Добірка наукової літератури з теми "Multi-Level Collision Risk"

The absence of a regional, open water vessel collision risk assessment system endangers maritime traffic and hampers safety management. Most recent studies have analysed the risk of collision for a pair of vessels and propose micro-level risk models. This study proposes a new method that combines density complexity and a multi-vessel collision risk operator for assessing regional vessel collision risk. This regional model considers spatial and temporal features of vessel trajectory in an open water area and assesses multi-vessel near-miss collision risk through danger probabilities and possible consequences of collision risks via four types of possible relative striking positions. Finally, the clustering method of multi-vessel encountering risk, based on the proposed model, is used to identify high-risk collision areas, which allow reliable and accurate analysis to aid implementation of safety measures.

Rear-end collision crash is one of the most common accidents on the road. Accurate driving style recognition considering rear-end collision risk is crucial to design useful driver assistance systems and vehicle control systems. The purpose of this study is to develop a driving style recognition method based on vehicle trajectory data extracted from the surveillance video. First, three rear-end collision surrogates, Inversed Time to Collision (ITTC), Time-Headway (THW), and Modified Margin to Collision (MMTC), are selected to evaluate the collision risk level of vehicle trajectory for each driver. The driving style of each driver in training data is labelled based on their collision risk level using K-mean algorithm. Then, the driving style recognition model’s inputs are extracted from vehicle trajectory features, including acceleration, relative speed, and relative distance, using Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), and statistical method to facilitate the driving style recognition. Finally, Supporting Vector Machine (SVM) is applied to recognize driving style based on the labelled data. The performance of Random Forest (RF), K-Nearest Neighbor (KNN), and Multi-Layer Perceptron (MLP) is also compared with SVM. The results show that SVM overperforms others with 91.7% accuracy with DWT feature extraction method.

The timing of a ship taking evasive maneuvers is crucial for the success of collision avoidance, which is affected by the perceived risk by the navigator. Therefore, we propose a collision alert system (CAS) based on the perceived risk by the navigator to trigger a ship’s evasive maneuvers in a timely manner to avoid close-quarters situations. The available maneuvering margins (AMM) with ship stability guarantees are selected as a proxy to reflect the perceived risk of a navigator; hence, the proposed CAS is referred to as an AMM-based CAS. Considering the dynamic nature of ship operations, the non-linear velocity obstacle method is utilized to identify the presence of collision risk to further activate this AMM-based CAS. The AMM of a ship are measured based on ship maneuverability and stability models, and the degree to which they violate the risk-perception-based ship domain determines the level of collision alert. Several typical encounter scenarios are selected from AIS data to demonstrate the feasibility of this AMM-based CAS. The promising results suggest that this proposed AMM-based CAS is applicable in both ship pair encounter and multi-vessel encounter scenarios. Collision risk can be accurately detected, and then a collision alert consistent with the risk severity is issued. This proposed AMM-based CAS has the potential to assist autonomous ships in understanding the risk level of the encounter situation and determining the timing for evasive maneuvers. The advantages and limitation of this proposed method are discussed.

Self-collision detection is fundamental to the safe operation of multi-manipulator systems, especially when cooperating in highly dynamic working environments. Existing methods still face the problem that detection efficiency and accuracy cannot be achieved at the same time. In this paper, we introduce artificial intelligence technology into the control system. Based on the Gilbert-Johnson-Keerthi (GJK) algorithm, we generated a dataset and trained a deep neural network (DLNet) to improve the detection efficiency. By combining DLNet and the GJK algorithm, we propose a two-level self-collision detection algorithm (DLGJK algorithm) to solve real-time self-collision detection problems in a dual-manipulator system with fast-continuous and high-precision properties. First, the proposed algorithm uses DLNet to determine whether the current working state of the system has a risk of self-collision; since most of the working states in a system workspace do not have a self-collision risk, DLNet can effectively reduce the number of unnecessary detections and improve the detection efficiency. Then, for the working states with a risk of self-collision, we modeled precise colliders and applied the GJK algorithm for fine self-collision detection, which achieved detection accuracy. The experimental results showed that compared to that with the global use of the GJK algorithm for self-collision detection, the DLGJK algorithm can reduce the time expectation of a single detection in a system workspace by 97.7%. In the path planning of the manipulators, it could effectively reduce the number of unnecessary detections, improve the detection efficiency, and reduce system overhead. The proposed algorithm also has good scalability for a multi-manipulator system that can be split into dual-manipulator systems.

