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Compared to the construction phase, the assessment of tunnel safety risks during the operational stage has not been thoroughly conducted, and the related research work is relatively lagging. To deepen the research and application of theoretical methods for assessing operational tunnel safety risks, and to improve the level of hazard investigation and prevention in long and large highway tunnels, this paper establishes a tunnel section assessment index system from four perspectives: tunnel condition, traffic characteristics, operational environment, and operational management. A combined qualitative and quantitative approach is employed, and a practical classification standard for the indicators is proposed. Based on the traditional Analytic Hierarchy Process (AHP) and fuzzy analysis theory, a new form of questionnaire survey, known as the expert system analysis method, is introduced to collect expert opinions. A novel approach for determining fuzzy numbers based on expert opinions is proposed. Consequently, a combined model for assessing operational tunnel safety risks in long and large highways is established by integrating the Fuzzy Analytic Hierarchy Process (FAHP) and the Set Pair Analysis (SPA). This model effectively combines subjective weighting with objective evaluation, thereby enhancing the accuracy of operational tunnel safety risk assessment for long and large highways. The safety risks of three long and large tunnels within the G1523 Yongguan Expressway were assessed using the evaluation method proposed in this paper. A comparative analysis was conducted between the results obtained using the proposed Fuzzy Analytic Hierarchy Process (FAHP) and Set Pair Analysis (SPA) method and the traditional Analytic Hierarchy Process (AHP) evaluation. The results indicate that the operational tunnel safety risk assessment method based on FAHP and SPA exhibits greater rationality and accuracy compared to the traditional AHP approach. [ABSTRACT FROM AUTHOR]

This study proposes and applies a systematic data analysis methodology to analyse experimental data for high-performance concrete (HPC) samples with different admixtures for offshore fan foundation grouting materials uses. In contrast with other relevant research, including experimental studies, the materials physics and chemistry studies, or cementitious material portfolio determination studies, this data-driven analysis provides a deep exploration of the experimental variables associated with the test data. To offer complete and in-depth perspectives, several methods are employed for the data analyses, including correlation analysis, cosine similarity analysis, simple linear regression (SLR) modelling, and heat map and heat-based tabularised visualisations; the outcome is a proposed methodology that is easily implementable. The results from these methods are validated using a pairwise comparison approach (PCA) to avoid unnecessary interference between data variables. There are several potential contributions from this work, including insights for cohered groups of variables, techniques for double check and 'third check', an established 'knowledge base' consisting of 504 SLR predictive models with their effectiveness (significance) and prediction accuracy (data-model fitness) used in practical applications, an alternative visualisations of the results, three data transforms which can be omitted in a future analysis, and three valuable theory-linking perspectives (e.g., for the relationships between destructive and non-destructive tests with respect to the variable categories). The implication that some variables are interchangeable will make future experiments less labour intensive and time consuming for pre-project HPC material testing. [ABSTRACT FROM AUTHOR]

Compared to the construction phase, the assessment of tunnel safety risks during the operational stage has not been thoroughly conducted, and the related research work is relatively lagging. To deepen the research and application of theoretical methods for assessing operational tunnel safety risks, and to improve the level of hazard investigation and prevention in long and large highway tunnels, this paper establishes a tunnel section assessment index system from four perspectives: tunnel condition, traffic characteristics, operational environment, and operational management. A combined qualitative and quantitative approach is employed, and a practical classification standard for the indicators is proposed. Based on the traditional Analytic Hierarchy Process (AHP) and fuzzy analysis theory, a new form of questionnaire survey, known as the expert system analysis method, is introduced to collect expert opinions. A novel approach for determining fuzzy numbers based on expert opinions is proposed. Consequently, a combined model for assessing operational tunnel safety risks in long and large highways is established by integrating the Fuzzy Analytic Hierarchy Process (FAHP) and the Set Pair Analysis (SPA). This model effectively combines subjective weighting with objective evaluation, thereby enhancing the accuracy of operational tunnel safety risk assessment for long and large highways. The safety risks of three long and large tunnels within the G1523 Yongguan Expressway were assessed using the evaluation method proposed in this paper. A comparative analysis was conducted between the results obtained using the proposed Fuzzy Analytic Hierarchy Process (FAHP) and Set Pair Analysis (SPA) method and the traditional Analytic Hierarchy Process (AHP) evaluation. The results indicate that the operational tunnel safety risk assessment method based on FAHP and SPA exhibits greater rationality and accuracy compared to the traditional AHP approach.

This study proposes and applies a systematic data analysis methodology to analyse experimental data for high-performance concrete (HPC) samples with different admixtures for offshore fan foundation grouting materials uses. In contrast with other relevant research, including experimental studies, the materials physics and chemistry studies, or cementitious material portfolio determination studies, this data-driven analysis provides a deep exploration of the experimental variables associated with the test data. To offer complete and in-depth perspectives, several methods are employed for the data analyses, including correlation analysis, cosine similarity analysis, simple linear regression (SLR) modelling, and heat map and heat-based tabularised visualisations; the outcome is a proposed methodology that is easily implementable. The results from these methods are validated using a pairwise comparison approach (PCA) to avoid unnecessary interference between data variables. There are several potential contributions from this work, including insights for cohered groups of variables, techniques for double check and ‘third check’, an established ‘knowledge base’ consisting of 504 SLR predictive models with their effectiveness (significance) and prediction accuracy (data-model fitness) used in practical applications, an alternative visualisations of the results, three data transforms which can be omitted in a future analysis, and three valuable theory-linking perspectives (e.g., for the relationships between destructive and non-destructive tests with respect to the variable categories). The implication that some variables are interchangeable will make future experiments less labour intensive and time consuming for pre-project HPC material testing.