natural Frequencies ◽  
Simulation Method ◽  
Effective Area ◽  
Monte Carlo Simulation Method ◽  
Sectional Area ◽  
Static Behavior ◽  
Parametric Sensitivity ◽  
Long Span ◽  
String Structure

Parametric sensitivity to static behavior and dynamic characteristics of Long-span Arch-truss String Structures (ATSS), which is based on statistical distribution of parameter errors including elastic modulus of the material, effective area and pre-stress of cable, and thickness of steel pipe, etc., was studied by Monte Carlo simulation method of ANSYS. The error of sectional area of cable is found to be the most sensitive parameter and the natural frequencies are greatly sensitive to the errors of modulus of members. The results help to determine suitable updating parameters of ATSS, and provide valuable advices to guide the construction control.

Frequency Reliability Sensitivity Analysis for Rotor System with Random Parameters

2014 ◽  
Vol 670-671 ◽  
pp. 1029-1032 ◽  
Author(s):  
Lei Meng ◽  
Shuo Li ◽  
He Li ◽  
Li Juan Guo
Keyword(s):  
Sensitivity Analysis ◽  
Natural Frequencies ◽  
Random Systems ◽  
Synthesis Method ◽  
Simulation Method ◽  
Rayleigh Quotient ◽  
Random Factor ◽  
Mean Values ◽  
Reliability Sensitivity ◽  
Reliability Sensitivity Analysis

The random factor method (RFM), an effective numerical simulation method, is employed to analyze the probabilistic characteristics and reliability sensitivity of uncertain structure system. The natural frequencies of the system can be expressed as the function of the random factors. By using the random variable’s algebra synthesis method, the expressions for the mean value and standard deviation of natural frequencies are derived from Rayleigh quotient. The reliability mode and the safety probability of random systems are defined, and then the frequency reliability sensitivity analysis method is presented. The formulas of failure probability sensitivity are derived when random variables are normally distributed. The reliability index is evaluated, and its sensitivity to mean values and variances are mathematically expressed, then the efficiency and accuracy of the proposed method are demonstrated by a numerical example.

Parameter Sensitivity Analysis of Vertical Deflection for Long-Span Continuous Rigid-Frame Bridge

2010 ◽  
Vol 163-167 ◽  
pp. 1500-1504 ◽  
Author(s):  
Heng Bin Zheng ◽  
Xiao Lin Yu ◽  
Jun Liang Hu ◽  
Quan Sheng Yan
Keyword(s):  
Sensitivity Analysis ◽  
Element Model ◽  
Simulation Method ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Long Span ◽  
Continuous Rigid Frame Bridge ◽  
Rigid Frame ◽  
Rigid Frame Bridge

The excessive long-term deflections of a long span continuous girder bridge may induce vehicles to move unsafely and hazard to the bridge operation, thus to limit the development of this bridge type. In this paper the main parameters influencing the long-term deflections of a continuous rigid-frame bridge, such as pre-stressed losses, mass distribution of the box girder and Young’s modules of concrete etc., were investigated. With the establishment of the finite element model of a real bridge and the premise of describing mechanism of each parameter, detailed parameter sensitivity analysis of long-term deflections were carried out with numerical simulation method. The results of this study may help to understand the main mechanism about the long-term deflection of continuous rigid-frame bridge and provide some reference for the wide use of this type of bridges.

scholarly journals ALGORITHM FOR CONTROLLING THE SPECTRUM OF EIGENFREQUENCIES AND VIBRATION MODES BY CHARDING THE GEOMETRIC PARAMETERS OF MAST SESTEMS

2021 ◽  
pp. 6-18
Author(s):  
Vladimir Grinyov ◽  
Vitaliy Vynogradov
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Maximum Principle ◽  
Optimality Conditions ◽  
Natural Frequency ◽  
Natural Frequencies ◽  
Sectional Area ◽  
Cross Sectional ◽  
The Maximum Principle ◽  
Natural Frequency Spectrum

The article considers a model of a mast with six levels of fastening of cables. The main attention in the work is considered to the methods of control of the natural frequency spectrum, due to the use of methods of sensitivity analysis and optimization. The above task is achieved by varying the cross-sectional area of the pipes - racks. Automation of computational processes is provided by programming the built-in module in the Revit program. For more convenient and faster control of the natural frequency spectrum, the algorithm described above was written in a free add-on for Revit - Dynamo. With the help of so-called nodes, an application was created that took data from the depicted 3D model Revit and performed calculations. This allows you to easily use optimality conditions similar to the maximum principle. The sensitivity analysis for the first and second own is carried out in the work. The mechanism of their management within the limits of the investigated model is shown. The relations in the case of the problem of finding the natural frequency extremum with a given number are given, provided that the total amount of varied bands is fixed. The numerical control algorithm is based on the necessary optimality conditions in the form of the maximum principle for rod models. A variant of varying the area of the belts along the height of the mast is proposed. The sensitivity analysis for the first and second natural frequencies is carried out and its use for construction of effective computational process is shown. Based on the results of the work, a working software algorithm was created for fast analysis of mast oscillations on extensions. Graphs of zones of possible change of the first and second frequencies are resulted. The distribution of the cross-sectional area for frequencies is shown. To compare the results of natural frequency calculations on other calculation models, the first and second natural frequencies of bending oscillations were calculated by the finite element method in the SCAD complex. The errors for the points of the curves (constant in the height of the mast area of the belts) do not exceed 10%. It should be noted that the consideration of optimization problems of the above type on the basis of finite element models is quite difficult; for them it is not possible to formulate the necessary conditions of optimality similar to the principle of maximum.

Parametric Sensitivity Analysis of Fuzzy Reliability Based on the Cut-Set of Fuzzy Mathematics

2010 ◽  
Vol 426-427 ◽  
pp. 60-64
Author(s):  
X.J. Cheng
Keyword(s):  
Sensitivity Analysis ◽  
Computational Model ◽  
Numerical Solution ◽  
Reliability Analysis ◽  
Simulation Method ◽  
Fuzzy Mathematics ◽  
Fuzzy Reliability ◽  
Parametric Sensitivity ◽  
Parametric Sensitivity Analysis ◽  
Cut Set

The problem of the parametric sensitivity of fuzzy reliability analysis was discussed in this paper. Firstly, based on the concept of cut-set of fuzzy mathematics, a computational model is introduced. Then, the expression of cut-set of fuzzy mathematics is built in the case of normal random stress and normal fuzzy strength, and the effect of each parameter is analyzed. Finally, a simulation method is given to obtain the numerical solution of parametric sensitivity, and its validity is proved successfully by an example.

scholarly journals Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Electricity Sector ◽  
Cost Functions ◽  
Density Estimator ◽  
Monte Carlo Simulation Method ◽  
Commercial Building ◽  
Complementary Method ◽  
The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

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