This paper focuses on the potential safety hazards of collision in car-following behaviour generated by deep learning models. Based on an intelligent LSTM model, combined with a Gipps model of safe collision avoidance, a new, Gipps-LSTM model is constructed, which can not only learn the intelligent behaviour of people but also ensure the safety of vehicles. The idea of the Gipps-LSTM model combination is as follows: the concept of a potential collision point (PCP) is introduced, and the LSTM model or Gipps model is controlled and started through a risk judgment algorithm. Dataset 1 and dataset 2 are used to train and simulate the LSTM model and Gipps-LSTM model. The simulation results show that the Gipps-LSTM can solve the problem of partial trajectory collision in the LSTM model simulation. Moreover, the risk level of all trajectories is lower than that of the LSTM model. The safety and stability of the model are verified by multi-vehicle loop simulation and multi-vehicle linear simulation. Compared with the LSTM model, the safety of the Gipps-LSTM model is improved by 42.02%, and the convergence time is reduced by 25 seconds.

Moose herd–train collisions represent one of the potential hazards that railway operations must contend with, making the assessment of passive train safety in such scenarios a crucial concern. This study analyzes the responses of bullet trains colliding with moose herds and investigates the influence of various factors under these conditions. To achieve this goal, a multibody (MB) model was developed using the MADYMO platform. The displacement of the moose’s center of gravity (CG) was employed to assess the safety boundaries, while the relative positions between the wheels and rails were used to evaluate the risk of derailment. The findings revealed that the collision forces exhibited multi-peak characteristics that were subsequently transmitted to the wheel–rail contact system, resulting in disturbances in the relative positions of the wheels and rails. However, these disturbances did not reach a level that would induce train derailment. Furthermore, larger moose herds exhibited higher throw heights, although these heights remained within safe limits and did not pose a threat to overhead lines. The primary safety risk in moose–train collisions stemmed from secondary collisions involving moose that had fallen onto the tracks and oncoming trains. This study offers valuable insights for enhancing the operational safety of high-speed trains and safeguarding wildlife along railway corridors.

The continuous growth in maritime traffic and recent developments towards autonomous navigation have directed increasing attention to navigational safety in which new tools are required to identify real-time risk and complex navigation situations. These tools are of paramount importance to avoid potentially disastrous consequences of accidents and promote safe navigation at sea. In this study, an adaptive ship-safety-domain is proposed with spatial risk functions to identify both collision and grounding risk based on motion and maneuverability conditions for all vessels. The algorithm is designed and validated through extensive amounts of Automatic Identification System (AIS) data for decision support over a large area, while the integration of the algorithm with other navigational systems will increase effectiveness and ensure reliability. Since a successful evacuation of a potential vessel-to-vessel collision, or a vessel grounding situation, is highly dependent on the nearby maneuvering limitations and other possible accident situations, multi-vessel collision and grounding risk is considered in this work to identify real-time risk. The presented algorithm utilizes and exploits dynamic AIS information, vessel registry and high-resolution maps and it is robust to inaccuracies of position, course and speed over ground records. The computation-efficient algorithm allows for real-time situation risk identification at a large-scale monitored map up to country level and up to several years of operation with a very high accuracy.

