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This study aims to provide a comprehensive review of electric tugboat deployment in maritime transportation, including an in-depth assessment of its advantages and disadvantages. Along with the identification of advantages and disadvantages of electric tugboat deployment, the present research also aims to provide managerial insights into the economic viability of different tugboat alternatives that can guide future investments in the following years.

A detailed literature review was conducted, aiming to gain broad insights into tugboat operations and focusing on different aspects, including tugboat accidents and safety issues, scheduling and berthing of tugboats, life cycle assessment of diesel tugboats and their alternatives, operations of electric and hybrid tugboats, environmental impacts and others. Moreover, a set of interviews was conducted with the leading experts in the electric tugboat industry, including DAMEN Shipyards and the Port of Auckland. Econometric analyses were performed as well to evaluate the financial viability and economic performance of electric tugboats and their alternatives (i.e. conventional tugboats and hybrid tugboats).

The advantages of electric tugboats encompass decreased emissions, reduced operating expenses, improved energy efficiency, lower noise levels and potential for digital transformation through automation and data analytics. However, high initial costs, infrastructure limitations, training requirements and restricted range need to be addressed. The electric tugboat alternative seems to be the best option for scenarios with low interest rate values as increasing interest values negatively impact the salvage value of electric tugboats. It is expected that for long-term planning, the electric and hybrid tugboat alternatives will become preferential since they have lower annual costs than conventional diesel tugboats.

The outcomes of this research provide managerial insights into the practical deployment of electric tugboats and point to future research needs, including battery improvements, cost reduction, infrastructure development, legislative and regulatory changes and alternative energy sources. The advancement of battery technology has the potential to significantly impact the cost dynamics associated with electric tugboats. It is essential to do further research to monitor the advancements in battery technology and analyze their corresponding financial ramifications. It is essential to closely monitor the industry’s shift toward electric tugboats as their prices become more affordable.

The maritime industry is rapidly transforming and facing pressing challenges related to sustainability and digitization. Electric tugboats represent a promising and innovative solution that could address some of these challenges through zero-emission operations, enhanced energy efficiency and integration of digital technologies. Considering the potential of electric tugboats, the present study provides a comprehensive review of the advantages and disadvantages of electric tugboats in maritime transportation, extensive evaluation of the relevant literature, interviews with industry experts and supporting econometric analyses. The outcomes of this research will benefit governmental agencies, policymakers and other relevant maritime transportation stakeholders.

This study focuses on the CFD numerical simulation and analysis of the vortex stacking problem at the top of the impeller of a high-speed fuel pump, mainly using LCS and entropy production theory to visualize the vortex at the top of the impeller as well as quantitatively analyzing the energy loss caused by the vortex at the top of the impeller. By combining the two methods, the two are well verified with each other that the stacking problem of the vortex at the top of the impeller and the location of the energy loss caused by the vortex are consistent with the vortex location. Such a method can reveal the problem of vortex buildup at the top of the lobe well, and provide a novel guidance idea for improving the performance of high-speed fuel pumps.

Based on CFD numerical simulation and analysis, this study mainly uses LCS and entropy production theory to visualize the top vortex of the impeller. Through the combination of the two methods, the accumulation problem of the top vortex of the impeller and the location of the energy loss caused by the vortex can be well revealed.

(1) The CFD numerical simulation analysis of the high-speed fuel pump is carried out, and the test is conducted to verify the numerical simulation results. The inlet and outlet pressure difference? P is used as the validation index, and the error analysis shows that the error between numerical simulation and test results is within 10%, which meets our requirements. Therefore, we carry out the next analysis with the help of CFD numerical simulation. By analyzing the full working condition simulation, its inlet and outlet differential pressure? P and efficiency? Are evaluated. It is found that its differential pressure decreases with the flow rate and its efficiency reaches its maximum at Qv = 9.87 L/s with a maximum efficiency of 78.32%. (2) We used the LCS in the analysis of vortices at the top of the impeller blades of a high-speed fuel pump. One of the metrics used to describe the LCS in fluid dynamics is the FTLE. The high FTLE region represents the region with the highest and fastest particle trajectory stretching velocity in the fluid flow. We performed a cross-sectional analysis of the FTLE field on the different height surfaces of the impeller on 25% Plane, 50% Plane, and 75% Plane, respectively. And a quarter turn of the rotor rotation was analyzed as a cycle divided into 8 moments. It is found that on 25% Plane, the vortex at the top of the lobe is not obvious, but there are high FTLE values on the shroud surface. On 50% Plane, the lobe top vortex is relatively obvious and the number of vortices is three. The vortex pattern remains stable with the rotating motion of the rotor. At 75% Plane, the lobe top vortex is more visible and its number of vortices increases to about 5 and the vortex morphology is relatively stable. The FTLE ridges visualize the vortex profile. This is a good guide for fluid dynamics analysis. (3) At the same time, we use the entropy production theory to quantitatively analyze the energy loss, and define the entropy production rate Ep. Through the entropy production analysis of the impeller shroud surface and the suction surface of the pressure surface of the blades at eight moments, we find that the areas of high energy loss are mainly concentrated in the leading and trailing edges of the blades as well as in the shroud surface close to the leading edge of the blades, and the value of the entropy production rate is up to 106 W/m3/K. The areas of high energy loss in the leading edge of the blades as well as the trailing edge show a curved arc, and the energy loss is decreasing as it moves away from the shroud surface and closer to the hub surface. The high energy loss areas at the leading and trailing edges of the blades are curved, and the energy loss decreases as they move away from the shroud surface and closer to the hub surface. The energy loss at the pressure surface of the blade is relatively small, about 5 × 105 W/m3/K, which is mainly concentrated near the leading edge of the blade near the shroud surface and the trailing edge of the blade near the hub surface. Such energy loss corresponds to the vortex LCS at the top of the impeller, and the two mirror each other.

