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Porous media flows are generally viewed as inefficient mixers, where solutes may be dispersed yet poorly mixed, making mixing a critical limiting factor for a wide range of processes. The complexity and opacity of porous structures have long made these dynamics difficult to observe. With emerging experimental techniques, concepts and models of mixing in porous media are rapidly evolving. Recent advances link mixing dynamics to fluid deformation arising in flow through porous materials. Unlike diffusion and dispersion, which only dissipate chemical gradients, fluid shear and stretching amplify and sustain them. This review explores the role of fluid deformation in governing mixing, chemical reactions, and biological processes in porous media. We begin by highlighting key experimental observations that have improved our understanding of mixing in these systems. We then examine the fundamental concepts, models, and open questions surrounding fluid deformation and mixing in porous media, emphasizing their dependence on material structure, heterogeneity, dimensionality, and transient flow phenomena, as well as their interaction with chemical and biological processes.
The squeezing of blood cells and vesicles through narrow constrictions, such as splenic slits, pulmonary capillaries, vascular endothelial gaps, and microfluidic channels, is crucial in physiology and biotechnology, with fluid mechanics playing a central role. The diverse geometries of these constrictions, the associated flow conditions, and the unique mechanical properties of cells and vesicles create a rich subject in fluid mechanics emerging from nonlinear dynamics of fluid–structure interactions involving both lubrication and Marangoni flows. Advances in microfluidics, video microscopy, and computational modeling have enabled investigations into these complex processes. This review surveys the key features and approaches, recent prominent studies, and unresolved challenges related to these processes, offering insights for researchers across biomechanics, biomedical engineering, biological physics, hematology, physiology, and applied mathematics.
In liquid filtration, a particulate-laden feed solution is passed through a porous material (the filter), often a membrane, designed to capture the particulate matter. Usually, the filter has a complex interior structure of interconnected pores, through which the feed passes, and in many cases of interest, it may be reasonable to approximate this interior structure as a network of interconnected tubes. This idea, which dates back about 70 years, greatly simplifies the modeling and simulation of the filtration process. In this article, we review the use of networks as a framework for modeling and investigating filtration, describing the key ideas and milestones. We also discuss some promising areas for future development of this field, particularly concerning the design of next-generation filters.
Earth is the only known planet with plate tectonics, which involves a mobile upper thermal boundary layer. Other terrestrial planets show a one-plate immobile lithosphere, or stagnant lid, that insulates and isolates their interior. Here, we first review the different types of lids that can develop on rocky and icy bodies. As they formed by accretion, involving high-energy impacts, terrestrial planets likely started hot and molten. We examine the process of lid initiation from a magma ocean stage and develop the equations for lid growth. We survey how lateral perturbations in lid and crust thickness can be amplified during their growth and finally discuss the possible processes at the origin of lid rupture and plate generation.
Electromagnetically forced flows in shallow electrolyte layers offer a versatile and nonintrusive method for exploring quasi-two-dimensional fluid dynamics. This review focuses on the experimental and theoretical aspects of such flows driven by Lorentz forces generated by the interaction of injected electric currents and the applied magnetic fields. The method is applicable to both liquid metals and electrolytes, with the latter more commonly used due to their wide availability and ease of handling. Experimental aspects of the method and key components of mathematical flow analysis are discussed. Initially developed for geophysical flow modeling, the method has been instrumental in exploring various other physical phenomena including vortex and wake dynamics, spatiotemporal chaos, and mixing processes. The review also addresses the challenges of achieving true two-dimensionality in laboratory settings and discusses the influence of various parameters, such as layer thickness and forcing intensity, on the flow behavior. Future research directions in the field are highlighted.
Internal waves, generated by wind and tides, are ubiquitous in the ocean. Their dissipation and the resulting vertical mixing play an important role in setting the ocean circulation, stratification, and energetics. Ocean models usually parameterize many or all of these effects. The current generation of parameterizations often relies on assumptions of uniform or slowly varying stratification profiles. Here, we review the growing theoretical, modeling, and observational evidence that vertical nonuniformity in the stratification profile can significantly modify the assumed wave dynamics. Linear scattering, wave–wave interactions, and solitary-like internal wave generation in idealized nonuniform stratification profiles are discussed. The nonuniform features in oceanic vertical stratification profiles are characterized, followed by a discussion of the validity of the slowly varying stratification assumption for such profiles. A concerted effort is made to synthesize research in both fluid dynamics and oceanography.
