scholarly journals An Accurate Cubic Law for the Upscaling of Discrete Natural Fractures

2021 ◽  
Author(s):  
Xupeng He ◽  
Marwa Alsinan ◽  
Hyung Kwak ◽  
Hussein Hoteit
Keyword(s):  
Hydraulic Properties ◽  
Reservoir Characterization ◽  
Flow Direction ◽  
Fractured Reservoirs ◽  
Computational Cost ◽  
Navier Stokes ◽  
Fracture Topography ◽  
Cubic Law ◽  
Proposed Model ◽  
Wide Range

Abstract Modeling fluid flow in fractured reservoirs requires an accurate evaluation of the hydraulic properties of discrete fractures. Full Navier-Stokes simulations provide an accurate approximation of the flow within fractures, including fracture upscaling. However, its excessive computational cost makes it impractical. The traditionally used cubic law (CL) is known to overshoot the fracture hydraulic properties significantly. In this work, we propose an alternative method based on the cubic law. We first develop geometric rules based on the fracture topography data, by which we subdivide the fracture into segments and local cells. We then modify the aperture field by incorporating the effects of flow direction, flow tortuosity, normal aperture, and local roughness. The approach is applicable for fractures in 2D and 3D spaces. This paper presented almost all existing CL-based models in the literature, which include more than twenty models. We benchmarked all these models, including our proposed model, for thousands of fracture cases. High-resolution simulations solving the full-physics Navier-Stokes (NS) equations were used to compute the reference solutions. We highlight the behavior of accuracy and limitations of all tested models as a function of fracture geometric characteristics, such as roughness. The obtained accuracy of the proposed model showed the highest for more than 2000 fracture cases with a wide range of tortuosity, roughness, and mechanical aperture variations. None of the existing methods in the literature provide this level of accuracy and applicability. The proposed model retains the simplicity and efficiency of the cubic law and can be easily implemented in workflows for reservoir characterization and modeling.

Rapid gust response simulation of large civil aircraft using computational fluid dynamics

2017 ◽  
Vol 121 (1246) ◽  
pp. 1795-1807 ◽  
Author(s):  
P. Bekemeyer ◽  
R. Thormann ◽  
S. Timme
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Stokes Equations ◽  
Lift Coefficient ◽  
Computational Cost ◽  
Aircraft Design ◽  
Navier Stokes ◽  
Surface Pressure Distribution ◽  
Wide Range ◽  
Civil Aircraft

ABSTRACTSeveral critical load cases during the aircraft design process result from atmospheric turbulence. Thus, rapidly performable and highly accurate dynamic response simulations are required to analyse a wide range of parameters. A method is proposed to predict dynamic loads on an elastically trimmed, large civil aircraft using computational fluid dynamics in conjunction with model reduction. A small-sized modal basis is computed by sampling the aerodynamic response at discrete frequencies and applying proper orthogonal decomposition. The linear operator of the Reynolds-averaged Navier-Stokes equations plus turbulence model is then projected onto the subspace spanned by this basis. The resulting reduced system is solved at an arbitrary number of frequencies to analyse responses to 1-cos gusts very efficiently. Lift coefficient and surface pressure distribution are compared with full-order, non-linear, unsteady time-marching simulations to verify the method. Overall, the reduced-order model predicts highly accurate global coefficients and surface loads at a fraction of the computational cost, which is an important step towards the aircraft loads process relying on computational fluid dynamics.

Saturated Hydraulic Conductivity of Scandinavian Tills

1990 ◽  
Vol 21 (2) ◽  
pp. 107-118 ◽  
Author(s):  
Bo B. Lind ◽  
Lars Lundin
Keyword(s):  
Grain Size ◽  
Hydraulic Conductivity ◽  
Hydraulic Properties ◽  
Flow Direction ◽  
Published Data ◽  
Soil Horizons ◽  
Wide Range ◽  
Mean Grain Size ◽  
Distinctive Difference ◽  
The Relationship

There is a distinctive difference in hydraulic properties between the upper horizons of Scandinavian till soil and the deeper C-horizon. The hydraulic conductivity has been studied in different soil profile types, mainly Podzolic variants. In the topsoil there are correlations from grain size and porosity to hydraulic conductivity. Both porosity and hydraulic conductivity are stratified with depth. Often high conductivity appears in the upper soil horizons decreasing with depth to low values at about one metre. This pattern varies with soil type. The soils vary with topographic location as does the groundwater level. Published data on hydraulic conductivity in the C-horizon of sandy-silty tills in Scandinavia covers a wide range, from about 5 × 10−9 m/s to 5 × 10−4 m/s, with a mean of 3 × 10−6 m/s. The correlation between porosity and hydraulic conductivity, as well as between mean grain size and hydraulic conductivity, is weak in the C-horizon. It is concluded that the sediment structure has a decisive influence on the hydraulic conductivity of till. A model of the relationship between fabric (in relation to water flow direction), the porosity in the poresize interval 30-95 μm and the hydraulic conductivity is presented.

scholarly journals A 2D vertical model for simulating surface and subsurface flows using finite element–finite volume methods

