Summary:
In January 2016, Dr. Charles Meneveau at Johns Hopkins University was awarded an RFP-V grant of $877,162 to lead the GoMRI project entitled, Transport and fate of oil in the upper ocean: Studying and modeling multi-scale physical dispersion mechanisms and remediation strategies using Large Eddy Simulation which consisted of 2 collaborative institutions and approximately 8 research team members (including students). In the aftermaths of deep water blowouts, oil plumes rise through and interact with various layers of the ocean and arrive in the upper ocean. There, several physical dispersion mechanisms such as turbulence, Langmuir circulations and sub-mesoscale eddies affect their evolution. Numerical modeling of these processes is playing an increasingly important role for estimating total oil spill volume and rate of biodegradation, planning for dispersant injection, and predictions/postdictions in general.
Existing mesoscale ocean transport models neglect processes that have been shown to be crucial in determining the transport direction, shape, and the overall size of oil plumes. Oil plumes consisting mostly of large droplets that stay predominantly at the surface move faster and in a different direction from plumes of mostly small droplets that are vertically better mixed within the ocean mixed layer subjected to Langmuir circulations. Chemical dispersants are known to strongly affect droplet diameter, drastically reducing it. Thus, dispersants may be used not only to affect the plume composition and susceptibility to be biodegraded, but also its transport direction, size and surface signature. To better quantify and understand such effects, a high-fidelity multiscale simulation framework must be developed that covers the relevant length and time scales and particular needs of modeling polydisperse oil droplet dispersion in the ocean. In this project the team developed and applied an enhanced Large Eddy Simulation (LES) framework for prediction of multiscale physical dispersion mechanisms and effectiveness of remediation strategies.
The proposed research activities have four main goals: (i) develop a transport model for evolution of entire distributions of oil droplet sizes in LES and effects of dispersants on the size distribution. To address this goal, a multi-species LES framework is developed to model droplet population dynamics (droplets of various sizes), and their interactions with surfactants. Another goal is to (ii) develop the Extended Nonperiodic Domain LES for Scalar Transport (ENDLESS) methodology that enables simulating plumes extending over physical scales that greatly exceed the size of the computational LES domain and thus couples the transport with outputs from larger (meso or sub-meso) scale regional ocean models. (iii) By means of a series of simulations, explore effects of dispersants on plume evolution for both underwater and surface application of oil dispersants, with various overall dosage, release rates and locations, under various wind and wave conditions. (iv) Results can be used to develop engineering tools for rapid real- time assessment and parameterizations for regional scale ocean models.
This 3-year project addresses GoMRI's Research Theme No. 1, dealing with physical distribution, dispersion, and dilution of petroleum under the action of physical oceanographic processes and air-sea interactions. By applying state-of-the-art enhanced
LES tools to the field of oil-spill modeling, fundamental new insights are developed in a research area with direct applications to the challenges confronting the Gulf of Mexico region and the energy industry.
Research Highlights
As of December 31, 2019, this project’s research resulted in 10 peer-reviewed publications and 28 scientific presentations and 11 datasets being submitted to the GoMRI Information and Data Cooperative (GRIIDC), which are/will be made available to the public. The project also engaged 5 PhD students over its award period. Significant outcomes of this project’s research according to GoMRI Research Theme are highlighted below. They all belong to Theme One.
An important outcome from the project has been the development of a new transport model to capture the size distribution evolution of oil drops in turbulent jets with cross flow. Knowledge of the dispersed phase size distribution and its evolution is critical to predicting important macroscopic features of plumes resulting from deep water blowouts. We develop a large eddy simulation (LES) model that can predict the turbulent transport and evolution of size distributions, for applications such as oil jets in which the dispersed phase can be assumed to consist of spherical droplets, and occurring at low volume fraction. We use a population dynamics model for polydisperse droplet distributions specifically adapted to a LES framework including a model for droplet breakup due to turbulence, neglecting coalescence consistent with the assumed small dispersed phase volume fractions. We model the number density fields using an Eulerian approach for each bin of the discretized droplet size distribution. The droplet breakup due to turbulent fluctuations is modelled by treating droplet–eddy collisions as in kinetic theory of gases. We applied the model for LES of a jet in cross-flow with large oil droplets of a single size being released at the source of the jet. We modeled the concentration fields using 15 bins of discrete droplet sizes and solved scalar transport equations for each bin. The resulting droplet size distributions were compared with published experimental data, and good agreement for the relative size distribution was obtained. The LES results also enable us to quantify size distribution variability. We find that the probability distribution functions of key quantities such as the total surface area and the Sauter mean diameter of oil droplets are highly variable, some displaying strong non-Gaussian intermittent behaviour. Results show that turbulent eddy-resolving numerical simulations can be deployed in conjunction with population balance models, that in the past were only used for ensemble averaged formulations.