This study focuses on the CFD numerical simulation and analysis of the vortex stacking problem at the top of the impeller of a high-speed fuel pump, mainly using LCS and entropy production theory to visualize the vortex at the top of the impeller as well as quantitatively analyzing the energy loss caused by the vortex at the top of the impeller. By combining the two methods, the two are well verified with each other that the stacking problem of the vortex at the top of the impeller and the location of the energy loss caused by the vortex are consistent with the vortex location. Such a method can reveal the problem of vortex buildup at the top of the lobe well, and provide a novel guidance idea for improving the performance of high-speed fuel pumps.

This study aims at improving combustion process to reduce emissions. Emissions such as carbon monoxide, particulate matter and unburnt hydrocarbons are a result of incomplete combustion. These emissions have useful energy but cannot be reclaimed. Hence, to enhance combustion, effect of biofuel blending on diesel combustion was investigated.

Essential oils have been found easier for blending with diesel because of simple molecular structure compared to vegetable oils. Lavender oil is an essential oil which has not yet been studied by blending with diesel. The major constituents of lavender oil are linalyl acetate (cetane number improver) and linalool (nitrogen oxides reduction). A single-cylinder, four-stroke diesel engine was run by blending diesel with lavender oil (Lavandula angustifolia oil [LAO]) in varying proportions, 5%, 10% and 15% by volume.

Higher heat release rate (HRR) was observed using lavender oil blends compared to pure diesel. Compared to diesel, an increase in brake-specific fuel consumption using blends was observed. LAO15 has the lowest CO emissions at all loading conditions, 29.3% less at 100% load compared to diesel. LAO5 and LAO15 have 6.9% less HC emissions at 100% load condition compared to diesel. LAO15 has only 1.3% higher NO_x emissions compared to diesel at 100% load condition. LAO5 has the lowest smoke content at all loading conditions.

Lavender oil was used directly without any processing. Tested on single-cylinder engine.

To the best of the author’s knowledge, currently, there is no published work on lavender oil–diesel combination. Lavender oil can provide a simple renewable solution for diesel additives with potential up to 15% blending.

Ocean transportation is not only the cheapest and the best mode of bulk transport but also the most polluting form of transportation. The International Maritime Organization (IMO) has set strict targets to cut down carbon dioxide (CO₂) emissions, following which several initiatives have been taken by the shipping industry to embrace new technologies that can make the industry greener. Significant investments have been made into research and development (R&D) to develop alternative marine fuels. This chapter explores the feasibility of setting up a Biomass Recycling Facility (BRF) in the Tirupur–Tuticorin region in Tamil Nadu. The region was chosen because Tirupur being a textile valley generates tonnes of textile wastes every year. It can become good feedstock for biofuel generation, and it is also near Tuticorin Port, which is one of the major ports in Tamil Nadu. On an average, every year 1,000 vessels of medium and large size call at this port. There is a high probability that a BRF established in the vicinity can generate and supply bioethanol for the ships calling at Tuticorin Port. It is apparent from the findings of the study that the feedstock generated by textile industry alone may not be sufficient to meet the huge volumes of biofuel requirements of vessels, more over considerable investments into infrastructure and technology are required. But the study points out that still it could become a viable option because of the government support and favourable Foreign Direct Investment (FDI) policies. The growing demand for biofuel and the increasing price in the world market can become an added advantage.

This study aims to propose an optimization framework using deep neural networks (DNN) coupled with nondominated sorting genetic algorithm II and technique for order preference by similarity to an ideal solution method to improve the tribological properties of camshaft bearing pairs of internal combustion engine.

A lubrication model based on the theory of elastohydrodynamic lubrication and flexible multibody dynamics was developed for a V6 diesel engine. Setting DNN model as fitness function, the multi-objective optimization genetic algorithm and decision-making method were used to optimize the bearing pair structure with the goal of minimizing the total friction loss and the difference of the average values of minimum oil film thickness.

The results show that the lubrication state corresponding to the optimized bearing pair structure is elastohydrodynamic lubrication. Compared with the original structure, the optimized structure significantly reduces the total friction loss.

The optimized performance and corresponding structural parameters are obtained, and the optimization results were verified through multibody dynamics simulation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0417/

This paper aims to conduct an experimental and theoretical investigation into fuel pre-delivery effects for a heavy fuel crankcase scavenged spark ignition two-stroke cycle engine for unmanned aerial vehicle application.