2019 ◽  
Vol 21 (5) ◽  
pp. 761-780
Author(s):  
Leila Farrokhpour ◽  
Masoud Montazeri Namin ◽  
Morteza Eskandari-Ghadi
Keyword(s):  
Stokes Equations ◽  
Time Discretization ◽  
Finite Volume Methods ◽  
Navier Stokes ◽  
Step Method ◽  
Fractional Step Method ◽  
Navier Stokes Equations ◽  
Proposed Model ◽  
Wide Range ◽  
Subsurface Flows

Abstract A numerical model is presented for simulation of hydrodynamics of a 2D vertical free surface domain consisting of an arbitrary partitioned porous and non-porous area. To this end, modified Navier–Stokes equations are considered which could be applied in surface water and in subsurface flows, simultaneously. A wide range of Reynolds number has been considered, from which non-Darcy effects have also been taken into account. A fractional step method has been used in the time discretization procedure, where the convection and diffusion terms are separated from the pressure term while solving the momentum equations. To include the variation of surface elevation in computation, the domain has been divided into two parts, namely, ‘interior subdomain’, which never gets dry during the simulation period, covered by fixed unstructured triangular grids and ‘top layer’ with only a one layer structured grid, the position of which varies with the water surface. The validation of the proposed model has been achieved by comparison of its results with both theoretical and experimental data reported in the literature.

scholarly journals Innovative analytical model for temperature prediction of front-end accessory drive

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xingchen Liu ◽  
Kamran Behdinan
Keyword(s):  
Heat Transfer ◽  
Computational Cost ◽  
Operating Conditions ◽  
Drive System ◽  
Belt Drive ◽  
Static State ◽  
Front End ◽  
Proposed Model ◽  
Wide Range ◽  
Analytical Thermal Model

AbstractThe front-end accessory drive belt drive system is a critical component in the vehicle engine. To avoid thermal deterioration under static state operating conditions, the thermal distribution for the belt drive system at each condition must be determined in an efficient manner. Due to the numerical approach is not feasible to address this concern because of its high computational cost, this paper proposes a reliable and efficient novel analytical thermal model to achieve this goal. This work develops the state-of-the-art heat transfer ordinary differential equations (ODEs) describing the thermal flow and heat dissipations on the complex structures of pulleys. Then it integrates these ODEs with heat transfer governing equations of the belt and heat exchanges to establish an innovative system of equations that can be solved within a few seconds to provide temperature plots. Moreover, experiments were conducted on a dynamometer to verify the accuracy of the proposed model under a wide range of conditions. The results indicate that the measured temperatures are in good agreement with the corresponding analytical results. Owing to its efficiency, the proposed model can be integrated with other mechanical characterizations of the belt drive system in terms of design, optimization, and thermal fatigue analyses.

Multiscale Mimetic Solvers for Efficient Streamline Simulation of Fractured Reservoirs

SPE Journal ◽  
2011 ◽  
Vol 16 (04) ◽  
pp. 880-888 ◽  
Author(s):  
J.R.. R. Natvig ◽  
B.. Skaflestad ◽  
F.. Bratvedt ◽  
K.. Bratvedt ◽  
K.-A.. -A. Lie ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Fractured Reservoirs ◽  
Computational Cost ◽  
Petroleum Reservoirs ◽  
Basis Functions ◽  
Flux Approximation ◽  
Complex Shapes ◽  
Scale Models ◽  
Volumetric Objects ◽  
Coarse Grids

Summary Advances in reservoir characterization and modeling have given the industry improved ability to build detailed geological models of petroleum reservoirs. These models are characterized by complex shapes and structures with discontinuous material properties that span many orders of magnitude. Models that represent fractures explicitly as volumetric objects pose a particular challenge to standard simulation technology with regard to accuracy and computational efficiency. We present a new simulation approach based on streamlines in combination with a new multiscale mimetic pressure solver with improved capabilities for complex fractured reservoirs. The multiscale solver approximates the flux as a linear combination of numerically computed basis functions defined over a coarsened simulation grid consisting of collections of cells from the geological model. Here, we use a mimetic multipoint-flux approximation to compute the multiscale-basis functions. This method has limited sensitivity to grid distortions. The multiscale technology is very robust with respect to fine-scale models containing geological objects such as fractures and fracture corridors. The methodology is very flexible in the choice of the coarse grids introduced to reduce the computational cost of each pressure solve. This can have a large impact on iterative modeling workflows.

