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Relevant bibliographies by topics / Oil-spill modelling

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Academic literature on the topic 'Oil-spill modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Oil-spill modelling"

1

Sohpal, Vipan Kumar, and Amarpal Singh. "Biodegradation: Study of Modelling and Simulative of Oil Spill in Marine." International Journal of Scientific Research 1, no. 5 (June 1, 2012): 55–57. http://dx.doi.org/10.15373/22778179/oct2012/18.

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Quon, Tony K. S., and George E. Bushell. "Modelling Navigational Risk and Oil Spill Probabilities." Journal of Navigation 47, no. 3 (September 1994): 390–402. http://dx.doi.org/10.1017/s0373463300012339.

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This paper examines first a statistical modelling of the number of navigational accidents (collisons, groundings and strikings) involving tankers and freighters in Canadian waters; it then looks at a direct method of modelling oil spill frequency and magnitude, given a navigational accident. The former is used to examine various hypotheses in the literature regarding the impact of various factors on navigational risk. The latter is based on a direct probability tree analysis which allows the estimation of detailed oil spill impacts by facilitating the examination of representative spill sizes.

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Aznar, F., M. Sempere, M. Pujol, R. Rizo, and M. J. Pujol. "Modelling Oil-Spill Detection with Swarm Drones." Abstract and Applied Analysis 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/949407.

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Nowadays, swarm robotics research is having a great increase due to the benefits derived from its use, such as robustness, parallelism, and flexibility. Unlike distributed robotic systems, swarm robotics emphasizes a large number of robots, and promotes scalability. Among the multiple applications of such systems we could find are exploring unstructured environments, resource monitoring, or distributed sensing. Two of these applications, monitoring, and perimeter/area detection of a given resource, have several ecological uses. One of them is the detection and monitoring of pollutants to delimit their perimeter and area accurately. Maritime activity has been increasing gradually in recent years. Many ships carry products such as oil that can adversely affect the environment. Such products can produce high levels of pollution in case of being spilled into sea. In this paper we will present a distributed system which monitors, covers, and surrounds a resource by using a swarm of homogeneous low cost drones. These drones only use their local sensory information and do not require any direct communication between them. Taking into account the properties of this kind of oil spills we will present a microscopic model for a swarm of drones, capable of monitoring these spills properly. Furthermore, we will analyse the proper macroscopic operation of the swarm. The analytical and experimental results presented here show the proper evolution of our system.

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Hartmann, T. "Oil spill modelling—Lessons to be learned?" Marine Pollution Bulletin 18, no. 2 (February 1987): 58–59. http://dx.doi.org/10.1016/0025-326x(87)90550-9.

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Masciangioli, Panfilo, German Febres, and María Elena Viale-Rigo. "Nissos Amorgos Oil Spill Experience." International Oil Spill Conference Proceedings 1999, no. 1 (March 1, 1999): 1127–31. http://dx.doi.org/10.7901/2169-3358-1999-1-1127.

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ABSTRACT The behavior of the Bachaquero crude oil spilled by tanker Nissos Amorgos, when it grounded in the Gulf of Venezuela, was studied through modelling its fate using the SIMAP model (Applied Science Associates, Inc.). The purpose of the simulations was to improve the cleanup activities, and to help in evaluating the environmental impact.

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Griffiths, Jonathan, Liam Harrington-Missin, and Sarah Hall. "What makes a great oil spill forecast?" International Oil Spill Conference Proceedings 2017, no. 1 (May 1, 2017): 2017–190. http://dx.doi.org/10.7901/2169-3358-2017.1.2017-190.