Sand dunes cover 5% of Earth's land surface, and they abundantly populate river bottoms and seabeds. The subtle dynamical interplay between the granular matter and the overlaying fluid leads to rich phenomenology at different scales, from colliding grains through migrating sand dunes to slowly evolving dune fields. In this review, we survey recent developments in the literature on the dynamics of sand dunes and focus in particular on the physics and mathematics. Our discussion is organized around four central paradigms of the field: flat bed instability, single dune migration, dune–dune interactions, and dune field statistics. Besides discussing the key scientific advances, we also highlight the methodological advances in observations, experiments, and simulations that facilitated them. We conclude our review by discussing the social implications of dune dynamics, such as the interaction between dune and infrastructure, and we offer speculation on what research topics related to sand dunes might become important in the next decade.
Decarbonization of buildings is one of the main challenges for the energy transition. In particular, the provision of heating, cooling, and ventilation to maintain a comfortable and healthy interior environment can be very energy intensive. Three approaches to help with the decarbonization of buildings are (a) upgrading the building envelope, especially the insulation, to reduce heat flow to or from the exterior; (b) improving the efficiency of the heating or cooling system, including the design and operation of ventilation flows; and (c) decarbonization of the heating and cooling systems, typically through electrification using heat pumps, and possibly the development of heat networks and interseasonal heat storage. This review touches on different elements of these challenges, mainly those related to ventilation, exploring some of the complexities of the fluid mechanics involved.
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Philipp Spelten, Dominik Wilde, Mario Christopher Bedrunka, Dirk Reith, Holger Foysi
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Amritpal Singh, Neeraj Kumar, Abdellah Hadjadj, Mostafa Safdari Shadloo
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Wasilij Barsukow, Praveen Chandrashekar, Christian Klingenberg, Lisa Lechner
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Jang Min Park
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Thomas S. Chyczewski, David A. Boger, Norman F. Foster
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Matteo Savino, Alessia Ferrari, Renato Vacondio, Paolo Mignosa
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Wenzhuo Xu, Madhav Karthikeyakannan, Christopher McComb, Noelia Grande Gutiérrez
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Anas Jnini, Flavio Vella, Marius Zeinhofer
Publication date: 15 March 2026
Source: Computers & Fluids, Volume 307
Author(s): Quentin Chauleur, Radu Chicireanu, Guillaume Dujardin, Jean-Claude Garreau, Adam Rançon
Publication date: Available online 5 February 2026
Source: Computers & Fluids
Author(s): Jing Zhang, Chris W. Letchford, Luca Patruno, Onkar Sahni, Daniel C. Lander

A gravity-driven granular flow model with Mohr–Coulomb friction is investigated. The exact Riemann solution is also established through classical and nonclassical symmetries of the Lie group. The derived solutions are discussed and validated in the context of weak discontinuity waves evolution and non-group invariants solutions through the method of conservation laws.
This study investigates a granular flow model on an inclined plane characterized by a constant friction coefficient to describe gravity-driven debris avalanches. We derive diverse sets of group-invariant solutions by employing both classical and nonclassical symmetries of the Lie group. Among these, solutions to 1 and 2 rarefaction waves corresponding to the Riemann problem are highlighted. The significance of nonclassical symmetries is explicitly demonstrated in our analysis. Essential conservation laws are derived using the multiplier method and the system's nonlinear self-adjointness. Additionally, we discuss the obtained solutions in the context of the evolution of weak discontinuity waves, and we derive new non-group invariant solutions using the method of conservation laws.

