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Processes
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Multiscale Modeling and Numerical Simulation of Multiphase Flow
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Multiscale Modeling and Numerical Simulation of Multiphase Flow

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: 25 December 2024 | Viewed by 3603

Special Issue Editors

Dr. Yupeng Xu

E-Mail Website
Guest Editor
National Energy Technology Laboratory, Morgantown, WV 26507, USA
Interests: multiscale modeling of multiphase flow; chemical reactors; coal, biomass, and plastic gasification; green energy
Special Issues, Collections and Topics in MDPI journals
Dr. Xiaogang Shi

E-Mail Website
Guest Editor
State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Beijing 102249, China
Interests: heavy oil processing; multiphase reaction engineering; numerical simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Lei Yang

E-Mail Website
Guest Editor
Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
Interests: chemical reaction engineering; fluidization; simulation; multiphase flow; process modeling; kinetic theory

Special Issue Information

Dear Colleagues,

Gas–solid flows are commonly encountered in different industrial applications and daily life. These flow systems exhibit dynamic structures of a wide range of spatial and temporal scales. Microscale short-duration events, such as particle–particle or particle–wall collisions and energy dissipation are closely related to mesoscale structures such as bubbles and clusters, which further affect macroscale flow behaviors at the device level. Because of the inherently unsteady and highly coupled multiscale characteristics of these flow structures, it is rarely computationally feasible to resolve all details using a single model. Multiscale modeling and numerical simulation approaches have been developed to study the complex physics associated with multiphase flows. Different interphase interaction, heat and mass transfer correlations have been developed to account for particle size, shape and various flow conditions. These advancements have allowed us improved understanding of various multiphase flow systems and helped the design and optimization of different reactors for industrial applications.

This Special Issue on ‘Multiscale Modeling and Numerical Simulation of Multiphase Flow’ seeks high quality papers focusing on the multiscale simulation of different multiphase flow system. Topics include, but are not limited to:

  • Development, verification and validation of advanced multiscale numerical models such as Direct Numerical Simulation, Discrete Element Method, Two Fluid Model, MPPIC, etc.
  • Model development for interphase drag, heat and mass transfer.
  • Coupling of multiscale models with machine learning.
  • Utilization of multiscale models in solving different industrial problems.
  • Design and optimization of various industrial reactors using multiscale modeling.

Dr. Yupeng Xu
Dr. Xiaogang Shi
Dr. Lei Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multiphase flow
  • particle
  • numerical simulation
  • heat and mass transfer
  • multiscale models

Published Papers (3 papers)