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Abstract (ID2017-190)This paper identifies the key information that should be included in an operational oil spill forecast. It shows how modellers convert huge quantities of data into a readily accessible modelling forecast report that can be rapidly interpreted and incorporated into the incident action plan.Effective response strategies can minimise the potentially devastating consequences of an oil spill. To protect nearby socio-economic and ecological sensitivities a response strategy needs to be implemented quickly.Oil spill forecasts help predict the behaviour of oil that has been spilled into the marine environment. These predictions are highly useful when planning response strategies for the coming days. Key operational information derived from oil spill forecasts can be broken down into two main areas:1. Where is oil expected to travel?By knowing where oil is expected to travel, response organisations can decide which sensitivities need protection. Forecasts will show if oil is predicted to reach fisheries, shorelines and other important resources. This information can be used within a Net Environmental Benefit Analysis (NEBA) to decide which sensitivities to prioritise for protection.2. What is expected to happen to the physical properties of the spilled oil?Once oil enters the marine environment it is subjected to weathering processes such as spreading, evaporation and biodegradation. These processes change the chemical makeup of the oil which usually becomes more viscous and can form emulsion. Information obtained from modelling can help decision makers choose the correct response options and equipment to use during a spill. For example, if a modelling forecast shows oil is likely to become highly viscous responders will know heavy oil skimmers will be needed if offshore recovery is to take place.The information referred to above can be extracted from the vast amount of data that is created when an oil spill model is run. As Incident Managers need to make informed decisions quickly, it is essential that oil spill forecasts are presented in a clear and concise fashion. From experience, it is often this extra step of making the data easily accessible to the decision maker that is overlooked and is of most value in a response.This means that response modellers need to be trained, not only in the science of oil spill modelling, but also in the art of conveying complex information to a range of end users from oil spill experts to interested members of the public.

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Nordam, Tor, CJ Beegle-Krause, Jørgen Skancke, Raymond Nepstad, and Mark Reed. "Improving oil spill trajectory modelling in the Arctic." Marine Pollution Bulletin 140 (March 2019): 65–74. http://dx.doi.org/10.1016/j.marpolbul.2019.01.019.

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Turrell, W. R. "Modelling the Braer oil spill—A retrospective view." Marine Pollution Bulletin 28, no. 4 (April 1994): 211–18. http://dx.doi.org/10.1016/0025-326x(94)90096-5.

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Toz, Ali Cemal, Burak Koseoglu, and Cenk Sakar. "Numerical modelling of oil spill in New York Bay." Archives of Environmental Protection 42, no. 4 (December 1, 2016): 22–31. http://dx.doi.org/10.1515/aep-2016-0037.

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Abstract New York Bay is one of the most important transition regions of ships trading to east America. The region plays an important role in the commerce of the New York metropolitan area. The area is surrounded with the coasts that have various levels of environmental sensitivity. The area accommodates high diversity of native ecosystems and species that are rather vulnerable in case of oil spill. Thus getting well informed about the likelihood, or fate, of oil spills around this region is of great importance so that proactive measures can be taken. The purpose of this study is to investigate the oil spill and predict the future accidents likely to be encountered around the Bay of New York. Two trajectory models have been conducted for the study. ADIOS (Automated Data Inquiry for Oil Spills), has been conducted for natural degradation calculations, and, GNOME (General NOAA Operational Modeling Environment), has been conducted for surface spread simulation. The results gained through these efforts are hoped to be useful for many organizations dealing with oil spill response operations and contribute to an effective and efficient coordination among the relevant institutions.

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Kileso, Alexander, Boris Chubarenko, Petras Zemlys, and Igor Kuzmenko. "Oil spill modelling methods: application to the south–eastern part of the Baltic Sea." Baltica 27, special (February 20, 2014): 15–22. http://dx.doi.org/10.5200/baltica.2014.27.11.

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The state-of-art in oil spill modelling methods is summarized, focusing on development since 2000. Some recommendations for possible application of these methods to the south–eastern part of the Baltic Sea are prepared. Particular attention is paid on the methods of parameterization of volume of oil spill and calculation of advection of the oil spills. Consideration is also given to methods used in oil weathering models.

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Dissertations / Theses on the topic "Oil-spill modelling"

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Robbe, Nils [Verfasser]. "Airborne Oil Spill Remote Sensing: Modelling, Analysis and Fusion of Multi-spectral Data / Nils Robbe." Aachen : Shaker, 2005. http://d-nb.info/1186579773/34.

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Bruciaferri, Diego. "Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6757/.

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The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.