The collision simulation between a city tram and a car at a level crossing is carried out based on the multi-body dynamics. Compared with the finite element method, this method has an obvious advantage of fast computation speed, so that it is convenient for the study on the dynamic responses and derailment mechanism of railway vehicles during a collision accident. The simulation results show that when a city tram is laterally impacted by a car at a level crossing, the dynamic response and the derailment risk of the collided city tram are greatly influenced by the boundary conditions, such as the mass and speed of the colliding car, the structural arrangement and the loading condition of the city tram. Moreover, in terms of the space limitation of the city tram, two measures are proposed to decrease the lateral impact force during its transition from car body to wheel set. One is to use the secondary damper and the other is to increase the secondary lateral clearance. The simulation results point out that the derailment coefficient of the improved city tram can be reduced by 52%, from 1.63 to 0.79.

High level efficiency and safety are of paramount importance for the improvement of fighting capability of an aircraft carrier. The task allocation problem for a team of aircraft launching on the carrier is studied in this paper. Although the study of this problem is of great significance, no relevant literature has been found on this issue. Firstly, the conceptual model of problem is formulated with the planning objectives and the constraints defined. Then the multi-aircraft and multi-catapult launching task allocation problem is decomposed into two consecutive sub-tasks, that is, catapult allocation and the launching sequence determination. The taxi time of aircraft is considered during the catapult allocation process, and the launching position of each aircraft is determined using a decision-making method. In the launching sequence determination step, the starting collision risk of aircraft is introduced to optimize the launching sequence which results in the minimum collision risk on each catapult. Thirdly, the proposed method is validated using the setups of the Nimitz-class aircraft carrier. The proposed method is used to solve the task allocation problem and is compared to the artificial heuristics approach and the brute force approach. Experiment results demonstrate that the proposed method has better performance than the artificial heuristics approach and has better performance than the brute force approach in balancing efficiency and safety.

Exploration of marine habitats is one of the key pillars of underwater science, which often involves collecting images at close range. As acquiring imagery close to the seabed involves multiple hazards, the safety of underwater vehicles, such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), is often compromised. Common applications for obstacle avoidance in underwater environments are often conducted with acoustic sensors, which cannot be used reliably at very short distances, thus requiring a high level of attention from the operator to avoid damaging the robot. Therefore, developing capabilities such as advanced assisted mapping, spatial awareness and safety, and user immersion in confined environments is an important research area for human-operated underwater robotics. In this paper, we present a novel approach that provides an ROV with capabilities for navigation in complex environments. By leveraging the ability of omnidirectional multi-camera systems to provide a comprehensive view of the environment, we create a 360° real-time point cloud of nearby objects or structures within a visual SLAM framework. We also develop a strategy to assess the risk of obstacles in the vicinity. We show that the system can use the risk information to generate warnings that the robot can use to perform evasive maneuvers when approaching dangerous obstacles in real-world scenarios. This system is a first step towards a comprehensive pilot assistance system that will enable inexperienced pilots to operate vehicles in complex and cluttered environments.