One-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline and fuels.

The experimental research has shown performance improvements using fuel preheating via use of auxiliary transfer port fuel injection. Computational simulation has allowed comparisons with auxiliary transfer port injection and direct in-cylinder injection to be made.

While some heavy fuel engines are now available for unmanned aerial vehicles the best solution to meet the military equipment single fuel policy remains an area of evolving research. The findings within this study show possibilities for fuel pre-treatment.

One-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline fuels.

To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This study examines the operational dynamics of a supply chain (SC) in Vietnam as a case study utilizing an ML simulation approach.

A robust fuel consumption estimation model is constructed by leveraging multiple linear regression (MLR) and artificial neural network (ANN). Subsequently, the proposed model is seamlessly integrated into a cutting-edge SC simulation framework.

This paper provides valuable insights and actionable recommendations, empowering SC practitioners to optimize operational efficiencies and fostering an avenue for further scholarly investigations and advancements in this field.

This study introduces a novel approach assessing sustainable SC performance by utilizing both traditional regression and ML models to estimate transportation costs, which are then inputted into the discrete event simulation (DES) model.

The aviation industry plays a vital role in supporting tourism and international businesses by providing the fastest transportation network in the world and also boosting economic growth and creating employment. However, it harms the environment, mainly through air pollution due to aircraft engines emitting heat and gases that contribute to global warming, acid rain, smog, and ozone depletion. Air travel has increased considerably over the years, and therefore aircraft emissions have contributed to the build-up of greenhouse gases (GHG), with the resultant changes in weather patterns leading to global warming and environmental deterioration. Although aviation contributes to economic and environmental development, it is a double-edged sword because it is thought to be the most challenging industry for formulating sustainable policies, based on the direct conflict between environmental impacts and economic development. This chapter explores different types of problems associated with the negative impacts of aviation carbon emissions and the carbon footprint of tourism. The chapter will also reflect on policy, regulations, and governance approaches currently in place to combat these negative impacts as well as challenges involved in policy interventions.

Recent advancements in technology have led to the exploration of solar-based thermal radiation and nanotechnology in the field of fluid dynamics. Solar energy is captured through sunlight absorption, acting as the primary source of heat. Various solar technologies, such as solar water heating and photovoltaic cells, rely on solar energy for heat generation. This study focuses on investigating heat transfer mechanisms by utilizing a hybrid nanofluid within a parabolic trough solar collector (PTSC) to advance research in solar ship technology. The model incorporates multiple effects that are detailed in the formulation.

The mathematical model is transformed using suitable similarity transformations into a system of higher-order nonlinear differential equations. The model was solved by implementing a numerical procedure based on the Wavelets and Chebyshev wavelet method for simulating the outcome.

The velocity profile is reduced by Deborah's number and velocity slip parameter. The Ag-EG nanoparticles mixture demonstrates less smooth fluid flow compared to the significantly smoother fluid flow of the Ag-Fe3O4/EG hybrid nanofluids (HNFs). Additionally, the Ag-Ethylene Glycol nanofluids (NFs) exhibit higher radiative performance compared to the Ag-Fe3O4/Ethylene Glycol hybrid nanofluids (HNFs).

Additionally, the Oldroyd-B hybrid nanofluid demonstrates improved thermal conductivity compared to traditional fluids, making it suitable for use in cooling systems and energy applications in the maritime industry.

The originality of the study lies in the exploration of the thermal transport enhancement in sun-powered energy ships through the incorporation of silver-magnetite hybrid nanoparticles within the heat transfer fluid circulating in parabolic trough solar collectors. This particular aspect has not been thoroughly researched previously. The findings have been validated and provide a highly positive comparison with the research papers.

The fertilizer industry (FI) is well known for its high energy needs, reliance on limited natural resources, and negative environmental impacts (EIs). The consumption of 14.2 billion tons (BT) of materials and the extraction of 1,580 tons of resources per acre are solely attributed to the FI. Because of FI's resource and energy-intensive nature, it becomes crucial for FI to adopt a Circular Economy (CE) to improve efficiency, energy, and resource reuse. However, FI needs to strengthen its progress toward CE adoption. The proposed study comprehends and examines the barriers that inhibit the adoption of CE in FI.

A total of 15 barriers obstructing the CE in FI are identified and categorized into seven different categories. The barriers were identified by performing a comprehensive literature review and expert input. The study employs the DEMATEL approach to analyze the barriers and establish a causal relationship between them.

The study reveals that the most significant challenge to implementing CE in FI is governmental restrictions, which are followed by a lack of awareness and understanding and a need for a steady supply of bulk materials. The results comprehensively comprehend the pivotal factors that jeopardize the CE in FI and furnish a robust foundation for the methodology and tactics to surmount the barriers to CE adoption.

The literature review encompasses the barriers to the transition to CE and offers management and policy perspectives that help the FI's policy and decision-makers surmount these barriers with future research endeavors.