✦ LIBER ✦

Monte Carlo Sensitivity Analysis of Unknown Parameters in Hazardous Materials Transportation Risk Assessment

✍ Scribed by Julia J. Pet-Armacost; Jose Sepulveda; Milton Sakude

Book ID: 114420749
Publisher: Springer
Year: 1999
Tongue: English
Weight: 263 KB
Volume: 19
Category: Article
ISSN: 1573-9147
DOI: 10.1023/a:1007090829762

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Efficient Monte Carlo Simulation of para

Efficient Monte Carlo Simulation of parameter sensitivity in probabilistic slope stability analysis

✍ Yu Wang; Zijun Cao; Siu-Kui Au 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 511 KB

Monte Carlo Simulation (MCS) method has been widely used in probabilistic analysis of slope stability, and it provides a robust and simple way to assess failure probability. However, MCS method does not offer insight into the relative contributions of various uncertainties (e.g., inherent spatial va

A Trichloroethylene Risk Assessment Usin

A Trichloroethylene Risk Assessment Using a Monte Carlo Analysis of Parameter Uncertainty in Conjunction with Physiologically-Based Pharmacokinetic Modeling

✍ William J. Cronin IV; Eric J. Oswald; Michael L. Shelley; Jeffrey W. Fisher; Car 📂 Article 📅 1995 🏛 Springer 🌐 English ⚖ 859 KB

A model to assess risk, equity and effic

A model to assess risk, equity and efficiency in facility location and transportation of hazardous materials

✍ John Current; Samuel Ratick 📂 Article 📅 1995 🏛 Elsevier Science 🌐 English ⚖ 952 KB

Correlation of 210Po implanted in glass

Correlation of 210Po implanted in glass with radon gas exposure: sensitivity analysis of critical parameters using a Monte–Carlo approach

✍ C Walsh; J.P McLaughlin 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 266 KB

Recommendations on the Testing and Use o

Recommendations on the Testing and Use of Pseudo-Random Number Generators Used in Monte Carlo Analysis for Risk Assessment

✍ Timothy M. Barry 📂 Article 📅 1996 🏛 Springer 🌐 English ⚖ 983 KB

093022 (M10) Importance of distributiona

093022 (M10) Importance of distributional form in characterising inputs to Monte Carlo risk assessments : Haas C.N., Risk Analysis, Vol. 17, No. 1, 1997, pp. 107–113

📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 80 KB

authors extend the solution to the case of a iognormal distribution with three parameters. Practical numerical results are given.