Les technologies des véhicules automatisés se développent rapidement et sont deplus en plus présentes dans notre vie quotidienne pour créer des systèmes de trans-port entièrement connectés. Les constructeurs automobiles équipent à présent lesderniers modèles de véhicules de certaines fonctions d'aide à la conduite. Les avan-tages potentiels de ces véhicules incluent la réduction des collisions, l'atténuationdes embouteillages, la réduction de la consommation de carburant, et une flexibil-ité accrue pour les personnes qui n'ont pas accès aux transports. Pour permettrel'automatisation de ces fonctions, il est nécessaire de disposer de données relativesà la détection d'obstacles, la configuration de la route et l'environnement.L'objectif de cette étude est d'examiner l'adaptabilité et l'aptitude du modèle decommunication de la feuille de branche de chaîne (Chain Branch Leaf-CBL) dansles systèmes coopératifs et d'examiner son impact sur les réponses de la circula-tion. De plus, la recherche vise à déterminer le rôle des unités en bord de route etl'efficacité de la perception à plusieurs niveaux dans la prévention des risques. Lebut ultime de cette recherche est d'améliorer la communication et la collaborationentre les véhicules conventionnels et autonomes, ce qui se traduira par une circu-lation plus sûre et plus efficace.Dans cette thèse, nous avons étudié l'utilisation d'une architecture et des stratégiesde communication adaptées pour améliorer la qualité de service en utilisant les in-formations des véhicules entourant l'égo véhicule. Nous avons proposé le conceptde Chain Branch Leaf-Gateway Clustering pour réaliser une topologie optimaled'unité de bord de route-UBR assurant une haute qualité et continuité de service.Nous avons également étudié la perception multi-niveau pour estimer les risquesde collision multi-niveau (local, local étendu, branche étendu et global).Par la suite, nous utilisons les métriques (Time to collision (TTC), Time TimeHeadway (TH), Distance of Gruyer (DG), Risk estimator with uncertainties andmultidimensional model (RIMUM)). Pour estimer les quatre risques de collision(étendus) dans des conditions optimales avec une localisation et une perceptionparfaites, et la situation d'incertitude de la perception avec une localisation par-faite. Les résultats montrent que les risques étendus permettent une meilleureanticipation de la collision que le risque local.De plus, nous avons développé une nouvelle version étendue du modèle Chainbranch leaf-Gateway (CBL-G), qui s'avère plus efficace en termes de couverture.L'architecture hiérarchique du modèle nous permet de calculer les risques de col-lision avec une plus grande précision. La classification en différents niveaux derisque nous permet de identifier les situations potentiellement dangereuses. Dans nos projets de recherche futurs, nous planifions d'étudier d'autres situationstelles que les intersections routières, les sorties et les entrées d'autoroutes ainsique les ronds-points. De plus, nous aimerions explorer les cas dans lesquels il est impossible de localiser les nœuds à travers la chaîne en passant à travers des tun-nels et élaborer des indicateurs de risque qui explorent tous les composants clés(véhicule ego, conducteur, obstacle, route et environnement)
The use of automated vehicle (AV) technologies such as self-driving cars is becoming more prevalent in daily life. These technologies aim to create fully- connectedtransportation systems, still there are concerns that remain unaddressed. Studieshave shown that AVs can reduce collisions, ease traffic congestion, and providetransportation options for those who lack access. Yet, car manufacturers havealready implemented certain automated features in their vehicles. One importantaspect of AVs is improving communication between the vehicle and roadside.The objective of this study is to investigate the adaptability and suitability of theChain branch leaf (CBL) communication model in cooperative systems to exam-ine its impact on traffic responses. Additionally, the research aims to determinethe role of Roadside Units and the effectiveness of multi-level perception in riskmitigation. The ultimate goal of this research is to improve communication andcollaboration between autonomous vehicles leading to safer and more efficient traf-fic flow.This thesis focuses on the estimation of obstacle attributes, the road, and theego-vehicle to improve the quality of service on the road through communication,localization, and perception functions. We propose architectures and communica-tion strategies that will take into account the information of surrounding vehiclesto optimize coverage and estimate collision risk at different levels including local,extended local, extended branch, and global.Subsequently, we use the most relevant metrics (Time to Collision (TTC), TimeHeadway (TH), Distance of Gruyer (DG), RISK (R), Risk estimator with Uncer-tainties and Multidimensional model (RIMUM)), to estimate the four (extended)collision risks. In optimal conditions first with perfect location and perception,and then the uncertainty scenario of perception with perfect location. Resultsshow that the extended risks allow better anticipation of the collision than thelocal risk.Furthermore, we have developed a new extended version of the Chain branch leaf-Gateway (CBL-G) model, which proves to be more efficient in terms of coverage.The hierarchical architecture of the model allows us to calculate collision riskswith greater accuracy. The different levels of risk allow us to identify potentiallydangerous situations earlier, which is considered to be very relevant for incidentprevention.In our future research projects, we plan to study other situations such as roadintersections, highway exits, and entrances, as well as roundabouts. Additionally,we would also like to explore cases where we are unable to locate nodes throughthe chain (such as passing through tunnels). And elaborate risk indicators thatexplore all key components (ego vehicle, driver, obstacle, road, and environment)