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Niu, Zhen Tao. "Valutazione delle conseguenze degli sversamenti accidentali di olio in mare." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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Oil spill is a leakage of a liquid petroleum hydrocarbon into the environment, especially into the marine ecosystem, due to human activity. Oceanic oil spills became a major environmental problem in the ‘60s, chiefly as a result of intensified petroleum exploration and production on continental shelves, of the use of supertankers capable of transporting more than 500,000 tonnes of oil, and of several accidents involving ships or oil rigs. Thousands of minor and several major oil spills related to well discharges and tanker operations are reported each year. As a consequence of a spill, crude oil and refined petroleum products may be released onto the surface of a large body of water. This can have disastrous consequences from the social, economical, and environmental point of view. This thesis focuses on evaluating the environmental consequences of accidental oil spills in the Mediterranean Sea through the use of the GNOME software. Releases of different types of oils, in various positions of the study area, in different meteorological conditions are taken into account. After Chapter 1, the introductory section, Chapter 2 is devoted to the processes of oil weathering. In Chapter 3, the software GNOME is introduced. In Chapter 4, some case studies are carried out and the significant factors that may influence the spill trajectory are examined, and then the results are discussed. Chapter 5 presents the conclusions.

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Goeury, Cédric. "Modélisation du transport des nappes d'hydrocarbures en zone continentale et estuarienne." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1131/document.

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L'application de la Directive Cadre sur l'Eau et l'obligation de surveillance de la qualité d'eau pour la consommation humaine et les activités récréatives ou industrielles, telles que la production d'eau potable, entraînent une forte demande pour des systèmes d'évaluation et de suivi de la qualité de l'eau. Le projet de recherche MIGR'HYCAR (http://www.migrhycar.com) a donc été mis en place pour répondre à un besoin opérationnel et à un défaut d'outils d'aide à la décision adaptés face aux déversements d'hydrocarbures en eaux continentales (rivières, lacs et estuaires) qui représente plus de 50% des déversements accidentels en France. Au cours du projet de recherche MIGR'HYCAR, un modèle mathématique de dérive de nappe d'hydrocarbures, composé d'un modèle lagrangien couplé à un modèle eulérien, a été développé dans la plate-forme hydro-informatique TELEMAC (http://www.opentelemac.org). Le modèle lagrangien décrit le mouvement de la nappe en surface en considérant celle-ci comme un ensemble de particules. Ainsi le modèle développé est capable de modéliser les principaux phénomènes agissant sur une nappe d'hydrocarbures une fois celle-ci déversée : convection, diffusion, échouage, re-largage, étalement, évaporation, dissolution et volatilisation. Bien que le phénomène de dissolution ne concerne qu'un très faible volume d'hydrocarbures, ce processus peut avoir des conséquences importantes du point de vue de la toxicité. Afin de suivre l'évolution du pétrole dissous, un modèle eulérien de suivi de traceurs a été adopté. La quantité de traceur dépend directement de la masse dissoute des particules lagrangiennes. Cette approche permet le suivi des hydrocarbures dissous dans la colonne d'eau. Des cinétiques effectuées en laboratoire ont pour but la calibration du modèle numérique. En complément de cas tests issus de la littérature et de cas réels, des résultats expérimentaux issus d'expérimentations effectuées en canal d'essai doivent permettre de vérifier et valider la qualité des simulations numériques sur des situations où les conditions ne sont que partiellement contrôlées
The application of the European Water Framework Directive on water quality for human consumption and industrial activities creates a need for water quality assessment and monitoring systems. The MIGR'HYCAR research project (http://www.migrhycar.com) was initiated to provide decisional tools for risks connected to oil spills in continental waters (rivers, lakes and estuaries), which represent more than 50% of accidental spills in France. Within the framework of this project, a new numerical oil spill model has been developed, as part of the Telemac hydro-informatics system (see: (http://www.opentelemac.org), by combining Lagrangian and Eulerian methods. The Lagrangian model describes the transport of an oil spill near the free surface. The oil spill model enables to simulate the main processes driving oil plumes: advection, diffusion, oil beaching, oil re-floating, evaporation, dissolution, spreading and volatilization. Though generally considered as a minor process, dissolution is important from the point of view of toxicity. To model dissolved oil in water, an Eulerian advection-diffusion model is used. The fraction of dissolved oil is represented by a passive tracer. This approach is able to follow dissolved hydrocarbons in the water column. Laboratory experiments were conducted to characterise the numerous kinetics of the processes listed above. In addition, meso-scale dynamic experiments in artificial channels and test cases derived from the literature are used to validate the numerical model

