Abstract

Abstract To ensure the accuracy of probabilistic integrity in design, management and research, various codes have been established to assess safety and reliability of pipelines such as ProLOCA, PROST, xLPR, etc. They are refined and improved through benchmark projects (BPs), obtaining well-recognized research outcomes. However, BPs only compare the relative errors of the same calculation conditions and ignore the usability of the codes. Therefore, in further refining overall performance of probabilistic integrity codes (PICs), it is necessary to improve the usability. This paper presents a novel application for evaluating the PICs, which is mainly divided into four main steps. Firstly, a multi-layer evaluation index system (EIS) is established which contains 3 layers and comprises three main aspects: Prediction Performance (PP), Software Usability (SU) and Option Diversity (OD). In the second step, we use the multi-layer best-worst method (MBWM) to determine the weights of different evaluation criteria. In the third step, a set of wv* experimental data is used to quantitatively mine the PP decision matrix, while the SU and OD decision matrixes are determined based on experience and expert knowledge. Finally, we adopt the sum weight method (SWM) to assess the overall performance of codes and provide suggestions for user selection and software optimization.

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