AbstractSome of the bridges across the Yangtze River in the Three Gorges Reservoir area are in the curved section, and the collision prevention of bridges is a hot issue in the current industry. The system of ships sailing across bridges is a complex system in the discipline of transportation engineering. It is affected by ship conditions, channel conditions, meteorology and hydrology, navigation management and human factors. In order to grasp the influence of turbulent flow near the piers of bridges in curved river sections and oblique flow during variable water level periods on ships crossing bridges, it is necessary to carry out numerical simulation analysis. Methods: By establishing a simple physical model of the water area of the bridge pier, the turbulent flow field of the bridge pier was simulated in two dimensions by Fluent software. Then the turbulent flow characteristics of the single pier and the tandem double pier were compared, and the flow velocity on the upstream side of the bridge pier was used as a parameter to carry out numerical simulation. Finally, the flow-induced drift of the ship is quantitatively calculated in combination with the flow velocity. Conclusion: The two-dimensional simulation confirms that the turbulent width of the bridge pier increases with the increase of the flow velocity. The turbulent width of the tandem double pier is larger than that of the single pier, but the vorticity extending downstream is smaller than that of the single pier. The deflection moment and flow-induced drift of the ship crossing the bridge confirm the risk of ship collision. It is necessary to add a multi-function navigation mark to collect water flow parameters in time, and introduce LED visual navigation in the bridge area to improve the reliability of ship navigation in the bridge area of the curved river section.

Against the background of using the Index of Subdivision as a reference to address the safety level of ships when damaged, following primarily collision accidents, the EC-funded FLARE project is making inroads towards a direct assessment of the flooding risk, which is ship specific and considers the operating conditions and all accident-types leading to hull breach and flooding, namely collisions, bottom and side groundings. This is enabled by using a newly developed two-level approach Potential Loss of Life (PLL) of People On Board (POB); level 1 is a semi-empirical approach with the risk models formulated by use of data from a newly composed accident database, while level 2 is determining the flooding risk by a first principles approach, using time-domain flooding and evacuation analyses simulation tools in pertinent emergencies. Level 2 is considered in two sub-levels (Level 2.1 and Level 2.2), the former involving some simplifying assumptions in the risk calculation. In addition to addressing all accident types and modes of loss of ship and of POB, the FLARE framework and methodology considers active and passive measures of risk prevention and control, hence with application potential to both newbuildings and existing ships. It also facilitates real-time flooding risk evaluation for risk monitoring and effective control in emergencies. Key objectives of the FLARE project are to provide the technical basis for the rational determination and assessment of flooding risk and to prepare a proposal for the revision of relevant IMO SOLAS regulations towards a risk-based approach to contain and control flooding emergencies. The paper briefly describes the FLARE flooding risk assessment framework and provides risk estimation results at all three levels for one cruise ship and one RoPax, including comparisons with available IMO societal criteria, as well as a summary of results for a further 7 ships at levels 2.1 and 2.2. In the light of the results presented, the paper draws conclusions on the progress made and offers recommendations for the way forward.

Against the background of using the Index of Subdivision as reference to address the safety level of ships when damaged, following primarily collision incidents, the EC-funded FLARE project is making inroads towards a direct assessment of flooding risk, which is ship, operating environment, and ancient type specific by addressing all the underlying elements, using a two-level approach; level 1 being semi-empirical with risk models informed through a newly composed accident database and level 2 with flooding risk, in the form of Potential Loss of Life, calculated from first principles, using time-domain flooding simulation tools and evacuation analyses in pertinent emergencies. In addition to addressing all accident types and modes of loss, the FLARE framework and methodology target active and passive measures of risk prevention and control, hence with application potential to both new buildings and existing ships as well as facilitate real-time flooding risk evaluation for risk monitoring and effective control in emergencies. A key objective of the FLARE project is to provide the technical basis and a proposal for the revision of relevant IMO regulations towards a risk-based approach to contain and control flooding emergencies. The paper provides a complete example of one cruise ship and one RoPax where levels 1 and 2 of flooding risk evaluation is presented and discussed, leading to conclusions and recommendations for the way forward.

