Добірка наукової літератури з теми "Long term prediction of vessel motion"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Long term prediction of vessel motion".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Long term prediction of vessel motion"
1
Miller, Paul H. "Fatigue Prediction Verification of Fiberglass Hulls." Marine Technology and SNAME News 38, no. 04 (October 1, 2001): 278–92. http://dx.doi.org/10.5957/mt1.2001.38.4.278.
Повний текст джерелаАнотація:
The growing use of marine composite materials has led to many technical challenges and one is predicting lifetime durability. This analysis step has a large uncertainty due to the lack of data from in-service composite vessels. Analytical models based on classical lamination theory, finite-element analysis, ship motions, probability and wind and wave mechanicswere used in this project to predict hull laminate strains, and fatigue tests were used to determine S-N residual stiffness properties of coupons. These predictions and test data were compared against two cored fiberglass sisterships having significantly different fatigue histories and undamaged laminates representing a new vessel. Strains were measured while underway and good correlation was achieved between predictions and measurements. Fatigue damage indicators were identified which could be used in vessel inspection procedures. Endurance limits were found to be near 25% of static failure load, indicating that a fatigue design factor of four is required for infinite service with this material. Standard moisture experiments using boiling water were compared with long-term exposure. Results indicated the boiling water test yielded significantly conservative values and was not a reliable means of predicting long-term effects. Panel tests were compared with a combined coupon and finite-element procedure. Results indicated the proposed procedure was a viable substitute, at least for the materials studied. A rational explanation for using thicker outer skin laminates in marine composites was identified through single-sided moisture flex tests. These showed that the reduced strength and stiffness due to moisture of the outer hull skin laminate could be compensated by increased thickness. Although the resulting unbalanced laminate is not ideal from a warping standpoint, the approach leads to consistent tensile failure of the inner skin when subjected to normal loads. Permeability considerations make this desirable for hull laminates.
2
Siniuta, K. O. "SHIP HANDLING IN CASE OF DISTURBANCE DURING SEQUENTIAL CALCULATION AND OBSERVATION OF SHIP MOTION." Shipping & Navigation 32, no. 2 (December 12, 2021): 88–94. http://dx.doi.org/10.31653/2306-5761.32.2021.88-94.
Повний текст джерелаАнотація:
Controllability is an important maritime quality that determines the efficiency of ship handling. When developing course control systems, it is necessary to take into account the operational characteristics of the vessel, as well as external factors affecting it. The complexity of ship handling, as an object of handling, arises due to the continuous influence of various factors that affect the controllability of the ship. The environmental conditions in which the course management task has to be solved are diverse - stormy weather, ice conditions, shallow water, tides, restricted waters(congested areas), proximity of other vessels, etc. All these factors cannot be comprehensively taken into account by traditional mathematical methods, while ensuring the necessary adequacy of real processes. This paper considers existing approaches to controlling the movement of a ship on a course, such as course control, disturbance control, ship movement control on a course based on the principle of long-term prediction, lateral deviation, intellectual approaches to ship control. The most necessary way to improve the quality of the vessel's course is to control the disturbance by consistently calculating and observing the vessel's movement. The main disturbing effect in stabilizing the course is caused by sea waves. In stormy weather, forced oscillations are imposed on the ship's own motions on the course. The amplitude and period of yawing depend on the level of sea state, the direction and strength of the wind, the tonnage of the vessel, its loading condition, speed, effectiveness of the rudder and the law of control. There is a need to increase the accuracy of determining the direct relationship between the measured value of the external perturbation and the magnitude of the yaw angle. The article provides an algorithm for calculating the return of the vessel to the path line, taking into account the modulus and direction of natural disturbance obtained as a result of observation of the ship's position.
3
Konon, N. M. "ANALYTICAL MODELLING OF SEAKEEPING QUALITIES OF CONTAINER VESSEL." Shipping & Navigation 30, no. 1 (December 1, 2020): 78–87. http://dx.doi.org/10.31653/2306-5761.30.2020.78-87.
