scholarly journals A Near–Far-Field Model for Bubbles Influenced by External Electrical Fields

2019 ◽  
Vol 9 (21) ◽  
pp. 4722
Author(s):  
Juergen Geiser ◽  
Paul Mertin

In this paper, we present a model that is based on near–far-field charged bubble formation and transportation in an underlying dielectric liquid. The bubbles are controlled by the dielectric liquid, which is influenced by an external electrical field. This allows us to control the shape and volume of the bubbles in the dielectric liquid, such as water. These simulations are important to close the gap between the formation of charged bubbles, which is a fine-scale model and their transport in the underlying liquid, which is a coarse-scale model. In the fine-scale model, the formation of the bubbles and their influence of the electric-stress is approached by a near-field model, which is done by the Young–Laplace equation plus additional force-terms. In the coarse-scale model, the transport of the bubbles is approached by a far-field model, which is done with a convection-diffusion equation. The models are coupled with a bubble in cell scheme, which interpolates between the fine and coarse scales of the different models. Such a scale-dependent approach allows us to apply optimal numerical solvers for the different fine and coarse time and space scales and help to foresee the fluctuations of the charged bubbles in the E-field. We discuss the modeling approaches, numerical solver methods and we present the numerical results for the near–far-field bubble formation and transport model in a dielectric carrier fluid.

1998 ◽  
Vol 38 (10) ◽  
pp. 323-330
Author(s):  
Philip J. W. Roberts

The results of far field modeling of the wastefield formed by the Sand Island, Honolulu, ocean outfall are presented. A far field model, FRFIELD, was coupled to a near field model, NRFIELD. The input data for the models were long time series of oceanographic observations over the whole water column including currents measured by Acoustic Doppler Current Profilers and density stratification measured by thermistor strings. Thousands of simulations were made to predict the statistical variation of wastefield properties around the diffuser. It was shown that the visitation frequency of the wastefield decreases rapidly with distance from the diffuser. The spatial variation of minimum and harmonic average dilutions was also predicted. Average dilution increases rapidly with distance. It is concluded that any impact of the discharge will be confined to a relatively small area around the diffuser and beach impacts are not likely to be significant.


2021 ◽  
pp. 108325
Author(s):  
Darpan Das ◽  
Emma Moynihan ◽  
Mark Nicas ◽  
Eric D. McCollum ◽  
Salahuddin Ahmed ◽  
...  

1996 ◽  
Vol 465 ◽  
Author(s):  
B. Gylling ◽  
L. Romero ◽  
L. Moreno ◽  
I. Neretnieks

ABSTRACTA coupled model concept which may be used for performance assessment of a nuclear repository is presented. The tool is developed by integration of two models, one near field and one far field model. A compartment model, NUCTRAN, is used to calculate the near field release from a damaged canister. The far field transport through fractured rock is simulated by using CHAN3D, based on a three-dimensional stochastic channel network concept. The near field release depends on the local hydraulic properties of the far field. The transport in the far field in turn depends on where the damaged canister(s) is located. The very large heterogeneities in the rock mass makes it necessary to study both the near field release properties and the location of release at the same time. In order to demonstrate the capabilities of the coupled model concept it is applied on a hypothetical repository located at the Hard Rock Laboratory in Äspö, Sweden. Two main items were studied; the location of a damaged canister in relation to fracture zones and the barrier function of the host rock. In the study of the near field rock as a transport barrier the effect of different tunnel excavation methods which may influence the damage level of the rock around the tunnel was addressed.


2005 ◽  
Vol 2005 (1) ◽  
pp. 725-730
Author(s):  
Zhen-Gang Ji ◽  
Walter R. Johnson ◽  
Charles F. Marshall ◽  
James M. Price

ABSTRACT As a Federal agency within the U.S. Department of the Interior (DOI), the Minerals Management Service (MMS) maintains a leasing program for commercial oil and gas development on the U.S. Outer Continental Shelf (OCS). Oil and gas activities in deep water (areas deeper than 340 meters) have proceeded at an unprecedented rate, and have led to concerns regarding the accidental release of oil near the seafloor. As production increases, the potential for an oil/gas spill increases. In addition to the environmental impacts of the oil spilled, major concerns from a deepwater oil/gas spill include fire, toxic hazard to the people working on the surface installations, and loss of buoyancy by ships and any floating installations. Oil and natural gas releases in deep water behave much differently than in shallow water, primarily due to density stratification, high pressures, and low temperatures. It is important to know whether oil will surface and if so, where, when, and how thick the oil slick will be. To meet these new challenges, spill response plans need to be upgraded. An important component of such a plan would be a model to simulate the behavior of oil and gasses accidentally released in deep water. This has significant implications for environmental impact assessment, oil-spill cleanup, contingency planning, and source tracing. The MMS uses the Clarkson Deepwater Oil and Gas Blowout (CDOG) plume model to simulate the behavior of oil and gas accidentally released in deepwater areas. The CDOG model is a near field model. In addition, MMS uses an adaptation of the Princeton Ocean Model called the Princeton Regional Ocean Forecast and Hindcast System for the Gulf of Mexico (PROFS-GOM). This model is a far field model and is employed to provide three dimensional current, temperature, and salinity data to the CDOG model. The PROFS-GOM model and the CDOG model are used to simulate deepwater oil spills in the Gulf of Mexico. Modeling results indicate that the two models can provide important information on the behavior of oil spills in deepwater and assist MMS in estimating the associated environmental risks. Ultimately, this information will be used in the pertinent environmental impact assessments MMS performs and in the development of deepwater oil-spill response plans.