The gas–liquid–solid three-phase flow of deep-sea hydrates is one of the main factors that induce the failure of mining risers, and a comprehensive understanding of its flow characteristics can effectively improve the safety of mining risers. Based on this, a simulation experimental platform for gas–liquid–solid three-phase flow in deep-sea hydrate horizontal wells was developed using the principle of similarity, which can simulate gas–liquid–solid three-phase flow under different particle sizes, flow velocities, and gas–liquid–solid ratios. On this basis, the control variable and orthogonal analysis methods were used to determine the multiphase flow patterns in the vertical and horizontal sections under different solid particle sizes, gas–liquid–solid ratios, and internal flow velocities, and to track the axial and radial velocities of key particles and bubbles inside the riser. The experimental results show that when the gas–liquid–solid ratio is different, the axial velocity of particles decreases with the increase of gas phase ratio in both vertical and horizontal sections, while the axial velocity and radial velocity of bubbles in the vertical section fluctuate greatly when the gas phase content is high. When the particle size is different, the radial velocity variation of particles in the vertical and horizontal sections is larger, and the axial velocity variation is smoother compared to the radial velocity. The radial velocity variation of bubbles is most significant in the vertical section, and more stable in other sections. When the flow velocity is different, whether it is vertical or horizontal, axial velocity or radial velocity, particles and bubbles tend to stabilize at lower flow velocities. The range analysis shows that the particle size has the most significant impact on the axial velocity and radial velocity of particles and bubbles in the horizontal section, while the flow velocity has the greatest impact on the axial velocity of bubbles in the horizontal section. The particle size still has the greatest impact on the axial velocity and radial velocity of vertical particles and bubbles, while the flow velocity has a significant impact on the radial velocity of vertical particles. The research results can effectively guide the optimization of commercial exploitation parameters for deep-sea hydrates and other operating conditions containing gas–liquid–solid three-phase flow.
To address the challenges of multiphase flow inside the mining riser of deep-sea natural gas hydrates, a three-dimensional simulation model of gas–liquid–solid three-phase flow in the mining riser of a horizontal well is established for deep-sea hydrate. A test system is developed for gas–liquid–solid three-phase flow in the hydrate mining riser using a similar principle. The experimental results are compared with numerical simulations, and the comparison accuracy is over 90.8%. The accuracy and effectiveness of the theoretical model are verified. Based on this, the effect of particle size, gas–liquid–solid ratio, and injection flow velocity on the multiphase flow transport characteristics and flow field-riser wall collision force are investigated. The results indicate that as the particle size increases, the overall gas and liquid phase velocities do not change significantly. In the radial direction, the velocities increase from near the wall to the center of the riser. However, the solid-phase velocity decreases with increasing particle size, while the gas-phase volume fraction decreases. In contrast, the liquid-phase volume fraction increases, the solid-phase concentration decreases, and the collision force on the riser wall becomes stronger. As the gas phase proportion increases, the velocity of the gas and liquid phases also increases, with the radial direction increasing from near the wall toward the center of the riser. The velocity of the solid phase decreases as the proportion of the gas phase increases. There is no clear trend in the volume fractions of the gas and liquid phases, but the concentration of the solid phase increases with the gas phase volume fraction, also increasing the collision force. In the actual mining project, a higher flow velocity should be selected, which can not only improve the transportation efficiency, but also effectively prevent the wear of the mining riser caused by the collision of particles on the riser wall. The research results can effectively guide the safe extraction of deep-sea natural gas hydrates.

A new Galerkin-type meshfree method is developed for incompressible Navier-Stokes equations by integrating the key strengths of SL method and EFG method. Given that the SL method exhibits unconditionally stable characteristics for convection terms, the Galerkin method offers an optimal approximation for diffusion terms, the fractional step algorithm decouples velocity and pressure variables, and the meshfree feature streamlines the implementation of the SL method, the proposed method becomes an efficient approach for solving the incompressible Navier-Stokes equations.
A new Galerkin-type meshfree method is developed for solving incompressible Navier-Stokes equations by integrating the key strengths of the semi-Lagrangian (SL) method and the element-free Galerkin (EFG) method. This integration not only effectively resolves the convection-dominance problem but also fully preserves the meshfree property of the EFG method. In the absence of grid constraints, the operations of backward tracing and interpolation in the SL method can be executed more conveniently. To achieve both good stability and accuracy, the SL method is employed to handle the convection terms, while the EFG method is utilized for the diffusion terms. To decouple the velocity and pressure, a novel fractional step algorithm is derived within the SL framework. This algorithm circumvents the Ladyzhenskaya-Babuška-Brezzi (LBB) constraint and permits the utilization of equal-order velocity-pressure interpolation. Given that the SL method exhibits unconditionally stable characteristics for convection terms, the Galerkin method offers an optimal approximation for diffusion terms, the fractional step algorithm decouples velocity and pressure variables, and the meshfree feature streamlines the implementation of the SL method, the proposed method is anticipated to be an efficient approach for solving the incompressible Navier-Stokes equations. Numerical examples with available analytical solutions are solved to show the accuracy, stability, and convergence behavior of the proposed method. The results demonstrate that the new method exhibits superior stability compared to the EFG method, and it reaches a first-order convergence rate in temporal direction and second-order convergence rate in spatial direction under first-order discretization. After that, numerical tests on the square-cavity-driven flow and the doubly periodic shear layer flow further validate the accuracy and stability of the proposed method.

