Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications
نویسندگان
چکیده
In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the probability distribution of different uncertain parameters. Usually, we can safely linearize the dependence of the desired quantities y (e.g., stress at different structural points) on the uncertain parameters xi – thus enabling sensitivity analysis. Often, the number n of uncertain parameters is huge, so sensitivity analysis leads to a lot of computation time. To speed up the processing, we propose to use special Monte-Carlo-type simulations.
منابع مشابه
Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Geophysical and Engineering Applications
To determine the geophysical structure of a region, we measure seismic travel times and reconstruct velocities at different depths from this data. There are several algorithms for solving this inverse problem, but these algorithms do not tell us how accurate these reconstructions are. Traditional approach to accuracy estimation assumes that the measurement errors are independently normally dist...
متن کاملMonte-carlo-type Techniques for Processing Interval Uncertainty and Their Engineering Applications
Typically, in engineering applications, we need to make decisions under uncertainty. In addition to measurement errors, some uncertainty comes from the fact that we do not know how exactly the engineering devices that we produced will be used: e.g., we have limits Li on the loads li in different rooms i, but we do not know how exactly these loads will be distributed – and we want to make sure t...
متن کاملAn Efficiency Studying of an Ion Chamber Simulation Using Vriance Reduction Techniques with EGSnrc
Background: Radiotherapy is an important technique of cancer treatment using ionizing radiation. The determination of total dose in reference conditions is an important contribution to uncertainty that could achieve 2%. The source of this uncertainty comes from cavity theory that relates the in-air cavity dose and the dose to water. These correction factors are determined from Monte Carlo calcu...
متن کاملUsing Supervised Learning to Improve Monte Carlo Integral Estimation
Monte Carlo (MC) techniques are often used to estimate integrals of a multivariate function using randomly generated samples of the function. In light of the increasing interest in uncertainty quantification and robust design applications in aerospace engineering, the calculation of expected values of such functions (e.g. performance measures) becomes important. However, MC techniques often su ...
متن کاملUncertainties due to Fuel Heating Value and Burner Efficiency on Performance Functions of Turbofan Engines Using Monte Carlo Simulation
In this paper, the impacts of the uncertainty of fuel heating value as well as the burner efficiency on performance functions of a turbofan engine are studied. The mean value and variance curves for thrust, thrust specific fuel consumption as well as propulsive, thermal and overall efficiencies are drawn and analyzed, considering the aforementioned uncertainties based on various Mach numbers at...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Reliable Computing
دوره 13 شماره
صفحات -
تاریخ انتشار 2007