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36 pages, 14909 KiB

Open AccessArticle

Enhanced Efficient 3D Poisson Solver Supporting Dirichlet, Neumann, and Periodic Boundary Conditions

by Chieh-Hsun Wu

Computation 2025, 13(4), 99; https://doi.org/10.3390/computation13040099 - 18 Apr 2025

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This paper generalizes the efficient matrix decomposition method for solving the finite-difference (FD) discretized three-dimensional (3D) Poisson’s equation using symmetric 27-point, 4th-order accurate stencils to adapt more boundary conditions (BCs), i.e., Dirichlet, Neumann, and Periodic BCs. It employs equivalent Dirichlet nodes to streamline [...] Read more.

This paper generalizes the efficient matrix decomposition method for solving the finite-difference (FD) discretized three-dimensional (3D) Poisson’s equation using symmetric 27-point, 4th-order accurate stencils to adapt more boundary conditions (BCs), i.e., Dirichlet, Neumann, and Periodic BCs. It employs equivalent Dirichlet nodes to streamline source term computation due to BCs. A generalized eigenvalue formulation is presented to accommodate the flexible 4th-order stencil weights. The proposed method significantly enhances computational speed by reducing the 3D problem to a set of independent 1D problems. As compared to the typical matrix inversion technique, it results in a speed-up ratio proportional to

n^{4}

, where

n

is the number of nodes along one side of the cubic domain. Accuracy is validated using Gaussian and sinusoidal source fields, showing 4th-order convergence for Dirichlet and Periodic boundaries, and 2nd-order convergence for Neumann boundaries due to extrapolation limitations—though with lower errors than traditional 2nd-order schemes. The method is also applied to vortex-in-cell flow simulations, demonstrating its capability to handle outer boundaries efficiently and its compatibility with immersed boundary techniques for internal solid obstacles. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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18 pages, 15002 KiB

Open AccessArticle

Numerical Analysis of the Impact of Variable Borer Miner Operating Modes on the Microclimate in Potash Mine Working Areas

by Lev Levin, Mikhail Semin, Stanislav Maltsev, Roman Luzin and Andrey Sukhanov

Computation 2025, 13(4), 85; https://doi.org/10.3390/computation13040085 - 24 Mar 2025

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Abstract

This paper addresses the numerical simulation of unsteady, non-isothermal ventilation in a dead-end mine working of a potash mine excavated using a borer miner. During its operations, airflow can become unsteady due to the variable operating modes of the borer miner, the switching [...] Read more.

This paper addresses the numerical simulation of unsteady, non-isothermal ventilation in a dead-end mine working of a potash mine excavated using a borer miner. During its operations, airflow can become unsteady due to the variable operating modes of the borer miner, the switching on and off of its motor cooling fans, and the movement of a shuttle car transporting ore. While steady ventilation in a dead-end working with a borer miner has been previously studied, the specific features of air microclimate parameter distribution in more complex and realistic unsteady scenarios remain unexplored. Our experimental studies reveal that over time, air velocity and, particularly, air temperature experience significant fluctuations. In this study, we develop and parameterize a mathematical model and perform a series of numerical simulations of unsteady heat and mass transfer in a dead-end working. These simulations account for the switching on and off of the borer miner’s fans and the movement of the shuttle car. The numerical model is calibrated using data from our experiments conducted in a potash mine. The analysis of the first factor is carried out by examining two extreme scenarios under steady-state ventilation conditions, while the second factor is analyzed within a fully unsteady framework using a dynamic mesh approach in the ANSYS Fluent 2021 R2. The numerical results demonstrate that the borer miner’s operating mode notably impacts the velocity and temperature fields, with a twofold decrease in maximum velocity near the cabin after the shuttle car departed and a temperature difference of about 1–1.5 °C between extreme scenarios in the case of forcing ventilation. The unsteady simulations using the dynamic mesh approach revealed that temperature variations were primarily caused by the borer miner’s cooling system, while the moving shuttle car generated short-term aerodynamic oscillations. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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10 pages, 7877 KiB

Open AccessArticle

A Molecular Dynamics Simulation on the Methane Adsorption in Nanopores of Shale

by Qiuye Yuan, Jinghua Yang, Shuxia Qiu and Peng Xu

Computation 2025, 13(3), 79; https://doi.org/10.3390/computation13030079 - 20 Mar 2025

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Abstract

Gas adsorption in nanoscale pores is one of the key theoretical bases for shale gas development. However, the influence mechanisms of gas adsorption capacity and the second adsorption layer in nanoscale pores are very complex, and are difficult to directly observe by using [...] Read more.