Повний текст джерелаАнотація:
The design of ships or any other floating systems intended to operate on or close to the surface of the sea is controlled to a large extent by what is usually referred to as seakeeping, or, in more common terminology, safety at sea. This is a primary consideration and criteria, which has to be fully met. Safety of a ship naturally includes the crew, cargo and the hull itself. Seakeeping is, indeed, a generalized term and reflects the ship's capability to survive all hazards at sea such as collision, grounding, fire, as well as heavy-weather effects related to the environment in general and waves in particular. The two most likely types of failure under these conditions are due to structural causes and capsizing resulting from insufficient stability under severe weather conditions. Such criteria as economical navigation of the ship as related to speed-keeping abilities, fuel consumption, avoidance of damage to ship components and cargo, and comfort to crew or passengers, or both, are key items. The operational limits of electronic equipment, mechanical components and weapon systems on board warships are other aspects of sea keeping. In this work it is highlighted that seakeeping is a generalized term that includes a wide variety of subjects such as ship motions (amplitudes, accelerations, phases), deck wetness, slamming, steering in waves, added resistance, hydrodynamic loadings (pressures, forces, moments) and transient loads. Since the ship environmental operability or its sea keeping characteristics are closely linked to the severity of the sea, the description of the seaway is usually considered as an integral part of sea keeping. It is taken into consideration that the severity of the sea cannot be considered in absolute terms, since for each floating system, be it a ship, a platform or a buoy, the intensity of the sea state can only be determined in terms of the system's responses. Hence, different thresholds apply to different problems, and sea state 4 may be just as severe for a small patrol craft as sea state 8 may be for a larger containership. Hence, the characteristics and frequency of occurrence of waves in specific sea zones are required if a possible reduction in the system environmental operability is expected. It is demonstrated that most texts or papers, which deal with the overall question of sea keeping, devote some attention to the basic phenomena, that is, the seaway and the motions of the ship or other floating platforms as a result of the excitation imposed by the seaway. Ship motions, as such, do not always constitute the criteria for sea keeping, and much more often other responses directly related to the magnitude and phasing of the motions or the resulting velocities and accelerations constitute the prime cause for exhibiting good or bad sea keeping qualities. Such responses could be a function of the motion only, as in the case of added resistance or hydrodynamic pressures, or they could be a function of motion and other design parameters, such as freeboard in the case of deck wetness or the longitudinal weight distribution in the case of vertical bending moments. In this work, latest methods of modeling and computation for body-wave interactions described and compared with data observed for container carrier. The foregoing calculation routine Судноводіння | Shipping & Navigation ISSN 2306-5761 | 2618-0073 30-2020 Національний університет «Одеська морська академія» 79 is fairly well accepted today among naval architects specializing in the sea keeping aspects of the ship design process. Differences between the results obtained by various techniques as presented by the available computer programs are insignificant. However, since the regular-wave results are of little or no value except as input for the more realistic long- and short-term response predictions in a real seaway environment, it is important to determine which wave data information and what statistical extrapolation techniques are used to obtain the latter. The format used to describe the seaway in most ship response calculations is the wave spectrum. However, since measured spectrum for a specific sea zone or route are very rarely available, it is often necessary to use spectrum measured in one location for predictions in another location. In such a case, while the basic spectruml shape and scatter remain unchanged, the percentage of wave height distribution would vary to represent realistic conditions for the sea area in question. Such data usually are based on observations, and assuming the sample is large enough the distribution of expected wave heights should be quite reliable. An alternative approach often used in ship design is to utilize one of several theoretical spectruml formulations [2, 3, 4] such as the Pierson-Moskowitz one-parameter spectrum, the ISSC spectrum, the JONSWAP spectrum, and other. In each of these cases, some input parameters are required usually in the form of wave height, period, peak frequency, fetch, etc. The reliability of the wave data depends in these cases both on the quality of the input parameter and the adequacy of the theoretical formulation.
4
Li, Xingyang, Kaiqiang Wu, and Haijing Deng. "Blood Pressure Monitoring Based on Carbonized Lens Cleaning Paper-Based Flexible Strain Sensor." Science of Advanced Materials 13, no. 9 (September 1, 2021): 1789–96. http://dx.doi.org/10.1166/sam.2021.4070.
Повний текст джерелаАнотація:
Blood pressure (BP) is an important indicator for measuring human health, especially continuous BP, which can indirectly reflect the operating conditions of the heart and blood vessels. The increase in wearable devices has promoted the development of high-performance flexible strain sensors that can monitor various physiological signals and human motion signals. In this work, we used carbonized non-woven lens cleaning paper as the sensitive element to prepare a wide working range (0–100% strain) and high sensitivity (sensitivity in the range of 0–60% is 32, sensitivity in the range of 60–100% strain is as high as 162), fast response capability (response time less than 20 ms), with long-term cycle stability (greater than 10,000 cycles). Based on this sensor, we collected the user’s radial artery pressure pulse wave signal, and proposed a wearable continuous BP monitoring method based on the pressure pulse wave signal. This method includes pulse wave signal monitoring, pulse wave feature extraction, and establishment of a BP prediction model. The results show that there is a strong correlation and satisfactory accuracy between the predicted BP value and the reference BP value, thus demonstrating its application potential in personal BP monitoring.