Abstract The decarbonization of the energy section urges a radical transformation to meet the net zero carbon emission target. In the last decades, many countries around the world have initiated the Carbon Capture and Storage (CCS) as one of the pilot projects aiming to permanent and environmentally safe storage of CO2 underground. However, only a few projects have strived and is eventually executed. Ones of the biggest challenges are technicality and commerciality to drive the success of the project. Thus, the objective of this paper is to mainly focus on the CCS well construction, design consideration, and optimization in Southeast Asia offshore CCS projects during the detailed planning phase. The process will start with the reservoir injection targets. Each well is planned to inject one single target to minimize the complexity of well architecture and completion equipment. Inevitably as being common in this area, stacked reservoirs or multi-target reservoirs are exceptional to achieve the intended CO2 injection target with a higher complexity level of completion equipment. Wellhead platform is a huge capital investment. Reuse of existing platform or new wellhead platform brings advantages and disadvantages. The key concerns include slot recovery issues, collision risk, fatigue concern on platform structure, and so on. The detailed consideration has been laid out to ensure the platform integrity and meets the expected design life. Well construction process is similar to normal oil and gas wells, but the main differences are CO2 injecting fluid and load cases analysis. Thus, material selection plays a major role for the well construction process to align with flow assurance study result and expected load case when majority of the worst-case scenario might occur in the late life injection. Material optimization is a key to bring the well construction cost down. Material testing has been constructed as per the expected downhole condition for the verification and optimization purposes. Detailed study of each type of wells are necessary to ensure the casing and completion equipment is fitted for purpose during the well life cycle. The Measurement, Monitoring and Verification (MMV) equipment is embedded since the designed phase with the ranking technique to comply with conformance and containment criteria.

<div class="section abstract"><div class="htmlview paragraph">Intelligent vehicle-to-everything connectivity is an important development trend in the automotive industry. Among various active safety systems, Autonomous Emergency Braking (AEB) has garnered widespread attention due to its outstanding performance in reducing traffic accidents. AEB effectively avoids or mitigates vehicle collisions through automatic braking, making it a crucial technology in autonomous driving. However, the majority of current AEB safety models exhibit limitations in braking modes and fail to fully consider the overall vehicle stability during braking. To address these issues, this paper proposes an improved AEB control system based on a risk factor (AERF). The upper-level controller introduces the risk factor (RF) and proposes a multi-stage warning/braking control strategy based on preceding vehicle dynamic characteristics, while also calculating the desired acceleration. Furthermore, a lower-level PID-based controller is designed to track the desired acceleration and compute the corresponding brake master cylinder pressure and throttle opening using an established inverse longitudinal dynamics model. Furthermore, to address vehicle stability during braking, an Anti-lock Braking System (ABS) controller is integrated with the proposed AERF. The effectiveness of the AERF is validated through software co-simulation and hardware-in-the-loop testing (HIL). The results demonstrate that the AERF can maintain a safe braking distance within 2 meters under Euro NCAP standard conditions, with excellent tracking performance of the actual braking deceleration and an error rate below 5%, ensuring a high level of system safety.</div></div>

In order to apply the multi-particle collision dynamics (MPCD) method to a magnetic particle suspension, we have elucidated the dependence of the translational and rotational Brownian motion of magnetic particles on the MPCD parameters that characterize the MPCD simulation method. We here consider a two-dimensional system composed of magnetic spherical particles in thermodynamic equilibrium. The diffuse reflection model has been employed for treating the interactions between fluid and magnetic particles. In the diffuse reflection model, the interactions between fluid and magnetic particles are transferred into the translational motion more strongly than into the rotational motion of magnetic particles. The employment of relatively small simulation time steps gives rise to a satisfactory level of the translational Brownian motion. The activation level of the Brownian motion is almost independent of both the size of the unit collision cell and the number of fluid particles per cell. Larger values of the maximum rotation angle induce stronger translational and rotational Brownian motion, but in the present magnetic particle suspension the range between around π/4 and π/2 seems to be reasonable. We may conclude that the MPCD method with the simple diffuse reflection model is a feasible simulation technique as the first approximation for analyzing the behavior of magnetic particles in a suspension. If more accurate solutions regarding the aggregate structures of magnetic particles are required, the introduction of the scaling coefficient regarding the interactions between fluid and magnetic particles can yield more accurate and physically reasonable aggregate structures in both a qualitative and quantitative meanings.