LES for Turbines: Methodologies, Cost and Future Outlooks

2013 ◽  
Author(s):  
James Tyacke ◽  
Paul Tucker ◽  
Richard Jefferson-Loveday ◽  
Nagabhushana Rao Vadlamani ◽  
Robert Watson ◽  
...  
Keyword(s):  
Computational Cost ◽  
Quality Data ◽  
Navier Stokes ◽  
Real Surface ◽  
Internal Cooling ◽  
Design Environment ◽  
Roughness Effects ◽  
Eddy Simulation ◽  
Wide Range ◽  
Large Eddy

Flows throughout different zones of turbines have been investigated using Large Eddy Simulation (LES) and hybrid Reynolds-Averaged Navier-Stokes-LES (RANS-LES) methods and contrasted with RANS modelling, more typically used in the design environment. Cases studied include low and high-pressure turbine cascades, real surface roughness effects, internal cooling ducts, trailing edge cut-backs and labyrinth and rim seals. Evidence is presented that shows that LES and hybrid RANS-LES produces higher quality data than RANS/URANS for a wide range of flows. The higher level of physics that is resolved allows greater flow physics insight which is valuable for improving designs and refining lower order models. Turbine zones are categorised by flow type, to assist in choosing the appropriate eddy resolving method and to estimate computational cost.

Shape Optimization of Transonic Compressor Blades Using Quasi-3D Flow Physics

2000 ◽  
Author(s):  
June Chung ◽  
Ki D. Lee
Keyword(s):  
Design Method ◽  
Computational Cost ◽  
Three Dimensional ◽  
Operating Conditions ◽  
Rotor Blades ◽  
Navier Stokes ◽  
Compressor Blades ◽  
Transonic Compressor ◽  
Compressor Rotor ◽  
Wide Range

A design method for transonic compressor rotor blades is developed based on Navier-Stokes physics. The method is applied to optimize the blade sections at several span stations, and new three-dimensional blades are constructed by interpolating the geometry of the designed blade sections. The method is demonstrated with NASA Rotor 37, producing new rotor blades with improved adiabatic efficiency over a wide range of operating conditions. The results indicate that the developed design process can find improved designs at an affordable computational cost.

scholarly journals Numerical simulation and experimental validation of cavitating flow in a multi-hole diesel fuel injector

2021 ◽  
pp. 146808742199863
Author(s):  
Aishvarya Kumar ◽  
Ali Ghobadian ◽  
Jamshid Nouri
Keyword(s):  
Computational Cost ◽  
Cavitating Flow ◽  
Field Analysis ◽  
Navier Stokes ◽  
Fuel Injector ◽  
Fluid Behavior ◽  
Flow Field Analysis ◽  
Charged Couple Device ◽  
Biodiesel Fuels ◽  
High Level

This study assesses the predictive capability of the ZGB (Zwart-Gerber-Belamri) cavitation model with the RANS (Reynolds Averaged Navier-Stokes), the realizable k-epsilon turbulence model, and compressibility of gas/liquid models for cavitation simulation in a multi-hole fuel injector at different cavitation numbers (CN) for diesel and biodiesel fuels. The prediction results were assessed quantitatively by comparison of predicted velocity profiles with those of measured LDV (Laser Doppler Velocimetry) data. Subsequently, predictions were assessed qualitatively by visual comparison of the predicted void fraction with experimental CCD (Charged Couple Device) recorded images. Both comparisons showed that the model could predict fluid behavior in such a condition with a high level of confidence. Additionally, flow field analysis of numerical results showed the formation of vortices in the injector sac volume. The analysis showed two main types of vortex structures formed. The first kind appeared connecting two adjacent holes and is known as “hole-to-hole” connecting vortices. The second type structure appeared as double “counter-rotating” vortices emerging from the needle wall and entering the injector hole facing it. The use of RANS proved to save significant computational cost and time in predicting the cavitating flow with good accuracy.

scholarly journals Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 930
Author(s):  
Fahimeh Hadavimoghaddam ◽  
Mehdi Ostadhassan ◽  
Ehsan Heidaryan ◽  
Mohammad Ali Sadri ◽  
Inna Chapanova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Viscosity Data ◽  
Oil Viscosity ◽  
Pvt Data ◽  
Proposed Model ◽  
Wide Range ◽  
Engineering Problems ◽  
Functional Forms ◽  
Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

scholarly journals Remote Sensing Image Stripe Detecting and Destriping Using the Joint Sparsity Constraint with Iterative Support Detection

2019 ◽  
Vol 11 (6) ◽  
pp. 608 ◽  
Author(s):  
Yun-Jia Sun ◽  
Ting-Zhu Huang ◽  
Tian-Hui Ma ◽  
Yong Chen
Keyword(s):  
Remote Sensing ◽  
Real Data ◽  
Total Variation Regularization ◽  
Joint Sparsity ◽  
Alternating Direction ◽  
Proposed Model ◽  
Comparison Results ◽  
Wide Range ◽  
Image Edges ◽  
Full Consideration

Remote sensing images have been applied to a wide range of fields, but they are often degraded by various types of stripes, which affect the image visual quality and limit the subsequent processing tasks. Most existing destriping methods fail to exploit the stripe properties adequately, leading to suboptimal performance. Based on a full consideration of the stripe properties, we propose a new destriping model to achieve stripe detection and stripe removal simultaneously. In this model, we adopt the unidirectional total variation regularization to depict the directional property of stripes and the weighted ℓ 2 , 1 -norm regularization to depict the joint sparsity of stripes. Then, we combine the alternating direction method of multipliers and iterative support detection to solve the proposed model effectively. Comparison results on simulated and real data suggest that the proposed method can remove and detect stripes effectively while preserving image edges and details.

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