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Matsodoum, Nguemte Pulchérie. "Phytoremédiation des sols pollués par les hydrocarbures : inventaires floristiques, évaluation des performances des espèces végétales et modélisation du transfert sol-plante des HAP." Thesis, Strasbourg, 2019. http://www.theses.fr/2019STRAD015/document.

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Proposer l’adoption de la procédure de phytoremédiation des sites de déversement d’hydrocarbures au Cameroun nécessite des arguments scientifiques vérifiés. L’objectif principal de cette thèse est de (i) faire une étude floristique des sites de déversement anarchique de produits pétroliers au Cameroun, (ii) tester les potentialités de phytoremédiation de quelques espèces végétales sur des sols contaminés au fioul domestique, (iii) évaluer l’effet de différentes concentrations d’hydrocarbures sur la morpho-anatomie et la physiologie des plantes, (iv) modéliser le transfert sol-plante des HAP. Les prospections floristiques des sites de déversement d’hydrocarbures menées dans 4 villes du Cameroun ont permis d’identifier 106 espèces appartenant à 76 genres et 30 familles ; dont seules 15 espèces sont qualifiées de polluo-tolérantes. Les expérimentations ont permis de montrer que toutes les 3 espèces (C. dactylon, E. indica et A. sessilis) sont impliquées dans les processus de rhizodégradation des HCT et HAP ; E. indica and C. dactylon ayant favorisé une meilleure phytoextraction de quelques HAP comparé à A. sessilis. La modélisation mécaniste du transfert sol-plante des HAP a confirmé ces observations. La tolérance aux HAP est plus accrue chez E. indica et C. dactylon par rapport à A. sessilis. La culture mixte de E. indica et C. dactylon est très impactée par les HAP. En culture seule, le ralentissement des processus physiologiques de C. dactylon dans les sols pollués n’a pas d’impacts majeurs sur ses capacités phytoremédiatrices. Ceci permet donc de recommander C. dactylon pour la gestion durable des sols pollués par les hydrocarbures dans le monde entier en général, et au Cameroun en particulier ; pour des pollutions de sols n’excédant pas 33500 ppm
To propose the implementation of phytoremediation process to clean up oil spill sites in Cameroon requires verified scientific arguments. The main objective of this thesis is to (i) carry out a floristic study of anarchic oil spill sites in Cameroon, (ii) test the phytoremediation potential of some plant species in soils contaminated with fuel oil, (iii) evaluate the effect of different hydrocarbon concentrations on morpho-anatomy and plant physiology, (iv) modelling the soil-plant transfer of PAHs. Floristic surveys of oil spill sites carried out in 4 Cameroonian cities have identified 106 species belonging to 76 genera and 30 families; amoung which 15 species are qualified as polluo-tolerant. Experiments have shown that the (C. dactylon, E. indica and A. sessilis) are involved into rhizodegradation of TPHs and PAHs; E. indica and C. dactylon having promoted a better phytoextraction of some PAHs compared to A. sessilis. Mechanistic modelling of the soil-plant transfer of PAHs confirmed these observations. Tolerance to PAHs is higher for both E. indica and C. dactylon than A. sessilis. The mixed cropping of E. indica and C. dactylon is highly impacted by PAHs. Cropping alone, the slowing down of C. dactylon's physiological processes in polluted soils does not have a significant impact on its phytoremediation potentialities. This makes it possible to recommend C. dactylon in the sustainable management of hydrocarbon-polluted soils worldwide in general, and particularly in Cameroon; for soil pollution not exceeding 33500 ppm

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Books on the topic "Oil-spill modelling"

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Oza, R. B. Measurements and modelling of the oil spill of 4 August 2011 in Mumbai Harbour Bay. Mumbai: Scientific Information Resource Division, Bhabha Atomic Research Centre, 2013.

