scholarly journals An Interval Process Method for Non-Random Uncertain Aeroelastic Analysis

Vibration ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 787-804
Author(s):  
Zahra Sotoudeh ◽  
Tyler Lyman ◽  
Leslie Montes Lucano ◽  
Natallia Urieva
Keyword(s):  
Monte Carlo Simulation ◽  
Sampling Method ◽  
Free Stream ◽  
Distribution Functions ◽  
Upper And Lower Bounds ◽  
Stream Velocity ◽  
Probability Distribution Functions ◽  
Aeroelastic Analysis ◽  
Practical Engineering ◽  
Process Method

In this paper, we use the Monte Carlo simulation to study aeroelastic behavior caused by non-random uncertain free-stream velocity. For sampling, we use the interval process method. Each family of samples is defined by a correlation function and upper and lower bounds. By using this sampling method, there is no need for constructing precise probability distribution functions; therefore, this method is suitable for practical engineering applications. We studied the aeroelastic behavior of an airfoil and a high aspect-ratio wing.

Extended two-dimensional belief function based on divergence measurement

2020 ◽  
pp. 1-8
Author(s):  
Jianping Fan ◽  
Jing Wang ◽  
Meiqin Wu
Keyword(s):  
Belief Function ◽  
Distribution Functions ◽  
Divergence Measure ◽  
Uncertain Information ◽  
Belief Functions ◽  
Two Dimensional ◽  
Probability Distribution Functions ◽  
Basic Probability ◽  
The Difference ◽  
Supporting Degree

The two-dimensional belief function (TDBF = (mA, mB)) uses a pair of ordered basic probability distribution functions to describe and process uncertain information. Among them, mB includes support degree, non-support degree and reliability unmeasured degree of mA. So it is more abundant and reasonable than the traditional discount coefficient and expresses the evaluation value of experts. However, only considering that the expert’s assessment is single and one-sided, we also need to consider the influence between the belief function itself. The difference in belief function can measure the difference between two belief functions, based on which the supporting degree, non-supporting degree and unmeasured degree of reliability of the evidence are calculated. Based on the divergence measure of belief function, this paper proposes an extended two-dimensional belief function, which can solve some evidence conflict problems and is more objective and better solve a class of problems that TDBF cannot handle. Finally, numerical examples illustrate its effectiveness and rationality.

scholarly journals Development and Evaluation of a Fluctuating Plume Model for Odor Impact Assessment

2021 ◽  
Vol 11 (8) ◽  
pp. 3310
Author(s):  
Marzio Invernizzi ◽  
Federica Capra ◽  
Roberto Sozzi ◽  
Laura Capelli ◽  
Selena Sironi
Keyword(s):  
Experimental Data ◽  
Distribution Functions ◽  
Plume Model ◽  
Probability Distribution Functions ◽  
Weibull Pdf ◽  
Fluctuating Plume ◽  
Concentration Statistics ◽  
Modified Weibull ◽  
Instantaneous Concentration ◽  
Mean Concentration

For environmental odor nuisance, it is extremely important to identify the instantaneous concentration statistics. In this work, a Fluctuating Plume Model for different statistical moments is proposed. It provides data in terms of mean concentrations, variance, and intensity of concentration. The 90th percentile peak-to-mean factor, R90, was tested here by comparing it with the experimental results (Uttenweiler field experiment), considering different Probability Distribution Functions (PDFs): Gamma and the Modified Weibull. Seventy-two percent of the simulated mean concentration values fell within a factor 2 compared to the experimental ones: the model was judged acceptable. Both the modelled results for standard deviation, σC, and concentration intensity, Ic, overestimate the experimental data. This evidence can be due to the non-ideality of the measurement system. The propagation of those errors to the estimation of R90 is complex, but the ranges covered are quite repeatable: the obtained values are 1–3 for the Gamma, 1.5–4 for Modified Weibull PDF, and experimental ones from 1.4 to 3.6.

Probability Distribution Functions for the Random Forced Burgers Equation

1997 ◽  
Vol 78 (10) ◽  
pp. 1904-1907 ◽  
Author(s):  
Weinan E ◽  
Konstantin Khanin ◽  
Alexandre Mazel ◽  
Yakov Sinai
Keyword(s):  
Probability Distribution ◽  
Burgers Equation ◽  
Distribution Functions ◽  
Probability Distribution Functions

Reliability Assessment of Power System Using Importance Sampling Technique Based on Layer Optimization Simulation

2011 ◽  
Vol 88-89 ◽  
pp. 554-558 ◽  
Author(s):  
Bin Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power System ◽  
Importance Sampling ◽  
System Reliability ◽  
Sampling Method ◽  
Sampling Technique ◽  
Test System ◽  
Importance Sampling Method ◽  
Importance Sampling Technique

An improved importance sampling method with layer simulation optimization is presented in this paper. Through the solution sequence of the components’ optimum biased factors according to their importance degree to system reliability, the presented technique can further accelerate the convergence speed of the Monte-Carlo simulation. The idea is that the multivariate distribution’ optimization of components in power system is transferred to many steps’ optimization based on importance sampling method with different optimum biased factors. The practice is that the components are layered according to their importance degree to the system reliability before the Monte-Carlo simulation, the more forward, the more important, and the optimum biased factors of components in the latest layer is searched while the importance sampling is carried out until the demanded accuracy is reached. The validity of the presented is verified using the IEEE-RTS79 test system.

Effects of Embedded Vortices on Film-Cooled Turbulent Boundary Layers

1989 ◽  
Vol 111 (1) ◽  
pp. 71-77 ◽  
Author(s):  
P. M. Ligrani ◽  
A. Ortiz ◽  
S. L. Joseph ◽  
D. L. Evans
Keyword(s):  
Heat Transfer ◽  
Boundary Layers ◽  
Film Cooling ◽  
Free Stream ◽  
Flow Behavior ◽  
Local Heat Transfer ◽  
Local Heat ◽  
Turbulent Boundary Layers ◽  
Stream Velocity ◽  
Longitudinal Vortices

Heat transfer effects of longitudinal vortices embedded within film-cooled turbulent boundary layers on a flat plate were examined for free-stream velocities of 10 m/s and 15 m/s. A single row of film-cooling holes was employed with blowing ratios ranging from 0.47 to 0.98. Moderate-strength vortices were used with circulating-to-free stream velocity ratios of −0.95 to −1.10 cm. Spatially resolved heat transfer measurements from a constant heat flux surface show that film coolant is greatly disturbed and that local Stanton numbers are altered significantly by embedded longitudinal vortices. Near the downwash side of the vortex, heat transfer is augmented, vortex effects dominate flow behavior, and the protection from film cooling is minimized. Near the upwash side of the vortex, coolant is pushed to the side of the vortex, locally increasing the protection provided by film cooling. In addition, local heat transfer distributions change significantly as the spanwise location of the vortex is changed relative to film-cooling hole locations.

Sign in / Sign up

Export Citation Format

Share Document