RescUSim and IPython : an environment for offshore emergency preparedness planning

Emergency preparedness is crucial for oil and gas operators. While accidents in this industry are commonly connected to oil spill disasters, helicopter accidents are, in terms of incidence rates, a more grave concern in Norway. A recent helicopter accident near Bergen has brought this subject back into focus. We introduce RescUSim, a simulator for rescue missions after offshore helicopter accidents, which is implemented as an open source library with bindings for the Python language. We discuss the modules in the existing Python ecosystem that are used for data preparation and analysis. We show how RescUSim and the interactive computing environment IPython can join forces to provide a tool for planning rescue preparedness for oil and gas related offshore activities.publishedVersio

RescUSim and IPython: An environment for offshore emergency preparedness planning

Emergency preparedness is crucial for oil and gas operators. While accidents in this industry are commonly connected to oil spill disasters, helicopter accidents are, in terms of incidence rates, a more grave concern in Norway. A recent helicopter accident near Bergen has brought this subject back into focus. We introduce RescUSim, a simulator for rescue missions after offshore helicopter accidents, which is implemented as an open source library with bindings for the Python language. We discuss the modules in the existing Python ecosystem that are used for data preparation and analysis. We show how RescUSim and the interactive computing environment IPython can join forces to provide a tool for planning rescue preparedness for oil and gas related offshore activities

Search and rescue (SAR) modeling for the coastal regions of Eastern Canada and the Arctic Gateway

The Search and Rescue (SAR) system plays a critical role in ensuring the safety of maritime activities in Eastern Canada and the Arctic Gateway. This thesis presents a comprehensive method for assessing SAR time in the region, specifically focusing on scenarios where helicopters are utilized as the primary rescue resource. The developed macro-scale SAR model incorporates a Discrete Event simulation approach with stochastic elements to account for uncertainties and variability inherent in SAR operations. By utilizing the SAR model, a wide range of scenarios can be analyzed, allowing users to define various factors such as helicopter deployment time variability, helicopter parameters, and more. The model employs a time-stepping approach, enabling real-time decision-making and operational adjustments at each time step. It considers multiple factors, including incident and helicopter location, weather conditions, and the number of individuals in distress, to assess SAR effectiveness. The model underwent rigorous verification tests, demonstrating close alignment with hand calculation methods. Furthermore, a validation test was conducted using data from a real-life incident involving the Viking Sky, where the model's predictions closely matched the actual incident timeline within a certain percentage of accuracy. The model was further utilized to examine the influence of incident location, the number of survivors, and refueling requirements systematically. Additionally, Arctic-based scenarios were explored to account for specific conditions in the Arctic region. The research findings indicate that incident location, the number of individuals in distress, and weather conditions significantly impact SAR time. Specifically, the total rescue time shows a greater increase with distance from the helicopter base compared to the number of survivors, particularly for smaller survivor groups. When the helicopter base was relocated to an Arctic location, the total rescue time for smaller survivor groups was halved. The importance of optimizing the location of SAR assets and facilities is emphasized throughout the research. The study also examines the effects of operating two or more helicopters simultaneously on SAR time, providing insights into its impact. Overall, this thesis underscores the importance of continuous improvement and collaboration to enhance SAR capabilities and ensure maritime safety in the coastal regions of Eastern Canada and the Arctic Gateway. The findings contribute valuable insights for policymakers, SAR organizations, and stakeholders involved in the maritime domain, aiming to reduce response times, increase operational efficiency, and ultimately save lives at sea

Aeronautical Engineering: A continuing bibliography with indexes, supplement 155, December 1982

This bibliography lists 272 reports, articles and other documents introduced into the NASA scientific and technical information system in November 1982

Technical Workshop: Advanced Helicopter Cockpit Design

Information processing demands on both civilian and military aircrews have increased enormously as rotorcraft have come to be used for adverse weather, day/night, and remote area missions. Applied psychology, engineering, or operational research for future helicopter cockpit design criteria were identified. Three areas were addressed: (1) operational requirements, (2) advanced avionics, and (3) man-system integration

A Study of Optimal Search and Rescue Operations Planning Problems

Search and Rescue (SAR) systems are vital to provide the quick response for saving lives in the first moments of natural and man-made calamities. In this dissertation, we present and discuss factors related to SAR operations planning and develop three SAR mathematical problems. In the first part we present an overview of SAR operations, highlighting questions affecting aerial search and rescue operations since it is the main object of our Thesis. In the second part, we consider an aerial fleet planning as a resource allocation problem and propose variations in the objective function of a binary integer programming (BIP) model according to different priorities related to area, time and type of the searching operation in high seas. We then study the problem for planning rescue missions in oceanic areas, modeled as a vehicle routing problem considering a heterogeneous fleet of vehicles and respective displacements during the operation. A BIP model is proposed and routing choices are assisted by probabilistic demands at each location that, when visited, may update previous decisions. In the fifth part, we consider the problem for planning a long-range mass rescue operation, modeled as an aircraft routing problem with pick-up and delivering, weight and endurance limits. A BIP model is proposed to minimize the flying time and feasible routes depend on factors such as aircraft endurance, fuel consumption rate, payload, take-off and landing weights, local demand and airfield capacities to operate different types of aircraft. The dissertation ends with conclusions and identified issues for future research

