To evaluate the transportation time reliability of the maritime transportation network for China’s crude oil imports under node capacity variations resulting from extreme events, a framework incorporating bi-level programming and a Monte Carlo simulation is proposed in this paper. Under this framework, the imported crude oil volume from each source country is considered to be a decision variable, and may change in correspondence to node capacity variations. The evaluation results illustrate that when strait or canal nodes were subject to capacity variations, the network transportation time reliability was relatively low. Conversely, the transportation time reliability was relatively high when port nodes were under capacity variations. In addition, the Taiwan Strait, the Strait of Hormuz, and the Strait of Malacca were identified as vulnerable nodes according to the transportation time reliability results. These results can assist government decision-makers and tanker company strategic planners to better plan crude oil import and transportation strategies.
Ice-breaking cones are commonly used in the design of marine structures in cold regions. This study investigates the effects of higher-harmonic wave loads and wave runup on a 5-MW offshore wind turbine with and without ice-breaking cones under extreme wave conditions on the Liaodong Peninsula in China. Two ice-breaking cones (upward-downward and inverted types) are considered. The numerical model adopts a two-phase flow by solving unsteady Reynolds-averaged Navier-Stokes (URANS) equations using the volume of fluid (VOF) method. A phase decomposition method through a ‘Stokes-like’ formulation was adopted to obtain the parameters for each harmonics. The presence of the conical part is seen to increase the second-harmonic wave loads by up to 40%, but it has only limited influence on the fourth and fifth harmonics. The upward-downward-type ice-breaking cone increases the third harmonic, while the inverted-type ice-breaking cone decreases the third harmonic. Due to the phase difference between the first-harmonic and higher harmonics, the largest wave runup occurs at 0°, and 135° is the location with the smallest wave runup. This is because at the 135-degree location, the linear component is positive but the other nonlinear components are negative. For the 0-degree location, all harmonics are positive. By contrast, the inverted type has little effect. The high harmonic wave runup of the minimum point is backwards compared with that of the monopile, and most nonlinear wave runups are different upstream of the monopile.
The wave loads and the resulting motions of floating wave energy converters are traditionally computed using linear radiation–diffraction methods. Yet for certain cases such as survival conditions, phase control and wave energy converters operating in the resonance region, more complete mathematical models such as computational fluid dynamics are preferred and over the last 5 years, computational fluid dynamics has become more frequently used in the wave energy field. However, rigorous estimation of numerical errors, convergence rates and uncertainties associated with computational fluid dynamics simulations have largely been overlooked in the wave energy sector. In this article, we apply formal verification and validation techniques to computational fluid dynamics simulations of a passively controlled point absorber.
The phase control causes the motion response to be highly nonlinear even for almost linear incident waves. First, we show that the computational fluid dynamics simulations have acceptable agreement to experimental data. We then present a verification and validation study focusing on the solution verification covering spatial and temporal discretization, iterative and domain modelling errors. It is shown that the dominating source of errors is, as expected, the spatial discretization, but temporal and iterative errors cannot be neglected. Using hexahedral cells with low aspect ratio and 30 cells per wave height, we obtain results with less than 5% uncertainty in motion response (except for surge) and restraining forces for the buoy without phase control. The amplified nonlinear response due to phase control caused a large increase in numerical uncertainty, illustrating the difficulty to obtain reliable solutions for highly nonlinear responses, and that much denser meshes are required for such cases.
The purpose of this paper is to investigate a multiple ship routing and speed optimization problem under time, cost and environmental objectives. A branch and price algorithm as well as a constraint programming model are developed that consider (a) fuel consumption as a function of payload, (b) fuel price as an explicit input, (c) freight rate as an input, and (d) in-transit cargo inventory costs. The alternative objective functions are minimum total trip duration, minimum total cost and minimum emissions. Computational experience with the algorithm is reported on a variety of scenarios.
