Modified shape factor incorporating gravity effects for scaling countercurrent imbibition

AbstractCarbon-neutral oil production is one way to improve the sustainability of petroleum resources. The emissions from produced hydrocarbons can be offset by injecting capture CO$$_{2}$$ 2 from a nearby point source into a saline aquifer for storage or a producing oil reservoir. The latter is referred to as enhanced oil recovery (EOR) and would enhance the economic viability of CO$$_{2}$$ 2 sequestration. The injected CO$$_{2}$$ 2 will interact with the oil and cause it to flow more freely within the reservoir. Consequently, the overall recovery of oil from the reservoir will increase. This enhanced oil recovery (EOR) technique is perceived as the most cost-effective method for disposing captured CO$$_{2}$$ 2 emissions and has been performed for many decades with the focus on oil recovery. The interaction between existing oil and injected CO$$_{2}$$ 2 needs to be fully understood to effectively manage CO$$_{2}$$ 2 migration and storage efficiency. When CO$$_{2}$$ 2 and oil mix in a fully miscible setting, the density can change non-linearly and cause density instabilities. These instabilities involve complex convective-diffusive processes, which are hard to model and simulate. The interactions occur at the sub-centimeter scale, and it is important to understand its implications for the field scale migration of CO$$_{2}$$ 2 and oil. In this work, we simulate gravity effects, namely gravity override and convective mixing, during miscible displacement of CO$$_{2}$$ 2 and oil. The flow behavior due to the competition between viscous and gravity effects is complex, and can only be accurately simulated with a very fine grid. We demonstrate that convection occurs rapidly, and has a strong effect on breakthrough of CO$$_{2}$$ 2 at the outlet. This work for the first time quantifies these effects for a simple system under realistic conditions.

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A cross-species neural integration of gravity for motor optimization

Science Advances ◽

10.1126/sciadv.abf7800 ◽

2021 ◽

Vol 7 (15) ◽

pp. eabf7800

Author(s):

Jeremie Gaveau ◽

Sidney Grospretre ◽

Bastien Berret ◽

Dora E. Angelaki ◽

Charalambos Papaxanthis

Keyword(s):

Optimization Strategy ◽

Motor Patterns ◽

Activation Patterns ◽

Single Degree Of Freedom ◽

Single Degree ◽

Neural Integration ◽

Gravity Effects ◽

Neural Signature ◽

Experimental Findings ◽

Muscular Activation

Recent kinematic results, combined with model simulations, have provided support for the hypothesis that the human brain shapes motor patterns that use gravity effects to minimize muscle effort. Because many different muscular activation patterns can give rise to the same trajectory, here, we specifically investigate gravity-related movement properties by analyzing muscular activation patterns during single-degree-of-freedom arm movements in various directions. Using a well-known decomposition method of tonic and phasic electromyographic activities, we demonstrate that phasic electromyograms (EMGs) present systematic negative phases. This negativity reveals the optimal motor plan’s neural signature, where the motor system harvests the mechanical effects of gravity to accelerate downward and decelerate upward movements, thereby saving muscle effort. We compare experimental findings in humans to monkeys, generalizing the Effort-optimization strategy across species.

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Correction to: thermal conductivity of porous sintered metal powder and the Langmuir shape factor

Heat and Mass Transfer ◽

10.1007/s00231-021-03064-3 ◽

2021 ◽

Author(s):

Osama M. Ibrahim ◽

Ahmed H. Al-Saiafi ◽

Sorour Alotaibi

Keyword(s):

Thermal Conductivity ◽

Metal Powder ◽

Shape Factor ◽

Sintered Metal

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Optimising the Complex Refractive Index Model for Estimating the Permittivity of Heterogeneous Concrete Models

Remote Sensing ◽

10.3390/rs13040723 ◽

2021 ◽

Vol 13 (4) ◽

pp. 723

Author(s):

Hossain Zadhoush ◽

Antonios Giannopoulos ◽

Iraklis Giannakis

Keyword(s):

Refractive Index ◽

Shape Factor ◽

Complex Refractive Index ◽

Fdtd Method ◽

Air Voids ◽

Water Fraction ◽

Index Model ◽

General Complex ◽

Ground Penetrating ◽

Fine Tune

Estimating the permittivity of heterogeneous mixtures based on the permittivity of their components is of high importance with many applications in ground penetrating radar (GPR) and in electrodynamics-based sensing in general. Complex Refractive Index Model (CRIM) is the most mainstream approach for estimating the bulk permittivity of heterogeneous materials and has been widely applied for GPR applications. The popularity of CRIM is primarily based on its simplicity while its accuracy has never been rigorously tested. In the current study, an optimised shape factor is derived that is fine-tuned for modelling the dielectric properties of concrete. The bulk permittivity of concrete is expressed with respect to its components i.e., aggregate particles, cement particles, air-voids and volumetric water fraction. Different combinations of the above materials are accurately modelled using the Finite-Difference Time-Domain (FDTD) method. The numerically estimated bulk permittivity is then used to fine-tune the shape factor of the CRIM model. Then, using laboratory measurements it is shown that the revised CRIM model over-performs the default shape factor and provides with more accurate estimations of the bulk permittivity of concrete.

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Significance of Shape Factor in Heat Transfer Performance of Molybdenum-Disulfide Nanofluid in Multiple Flow Situations; A Comparative Fractional Study

Molecules ◽

10.3390/molecules26123711 ◽

2021 ◽

Vol 26 (12) ◽

pp. 3711

Author(s):

Asifa ◽

Talha Anwar ◽

Poom Kumam ◽

Zahir Shah ◽

Kanokwan Sitthithakerngkiet

Keyword(s):

Heat Transfer ◽

Skin Friction ◽

Molybdenum Disulfide ◽

Heat Transfer Rate ◽

Shape Factor ◽

Transfer Rate ◽

Maximum Heat ◽

Left Wall ◽

Maximum Heat Transfer ◽

Mos2 Nanoparticles

In this modern era, nanofluids are considered one of the advanced kinds of heat transferring fluids due to their enhanced thermal features. The present study is conducted to investigate that how the suspension of molybdenum-disulfide (MoS2) nanoparticles boosts the thermal performance of a Casson-type fluid. Sodium alginate (NaAlg) based nanofluid is contained inside a vertical channel of width d and it exhibits a flow due to the movement of the left wall. The walls are nested in a permeable medium, and a uniform magnetic field and radiation flux are also involved in determining flow patterns and thermal behavior of the nanofluid. Depending on velocity boundary conditions, the flow phenomenon is examined for three different situations. To evaluate the influence of shape factor, MoS2 nanoparticles of blade, cylinder, platelet, and brick shapes are considered. The mathematical modeling is performed in the form of non-integer order operators, and a double fractional analysis is carried out by separately solving Caputo-Fabrizio and Atangana-Baleanu operators based fractional models. The system of coupled PDEs is converted to ODEs by operating the Laplace transformation, and Zakian’s algorithm is applied to approximate the Laplace inversion numerically. The solutions of flow and energy equations are presented in terms of graphical illustrations and tables to discuss important physical aspects of the observed problem. Moreover, a detailed inspection on shear stress and Nusselt number is carried out to get a deep insight into skin friction and heat transfer mechanisms. It is analyzed that the suspension of MoS2 nanoparticles leads to ameliorating the heat transfer rate up to 9.5%. To serve the purpose of achieving maximum heat transfer rate and reduced skin friction, the Atangana-Baleanu operator based fractional model is more effective. Furthermore, it is perceived that velocity and energy functions of the nanofluid exhibit significant variations because of the different shapes of nanoparticles.

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