Preparing the Arctic: Optimally Locating Aeronautical Search and Rescue Stations along Canada’s Northwest Passage

Although historically ice-covered, the Northwest Passage (NWP)—a maritime corridor located in the Canadian Arctic—has been experiencing melting trends in recent decades. Declining sea ice concentrations would lead to improved navigability along the NWP, suggesting promising opportunities for both domestic and international shippers. With vessel traffic expected to rise, and the lack of emergency response resources currently stationed in the region, Canada would be responsible for equipping its North with a search and rescue (SAR) network that is capable of providing relief to the users of its waterways. Since the Royal Canadian Air Force (RCAF) oversees the majority of SAR activities in Canada, the distribution of its response aircraft throughout the Arctic is crucial in the design of a successful response network. To address these concerns, we formulated the location problem as an integer linear program (ILP) that looked to determine optimal sites for aeronautical SAR stations and the allocation of aircraft so that the weighted primary and secondary coverage of demand points was maximized. To do so, we modelled the response capacities of the RCAF's fleet by designing a set of response functions based on each asset's performance specifications. We analyzed 29 arrangements across two cases: one in which the secondary coverage of demand points was optional (Case A), and another in which it was mandatory (Case B). Using six to seven aircraft, our approach led to three arrangements that would best address SAR concerns in the North: Arrangement 7A which was proposed for Case A, Arrangement 6B for Case B, and Arrangement 7B as a compromise of the two

Vision-Based Monocular SLAM in Micro Aerial Vehicle

Micro Aerial Vehicles (MAVs) are popular for their efficiency, agility, and lightweights. They can navigate in dynamic environments that cannot be accessed by humans or traditional aircraft. These MAVs rely on GPS and it will be difficult for GPS-denied areas where it is obstructed by buildings and other obstacles.  Simultaneous Localization and Mapping (SLAM) in an unknown environment can solve the aforementioned problems faced by flying robots.  A rotation and scale invariant visual-based solution, oriented fast and rotated brief (ORB-SLAM) is one of the best solutions for localization and mapping using monocular vision.  In this paper, an ORB-SLAM3 has been used to carry out the research on localizing micro-aerial vehicle Tello and mapping an unknown environment.  The effectiveness of ORB-SLAM3 was tested in a variety of indoor environments.   An integrated adaptive controller was used for an autonomous flight that used the 3D map, produced by ORB-SLAM3 and our proposed novel technique for robust initialization of the SLAM system during flight.  The results show that ORB-SLAM3 can provide accurate localization and mapping for flying robots, even in challenging scenarios with fast motion, large camera movements, and dynamic environments.  Furthermore, our results show that the proposed system is capable of navigating and mapping challenging indoor situations

Variable rotor speed and active blade twist for civil rotorcraft: optimum scheduling, mission analysis, and environmental impact

The concepts of variable rotor speed and active blade twist constitute promising technologies in terms of improving the operational performance and environmental impact of rotorcraft. Modern civil helicopters typically operate using nearly constant main and tail rotor speeds throughout their operational envelope. However, previous research has shown that decreasing the main rotor speed within salient points of the operational envelope can result in a notable reduction of rotor power requirement, resulting in more efficient aircraft. This work aims to develop an integrated approach able to evaluate the potential improvements in fuel economy and environmental impact through optimum implementation and scheduling of variable rotor speed combined with active blade twist. A comprehensive rotorcraft analysis method is utilized, comprising models applicable to flight dynamics, rotor blade aeroelasticity, engine performance, gaseous emission prediction, and flight path analysis. A holistic optimization strategy comprising methods for Design of Experiment (DOE), Gaussian Process-based (GP) surrogate-modeling, and genetic optimization is developed. The combined framework is used to predict globally optimum variable rotor speed and active blade twist schedules resulting in minimum fuel consumption. The overall method is employed to assess the impact of the investigated concepts for a representative Twin-Engine Light (TEL) helicopter operating within realistic mission scenarios. The optimizations carried out suggest that variable rotor speed combined with active blade twist may result in mission fuel consumption and nitrogen oxides emission (NOx) reductions of the order of 5% and 8%, relative to the fixed rotor speed case. The developed method constitutes an enabling technology for the investigation of novel technologies at multiple levels of assessment including aircraft-engine and mission levels