Cost‐Benefit Analysis of Passive Fire Protections in Road LPG Transportation

The cost‐benefit evaluation of passive fire protection adoption in the road transport of liquefied petroleum gas (LPG) was investigated. In a previous study, mathematical simulations of real scale fire scenarios proved the effectiveness of passive fire protections in preventing the “fired” boiling liquid expanding vapor explosion (BLEVE), thus providing a significant risk reduction. In the present study the economical aspects of the adoption of fire protections are analyzed and an approach to cost‐benefit analysis (CBA) is proposed. The CBA model is based on the comparison of the risk reduction due to fire protections (expressed in monetary terms by the value of a statistical life) and the cost of the application of fire protections to a fleet of tankers. Different types of fire protections were considered, as well as the possibility to apply protections to the entire fleet or only to a part of it. The application of the proposed model to a real‐life case study is presented and discussed. Results demonstrate that the adoption of passive fire protections on road tankers, though not compulsory in Europe, can be economically feasible, thus representing a concrete measure to achieve control of the “major hazard accidents” cited by the European legislation.     

A New Approach to Rank Several Multivariate Normal Populations with Application to Life Cycle Assessment

The need to establish the relative superiority of each treatment when compared to all the others, i.e., ordering the underlying populations according to some pre-specified criteria, often occurs in many applied research studies and technical/business problems. When populations are multivariate in nature, the problem may become quite difficult to deal with especially in case of small sample sizes or unreplicated designs. The purpose of this work is to propose a new approach for the problem of ranking several multivariate normal populations. It will be theoretically argued and numerically proved that our method controls the risk of false ranking classification under the hypothesis of population homogeneity while under the nonhomogeneity alternatives we expect that the true rank can be estimated with satisfactory accuracy, especially for the “best” populations. Our simulation study proved also that the method is robust in the case of moderate deviations from multivariate normality. Finally, an application to a real case study in the field of life cycle assessment is proposed to highlight the practical relevance of the proposed methodology.