This study investigates heat and mass transfer in electrically conducting Casson ternary hybrid nanofluid flows (Al2O3–Cu–TiO2/blood$$ {\mathrm{Al}}_2{\mathrm{O}}_3\hbox{--} \mathrm{Cu}\hbox{--} {\mathrm{TiO}}_2/\mathrm{blood} $$) under variable thermal conductivity, Joule heating,viscous dissipation, and nonlinear thermal radiation. Using the Sixth-Order Runge–Kutta method in MATLAB, the results show that stronger magnetic fields, higher Casson parameters, and Darcy–Forchheimer effects reduce velocity, while curvature and Stefan blowing enhance heat transfer. Increased nanoparticle concentration improves thermal conductivity, leading to higher Nusselt numbers, making these fluids valuable for engineering applications like heat exchangers and electronic cooling.
In this study, the heat and mass transfer rates in electrically conducting Casson ternary hybrid nanofluid flows (Al2O3−Cu−TiO2/blood$$ A{l}_2{O}_3- Cu- Ti{O}_2/\mathrm{blood} $$) were investigated, considering various factors such as variable thermal conductivity, Joule heating, viscous dissipation, chemical reactions, Darcy–Forchheimer flow, and nonlinear thermal radiation. The use of ternary hybrid nanofluids, combining aluminum oxide, copper nanoparticles, and titanium oxide in blood, can significantly improve thermal conductivity and heat transfer efficiency, making them useful in engineering fields such as heat exchangers, aerospace, renewable energy, and electronic cooling. The study focuses on the effects of nonlinear thermal radiation, viscous dissipation, Joule heating, Soret number, chemical reactions, Darcy–Forchheimer effect, and curvature on the flow of Casson fluid over a stretching cylinder. The partial differential equations governing the system are transformed into ordinary differential equations using a similarity variable and solved using the Sixth-Order Runge–Kutta (RK6) method in MATLAB, validated against previous studies for accuracy. The analysis includes the impact of physical parameters on velocity, temperature, and concentration profiles, as well as skin friction coefficient, local Nusselt number, and Sherwood number. A higher Casson parameter leads to an increased yield stress, resulting in greater resistance and a reduction in the velocity distribution. Variable thermal conductivity, nonlinear thermal radiation, Eckert number, and nanoparticle volume fraction improve heat transfer. Higher nanoparticle concentrations increase thermal conductivity, leading to improved heat transfer and higher Nusselt numbers.

We present a numerical framework based on the Cahn-Hilliard-Navier-Stokes (CHNS) model to simulate biphasic flow in confined environments. After deriving the mathematical model, we develop the weak form of the system of PDEs using a pedagogical approach to enable its implementation in FEniCS. The model is validated against experimental data from the literature and subsequently applied to a microfluidic experiment conducted by the authors. All data and code related to this work are available on GitHub.
This study presents a numerical framework for modeling two-phase flow in confined environments, focusing on the interplay between capillary and viscous forces. The model integrates the Cahn-Hilliard and Navier-Stokes (CH-NS) equations, utilizing a diffuse-interface approach to capture interfacial dynamics without the limitations of sharp-interface models. Implemented in the finite element platform FEniCS, the framework incorporates Dirichlet boundary conditions to model a fully non-wetting phase. The validation of the proposed model is achieved through two applications: The retraction of an oil droplet from a capillary tube and the drainage of water-wet microfluidic chips. Numerical results align with experimental data, demonstrating the framework's ability to replicate interfacial behaviors, including capillary-driven dynamics and fingering phenomena. This work provides a versatile computational tool for studying immiscible fluid flow, offering potential for advancements in fundamental research on microfluidics, enhanced oil recovery, and remediation of contaminated soil.