5
Wiegand, T., Xiaozheng Zhang, and B. Girod. "Long-term memory motion-compensated prediction." IEEE Transactions on Circuits and Systems for Video Technology 9, no. 1 (1999): 70–84. http://dx.doi.org/10.1109/76.744276.
Повний текст джерела
6
Tang, Gang, Jinman Lei, Chentong Shao, Xiong Hu, Weidong Cao, and Shaoyang Men. "Short-Term Prediction in Vessel Heave Motion Based on Improved LSTM Model." IEEE Access 9 (2021): 58067–78. http://dx.doi.org/10.1109/access.2021.3072420.
Повний текст джерела
7
Kim, Jonghee, Chanho Jung, Dokeun Kang, and Chang Jin Lee. "A New Vessel Path Prediction Method using Long Short-term Memory." Transactions of The Korean Institute of Electrical Engineers 69, no. 7 (July 31, 2020): 1131–34. http://dx.doi.org/10.5370/kiee.2020.69.7.1131.
Повний текст джерела
8
Su, Xiaoqing, Lintao Liu, Hsu Houtse, and Guocheng Wang. "Long-term polar motion prediction using normal time–frequency transform." Journal of Geodesy 88, no. 2 (November 30, 2013): 145–55. http://dx.doi.org/10.1007/s00190-013-0675-7.
Повний текст джерела
9
Liu, Chao, Shuai Guo, Yuan Feng, Feng Hong, Haiguang Huang, and Zhongwen Guo. "L-VTP: Long-Term Vessel Trajectory Prediction Based on Multi-Source Data Analysis." Sensors 19, no. 20 (October 9, 2019): 4365. http://dx.doi.org/10.3390/s19204365.
Повний текст джерелаАнотація:
With the rapid development of marine IoT (Internet of Things), ocean MDTN (Mobile Delay Tolerant Network) has become a research hot spot. Long-term trajectory prediction is a key issue in MDTN. There are no long-term fine-grained trajectory prediction methods proposed for ocean vessels because a vessel’s mobility pattern lacks map topology support and can be easily influenced by the fish moratorium, sunshine duration, etc. A traditional on-land trajectory prediction algorithm cannot be directly utilized in this field because trajectory characteristics of ocean vessels are far different from that on land. To address the problem above, we propose a novel long-term trajectory prediction algorithm for ocean vessels, called L-VTP, by utilizing multiple sailing related parameters and K-order multivariate Markov Chain. L-VTP utilizes multiple sailing related parameters to build multiple state-transition matrices for trajectory prediction based on quantitative uncertainty analysis of trajectories. Trajectories’ sparsity of ocean vessels results in a critical state missing problem of a high-order state-transition matrix. L-VTP automatically traverses other matrices in a specific sequence in terms of quantitative uncertainty results to overcome this problem. Furthermore, the different mobility models of the same vessel during the day and the night are also exploited to improve the prediction accuracy. Privacy issues have been taken into consideration in this paper. A quantitative model considering Markov order, training metadata and privacy leak degree is proposed to help the participant make the trade-off based on their customized requirements. We have performed extensive experiments on two years of real-world trajectory data that include more than two thousand vessels. The experiment results demonstrate that L-VTP can realize fine-grained long-term trajectory prediction with the consideration of privacy issues. The average error of 4.5-hour fine-grained prediction is less than 500 m. In addition, the proposed method can be extended to 10-hour prediction with an average error of 2.16 km, which is also far less than the communication range of ocean vessel communication devices.
10
Zhang, Minglong, Liang Huang, Yuanqiao Wen, Jinfen Zhang, Yamin Huang, and Man Zhu. "Short-Term Trajectory Prediction of Maritime Vessel Using k-Nearest Neighbor Points." Journal of Marine Science and Engineering 10, no. 12 (December 7, 2022): 1939. http://dx.doi.org/10.3390/jmse10121939.
