Non-indigenous species (NIS) pose a major threat to biodiversity and the functioning and services of ecosystems. Despite their rapid spread in coastal waters worldwide, biotic invasions are widely disregarded in marine conservation planning. To guide conservation actions, a better understanding of the underlying mechanisms determining the success of NIS are therefore needed. Here we develop a combined modelling approach to identify the key drivers and community assembly processes determining the occurrence of invasive benthic invertebrates, using Danish coastal waters as a case study. To reflect factors affecting the introduction, establishment and spread of NIS throughout the area, we compiled long-term monitoring data on NIS, as well as information on commercial shipping, environmental conditions and estimates of larvae settling densities derived from drift model simulations informed by species traits. We then applied a set of species distribution models to identify the key drivers determining the occurrence of NIS. Our results demonstrate a significant positive effect of vessel activity, a negative effect of depth and bottom salinity, as well as a positive effect of the simulated settling densities on the probability of presence. Taken together, our results highlight the role of commercial shipping, habitat characteristics and passive advection of early-life stages on the presence of NIS. Our combined modelling approach provide improved process understanding on the key community assembly processes determining the presence of NIS and may serve to guide monitoring, management and conservation planning in order to limit future invasions and their negative consequences on coastal ecosystems.
Having the right spare part at the right time to the right place for ship maintenance to the minimal possible costs is an exigent management problem that maritime shipping companies face. This is especially challenging in bulk shipping where routes are not fixed, but subsequent port calls depend on spot market dynamics. Thus, spare parts allocation ahead in time is limited, but possible if failures rates of ship components and their timing can be foreseen, so that spare parts can be allocated to hedge against the risk of long waiting times and thus ship downtimes. Thus, monitoring the condition of components key to the ships performance is essential to the task. This can enable companies to significantly reduce operational costs of their fleet leading to a competitive advantage in a highly volatile market regarding demand and demand-driven freight rates.
However, shipping companies seem far away from applying such methods due to various challenges ranging from data gathering and cultivating an understanding of data quality needs, adaptation to move from preventive towards predictive and condition-based monitoring, and the introduction and application of decision support tools for sourcing, spare parts allocation, and inventory management.
In this paper, we investigate the current state of the art of maintenance and related spare parts logistics management for maritime shipping and discuss the application of methods to the bulk carriage market. We add practical knowledge from case companies and discuss how challenges can be overcome in providing guidelines for companies.
The maritime sector contributes significantly to climate change, given thenumber of global emissions that this represents. Emissions inventorying isone of the measurement system approaches considered in terminals to mitigate harmful emissions. The concept of sustainability has gained attentionwhere economic, social, and environmental dimensions need to be balanced.Assessing all three sustainability dimensions is important. Both the environment and the society, e.g., human health and safety, are impacted by terminal operations. Reducing their negative impact can compromise the economicgrowth of the terminal. This is challenging the maritime sector, and althoughsome authors define methods to evaluate sustainability in terminals, nostandard guideline is available in the literature. The lack of a common reference guideline makes comparison of sustainability actions in terminals difficult.This paper presents a sustainability assessment framework based on theanalysis of the state of the art in literature contributing to sustainable development of terminals and supporting decision-makers.
This paper presents a new approach to attain estimates of the sea state based on short-time sequences of wave-induced ship responses. The present sea state estimation method aims at reconstructing the incident wave profiles in time domain. In order to identify phase components of the incident waves, the Prolate Spheroidal Wave Functions (PSWF) are employed. The use of PSWF offers an explicit expression of phase components in the measured responses and incident waves, indicating that estimations can be efficiently attained. A method to estimate the relative wave heading angle based on the response measurements and pre-computed transfer functions of the responses is also proposed. The method is tested with numerical simulations and experimental measurements of ship motions, i.e. heave, pitch, and roll, together with vertical bending moment and local pressure in a post-panamax size containership. Validation is made by comparing the reconstructed wave profiles with the incident waves. The accuracy and efficiency of the present approach are promising. At the same time, it is shown that the use of responses, which are more broad-banded in their frequency characteristics, is an effective means to cope with high frequency noise in reconstructed waves.