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Research

20 pages, 8468 KiB  
Article
DEM Investigation on the Flow and Heat Transmission Characteristics of Multi-Size Particles Mixed Flow in Moving Bed
by Wenbo Cao, Fengxia Zhang, Jianhang Hu, Shiliang Yang, Huili Liu and Hua Wang
Processes 2024, 12(2), 408; https://doi.org/10.3390/pr12020408 - 18 Feb 2024
Viewed by 495
Abstract
The moving bed heat exchanger (MBHE) has been widely applied in the recovery of waste heat of industrial particles. Currently, investigations focus on uniform-size particles in the MBHE, but few studies are conducted on multi-size particles produced by industrial granulation. Therefore, based on [...] Read more.
The moving bed heat exchanger (MBHE) has been widely applied in the recovery of waste heat of industrial particles. Currently, investigations focus on uniform-size particles in the MBHE, but few studies are conducted on multi-size particles produced by industrial granulation. Therefore, based on the discrete element method (DEM), the heat transmission model of multi-size particles is established, and flow and heat transmission processes of typically normal distribution particles in the MBHE are studied. In conclusion, there are significant differences in particles tangential velocity and contact number in local regions of a heat exchanger pipe, resulting in different local heat transmission coefficients. In addition, the increases in outlet particle velocity and inlet particle temperature significantly enhance the heat transmission. When the outlet particle velocity grows from 1 mm/s to 5 mm/s, the overall heat transmission coefficient increases by 36.4%, and as the inlet particle temperature rises from 473 K to 873 K, the overall heat transmission coefficient increases by 16.1%. Full article
(This article belongs to the Special Issue Multiscale Modeling and Numerical Simulation of Multiphase Flow)
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17 pages, 6951 KiB  
Article
CFD Validation of Moment Balancing Method on Drag-Dominant Tidal Turbines (DDTTs)
by Yixiao Zhang, Shivansh Mittal and Eddie Yin-Kwee Ng
Processes 2023, 11(7), 1895; https://doi.org/10.3390/pr11071895 - 23 Jun 2023
Cited by 1 | Viewed by 1244
Abstract
Current performance analysis processes for drag-dominant tidal turbines are unsuitable as disk actuator theory lacks support for varying swept blockage area, bypass flow downstream interaction, and parasitic rotor drag, whereas blade element momentum theory is computably effective for three-blade lift-dominated aerofoil. This study [...] Read more.
Current performance analysis processes for drag-dominant tidal turbines are unsuitable as disk actuator theory lacks support for varying swept blockage area, bypass flow downstream interaction, and parasitic rotor drag, whereas blade element momentum theory is computably effective for three-blade lift-dominated aerofoil. This study proposes a novel technique to calculate the optimal turbine tip speed ratio (TSR) with a cost-effective and user-friendly moment balancing algorithm. A reliable dynamic TSR matrix was developed with varying rotational speeds and fluid velocities, unlike previous works simulated at a fixed fluid velocity. Thrust and idle moments are introduced as functions of inlet fluid velocity and rotational speed, respectively. The quadratic relationships are verified through regression analysis, and net moment equations are established. Rotational speed was a reliable predictor for Pinwheel’s idle moment, while inlet velocity was a reliable predictor for thrust moment for both models. The optimal (Cp, TSR) values for Pinwheel and Savonius turbines were (0.223, 2.37) and (0.63, 0.29), respectively, within an acceptable error range for experimental validation. This study aims to improve prevailing industry practices by enhancing an engineer’s understanding of optimal blade design by adjusting the rotor speed to suit the inlet flow case compared to ‘trial and error’ with cost-intensive simulations. Full article
(This article belongs to the Special Issue Multiscale Modeling and Numerical Simulation of Multiphase Flow)
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29 pages, 3259 KiB  
Article
Optimum Volume Fraction and Inlet Temperature of an Ideal Nanoparticle for Enhanced Oil Recovery by Nanofluid Flooding in a Porous Medium
by Abdullah Al-Yaari, Dennis Ling Chuan Ching, Hamzah Sakidin, Mohana Sundaram Muthuvalu, Mudasar Zafar, Yousif Alyousifi, Anwar Ameen Hezam Saeed and Abdurrashid Haruna
Processes 2023, 11(2), 401; https://doi.org/10.3390/pr11020401 - 28 Jan 2023
Cited by 11 | Viewed by 1502
Abstract
Nowadays, oil companies employ nanofluid flooding to increase oil production from oil reservoirs. Herein the present work, a multiphase flow in porous media was used to simulate oil extraction from a three-dimensional porous medium filled with oil. Interestingly, the finite element method was [...] Read more.
Nowadays, oil companies employ nanofluid flooding to increase oil production from oil reservoirs. Herein the present work, a multiphase flow in porous media was used to simulate oil extraction from a three-dimensional porous medium filled with oil. Interestingly, the finite element method was used to solve the nonlinear partial differential equations of continuity, energy, Darcy’s law, and the transport of nanoparticles (NPs). The proposed model used nanofluids (NFs) empirical formulas for density and viscosity on NF and oil relative permeabilities and NP transport equations. The NPs thermophysical properties have been investigated and compared with their oil recovery factor (ORF) to determine the highest ORF. Different NPs (SiO2, CuO, and Al2O3) were used as the first parameter, keeping all parameters constant. The simulation was run three times for the injected fluid using the various NPs to compare the effects on enhanced oil recovery. The second parameter, volume fraction (VF), has been modeled six times (0.5, 1, 2, 3, 4, and 5%), with all other parameters held constant. The third parameter, the injected NF inlet temperature (293.15–403.15 K), was simulated assuming that all other parameters are kept constant. The energy equation was applied to choose the inlet temperature that fits the optimum NP and VF to determine the highest ORF. Findings indicated that SiO2 shows the best ORF compared to the other NPs. Remarkably, SiO2 has the lowest density and highest thermal capacity. The optimum VF of SiO2 was 4%, increasing the ORF but reduced when the VF was higher than 4%. The ORF was improved when the viscosity and density of the oil decreased by increasing the injected inlet temperature. Furthermore, the results indicated that the highest ORF of 37% was obtained at 353.15 K when SiO2 was used at a VF of 4%. At the same time, the lowest recovery is obtained when a volume of 5% was used at 403.15 K. Full article
(This article belongs to the Special Issue Multiscale Modeling and Numerical Simulation of Multiphase Flow)
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