Повний текст джерелаАнотація:
The prediction of ship location has become an increasingly popular research hotspot in the field of maritime transportation engineering, which benefits maritime safety supervision and security. Existing methods of ship location prediction based on motion characteristics have a large uncertainty and cannot guarantee trajectory prediction accuracy of the target ship. An improved method of location prediction using k-nearest neighbor (KNN) is proposed in this paper. An expanded circle area of the latest point of the target ship is first generated to find the reference points with similar movement characteristics in the constraints of distance and time intervals. Then, the top k-nearest neighbors are determined based on the degree of similarity. Relationships between the reference point of each neighbor and the latest points of the target ship are calculated. The predicted location of the target ship can then be determined by a weighted calculation of the locations of all neighbors at the predicted time and their relationships with the target ship. Experiments of ship location prediction in 10 min, 20 min, and 30 min were conducted. The correlation coefficient of the location prediction error for the three experiments was 0.992, 0.99, and 0.9875, respectively. The results show that ship location prediction with reference to multiple nearest neighbors with similar movements can provide better accuracy.
Дисертації з теми "Long term prediction of vessel motion"
1
Wiest, Jürgen [Verfasser]. "Statistical long-term motion prediction / Jürgen Wiest." Ulm : Universität Ulm, 2017. http://d-nb.info/1128728931/34.
Повний текст джерела
2
Schenk, Konrad [Verfasser], Horst-Michael [Akademischer Betreuer] Groß, Hans-Joachim [Gutachter] Böhme, and Christian [Gutachter] Wöhler. "Contribution to the long term prediction of motion trajectories / Konrad Schenk ; Gutachter: Hans-Joachim Böhme, Christian Wöhler ; Betreuer: Horst-Michael Groß." Ilmenau : TU Ilmenau, 2018. http://d-nb.info/117812858X/34.
Повний текст джерела
3
Shan, Mao. "Cooperative Vehicle Tracking in Large Environments." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/10100.
Повний текст джерелаАнотація:
Vehicle position tracking and prediction over large areas is of significant importance in many industrial applications, such as mining operations. In a small area, this can be easily achieved by providing vehicles with a constant communication link to a control centre and having the vehicles broadcast their position. The problem changes dramatically when vehicles operate within a large environment of potentially hundreds of square kilometres and in difficult terrain. This thesis presents algorithms for cooperative tracking of vehicles based on a vehicle motion model that incorporates the properties of the working area, and information collected by infrastructure collection points and other mobile agents. The probabilistic motion prediction approach provides long-term estimates of vehicle positions using motion profiles built for the particular environment and considering the vehicle stopping probability. A limited number of data collection points distributed around the field are used to update the position estimates, with negative information also used to improve the estimation. The thesis introduces the concept of observation harvesting, a process in which peer-to-peer communication between vehicles allows egocentric position updates and inter-vehicle measurements to be relayed among vehicles and finally conveyed to the collection points for an improved position estimate. It uses a store-and-synchronise concept to deal with intermittent communication and aims to disseminate data in an opportunistic manner. A nonparametric filtering algorithm for cooperative tracking is proposed to incorporate the information harvested, including the negative, relative, and time delayed observations. An important contribution of this thesis is to enable the optimisation of fleet scheduling when full coverage networks are not available or feasible. The proposed approaches were validated with comprehensive experimental results using data collected from a large-scale mining operation.
4
d'Afflisio, Enrica. "Maritime anomaly detection based on statistical methodologies: theory and applications." Doctoral thesis, 2022. http://hdl.handle.net/2158/1259001.
Повний текст джерелаАнотація:
The proposed research aims at contributing to advances in the anomaly detection methodologies within the framework of maritime domain, in order to improve the ability to reveal, understand, anticipate and prevent illegitimate activities at sea. This work has been developed based on three fundamental tools: a prior information from a maritime traffic graph that can be derived from a route atlas or from historical data, the Ornstein-Uhlenbeck mean reverting stochastic process to model the vessel's dynamics in deep waters, and the complete or incomplete observation of the available data from heterogeneous sensor systems. Relying on the statistical hypothesis testing framework, the work treats the problem of detecting a vessel's anomalous deviations from the expected conditions in the presence of different levels of data unavailability. The problem is further complicated by the possible falsification of dynamic data self-reported by the vessel. A worst-case scenario in terms of detection capability is finally tackled by proposing an optimization methodology to make the trajectory of a malicious vessel as stealth as possible.
The effectiveness of the proposed strategies has been assessed through experimental analyses concerning both synthetic and real-world maritime operational scenarios.
Книги з теми "Long term prediction of vessel motion"
1
Kucharski, Fred, and Muhammad Adnan Abid. Interannual Variability of the Indian Monsoon and Its Link to ENSO. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.615.