Gas adsorption in nanoscale pores is one of the key theoretical bases for shale gas development. However, the influence mechanisms of gas adsorption capacity and the second adsorption layer in nanoscale pores are very complex, and are difficult to directly observe by using traditional experimental methods. Therefore, multilayer graphene is used to model the nanopores in a shale reservoir, and the molecular dynamics method is carried out to study the adsorption dynamics of methane molecules. The results show that the adsorption density of methane molecules is inversely proportional to the temperature and pore size, and it positively correlates to the graphene layer number and pressure. The smaller adsorption region will reach the adsorption equilibrium state earlier, and the adsorption layer thickness is smaller. When the pore size is larger than 1.7 nm, the single-layer adsorption becomes double-layer adsorption of methane molecules. The peak of the second adsorption layer depends on the pressure and temperature, while the position of the second adsorption layer depends on the pore size. The present work is useful for understanding the dynamics mechanism of gas molecules in a nanoscale confined space, and may provide a theoretical basis for the development of unconventional natural gas. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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17 pages, 5071 KiB

Open AccessArticle

Non-Hydrostatic Galerkin Model with Weighted Average Pressure Profile

by Lucas Calvo, Diana De Padova and Michele Mossa

Computation 2025, 13(3), 73; https://doi.org/10.3390/computation13030073 - 13 Mar 2025

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Abstract

This work develops a novel two-dimensional, depth-integrated, non-hydrostatic model for wave propagation simulation using a weighted average non-hydrostatic pressure profile. The model is constructed by modifying an existing non-hydrostatic discontinuous/continuous Galerkin finite-element model with a linear, vertical, non-hydrostatic pressure profile. Using a weighted [...] Read more.

This work develops a novel two-dimensional, depth-integrated, non-hydrostatic model for wave propagation simulation using a weighted average non-hydrostatic pressure profile. The model is constructed by modifying an existing non-hydrostatic discontinuous/continuous Galerkin finite-element model with a linear, vertical, non-hydrostatic pressure profile. Using a weighted average linear/quadratic non-hydrostatic pressure profile has been shown to increase the performance of earlier models. The results suggest that implementing a weighted average non-hydrostatic pressure profile, in conjunction with a calculated or optimized

Ө

weight parameter, improves the dispersion characteristics of depth-integrated, non-hydrostatic models in shallow and intermediate water depths. A series of analytical solutions and data from previous laboratory experiments verify and validate the model. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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14 pages, 3732 KiB

Open AccessArticle

Computational Analysis of Pipe Roughness Influence on Slurry Flow Dynamics

by Tanuj Joshi, Om Parkash, Ralph Kristoffer B. Gallegos and Gopal Krishan

Computation 2025, 13(3), 65; https://doi.org/10.3390/computation13030065 - 4 Mar 2025

Viewed by 471

Abstract

Slurry transportation is an essential process in numerous industrial applications, widely studied for its efficiency in material conveyance. Despite substantial research, the impact of pipe wall roughness on critical metrics such as pressure drop, specific energy consumption (SEC), and the Nusselt number remains [...] Read more.

Slurry transportation is an essential process in numerous industrial applications, widely studied for its efficiency in material conveyance. Despite substantial research, the impact of pipe wall roughness on critical metrics such as pressure drop, specific energy consumption (SEC), and the Nusselt number remains relatively underexplored. This study provides a detailed analysis using a three-dimensional computational model of a slurry pipeline, with a 0.0549 m diameter and 3.8 m length. The model employs an Eulerian multiphase approach coupled with the RNG k-ε turbulence model, assessing slurry concentrations C_w = 40–60% (by weight). Simulations were conducted at flow velocities V_m = 1–5 m/s, with pipe roughness (R_h) ranging between 10 and 50 µm. Computational findings indicate that both pressure drop and SEC increase proportionally with roughness height, V_m, and C_w. Interestingly, the Nusselt number appears unaffected by roughness height, although it rises corresponds to V_m, and C_w. These insights offer a deeper understanding of slurry pipeline dynamics, informing strategies to enhance operational efficiency and performance across various industrial contexts. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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10 pages, 4605 KiB

Open AccessArticle

Transport Characteristics of Small Molecules Diffusing near Deforming Blood Cells

by Stephanie Nix

Computation 2025, 13(2), 47; https://doi.org/10.3390/computation13020047 - 7 Feb 2025

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Abstract

Understanding the transport of small molecules such as oxygen in biological systems requires knowledge about how molecules dynamically interact with these molecules. This study investigates how red blood cells influence the diffusion of small molecules in simple shear flow by coupling Brownian dynamics [...] Read more.

