An Evaluation Method for Tornado Missile Strike Probability with Stochastic Correlation

An efficient evaluation method for the probability of a tornado missile strike without using the Monte Carlo method is proposed in this paper. A major part of the proposed probability evaluation is based on numerical results computed using an in-house code, Tornado-borne missile analysis code, which...

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Bibliographic Details
Main Authors: Yuzuru Eguchi, Takahiro Murakami, Hiromaru Hirakuchi, Soichiro Sugimoto, Yasuo Hattori
Format: Article
Language:English
Published: Elsevier 2017-03-01
Series:Nuclear Engineering and Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1738573316303229
Description
Summary:An efficient evaluation method for the probability of a tornado missile strike without using the Monte Carlo method is proposed in this paper. A major part of the proposed probability evaluation is based on numerical results computed using an in-house code, Tornado-borne missile analysis code, which enables us to evaluate the liftoff and flight behaviors of unconstrained objects on the ground driven by a tornado. Using the Tornado-borne missile analysis code, we can obtain a stochastic correlation between local wind speed and flight distance of each object, and this stochastic correlation is used to evaluate the conditional strike probability, QV(r), of a missile located at position r, where the local wind speed is V. In contrast, the annual exceedance probability of local wind speed, which can be computed using a tornado hazard analysis code, is used to derive the probability density function, p(V). Then, we finally obtain the annual probability of tornado missile strike on a structure with the convolutional integration of product of QV(r) and p(V) over V. The evaluation method is applied to a simple problem to qualitatively confirm the validity, and to quantitatively verify the results for two extreme cases in which an object is located just in the vicinity of or far away from the structure.
ISSN:1738-5733