Повний текст джерелаАнотація:
The interannual variability of Indian summer monsoon is probably one of the most intensively studied phenomena in the research area of climate variability. This is because even relatively small variations of about 10% to 20% from the mean rainfall may have dramatic consequences for regional agricultural production. Forecasting such variations months in advance could help agricultural planning substantially. Unfortunately, a perfect forecast of Indian monsoon variations, like any other regional climate variations, is impossible in a long-term prediction (that is, more than 2 weeks or so in advance). The reason is that part of the atmospheric variations influencing the monsoon have an inherent predictability limit of about 2 weeks. Therefore, such predictions will always be probabilistic, and only likelihoods of droughts, excessive rains, or normal conditions may be provided. However, even such probabilistic information may still be useful for agricultural planning. In research regarding interannual Indian monsoon rainfall variations, the main focus is therefore to identify the remaining predictable component and to estimate what fraction of the total variation this component accounts for. It turns out that slowly varying (with respect to atmospheric intrinsic variability) sea-surface temperatures (SSTs) provide the dominant part of the predictable component of Indian monsoon variability. Of the predictable part arising from SSTs, it is the El Niño Southern Oscillation (ENSO) that provides the main part. This is not to say that other forcings may be neglected. Other forcings that have been identified are, for example, SST patterns in the Indian Ocean, Atlantic Ocean, and parts of the Pacific Ocean different from the traditional ENSO region, and springtime snow depth in the Himalayas, as well as aerosols. These other forcings may interact constructively or destructively with the ENSO impact and thus enhance or reduce the ENSO-induced predictable signal. This may result in decade-long changes in the connection between ENSO and the Indian monsoon. The physical mechanism for the connection between ENSO and the Indian monsoon may be understood as large-scale adjustment of atmospheric heatings and circulations to the ENSO-induced SST variations. These adjustments modify the Walker circulation and connect the rising/sinking motion in the central-eastern Pacific during a warm/cold ENSO event with sinking/rising motion in the Indian region, leading to reduced/increased rainfall.
Частини книг з теми "Long term prediction of vessel motion"
1
Wiegand, Thomas, and Bernd Girod. "Long-Term Memory Motion-Compensated Prediction." In Multi-Frame Motion-Compensated Prediction for Video Transmission, 37–59. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1487-9_3.
Повний текст джерела
2
Cao, Zhe, Hang Gao, Karttikeya Mangalam, Qi-Zhi Cai, Minh Vo, and Jitendra Malik. "Long-Term Human Motion Prediction with Scene Context." In Computer Vision – ECCV 2020, 387–404. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58452-8_23.
Повний текст джерела
3
Dobrkovic, Alexander, Maria-Eugenia Iacob, Jos van Hillegersberg, Martin R. K. Mes, and Maurice Glandrup. "Towards an Approach for Long Term AIS-Based Prediction of Vessel Arrival Times." In Logistics and Supply Chain Innovation, 281–94. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22288-2_16.
Повний текст джерела
4
Vinayavekhin, Phongtharin, Michiaki Tatsubori, Daiki Kimura, Yifan Huang, Giovanni De Magistris, Asim Munawar, and Ryuki Tachibana. "Human-Like Hand Reaching by Motion Prediction Using Long Short-Term Memory." In Social Robotics, 156–66. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70022-9_16.
Повний текст джерела
5
Lu, Weitao, Lue Chen, Zhijin Zhou, Songtao Han, and Tianpeng Ren. "A Super-Long-Term Prediction Method of Earth Polar Motion Based on Spectrum Analysis." In Lecture Notes in Electrical Engineering, 619–28. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3138-2_57.
Повний текст джерела
6
Marpe, Detlev, Thomas Wiegand, and Hans L. Cycon. "Wavelet-Based Video Compression Using Long-Term Memory Motion-Compensated Prediction and Context-Based Adaptive Arithmetic Coding." In Wavelet Analysis and Its Applications, 76–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45333-4_12.
Повний текст джерела
7
Wang, Shangbo. "Traffic State Prediction and Traffic Control Strategy for Intelligent Transportation Systems." In Intelligent Electronics and Circuits - Terahertz, IRS, and Beyond [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.101675.