2016 ◽  
Vol 9 (3) ◽  
pp. 1111-1123 ◽  
Author(s):  
Hyun Cheol Kim ◽  
Pius Lee ◽  
Laura Judd ◽  
Li Pan ◽  
Barry Lefer

Abstract. Nitrogen dioxide vertical column density (NO2 VCD) measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measurement has been used as a proxy for surface nitrogen oxide (NOx) emission, especially for anthropogenic urban emission, so accurate comparison of satellite and modeled NO2 VCD is important in determining the future direction of NOx emission policy. The NASA Ozone Monitoring Instrument (OMI) NO2 VCD measurements, retrieved by the Royal Netherlands Meteorological Institute (KNMI), are compared with a 12 km Community Multi-scale Air Quality (CMAQ) simulation from the National Oceanic and Atmospheric Administration. We found that the OMI footprint-pixel sizes are too coarse to resolve urban NO2 plumes, resulting in a possible underestimation in the urban core and overestimation outside. In order to quantify this effect of resolution geometry, we have made two estimates. First, we constructed pseudo-OMI data using fine-scale outputs of the model simulation. Assuming the fine-scale model output is a true measurement, we then collected real OMI footprint coverages and performed conservative spatial regridding to generate a set of fake OMI pixels out of fine-scale model outputs. When compared to the original data, the pseudo-OMI data clearly showed smoothed signals over urban locations, resulting in roughly 20–30 % underestimation over major cities. Second, we further conducted conservative downscaling of OMI NO2 VCDs using spatial information from the fine-scale model to adjust the spatial distribution, and also applied averaging kernel (AK) information to adjust the vertical structure. Four-way comparisons were conducted between OMI with and without downscaling and CMAQ with and without AK information. Results show that OMI and CMAQ NO2 VCDs show the best agreement when both downscaling and AK methods are applied, with the correlation coefficient R = 0.89. This study suggests that satellite footprint sizes might have a considerable effect on the measurement of fine-scale urban NO2 plumes. The impact of satellite footprint resolution should be considered when using satellite observations in emission policy making, and the new downscaling approach can provide a reference uncertainty for the use of satellite NO2 measurements over most cities.


2010 ◽  
Vol 13 (03) ◽  
pp. 473-484 ◽  
Author(s):  
Seyyed Abolfazl Hosseini ◽  
Mohan Kelkar

Summary A geocellular model contains millions of gridblocks and needs to be upscaled before the model can be used as an input for flow simulation. Available techniques for upgridding vary from simple methods such as proportional fractioning to more complicated methods such as maintaining heterogeneities through variance calculations. All these methods are independent of the flow process for which simulation is going to be used, and are independent of well configuration. We propose a new upgridding method that preserves the pressure profile at the upscaled level. It is well established that the more complex the flow process, the more detailed the level of heterogeneity needed in the simulation model. In general, ideal upscaling is the process that preserves the "pressure profile" from the fine-scale model under the applicable flow process. In our method, we upgrid the geological model using simple flow equations in porous media. However, it should be remembered that to obtain a better match between fine scale and coarse scale, we also need to use appropriate upscaling of the reservoir properties. The new method is currently developed for single-phase flow; however, we used it for both single-phase and two-phase flows for 2D and 3D cases. The method differs fundamentally from the other methods that try to preserve heterogeneities. In those methods, gridblocks are combined that have similar velocities (or other properties) by assuming constant pressure drop across the blocks. Instead, we combine the gridblocks that have similar pressure profiles, although to release some of our assumptions such as having constant velocities in gridblocks, we balance our equation with the K2 term. The procedure is analytical and, hence, very efficient, but preserves the pressure profile in the reservoir. The gridblocks (or layers) are combined in a way so that the difference between fine- and coarse-scale pressure profiles is minimized. In addition, we also propose two new criteria that allow us to choose the optimum number of layers more accurately so that a critical level of heterogeneity is preserved. These criteria provide insight into the overall level of heterogeneity in the reservoir and the effectiveness of the layering design. We compare the results of our method with proportional layering and the King et al. method (King et al. 2006) and show that, for the same number of layers, the proposed method captures the results of the fine-scale model better. We show that the layer merging not only depends on the variation in the permeability between the gridblocks (K2 term), but also on the relative magnitude of the permeability values by combining 1/K2 and K2 terms.


