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SIMULATION-BASED FORECASTING EFFECTS OF AN ACCIDENTAL EXPLOSION ON THE ROAD. PART I: METHODOLOGICAL FRAMEWORK
Author(s) -
Egidijus Rytas Vaidogas
Publication year - 2006
Publication title -
transport
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 31
eISSN - 1648-4142
pISSN - 1648-3480
DOI - 10.3846/16484142.2006.9638061
Subject(s) - probabilistic logic , explosive material , context (archaeology) , computer science , statistical model , bayesian probability , data mining , machine learning , artificial intelligence , paleontology , chemistry , organic chemistry , biology
Forecasting mechanical actions induced by accidental explosions on the road is of crucial importance to assessing potential damage to structures and non‐structural property exposed to them. A logical result of such forecasting may be expressed in the form of probabilistic models. They should quantify likelihood of occurrence and physical characteristics of accidental explosions. Generally the models are to be selected under the conditions of sparse statistical information on intensities and likelihood of explosive actions. The first part of the present paper proposes a simulation‐based procedure intended for selection of the probabilistic models in the absence of direct statistical data on the explosive actions. The proposed procedure is formulated in the context of the classical Bayesian approach to risk assessment. The main idea of the procedure is that statistical samples necessary for fitting the probabilistic models can be acquired from a stochastic simulation of an accident involving an explosion on the road. The proposed simulation‐based procedure can be used for damage assessment and risk studies within the methodological framework provided by the above‐mentioned approach. A case study illustrating an application of the proposed procedure is given in the second part of the paper.

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