Повний текст джерелаАнотація:
The recent development of V2V (Vehicle-to-Vehicle), V2I (Vehicle-to-Infrastructure), V2X (Vehicle-to-Everything) and vehicle automation technologies have enabled the concept of Connected and Automated Vehicles (CAVs) to be tested and explored in practice. Traffic state prediction and control are two key modules for CAV systems. Traffic state prediction is important for CAVs because adaptive decisions, control strategies such as adjustment of traffic signals, turning left or right, stopping or accelerating and decision-making of vehicle motion rely on the completeness and accuracy of traffic data. For a given traffic state and input action, the future traffic states can be predicted via data-driven approaches such as deep learning models. RL (Reinforcement Learning) - based approaches gain the most popularity in developing optimum control and decision-making strategies because they can maximize the long-term award in a complex system via interaction with the environment. However, RL technique still has some drawbacks such as a slow convergence rate for high-dimensional states, etc., which need to be overcome in future research. This chapter aims to provide a comprehensive survey of the state-of-the-art solutions for traffic state prediction and traffic control strategies.
Тези доповідей конференцій з теми "Long term prediction of vessel motion"
1
Vestbo̸stad, Tone M., Sverre Haver, Odd Jan Andersen, and Arne Albert. "Prediction of Extreme Roll Motion on an FPSO Using Long Term Statistics." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28117.
Повний текст джерелаАнотація:
This paper presents a method for predicting extreme roll motion on an FPSO using long-term statistics. The method consists of a long-term simulation where a database of consecutive short-term sea states with combined weather conditions, including direction and magnitude of wind, wind waves and swell waves, is used. The vessel heading in given weather conditions is simulated. For each combined sea state, the short-term roll motion maxima are calculated to form a long-term probability distribution, and the extreme roll motion, e.g. the 100-year value, can be estimated from the distribution. For an example FPSO, the results from the long-term analysis have been compared with full-scale measurements, giving a validation of the method. This paper is a shortened version of [1].
2
Yoshida, Hisafumi, Hideo Orihara, and Keiichi Yamasaki. "Long-Term Wave Measurement by an Onboard Radar Wave Meter and Prediction of Ship Motions Based on the Onboard Wave Measurements." In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/omae2015-42280.
Повний текст джерелаАнотація:
Continuous measurement of waves, ship motions (roll and pitch), and so on has been carried out for about five years by onboard monitoring system installed ocean-going vessel. Measured wave data, including wave height, wave period and wave direction, are thoroughly evaluated with corresponding onboard weather observation data by comparing directly in terms of time series and statistical values. Then, short term prediction of ship motions (roll and pitch) based on the measured wave data are compared with onboard motion data measured by vertical gyro. From the results described, good accuracy and effectiveness of wave measurements by an onboard radar wave meter for safe navigation are demonstrated.
3
Fyfe, Alexander, and Edward Ballard. "Prediction of Green Water Events on FPSO Vessels." In ASME 2003 22nd International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2003. http://dx.doi.org/10.1115/omae2003-37452.
Повний текст джерелаАнотація:
Most floating vessels experience some sea states, not necessarily extreme storms, which cause large volumes of green water to flow across the deck. Due to the location of safety critical equipment on the deck of FPSOs, the determination of the likely occurrences and the magnitudes of such events are critical to safe design and operation. A method for the determination of green water heights on the deck of an FPSO has been presented in references 1–5. This paper examines the long-term distributions of heights implied by these references and the identification of sea states in which extreme events are likely to occur. The method is based upon the long term distribution of sea states at the intended location, combined with the motion characteristics of the vessel. Freeboard exceedance at the bow and at a point along the side is considered for two typical FPSO configurations. The methodology presented is widely applicable to many locations but wave conditions typical of the Central North Sea are used by way of illustration. The results presented include long term probability distributions of green water height on deck at locations of interest. Relative contributions of each combination of significant wave height and peak period to the probability of the largest single event in a defined return period are determined and discussed. It is shown that the wave conditions most likely to give rise to the most severe green water events are seldom those characterized by the largest wave crest heights. Instead, there exists a complex dependence on characteristic periods associated with vessel motions and on the long-term occurrences of particular sea states. The ability to predict conditions in which the largest green water events are most likely to occur offers the possibility of providing improved operational guidelines for FPSOs, allowing action to be taken to avoid unfavourable loading conditions and/or vessel headings in certain sea conditions. However, it is also shown that it may be difficult to identify some severe green water sea states from normally available forecast data and hence it is important that appropriate provision is made at the design stage.
4
Feng, Pei Yuan, Ning Ma, and Xie Chong Gu. "Long-Term Prediction of Speed Reduction Due to Waves and Fuel Consumption of a Ship at Actual Seas." In ASME 2010 29th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/omae2010-20308.