Abstract After a first part of the drilling campaign, including about 10 wells and branches achieved within two years, the operator started questioning the geological reservoir model and reserves implications for the field Offshore Congo. Considering the potential economic impact of this development, the decision was made to reduce wellbore positioning uncertainty relying on optimization and survey QAQC processes that could be applied without adding cost of extra equipment, operational time or personnel. With more than 10 wells drilled using recent while drilling measurement and directional tools in the same environment, a wide range of wellbore positioning information was available for analysis, post-correction, and geological/reservoir model deeper understanding. Also, investigation was done to recover existing geomagnetic data acquired during the geophysical campaign. Thanks to this extensive data set, enhanced wellbores positioning was implemented using meticulous combination of processes. The "process" overall impact is often underestimated while most of the data is already available. For lateral positioning correction, it included the processing of geomagnetic IFR data over the Moho field associated to Multi Station Correction. For vertical repositioning, BHA sag correction was applied with scrutinous assessment of residual sag uncertainty and detailed analysis of continuous survey data. This robust, cost-effective, and valuable solution was chosen to be applied by the operator in the Moho field. The process was first applied post-drilling to evaluate the level of improvement that could be brought to another well also exposed to challenging trajectory context (ERD 2 with reduced target 25 × 50 m at almost 8000m MD/RT). It confirmed that the achievable uncertainty reduction would meet well objectives without adding any risk or operational time nor jeopardizing wellbore positioning and collision avoidance. Thus, it brought up to 50 to 60% of uncertainty reduction and about 30m lateral and 3m vertical displacement. The reduction of the uncertainty and trajectory adjustment allowed to enhance geologic context understanding. The vertical position of the well was offset following this revision. This had a 5% consequence in term of oil layer thickness for this well. Then, the team designed and rolled out to the operator and contractors an execution strategy and operational workflow including remote monitoring with near real-time survey QAQC that would ensure the best correction process customized for the specific drilling challenges. This monitoring enabled reducing the ellipsoid to ~20 by 50m radius at TD = 7618m. This allowed entering in the reservoir at the exact top of the structure, behind the fault that was the optimum in term of reserves and secured 90% of potential reserves of this well. The operator's choice of valuing the available information to enhance their asset is a very interesting way to optimize the past efforts put in wellbore positioning to face the current economically constrained environment.

Sub-sea installation operations require a high level of accuracy and control in order to avoid misalignment and possible collisions between modules on the sea bed. To reduce costs, smaller and lighter construction vessels are now performing these operations. The most critical parts of the operation are lift-off from the deck, passing through the splash zone, and landing sensitive equipment on the sea bed. The hazards are: high dynamic loads, resonance effects, and slack line snap. Therefore, in this study, modeling and simulation are applied to optimize design parameters and develop operational procedures for each operation to reduce risk of failure. Further, the same models can be used in operator simulator training. Modeling and simulation of interactive multi body systems is a rather complex task, involving the vessel as a moving platform, lifting equipment such as cranes and winches, guiding devices, lifting cables and payload behavior in air, all while partly to fully submerged. It is a multi-physics problem involving hydrodynamics, mechanics, hydraulics, electronics, and control systems. This paper describes an approach to link the different models to simulate the operations including interactions between the sub-systems. The paper focuses on the modeling approach used to connect the various dynamic systems into the complete operating system. The work is in its initial phase, and some of the sub-systems models are not complete. The models are described in this paper and will be included in future work. Some initial operational examples are included, to show how the models work together.