This study examines buoyancy-driven magneto-convection within an anisotropic porous cavity incorporating internal heat generation/absorption. The top and bottom boundaries are subjected to sinusoidal heat fluxes, whereas the vertical walls are thermally insulated. The flow and heat transfer behavior are numerically analyzed using the Darcy-Brinkman extended model, implemented via FVM and the semi-implicit method for pressure-linked equations (SIMPLE) algorithm. The influence of key parameters, including the periodicity parameter, permeability ratio, thermal conductivity ratio, Hartmann number, internal heat generation/absorption, and orientation angle on the flow structure and heat transfer efficiency within the system is analyzed. The findings show that the cavity exhibits a multicellular convective pattern, where the anisotropic permeability tilt induces sinusoidal flow features near the thermally active walls. In contrast, a strong magnetic field (Ha=100)$$ \left( Ha=100\right) $$suppresses the flow circulation and higher levels of internal heat generation/absorption (Q=5,−5)$$ \left(Q=5,-5\right) $$lead to reduced heat transfer efficiency. The study is conducted for a steady, two-dimensional, Darcy-Brinkman model. This study could be beneficial for the solar collector designs, thermal management systems, setups for room ventilation, and electronic cooling applications.
This study examines buoyancy-driven magneto-convection within an anisotropic porous cavity incorporating internal heat generation/absorption. The top and bottom boundaries are subjected to sinusoidal heat fluxes, whereas the vertical walls are thermally insulated. The flow and heat transfer behavior are numerically analyzed using the Darcy-Brinkman extended model, implemented via FVM and the semi-implicit method for pressure-linked equations (SIMPLE) algorithm. The influence of key parameters, including the periodicity parameter, permeability ratio, thermal conductivity ratio, Hartmann number, internal heat generation/absorption, and orientation angle on the flow structure and heat transfer efficiency within the system is analyzed. The findings show that the cavity exhibits a multicellular convective pattern, where the anisotropic permeability tilt induces sinusoidal flow features near the thermally active walls. In contrast, a strong magnetic field (Ha=100$$ Ha=100 $$) suppresses the flow circulation, and higher levels of internal heat generation/absorption (Q=5,−5)$$ \left(Q=5,-5\right) $$ lead to reduced heat transfer efficiency. The study is conducted for a steady, two-dimensional, Darcy-Brinkman model. This study could be beneficial for the solar collector designs, thermal management systems, setups for room ventilation, and electronic cooling applications.

The Lagrange multipliers approach and Knudsen-number-dependent relaxation time is introduced in the lattice Boltzmann community. Large adaptive stencils in the velocity discretization scheme are introduced to reduce the perturbations in macroscopic characteristics. Tandem, vertical, and staggered arrangements of the cylinders are studied for validation. New insights into the separation of the bow shock wave inside the channel are presented.
The present study is focused on several numerical experiments on high-speed compressible fluid flows inside a long horizontal multi-cylinder positioned channel using a double distribution function based extended lattice Boltzmann (LB) approach. Initially, an algorithm of the lattice Boltzmann approach to simulate the compressible flows is developed and stabilized by introducing the Lagrange multipliers approach to calculate the equilibrium distribution function, Knudsen-number-dependent relaxation time, and large adaptive stencils in the velocity discretization scheme. Subsequently, the algorithm/code is validated by comparison of the present results against the existing benchmark results. The LB simulations are carried out at the supersonic state for two different Mach numbers, 1.5 and 1.7. The channel is enclosed from the top and bottom sides, with surfaces having symmetric boundary conditions. At the inlet and outlet, Dirichlet and Neumann boundary conditions are employed, respectively, for density, velocity, temperature, and pressure. Three different studies based on the configuration of the multi-cylinders are carried out. Inside the channel, the multi-cylinders are either positioned in a tandem manner, vertical (side-by-side) manner, or staggered manner with varying angles of incidences. Various physical parameters like the coefficient of pressure, drag and lift coefficient, temperature flow field, and so forth, are computed and reported throughout the study.

Comparison of pressure at 10 seconds. Left–reference data, right–model predictions.