Повний текст джерелаАнотація:
The improvement of ship motion and propulsive performance becomes vital in various ocean engineering applications. As the notion of energy saving and environmental protection gradually finds its way deep into people’s heart, the issue of energy efficient design and operation of the vessels has attracted more and more attentions. How to make the vessels maintain service speed while consuming less fuel has quickly become the main concern of the naval architects. In this paper, we present a new procedure to predict speed reduction and fuel consumption of a ship at actual seas. The prediction takes into account the added resistance due to waves since it is recognized to be the predominant component, while wind resistance, fouling effect and other resistance components are relatively small and temporarily ignored. The calculation of the added resistance is based on a three-dimensional frequency-domain panel method for regular waves and spectral approach is applied to obtain the mean value. Then speed prediction is performed based on a simplified model assuming the balanced working point among the ship, propeller and the engine under the assumption of linear relationship between the engine torque and its rotation. Fuel consumption prediction is carried out through calculating the engine power, the effective fuel consumption rate and the time for sailing. Long-term prediction is made through combining the short-term result with the long-term ocean wave statistics from the Database of Winds and Waves which is newly developed in Shanghai Jiao Tong University (SJTU). A long-term probability model which takes into account the ship’s actual navigation conditions is applied, and the expected ship speed and fuel consumption along her actual sea route are predicted accordingly. For the purposed of practical use, a VLCC ship type is adopted for the prediction as an example. Finally, it has been concluded that the propulsive performance, i.e. speed and fuel consumption, of the vessel at actual seas can be improved through design considerations such as hull form optimization, engine selection and weather routing.
5
Kuehnlein, Walter L., and K. E. Brink. "Model Tests for the Validation of Extreme Roll Motion Predictions." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28269.
Повний текст джерелаАнотація:
At present common stability criteria are based on practical knowledge gained from the operation of ships. Therewith the assessment of ship safety against capsizing is partly determined by long-term statistics of accidents. Regulations like the IMO-Resolution A 167 do not rate the typical seakeeping characteristics of different hull form geometries. Therefore strictly speaking, these criteria are just applicable for ships of similar types as included in statistics. Rapid development in ship design calls for the determination of ship and cargo safety in regard of extreme roll motions or capsizing during early design stage. Within the ROLL-S project, which was founded by the German Federal Ministry of Education and Research, dynamic stability tests with a box shaped Container Ship and a RO-RO vessel have been performed. The performance of model tests, which are intended to serve for the validation of numerical simulation methods, put high demands on test and data acquisition techniques. The data of the waves encountered, course and position, as well as the response of the model had to be determined by model tests in order to use these data for the validation of numerical ship motion simulations. During the tests extreme roll motions of the two considered vessels could be observed in head seas and in following seas. Besides critical motion characteristics in following seas, like broaching, parametric induced roll motion effects were investigated in head sea condition. Remark: This paper should be read in conjunction with paper OMAE 2002-28297 which describes generation and transformation of the used waves.
6
de Kat, Jan O., Dirk-Jan Pinkster, and Kevin A. McTaggart. "Random Waves and Capsize Probability Based on Large Amplitude Motion Analysis." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28477.
Повний текст джерелаАнотація:
The objective of this paper is to apply a methodology aimed at the probabilistic capsize assessment of two naval ships: a frigate and a corvette. Use is made of combined knowledge of the wave and wind climate a ship will be exposed to during its lifetime and of the physical behavior of that ship in the various sea states it is likely to encounter. This includes the behavior in extreme wave conditions that have a small probability of occurrence, but which may be critical to the safe operation of a ship. Time domain simulations provide the basis for deriving short-term and long-term statistics for extreme roll angles. The numerical model is capable of predicting the 6 DOF behavior of a steered vessel in wind and waves, including conditions that may lead to broaching and capsizing.
7
Peric, Milovan, Tobias Zorn, Ould el Moctar, Thomas E. Schellin, and Yong-Soo Kim. "Simulation of Sloshing in LNG Tanks." In ASME 2007 26th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2007. http://dx.doi.org/10.1115/omae2007-29555.