The Belt and Road Initiative (BRI) entails investments to improve overland (rail) transport between Europe and China. This paper introduces a microscopic Multi-Commodity Flow Service Selection Problem for freight transport under the BRI and provides a decision tool for shippers to make door-to-door service plans. The minimizing objective function considers transportation costs, in-transit inventory costs, and carbon emissions. A series of sampled data of each provincial region of China are collected from Chinese multimodal transport operators. Results show that inland regions are strongly attracted to the rail mode for shipments to Europe. However, the “last mile” (including “first mile”) transport from the shipper to the long-haul transport terminal strongly influences this choice, and carbon emissions are strongly influenced by the available last mile transport links. Under the dual impact of in-transit inventory and carbon emission costs, regions that prefer rail to maritime are much further east than suggested by previous literature.
This paper studies the design of a mid-scale maritime supply chain for distribution of liquefied natural gas (LNG) from overseas sourcing locations, via a storage located at the coast, before transporting the LNG on land to industrial customers. The case company has signed contracts with a number of initial customers and expect that there will be more customers and increased demand in the years to come. However, it is currently uncertain whether and when new contracts will be signed. To capture this uncertainty with regard to which and how many future customers there will be, which directly affects the demand, we propose a multi-stage stochastic programming model, which maximizes the expected profits of the supply chain. The model aims at aiding decisions concerning the import of LNG, investments in floating storage units and customer distribution systems, and it has been applied on a real case study for distributing LNG to customers in a Brazilian state. It is shown that explicitly considering uncertainty in the modeling of this problem is very important, with a Value of Stochastic Solution of 13.2%, and that there are significant economies of scale in this supply chain. Most importantly, the multi-stage stochastic programming model and the analysis presented in this paper provided valuable decision support and managerial insights for the case company in its process of setting up the LNG supply chain.
The Ghana National Single Window has become the focus of attention over its potential to move goods swiftly. However, since its inception in 2002, the controversies surrounding the implementation suggest issues beyond trade facilitation. The Information Systems literature primarily ascribes the controversies to resistance to technology. By adopting the Soft Systems Methodology (SSM) as a learning process for understanding port stakeholders' relations and attitudes, we explore the controversies to determine the meanings port stakeholders attribute to them. We combined SSM with interviews, media content analysis and focus groups made possible by snowballing. The responses were analyzed using rich pictures and validated through a conceptual model. The results reveal a fragmented government where ministries, agencies, and personalities assert power in single window implementation through I.T. vendor contracts. The situation results in a high cost of doing business at the port for shippers due to non-transparent and questionable contracts. The public's attitude towards the controversies reflects fears, hopes and expectations and legitimate concerns about important political and social goals. Using SSMs focus on relations and attitudes, we can document how controversies attributed to new technology is not a question of technology but of perceived political interference.
This work is part of the ongoing implementation of generalized modes for ship hydroe- lasticity inside the OceanWave3D-seakeeping solver. The solver has been developed by the Mar- itime Group at DTU- Civil & Mechanical Engineering based on solving the linearized potential flow problem using a high-order finite difference method on overlapping grids. The focus of this paper is a comparison between the hydroelastic solutions obtained using two different implementations of the hydrostatic restoring force coefficients. The first hydrostatic model is according to Newman, and the second model is based on Malenica and Bigot. These two hydrostatic models agree for the rigid modes, but are slightly different for the flexible modes. The results are validated using both numerical and experimental solutions for two different ship geometries at zero forward speed.
This paper presents a study focused on wave spectrum estimation in practical scenarios where multiple ships operate in the same geographical area, potentially forming a network of wave recorders. A novel methodology is proposed to improve the accuracy and precision of the wave spectrum estimates, by combining sea state estimation methods and techniques for tuning the wave-to-motion transfer functions. The framework of the wave buoy analogy is used to derive estimates for each ship through the use of measured ship motion data and available initial estimates of transfer functions. Simultaneously, the wave-to-motion transfer functions of the individual ship are tuned by utilizing a weighted version of the wave data inferred on board the other ships in the network. The overall architecture of the procedure is modular, in the sense that various approaches may be implemented for obtaining sea state estimates and tuned transfer functions. The methodology is demonstrated through two case studies, one based on simulated vessel responses, and the other using model test data of ship motions in a wave tank. Both case studies consider a network of three ships in long-crested waves equipped with a dynamic positioning system. It is shown that the procedure provides good wave spectrum estimates, and leads to reduced uncertainty in the estimates via tuning of the vessel transfer functions.