This paper examines the application of PINN models to solving a two-dimensional cylinder flow problem with limited data. Using data obtained by direct numerical simulation, a surrogate PINN model was developed and trained. The model utilizes the governing equations of fluid dynamics and heat transfer, enabling it to accurately predict flow parameters such as velocity components, pressure, and temperature. The direct computational flow model was numerically solved using the SIMPLE algorithm, which couples pressures and velocities. The results showed that the PINN model, which does not contain initial and boundary conditions from direct numerical simulation, is capable of reproducing complex dynamic processes such as the formation of a Kármán vortex street behind a cylinder. However, limitations were identified due to the lack of initial and boundary conditions, which led to increased errors at the boundaries of the computational domain. For example, from the data obtained using the PINN model, a very small absolute difference in error for the velocity and temperature components between the reference data and the predicted values can be noted. Thus, for the horizontal velocity component, the maximum relative error was no more than 2.5%. For the temperature component, the relative error was no more than 0.02%. However, the relative error for pressure was 60%–75%. The main reason for this large error is the lack of a reference pressure value or initial pressure conditions in the loss function. The results show that the PINN surrogate model with eight hidden layers of 200 neurons successfully copes with the task of modeling complex unsteady flow. The integration of physical laws made it possible to achieve relatively satisfactory accuracy using only 10,000 data points.

A hybrid RANS-LES turbulence model adapted for the Moving Particle Semi-implicit method is employed to investigate a turbulent free surface flow. A method based on the cell-linked list is proposed to speed up the nearest wall search for the turbulence model. Validation using lid-driven flow showed better convergence and improvements achieved by the turbulence model. The flows around a square cylinder near the surface with a Reynolds number of 25,000 were simulated and the influence of the cylinder submergence depths was investigated.
Engineering problems often comprise free-surface flows in turbulent regime. Lagrangian mesh-free particle-based methods are well suited for the simulation of flows involving complex free-surface deformation. However, the analysis of turbulent modeling for particle-based methods is relatively scarce in the literature. In this work, an analysis of a hybrid RANS-LES turbulence model adapted for the Moving Particle Semi-implicit (MPS) method is performed. In the turbulence model, a zero-equation RANS is applied near the wall boundaries and a standard Smagorinsky LES model is applied elsewhere. Given that the eddy viscosity of the turbulent modeling depends on the distance between the fluid and the nearest wall particle, the calculation of the fluid-wall particle distance may demand a high computational cost due to undefined topology among moving particles. In this way, a method based on the cell-linked list is proposed to improve the nearest wall search for the turbulence model. The implementation is verified through simulation of a lid-driven flow with Reynolds number between 10,000$$ \mathrm{10,000} $$ and 50,000$$ \mathrm{50,000} $$. The result shows that despite the overhead when the turbulence model is adopted, the time needed to reach steady state is shortened so that the overall computational costs are almost the same. In addition, the improvement due to the adoption of turbulence model is more evident for the highest Reynolds numbers. As an application, the flow around a submerged square cylinder near the surface with Reynolds number of 25,000$$ \mathrm{25,000} $$ is simulated. The influences of the cylinder submergence depths on the drag and lift coefficients are investigated for a range of depth-to-length ratios between 0.3$$ 0.3 $$ and 3.0$$ 3.0 $$. When the turbulence model is applied, a smoother convergence tendency is obtained as the resolution increases. Moreover, the flow around the square cylinder is better represented, resulting in more regular vortex shedding. Different flow behaviors were identified around the square cylinder as the submergence depth changes.
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): Tong Zhu, Bingqian Si, Lin Fu, Yanglong Lu
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): Longqiang Xu, Weishi Yin, Pinchao Meng, Zhengxuan Shen, Hongyu Liu
Publication date: Available online 7 February 2026
Source: Journal of Computational Physics
Author(s): Xiuping Wang, Huangxin Chen, Jisheng Kou, Shuyu Sun
Publication date: Available online 7 February 2026
Source: Journal of Computational Physics
Author(s): P. Gan, J. Li, F. Fang, X. Wu, J. Zhu, Z. Wang, M. Zhu, X. Zou
Publication date: Available online 6 February 2026
Source: Journal of Computational Physics
Author(s): Zhengshou Lai, Shuai Huang, Yong Kong, Shiwei Zhao, Jidong Zhao, Linchong Huang
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): Tom Hickling, Jonathan F. MacArt, Justin Sirignano, Den Waidmann
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): Jingfei Chen, Minxin Chen, Jingrun Chen
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): A. Colaïtis, S. Guisset, J. Breil
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): Jiachuan Zhang
Publication date: 1 May 2026
Source: Journal of Computational Physics, Volume 552
Author(s): Arnaud Colaïtis, Sébastien Guisset, Jérôme Breil