COMPARISON OF UNSTEADY REYNOLDS-AVERAGED NAVIER-STOKES PREDICTION OF SELF-PROPELLED CONTAINER SHIP SQUAT AGAINST EMPIRICAL METHODS AND BENCHMARK DATA

The demand to increase port throughput has driven container ships to travel relatively fast in shallow water whilst avoiding grounding and hence, there is need for more accurate high-speed squat predictions. A study has been undertaken to determine the most suitable method to predict container ship squat when travelling at relatively high speeds (Frh ≥ 0.5) in finite water depth (1.1 ≤ h/T ≤ 1.3). The accuracy of two novel self-propelled URANS CFD squat model are compared with that of readily available empirical squat prediction formulae. Comparison of the CFD and empirical predictions with benchmark data demonstrates that for very low water depth (h/T < 1.14) and when Frh < 0.46; Barass II (1979), ICORELS (1980), and Millward’s (1992) formulae have the best correlation with benchmark data for all cases investigated. However, at relatively high speeds (Frh ≥ 0.5) which is achievable in deeper waters (h/T ≥ 1.14), most of the empirical formulae severely underestimated squat (7-49%) whereas the quasi-static CFD model presented has the best correlation. The changes in wave patterns and effective wake fraction with respect to h/T are also presented.

Evaluating the efficiency of Mediterranean container ports using data envelopment analysis

Mediterranean container ports are constantly requested to face new market challenges after years of decline of their traffic in favour of a stronger leadership of Northern range ports, also favoured by the consolidation of the Arctic Route and the Belt and Road Initiative. To regain competitiveness, Mediterranean ports must undertake a path of operational, managerial and infrastructural strengthening. This study applies Data Envelopment Analysis (DEA) to 35 Mediterranean container ports in order to identify the potential key success factors on which to intervene to improve their competitiveness potential and response to the new market needs. The application uses the port throughput as output, and three inputs: yard area, number of quay cranes and distance of the port from the Suez–Gibraltar axis. The latter has been inserted in the study to evaluate whether it can affect port efficiency. Both input- and output-oriented approaches are used in order to investigate the port competitiveness through the production function (input-oriented), and the port commercial competitiveness based on the output and feasibility of its production (output-oriented). Results can provide insights for the implementation of future policies and management strategies aimed to strengthen the Mediterranean port context.

Mutual information analysis of the factors influencing port throughput

Purpose Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose a quantitative method to facilitate port throughput analysis by identification of important cargos and key macroeconomic variables. Design/methodology/approach Mutual information is applied to measure the linear and nonlinear correlation among variables. The method gives a unique measure of dependence between two variables by quantifying the amount of information held in one variable through another variable. Findings This study uses the mutual information to the Port of Isafjordur in Iceland to underpin the port throughput analysis. The results show that marine products are the main export cargo, whereas most imports are fuel oil, industrial materials and marine product. The aggregation of these cargos, handled in the port, meaningfully determines the non-containerized port throughput. The relation between non-containerized export and the national gross domestic product (GDP) is relatively high. However, non-containerized import is mostly related to the world GDP. The non-containerized throughput shows a strong relation to the national GDP. Furthermore, the results reveal that the volume of national export trade is the key influencing macroeconomic variable to the containerized throughput. Originality/value Application of the mutual information in port throughput analysis effectively reduces epistemic uncertainty in the identification of important cargos and key influencing macroeconomic variables. Thus, it increases the reliability of the port throughput forecast.