This paper investigates the simultaneous optimization problem of routing and sailing speed in the context of full-shipload tramp shipping. In this problem, a set of cargoes can be transported from their load to discharge ports by a fleet of heterogeneous ships of different speed ranges and load-dependent fuel consumption. The objective is to determine which orders to serve and to find the optimal route for each ship and the optimal sailing speed on each leg of the route so that the total profit is maximized. The problem originated from a real-life challenge faced by a Danish tramp shipping company in the tanker business. To solve the problem, a three-index mixed integer linear programming formulation as well as a set packing formulation is presented. A novel Branch-and-Price algorithm with efficient data preprocessing and heuristic column generation is proposed. The computational results on the test instances generated from real-life data show that the heuristic provides optimal solutions for small test instances and near-optimal solutions for larger test instances in a short running time. The effects of speed optimization and the sensitivity of the solutions to the fuel price change are analyzed. It is shown that speed optimization can improve the total profit by 16% on average and the fuel price has a significant effect on the average sailing speed and total profit.
This study concerns nitrogen based emissions from a hydrogen enriched ammonia fueled SI engine. These emissions deserve special attention as their formation may differ from conventional HC combustion due to the nitrogen content in the fuel. A range of experiments are conducted with a single cylinder 0.612 l CFR engine with a compression ratio varying from 7 to 15 using a fuel composition of 80 vol% NH3 and 20 vol% H2. Wet exhaust samples are analysed with an FT-IR. Emission measurements reveal that nitric oxide stem from other reaction paths than the dissociation of molecular nitrogen. This causes the NO emissions to peak around 35% rather than 10% excess air, as is typical in HC fueled SI-engines. However the magnitude of NO emissions are comparable to that of measurements conducted with gasoline due to lower flame temperatures. Nitrogen dioxide levels are higher when comparing with gasoline, but has a relatively low share of the total NOx emissions (3–4%). Nitrous oxide is a product of NH2 reacting with NO2 and NH reacting with NO. The magnitude is largely affected by ignition timing due to the temperature development during expansion and the amount of excess air, as increased oxygen availability stimulates the formation of the NH2 radical and the levels of NO2 are higher. Under ideal operating conditions (MBT ignition timing) N2O levels are very low. The dominating contributors to unburned ammonia are chamber crevices as the magnitude of these emissions is greatly affected by the compression ratio. However, levels are lower than required in order to eliminate all NOx emissions with a SCR catalyst.
This paper presents a detailed BC, NOx and SO2 emission inventory for ships in the Arctic in 2012 based on satellite AIS data, ship engine power functions and technology stratified emission factors. Emission projections are presented for the years 2020, 2030 and 2050. Furthermore, the BC, SO2 and O3 concentrations and the deposition of BC are calculated for 2012 and for two arctic shipping scenarios – with or without arctic diversion routes due to a possible polar sea ice extent in the future.
In 2012, the largest shares of Arctic ships emissions are calculated for fishing ships (45% for BC, 38% for NOx, 23% for SO2) followed by passenger ships (20%, 17%, 25%), tankers (9%, 13%, 15%), general cargo (8%, 11%, 12%) and container ships (5%, 7%, 8%). In 2050, without arctic diversion routes, the total emissions of BC, NOx and SO2 are expected to change by +16%, −32% and −63%, respectively, compared to 2012. The results for fishing ships are the least certain, caused by a less precise engine power – sailing speed relation.
The calculated BC, SO2, and O3 surface concentrations and BC deposition contributions from ships are low as a mean for the whole Arctic in 2012, but locally BC additional contributions reach up to 20% around Iceland, and high additional contributions (100–300%) are calculated in some sea areas for SO2. In 2050, the arctic diversion routes highly influence the calculated surface concentrations and the deposition of BC in the Arctic. During summertime navigation contributions become very visible for BC (>80%) and SO2 (>1000%) along the arctic diversion routes, while the O3 (>10%) and BC deposition (>5%) additional contributions, respectively, get highest over the ocean east of Greenland and in the High Arctic.
