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Global seaport network efficiency can be measured using the Liner Shipping Connectivity Index (LSCI) with Gross Domestic Product. This paper utilizes k-means and hierarchical strategies by leveraging the results obtained from Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) to cluster 133 countries based on their seaport network efficiency scores. Previous studies have explored hkmeans clustering for traffic, maritime transportation management, swarm optimization, vessel trajectory prediction, vessels behaviours, vehicular ad hoc network etc. However, there remains a notable absence of clustering research specifically addressing the efficiency of global seaport networks. This research proposed hkmeans as the best strategy for the seaport network efficiency clustering where our four newly founded clusters; low connectivity (LC), medium connectivity (MC), high connectivity (HC) and very high connectivity (VHC) are new applications in the field. Using the hkmeans algorithm, 24 countries have been clustered under LC, 47 countries under MC, 40 countries under HC and 22 countries under VHC. With and without a fuzzy dataset distribution, this demonstrates that the hkmeans clustering is consistent and practical to form grouping of general data types. The findings of this research can be useful for researchers, authorities, practitioners and investors in guiding their future analysis, decision and policy makings involving data grouping and prediction especially in the maritime economy and transportation industry. [ABSTRACT FROM AUTHOR]

This paper examines the transport of a chemically reacting nanofluid in a porous medium between two rotary disks with Cattaneo-Christov's heat flux. The non--linear ordinary differential system formed under Vonn Karman transformation of a non-linear partial differential system is solved via a shooting method with MATLAB bvp4c. The nanofluid thermodynamics profiles with variation in physical properties of thermal relaxation time, thermal radiation, porosity, and chemical reaction are observed. Axial, radial, and tangential velocities are found to be increasing functions of porous medium. A decrease in the fluid temperature is perceived as thermal radiation and thermal relaxation increase since more heat can be transported to neighboring surroundings. The concentration is enhanced with intensified Cattaneo-Christov's thermal relaxation but it oscillates with reacting chemicals. The rotary disks bound the oscillating nanofluid from downward to upward directions and vice versa. The axial velocity represents the change in force due to porosity and radial stretching of the disks. [ABSTRACT FROM AUTHOR]

Heat flux enhancement due to utilization of graphene, graphene nanoplatelets, and graphene oxides in water/ethylene-glycol based nanofluids over an inclined permeable cylinder is focused in the present study. The governing PDE are reformulated into non-linear ODE by applying similarity expressions. A shooting procedure is opted to reformulate the equations into boundary value problems which are solved by employing a numerical finite difference code in MATLAB. The effects of constructive parameters toward the model on non-dimensional velocity and temperature dissemination, reduced skin friction coefficient and reduced Nusselt number are graphically reported and discussed in details. It is observed that by increasing the thermal stratification and inclination angle, the temperature profile and Nusselt number for the selected nanofluids will be decreased. [ABSTRACT FROM AUTHOR]

A stagnation-point flow of a Powell–Eyring nanofluid along a vertical stretching surface is examined. The buoyancy force effect due to mixed convection is taken into consideration along with the Brownian motion and thermophoresis effect. The flow is investigated under active and passive controls of nanoparticles at the surface. The associating partial differential equations are converted into a set of nonlinear, ordinary differential equations using similarity conversions. Then, the equations are reduced to first-order differential equations before further being solved using the shooting method and b v p 4 c function in MATLAB. All results are presented in graphical and tabular forms. The buoyancy parameter causes the skin friction coefficient to increase in opposing flows but to decrease in assisting flows. In the absence of buoyancy force, there is no difference in the magnitude of the skin friction coefficient between active and passive controls of the nanoparticles. Stagnation has a bigger influence under passive control in enhancing the heat transfer rate as compared to when the fluid is under active control. Assisting flows have better heat and mass transfer rates with a lower magnitude of skin friction coefficient as compared to opposing flows. In this case, the nanofluid parameters, the Brownian motion, and thermophoresis altogether reduce the overall heat transfer rates of the non-Newtonian nanofluid. [ABSTRACT FROM AUTHOR]