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Regional Workshop on Oil Spill Modelling (1996 Pusan, Korea). Oil spill modelling in the East Asian region with special reference to the Malacca Straits: Proceedings of the Regional Workshop on Oil Spill Modelling, 31 May to 3 June 1996, Pusan, Republic of Korea. Quezon City, Philippines: GEF/UNDP/IMO Regional Programme for the Prevention and Management of Marine Pollution in the East Asian Seas, 1997.

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Brebbia, C. A. Oil Spill Modelling and Processes. Computational Mechanics, Inc., 2001.

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A, Brebbia C., ed. Oil spill modelling and processes. Southampton: WIT, 2001.

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Oil spill modelling in the East Asian region with special reference to the Malacca Straits: Proceedings of the Regional Workshop on Oil Spill Modelling, 31 May to 3 June 1996, Pusan, Republic of Korea. Korea Ocean Research and Development Institute, 1997.

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Book chapters on the topic "Oil-spill modelling"

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Muttin, Frédéric. "Structural Analysis of Oil-Spill Booms." In Mathematical Modelling and Numerical Simulation of Oil Pollution Problems, 141–66. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16459-5_7.

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Józsa, J. "Subsurface Shear Dispersion in River Oil Spill Modelling." In Computational Methods in Water Resources X, 1157–64. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-010-9204-3_140.

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Stephansen, Cathrine, Anders Bjørgesæter, Odd Willy Brude, Ute Brönner, Tonje Waterloo Rogstad, Grethe Kjeilen-Eilertsen, Jean-Marie Libre, and Christian Collin-Hansen. "Introduction to the Concepts and Use of ERA Acute." In Assessing Environmental Risk of Oil Spills with ERA Acute, 1–19. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70176-5_1.

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AbstractIntroducing the main concepts of ERA Acute, this chapter describes the overall framework and purpose of the methodology. ERA Acute is a recently developed oil spill risk assessment (OSRA) methodology for quantification of oil spill impacts and risk (Environmental Risk Assessment, ERA). It covers four environmental compartments; sea surface (seabirds, turtles, marine mammals), water column (fish eggs/larvae), shoreline and seafloor (species and habitats) using continuous impact functions and introduces the Resource Damage Factor (RDF). The methodology depends on external oil spill modelling and input data related to the presence and vulnerability of Valued Ecosystem Components (VECs). ERA Acute is developed to provide an improvement over the currently used “MIRA” method on the Norwegian Continental Shelf (NCS) and is better suited for risk management, decision-making and analyses from screening studies to full environmental risk assessments.

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Benard, Laurencia Debbie, and Piakong Mohd Tuah. "Bioremediation of Petroleum Hydrocarbons in Seawater: Oil Spill Plume Modelling Approaches." In Microbial Action on Hydrocarbons, 35–62. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1840-5_3.

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Chandler, Peter C. P. "The Juxtaposition of Long-Term and Real-Time Oil Spill Modelling." In Chemical Spills and Emergency Management at Sea, 73–81. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-011-7790-0_6.

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Chandler, Peter C. P. "The Juxtaposition of Long-Term and Real-Time Oil Spill Modelling." In Chemical Spills and Emergency Management at Sea, 73–81. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-0887-1_6.

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Guo, Weijun, and Tiaojian Xu. "Application of a Numerical Statistical Model to Estimate Potential Oil Spill Risk." In Mathematical Modelling and Numerical Simulation of Oil Pollution Problems, 127–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16459-5_6.

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Hodges, Ben R., Alejandro Orfila, Juan M. Sayol, and Xianlong Hou. "Operational Oil Spill Modelling: From Science to Engineering Applications in the Presence of Uncertainty." In Mathematical Modelling and Numerical Simulation of Oil Pollution Problems, 99–126. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16459-5_5.