Understanding the transport of small molecules such as oxygen in biological systems requires knowledge about how molecules dynamically interact with these molecules. This study investigates how red blood cells influence the diffusion of small molecules in simple shear flow by coupling Brownian dynamics simulations with a finite element–boundary integral method to simulate particle transport near spherical and red blood cells. The simulation found that the presence of a rotating cell significantly reduces the effective diffusion rate of small molecules. Specifically, the circulatory flow induced by cell deformation during tank-treading motion leads to a diminished mean squared displacement of particles. Notably, a tumbling red blood cell produces a more pronounced effect on particle motion compared with a spherical cell under identical flow conditions. This research has broader implications for understanding complex diffusion processes in various biological systems, by highlighting the complex interactions between cellular motion and molecular transport. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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16 pages, 1606 KiB

Open AccessArticle

Estimation of Wind Farm Losses Using a Jensen Model Based on Actual Wind Turbine Characteristics for an Offshore Wind Farm in the Baltic Sea

by Ziemowit Malecha and Maciej Chorowski

Computation 2025, 13(1), 20; https://doi.org/10.3390/computation13010020 - 20 Jan 2025

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Abstract

This study investigates the effects of velocity deficits on the performance of wind turbines in multi-row wind farms, focusing on two types of turbines: Gamesa G132 and Gamesa SG8. The analysis examines the impact of turbine spacing on key performance metrics, including Annual [...] Read more.

This study investigates the effects of velocity deficits on the performance of wind turbines in multi-row wind farms, focusing on two types of turbines: Gamesa G132 and Gamesa SG8. The analysis examines the impact of turbine spacing on key performance metrics, including Annual Energy Production, energy production losses, and the capacity factor. Two models are used: the classical Jensen model, assuming a constant thrust coefficient (

C_{T}

), and an updated model that incorporates the actual turbine-specific

C_{T} (U)

characteristics. The results demonstrate that as turbine spacing decreases, the velocity deficit behind the turbines increases, leading to significant reductions in AEP and higher energy losses. These effects are particularly pronounced for spacings of 5D and 3D, raising concerns about the economic feasibility of such wind farms. This study also highlights that the proposed updated Jensen model, which accounts for the specific turbine characteristics, provides results that are closer to real-world observations. This study showed that for a Baltic Sea wind farm location, the capacity factor for the wind farm is in the range of 0.366 to 0.476, depending on the turbine spacing. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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11 pages, 16045 KiB

Open AccessArticle

Study of Ventilation Strategies in a Passenger Aircraft Cabin Using Numerical Simulation

by S. M. Abdul Khader, John Valerian Corda, Kevin Amith Mathias, Gowrava Shenoy, Kamarul Arifin bin Ahmad, Augustine V. Barboza, Sevagur Ganesh Kamath and Mohammad Zuber

Computation 2025, 13(1), 1; https://doi.org/10.3390/computation13010001 - 24 Dec 2024

Cited by 1 | Viewed by 1001

Abstract

Aircraft cabins have high occupant densities and may introduce the risk of COVID-19 contamination. In this study, a segment of a Boeing 767 aircraft cabin with a mixing type of air distribution system was investigated for COVID-19 deposition. A section of a Boeing [...] Read more.

Aircraft cabins have high occupant densities and may introduce the risk of COVID-19 contamination. In this study, a segment of a Boeing 767 aircraft cabin with a mixing type of air distribution system was investigated for COVID-19 deposition. A section of a Boeing 737-300 cabin, featuring four rows with 28 box-shaped mannequins, was used for simulation. Conditioned air entered through ceiling inlets and exited near the floor, simulating a mixed air distribution system. Cough droplets were modeled using the Discrete Phase Model from two locations: the centre seat in the second row and the window seat in the fourth row. These droplets had a mean diameter of 90 µm, an exhalation velocity of 11.5 m/s and a flow rate of 8.5 L/s. A high-quality polyhedral mesh of about 7.5 million elements was created, with a skewness of 0.65 and an orthogonality of 0.3. The SIMPLE algorithm and a second-order upwind finite volume method were used to model airflow and droplet dynamics. It was found that the ceiling accounted for the maximum concentration followed by the seats. The concentration of deposits was almost 50% more when the source was at window as compared to the centre seat. The Covid particles resided for longer duration when the source was at the centre of the cabin than when it was located near the widow. Full article

(This article belongs to the Special Issue Advances in Computational Methods for Fluid Flow)

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