The geospatial ship type specific emission results presented in this paper have increased the accuracy of the emission inventories for ships in the Arctic. The methodology can be used to estimate shipping emissions in other regions of the world, and hence may serve as an input for other researchers and policy makers working in this field.
An increasing number of disruptions in ports, plants and warehouses have generated ripple effects over supply networks impacting economic activity. We demonstrate how the spread of the pandemic geographically expands the ripple effect by reducing the workers' participation in production, so undermining the ability of firms and, as a result, the entire cross-border sup- ply chain network to satisfy customers' demands. Our model of the spatio-temporal dynamics of the propagation of Covid-19 infection for supply networks contributes toward ripple effect visualisation and quantification by combining the flow of goods and materials through a typical global supply chain with an epidemiological model. The model enables prospective analyses to be performed in what-if scenarios to simulate the impact on the workforce in each node. The outcome should be helpful tools for managers and scholars. Results from this research will help mitigate the impact and spread of a pandemic in a particular region and the ability of a supply network to overcome the ripple effect. A stylised case study of a cross-border supply chain illustrates the ripple effect by showing how waves with crests at varying dates impact the ability to serve demand showing how a supply chain manager can obtain a forward-looking picture.
Improving the power density of solid oxide fuel cell stacks would significantly enhance this technology for transportation. Using a monolithic structure to downsize the stack dimension offers a key to elevate the power density of solid oxide fuel cell stacks. This innovative design is promising but manufacturing is a challenge. The monolith is co-sintered in one firing step, and the gas channels are formed by burning off sacrificial organic materials. Structure distortion or fracture was observed in post-mortem investigations. In this work a multiscale, multiphysics modelling approach is proposed to describe and resolve this challenge in the debinding process occurring in a monolithic stack, i.e. the burning of organics and transportation of gases through the gradually opening microstructure, as well as the pressure build-up in the microstructure due to gas development. Simulation results show that a prominent pressure peak is experienced in the stack when a plasticiser (polyethylene glycol) and a pore-former (polymethyl methacrylate) are decomposed simultaneously. To reduce the high pressures, we investigate two possible strategies: (i) changing the mixture of organic additives; (ii) modifying the debinding temperature profile. Three tapes with different pore-formers are prepared, and the generated pressures during debinding of the three stacks are compared. The corresponding stack shapes after debinding are recorded. Numerical investigations show a good agreement with the post-mortem observations. By changing the composition of organics the distortion or fracturing of the stack can be avoided. Furthermore, to facilitate stack manufacturing, the high pressures can also be reduced by adjusting the heating rates and dwell temperatures of debinding. By using the new temperature profile suggested by the simulation study, the duration of debinding can also be reduced.
A two-dimensional (2D) Reynolds-averaged Navier–Stokes (RANS) equations solver with k–ω turbulence closure is developed, employing immersed boundary (IB) technique on Cartesian grids. Generalized wall functions are introduced to enhance computational efficiency for problems with high Reynolds numbers. To address existing challenges in applying wall functions within IB methods, a novel, effective and easy-to-implement strategy is proposed. Another distinguishing feature of this turbulent-flow solver is that it employs the highly accurate immersed-boundary generalized harmonic polynomial cell (IB-GHPC) method to solve the Poisson equation for fluid pressure. The new solver is firstly validated by simulating channel flows on both hydraulically smooth and rough walls, achieving excellent agreement with benchmark experimental and numerical studies for various flow parameters including velocity, turbulent kinetic energy and shear stress. For channel flow simulations, our implementation of generalized wall functions using the proposed strategy results in a remarkable reduction of grid nodes by over 80%. Moreover, the solver is applied to simulate flow around both smooth and rough cylinders, producing promising results for drag, lift, and pressure coefficients. Our analysis demonstrates a robust performance of the developed solver in modeling turbulent flows based on Cartesian grids, offering a substantial improvement in computational efficiency for tackling problems involving large Reynolds numbers.