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Goni, Gustavo J., Joaquin A. Trinanes, Amy MacFadyen, Davida Streett, María Josefina Olascoaga, Marc L. Imhoff, Frank Muller-Karger, and Mitchell A. Roffer. "Variability of the Deepwater Horizon Surface Oil Spill Extent and Its Relationship to Varying Ocean Currents and Extreme Weather Conditions." In Mathematical Modelling and Numerical Simulation of Oil Pollution Problems, 1–22. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16459-5_1.

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Zodiatis, George, Robin Lardner, Katerina Spanoudaki, Sarantis Sofianos, Hari Radhakrishnan, Giovanni Coppini, Svitlana Liubartseva, et al. "Operational oil spill modelling assessments." In Marine Hydrocarbon Spill Assessments, 145–97. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-819354-9.00010-7.

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Conference papers on the topic "Oil-spill modelling"

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Sukhinov, Alexandr, Alexandr Chistyakov, Alla Nikitina, Alena Semenyakina, Iakov Korovin, and Gerald Schaefer. "Modelling of oil spill spread." In 2016 International Conference on Informatics, Electronics and Vision (ICIEV). IEEE, 2016. http://dx.doi.org/10.1109/iciev.2016.7760176.

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Michel, Cedric, Valerie Quiniou, and Xavier Vigan. "Metocean and oil spill modelling." In International Conference on Health, Safety and Environment in Oil and Gas Exploration and Production. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/156622-ms.

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Samudre, Rahul, Shubhada Khatri, Nilesh Sakpal, and Samarth Patwardhan. "Modelling of Critical Parameters of Oil Spill." In SPE Oil and Gas India Conference and Exhibition. Society of Petroleum Engineers, 2019. http://dx.doi.org/10.2118/194612-ms.

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Sherbina, Sergey A., Maria S. Kuyukina, Irena B. Ivshina, and Sergey O. Makarov. "Risk Assessment Program for Terrestrial Oil Spill Management in Russia." In Applied Simulation and Modelling. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.776-026.

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Yang, Lin, Yongqiang Chu, Peng Liu, Lixin Wei, and Dehui Guan. "Numerical Simulation of Spill Oil Diffusion in Offshore Oil Pipeline." In 2018 3rd International Conference on Modelling, Simulation and Applied Mathematics (MSAM 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/msam-18.2018.23.

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Muttin, F. "Oil spill boom modelling by the finite-element method." In WATER POLLUTION 2008. Southampton, UK: WIT Press, 2008. http://dx.doi.org/10.2495/wp080371.

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Nandakumar, Krishnaswamy, Abhijit Rao, and Kalliat T. Valsaraj. "Advanced Multiphase CFD Modelling to Understand Impact of Undersea Oil Spill." In Qatar Foundation Annual Research Conference Proceedings. Hamad bin Khalifa University Press (HBKU Press), 2016. http://dx.doi.org/10.5339/qfarc.2016.eesp2097.

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Bassey, B. O., T. O. Ajare, and A. P. Santoso. "Comparative Oil Spill Transport and Fate Modelling for an Indonesian Coastal Area." In Offshore Technology Conference Asia. Offshore Technology Conference, 2018. http://dx.doi.org/10.4043/28620-ms.

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Benito-Ortiz, Mari-Cortes, David Mata-Moya, Maria-Pilar Jarabo-Amores, Nerea del Rey-Maestre, and Pedro-Jose Gomez-del-Hoyo. "Generalized Gamma Distribution SAR Sea Clutter Modelling for Oil Spill Candidates Detection." In 2019 27th European Signal Processing Conference (EUSIPCO). IEEE, 2019. http://dx.doi.org/10.23919/eusipco.2019.8903047.

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Muttin, F., R. Campbell, A. Ouansafi, and Y. Benelmostafa. "Numerical modelling and experimentation of oil-spill curtain booms: Application to a harbor." In ICNPAA 2016 WORLD CONGRESS: 11th International Conference on Mathematical Problems in Engineering, Aerospace and Sciences. Author(s), 2017. http://dx.doi.org/10.1063/1.4972696.

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