Community Sector Council Newfoundland and Labrador

Accurate emissions monitoring of icebreaking vessels is necessary for evaluating compliance with maritime sustainability goals set by the International Maritime Organization (IMO). Traditional Tank-to-Wake (T2W) estimation methods rely on fuel consumption and fixed emission factors but often fail to reflect real-time variations caused by changing engine loads and operational profiles. This study introduces an empirical correction methodology to enhance T2W estimates using correction factors derived from onboard exhaust gas measurements. Data were collected using a portable Testo 350 analyzer aboard the Canadian Coast Guard Ship (CCGS) Sir Wilfrid Laurier, measuring emissions during selected operational instances. Correction functions for carbon dioxide (CO2), nitrogen oxides (NOx), and carbon monoxide (CO) were developed based on engine load and validated using stratified cross-validation. The corrected estimates demonstrated significantly improved alignment with measured values, especially under dynamic operating conditions such as cruising and maneuvering along with hotelling. This approach provides a practical and scalable pathway for improving emissions accuracy on vessels lacking continuous monitoring systems, supporting better alignment with regulatory reporting and decarbonization goals.

Abstract This paper presents an application example of the body force propeller method to consider hydrodynamic interaction between the hull, pod and propeller blades; and predict the overall propulsion performance without implementing the actual rotating propeller model. As a test case, a tugboat with twin puller-pod units is selected, and a series of simulations, from a stand-alone propeller operation to a fully equipped hull under propeller overload conditions, are conducted. To evaluate the simulation performance improvement, two different modelling options in the body force propeller model, inflow sampling and induced velocity correction, are investigated. The estimated thrust, torque and tow force are then compared with the model test results. Finally, it is proposed to adopt the varying inflow sampling technique to enhance the simulation accuracies of the body force propeller method, particularly for propeller overload test cases.

Abstract This paper provides a general review of available models used in the NRC-OCRE (National Research Council – Ocean, Coastal and River Engineering) that could be used to support the assessment of a ship’s performance in ice conditions. The models were separated into three main categories: empirical, numerical and real-time, and reviewed in terms of key strengths and weaknesses. A general overview of the modelling categories and specific models within each category is given. Within each modelling category, specific models were compared to outline the key features of both the independent models and the modelling category itself. A representative model within each category and sub-category was selected and used to present the output for a given scenario. This enabled a demonstration of output capabilities for each modelling category. It also provides the reader with additional information pertaining to the input requirements and validation for the selected models. A discussion of the integration of an ice loading model into an existing ship simulation framework is included. A specific case was reviewed in which a successful integration had occurred and was documented. This allowed for demonstration of a process that could be followed for updating one’s numerical modelling capabilities. Based on this review, guidance was provided in terms of selecting a numerical tool to extend current ship performance modelling capabilities to consider ice operations. Each modelling category and sub-category has a unique set of advantages and disadvantages. These should be considered in detail to ensure that the numerical model(s) selected are optimal in terms of their ability to assess desired scenarios and interface with existing software.

Abstract Mechanical recovery techniques are used to clean up oil spills in marine environments; however, their efficiency is challenged when dealing with heavy oil, ice covered water and high sea states. Current mechanical recovery techniques are based on removing oil from the water surface, however, a significant amount of oil could remain in the water column below the surface due to turbulent ocean conditions, the density of heavy oil and oil escaping underneath the booms when the sweeping speed increases. To enhance the oil recovery effectiveness, oil particles in the water column need to be guided to the surface to be recovered by the skimmers. This paper focusses on the development of a test protocol and physical testing in C-CORE’s lab of a bubbler system for enhancing the harsh environment oil spill recovery. Air bubbles produce an upward flow in the water body, which guides the submerged particles to the surface. The air bubbles also attach to the oil particles, leading to an increase in the buoyancy and rate at which oil droplets rise to the surface. By adopting this technique for oil recovery, additional oil particles can be brought to the surface. In the study, the bubbler system was tested in both stationary and advancing conditions with medium and heavy oils. The results of the stationary and advancing tests indicate that the oil recovery ratios can be significantly enhanced by using an optimized bubbler system. Different types and configurations of bubblers were tested by varying the airflow rates and bubbler advancing speeds to determine the optimal solution. The optimal bubbler system has been observed to enhance the recovery ratio from 41.5% to 84.8% with airflow rates ranging from 0.05 to 0.20 CFM/foot. Furthermore, the effective integration of the bubbler system with a mechanical recovery system, its deployment and retrieval in a near field condition were demonstrated during tests in an outdoor tank.

Ensuring the integrity of subsea process components is one of the primary business objectives of the oil and gas industry. Leak detection system (LDS) is one type of system used to safeguard reliability of a pipeline. Different types of LDS use different technologies for detecting and locating leaks in pipelines. One technology, which is gaining wide acceptance by the industry, is the fiber optic-based LDS. This technology has great potential for subsea pipeline applications. It is the most suited for underwater applications due to the ease of installation and reliable sensing capabilities. Having pipelines underwater in the deep sea presents a great challenge and a potential threat to the environment and operation. Thus, there is a need to have a reliable and effective system to provide the assurances that the monitored subsea pipeline is safe and functioning as per operating conditions. Two important performance parameters that are of concern to operators are the probability of detection and probability of false alarm. This paper presents a probabilistic formulation of the probability of detection and probability of false detection for a fiber optic-based LDS.