SPE Journal ◽  
2006 ◽  
Vol 11 (03) ◽  
pp. 304-316 ◽  
Author(s):  
Arild Lohne ◽  
George A. Virnovsky ◽  
Louis J. Durlofsky

Summary In the coarse-scale simulation of heterogeneous reservoirs, effective or upscaled flow functions (e.g., oil and water relative permeability and capillary pressure) can be used to represent heterogeneities at subgrid scales. The effective relative permeability is typically upscaled along with absolute permeability from a geocellular model. However, if no subgeocellular-scale information is included, the potentially important effects of smaller-scale heterogeneities (on the centimeter to meter scale) in both capillarity and absolute permeability will not be captured by this approach. In this paper, we present a two-stage upscaling procedure for two-phase flow. In the first stage, we upscale from the core (fine) scale to the geocellular (intermediate) scale, while in the second stage we upscale from the geocellular scale to the simulation (coarse) scale. The computational procedure includes numerical solution of the finite-difference equations describing steady-state flow over the local region to be upscaled, using either constant pressure or periodic boundary conditions. In contrast to most of the earlier investigations in this area, we first apply an iterative rate-dependent upscaling (iteration ensures that the properties are computed at the appropriate pressure gradient) rather than assume viscous or capillary dominance and, second, assess the accuracy of the two-stage upscaling procedure through comparison of flow results for the coarsened models against those of the finest-scale model. The two-stage method is applied to synthetic 2D reservoir models with strong variation in capillarity on the fine scale. Accurate reproduction of the fine-grid solutions (simulated on 500'500 grids) is achieved on coarse grids of 10'10 for different flow scenarios. It is shown that, although capillary forces are important on the fine scale, the assumption of capillary dominance in the first stage of upscaling is not always appropriate, and that the computation of rate-dependent effective properties in the upscaling can significantly improve the accuracy of the coarse-scale model. The assumption of viscous dominance in the second upscaling stage is found to be appropriate in all of the cases considered. Introduction Because of computational costs, field-simulation models may have very coarse cells with sizes up to 100 to 200 m in horizontal directions. The cells are typically populated with effective properties (porosity, absolute permeability, relative permeabilities, and capillary pressure) upscaled from a geocellular (or geostatistical) model. In this way, the effects of heterogeneity on the geocellular scale will be included in the large-scale flow calculations. The cell sizes in geocellular models may be on the order of 20 to 50 m in horizontal directions. However, heterogeneities on much smaller scales (cm- to m- scale) may have a significant influence on the reservoir flow (Coll et al. 2001; Honarpour et al. 1994), and this potential effect cannot be captured if the upscaling starts at the geocellular scale.


2011 ◽  
Vol 8 (3) ◽  
pp. 6031-6067
Author(s):  
H. Vernieuwe ◽  
B. De Baets ◽  
J. Minet ◽  
V. R. N. Pauwels ◽  
S. Lambot ◽  
...  

Abstract. In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data can be cursed with epistemic uncertainty. Hence, a method is needed that not only integrates the external data into the model, but that also takes into account the difference in scale and the uncertainty of the observations. In this paper, a synthetic hydrological modelling scenario is set up in which a high-resolution distributed hydrological model is run over an agricultural field. At regular time steps, coarse-scale field-averaged soil moisture data, described by means of possibility distributions (epistemic uncertainty), are retrieved by synthetic aperture radar and assimilated into the model. A method is presented that allows to integrate the coarse-scale possibility distribution of soil moisture content data with the fine-scale model-based soil moisture data. To this end, a scaling relationship between field-averaged soil moisture content data and its corresponding standard deviation is employed.


2013 ◽  
Vol 67 (10) ◽  
pp. 2210-2220 ◽  
Author(s):  
Robin Morelissen ◽  
Theo van der Kaaij ◽  
Tobias Bleninger

In many cases, (processed) wastewater or thermal effluents are discharged into the marine environment, rivers or lakes. To accurately determine the dispersion, recirculation and environmental impacts of outfall plumes, it is important to be able to model the different characteristics of the outfall plume in detail – from the near field (metres around the outfall) to the far field (up to kilometres away). The solution for engineering practice is to combine different types of models (near and far field models) that each focus on specific scales, with corresponding optimised resolutions and processes. However, to adequately describe the hydrodynamic processes on these different scales, it is essential to couple these models in a dynamic and comprehensive way. To achieve this, a dynamic coupling between the open-source Delft3D-FLOW far field model and the CORMIX near field expert system is proposed. This coupled modelling system is able to use the computed far field ambient conditions in the near field computations and, conversely, to use the initial near field dilution and mixing behaviour in the far field model. Preliminary results are presented to provide a first indication of the potential of the method for modelling the complete trajectory of effluent outfall plumes, allowing an accurate assessment of the environmental effects and the design of possible mitigating measures.


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