Повний текст джерелаАнотація:
The aim of this paper is to demonstrate the prediction of internal loads on liquified natural gas (LNG) tanker ships and on offshore platforms. We use the moving grid approach and a finite volume solution method designed to allow for arbitrary ship motion. The motion of liquid is computed using an interface-capturing scheme which allows overturning and breaking waves. By performing a coupled simulation of the flow and vessel motion, it is possible to obtain a realistic response of the liquid in a tank to external excitation, e.g. by sea waves. Results are first presented for an LNG tanks whose motion is prescribed in accordance with planned laboratory experiments. Both two-dimensional (2D) and three-dimensional (3D) simulations are performed. The aim is to demonstrate that 1) realistic loads can be predicted using grids of moderate fineness, 2) the numerical method is able to accurately resolve the free surface even when severe fragmentation occurs, and 3) long-term simulations over many oscillation periods are possible without numerical mixing of liquid and gas. The plausibility of a coupled simulation of both vessel motion and the flow inside tanks and outside the vessel is then demonstrated for a full-size ship with partially-filled tanks exposed to head waves. In this simulation the forces and moments exerted by the sea cause the vessel to move, exciting the sloshing of liquid in tanks. For the computation of vessel motion, both sea-induced forces and forces due to sloshing in tanks are taken into account when determining the resultant forces and moments. While there are no experimental data for comparison at this time, the results look plausible and encourage further validation and application studies.
8
Chen, Limu, Ye Xia, Dexiong Pan, and Chengbin Wang. "Deep Learning Based Active Monitoring for Anti-collision between Vessels and Bridges." In IABSE Symposium, Guimarães 2019: Towards a Resilient Built Environment Risk and Asset Management. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/guimaraes.2019.0487.
Повний текст джерелаАнотація:
<p>Deep-learning based navigational object detection is discussed with respect to active monitoring system for anti-collision between vessel and bridge. Motion based object detection method widely used in existing anti-collision monitoring systems is incompetent in dealing with complicated and changeable waterway for its limitations in accuracy, robustness and efficiency. The video surveillance system proposed contains six modules, including image acquisition, detection, tracking, prediction, risk evaluation and decision-making, and the detection module is discussed in detail. A vessel-exclusive dataset with tons of image samples is established for neural network training and a SSD (Single Shot MultiBox Detector) based object detection model with both universality and pertinence is generated attributing to tactics of sample filtering, data augmentation and large-scale optimization, which make it capable of stable and intelligent vessel detection. Comparison results with conventional methods indicate that the proposed deep-learning method shows remarkable advantages in robustness, accuracy, efficiency and intelligence. In-situ test is carried out at Songpu Bridge in Shanghai, and the results illustrate that the method is qualified for long-term monitoring and providing information support for further analysis and decision making.</p>
9
Armstrong, C., Y. Drobyshevski, C. Chin, and I. Penesis. "Variability of Extreme Riser Responses due to Wave Frequency Motions of a Weather-Vaning FPSO." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61745.
Повний текст джерелаАнотація:
The variability of extreme responses of a flexible riser due to wave frequency motions of weather-vaning FPSO is investigated numerically. The objective of this study is to examine such variability in isolation from that caused by the low frequency (slow drift) vessel motions and vessel offsets. Investigation of the extreme value distributions of flexible risers provides the statistical foundation for flexible riser Response Based Analysis (RBA) for use in system design; the determination of the statistical properties of extreme flexible riser responses provides a method for the prediction of extreme responses of offshore systems in cyclonic conditions. A case study conducted in OrcaFlex included an FPSO vessel with a Lazy-S configured riser system. Five riser responses were selected in critical locations including tension, heave, and curvature responses. The environmental cases included two cyclonic storms consisting of multiple half-hour intervals. For each interval, time domain simulations included 40 wave realizations in order to provide a dataset for robust fitting of the extreme value distributions in the Gumbel format. Once the short term interval distributions were established, response distributions in a storm were generated by multiplying the short term distributions and the most probable maximum (MPM) response in a storm computed. A comparison of maximum interval, storm and 3-hour MPMs is presented, which indicates to what extent the MPM response in a storm exceeds the corresponding maximum interval response. Differences between the tension and heave responses are compared with those observed in the curvature responses. This study was limited to riser excitation by waves, current and wave frequency motions of a turret moored FPSO and it is expected that further inclusion of low frequency motions would contribute to the response variability. The inclusion of such variability will ultimately enable the storm-based statistical approach to be used for the development of long-term distribution of the riser responses.
10
Hermes, Christoph, Christian Wohler, Konrad Schenk, and Franz Kummert. "Long-term vehicle motion prediction." In 2009 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2009. http://dx.doi.org/10.1109/ivs.2009.5164354.
Повний текст джерела