Another major outcome has been the development of a new multi-scale modeling approach (called ENDLESS) to simulate oil plumes in the upper ocean using highly resolved numerical simulations of turbulence. The model includes the effects of wind drift, small-scale turbulence, Langmuir cells, and sub-mesoscale eddies. ENDLESS coupled with sub-mesoscale motions can be applied to follow plumes of oil droplets over very large areas of the ocean in which the turbulent flow features are solved only over much smaller extensions and simply replicated periodically.
Another significant result has been the development of a new turbulence velocity scale for predicting the fate of buoyant materials in the Oceanic Mixed Layer (OML).
The flow of the ocean near the surface is influenced by many different natural phenomena. The three most important are waves, wind, and the cooling of seawater.
These influences make the ocean behave in very distinct ways, which is a challenge for investigators trying to understand and predict the fate of pollutants that may happen to be dispersed in the water (e.g., oil or plastic). In practice this means that it is difficult for investigators to know, for example, whether oil will form a slick at the surface or be mixed downward into the water column, or where the oil will be transported. We present a framework that is general enough to be valid over a wide range of conditions that are naturally found in ocean. With this framework it is possible to make predictions that hold over a more realistic general range of situations without the need for large computer simulations. We demonstrate its applicability by making hypothetical predictions for the transport and mixing of oil and comparing them with computer models of the same conditions, as well as applying it to data measured in the Gulf of Mexico.
Furthermore, we have elucidated mechanisms for preferential concentration of non-inertial buoyant particles in the ocean mixed layer under free convection. We investigated buoyant particle dynamics in the ocean mixed layer (OML) under a purely convective regime, focusing on non-inertial particles that are lighter than the surrounding seawater (thus, buoyant), which is a useful configuration when representing oil, microplastic debris, and other buoyant materials that do not necessarily exhibit strong inertial effects. Our main goal was to understand and describe the physical mechanisms that control the buoyant particles’ surface concentration under such conditions, specifically the preferential concentration effects that arise independently of inertia (rather than the well-known centrifuging mechanism for heavy particles). Using LES, we find that in addition to the preferential concentration effect that clusters particles into convergence regions on the surface (which is a well-known and straightforward effect on free surfaces), there is a secondary effect for highly buoyant particles that drives them into vorticity-dominated regions. We explain this effect as the advection of buoyant particles by persistent vortices in the flow, which turns out to be the dominating mechanism controlling the surface particle distribution. Highly buoyant particles are trapped in the interior of the vortices (at the surface), which favors clustering in vorticity- dominated regions, while for particles with low buoyancy this effect is negligible.
Another highlight concerns the development of tools to model gas bubble dissolution in LES of hydrocarbon plumes from deep-sea blowouts. Hydrocarbon plumes released from deep-sea wellhead blowouts are typically formed by a mixture of gas bubbles and oil droplets. For the dynamics of the nearfield plume, the buoyant gas bubbles play a critical role by driving the plume to rise. When rising towards higher elevation, two processes occur simultaneously and induce opposite effects on bubble buoyancy: (i) the bubbles expand while rising due to the decrease of hydrostatic pressure;
(ii) a considerable amount of natural gas in the bubbles is dissolved into seawater, which significantly reduces the bubble buoyancy. The combined effect of these two processes together with the seawater stratification eventually determines the characteristics of the plume dynamics. By simultaneously simulating the evolutions of the bubble mass concentration function and the number density function, the average bubble size in each LES computational cell can be calculated locally. Based on this information, the local gas dissolution rate and bubble rise velocity are computed, which are then used in the gas transport equations. This fast Eulerian LES model can capture the effect of gas bubble dissolution on the macroscopic plume characteristics with reasonable computational cost.
Proposal Abstract - RFP-V PI Charles Meneveau
Project Research Overview (2016):
An overview of the proposed research activities from the GoMRI 2016 Meeting in Tampa.
Direct link to the Research Overview presentation.