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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.
Direct-ink writing (DIW) has rapidly become a versatile 3D fabrication method due to its ability to deposit a wide range of complex fluids into customizable 3D geometries. This review highlights key fundamental fluid mechanics and soft matter challenges across the different stages of the DIW printing process. The rheology of fluids and suspensions governs the flow behavior through narrow nozzles, posing questions about extrudability, confined flow dynamics, and clogging mechanisms. Downstream, the formation and deposition of extruded filaments involve extensional flows and potential instabilities, while postdeposition dynamics introduces complexities related to yield stress and structural stability. These stages are inherently interdependent, as optimizing material composition without considering filament stability risks compromising the final structure. As DIW applications expand through advanced ink formulations, developing fundamental fluid mechanics frameworks is essential to replace trial-and-error approaches with predictive design methodologies to enable more precise control over and reliability of the printing process.
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.
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.
Microplastic pollution is now ubiquitous in marine environments, posing risks to ecosystem and human health. In order to assess and mitigate this threat, we require accurate prediction of microplastic fate and transport in the ocean. While progress has been made studying global-scale transport pathways, our models often fall short at smaller scales; processes such as vertical transport, horizontal dispersion, particle transformation, and boundary fluxes (e.g., at beaches and the air–sea interface) remain poorly understood. The difficulty lies in the physical features of plastic particles: namely, near-neutral buoyancy in seawater, finite size, and irregular shape. These complexities are compounded by the multiscale forcing from waves and turbulence near the ocean surface where microplastics tend to reside. This review synthesizes recent advances in the fluid dynamics of marine plastic transport, emphasizing the role of fluid–particle interactions in ocean flows and highlighting outstanding challenges.
Geophysical and astrophysical fluid dynamics (GAFD) is an interdisciplinary field. It encompasses a wide range of fluid systems, from planetary atmospheres and the oceans of Earth and icy moons to the interiors of telluric planets, giant planets, and stars. It also spans vast timescales and space scales. Despite this diversity, GAFD is built on common challenges in fundamental fluid mechanics, requiring a multi-approach strategy that integrates theory, simulations, and experiments to explain observations. This review highlights the role of laboratory experiments in GAFD. We first emphasize recent advances in experimental design, methods, and metrology, including large-scale facilities as well as innovative and analog setups. We then focus on two areas where experiments have driven recent breakthroughs: rotating turbulence and flows involving multiphase and phase-change processes. Finally, we discuss emerging challenges and the potential of outreach experiments to stimulate interest in fluid mechanics among students and the public.
Particulate suspensions, consisting of solid particles dispersed in a fluid, exhibit complex flow behaviors influenced by multiple factors, including particle interactions, concentration gradients, and external forces. Suspensions play an important role in diverse processes, from sediment transport to food processing, and display instabilities triggered by shear-driven effects, frictional interactions, and viscous forces. These instabilities can often be understood by identifying the key mechanical quantities that govern the dynamics. Following hydrodynamic tradition, such mechanics can be characterized by dimensionless numbers, which encapsulate the interplay between geometric, kinematic, and mechanical factors. Many of these numbers represent competitions between opposing pairs of mechanical quantities, which we discuss in detail while also considering a few phenomena that require more complex combinations. By emphasizing the underlying mechanical principles, this review provides a perspective for understanding pattern formation and flow instabilities in confined particulate suspensions across different flow geometries.
The objective of this contribution is to review more than 80 years of experimental measurements of the settling of snow particles and surrogates in natural and laboratory settings and suggest viable directions for future research. Under the broad category of frozen hydrometeors, snow particles are characterized by a variety of shapes and inertial properties that we broadly refer to as snow morphology attributes and depend on the micrometeorology of the air column, including temperature, relative humidity, wind speed, and turbulence. The uncertainty in the prediction of snow settling velocity is partly due to the significant variability in snow crystal shape, density, and drag properties, as well as the modulating effect of ambient turbulence, which has been observed to affect particle orientation and falling style and enhance or reduce the terminal velocity, as compared to quiescent flow conditions. Because of the complexity of finite-size, nonspherical particles’ interaction with turbulent flows at high Reynolds numbers, we stress the need for simultaneous flow and snow morphology measurements in the field and we review past and current experimental techniques and methodologies.
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.
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Dongheng Lai, Xingyu Zhu
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Manuel A. Taborda, Martin Sommerfeld
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Yair Mor-Yossef
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Quentin Martinez, Chetan Jagadeesh, Marinos Manolesos, Mohammad Omidyeganeh
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Matěj Klíma, Milan Kuchařík, Richard Liska
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Yixiang Xu, Gang Yang, Yulin Xing, Dean Hu
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Qiushuo Qin, Jie Wu, Lan Jiang
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Gaurav Bokil, Sebastian Merbold, Stefanie De Graaf
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Liangzhong Fan, Qingyong Zhu, Zhihui Li, Dongheng Lai
Publication date: 15 February 2026
Source: Computers & Fluids, Volume 306
Author(s): Evert Bunschoten, Alessandro Cappiello, Matteo Pini
Data assimilation in compressible flows with shocks has not been widely explored, especially when using sparse and incomplete measurements. Here sequential and variational data assimilation methods are applied to 1D, nonreacting, shock-laden flows using sparse and incomplete measurements. The methods are assessed, successes and challenges are identified, paving the way for application to more complex flows.
Data assimilation (DA) combines noisy observations with uncertain model predictions to obtain optimal state estimation. It has been used extensively in numerical weather prediction and is increasingly used in computational fluid dynamics. However, the application of DA to compressible flows with discontinuities such as shocks or detonation fronts is far less explored. In this paper, we examine three different DA algorithms applied to 1D, non-reacting, compressible flows: The particle filter (PF), the ensemble Kalman filter (EnKF), and 4D-Var. The Sod's shock tube problem is employed as a canonical test case. While the sequential DA methods (PF and EnKF) are able to successfully assimilate sparse pressure measurements, this comes at the risk of smearing sharp gradients due to reconstructing the state as an ensemble average. On the other hand, the 4D-Var method, applied in the context of a small parameter inverse problem, preserves sharp gradients within the resolution of the forward solver, but may require many iterations to converge to the truth. This study therefore provides assessments of sequential and variational DA methods in 1D shock tube problems and contributes towards applying DA to more complex shock-laden flows (e.g., in higher dimensions, or reacting flows).
This study presents an efficient method to compute polymer stress-tensor components in viscoelastic laminar jet flows using models such as Oldroyd-B, Giesekus, PTT, and FENE. By assuming a stationary and parallel flow, the methodology significantly reduces computational cost. Numerical results show excellent agreement with the analytical solution available for the UCM and Oldroyd-B models and reveal how non-Newtonian parameters influence stress distributions across different models.
Viscoelastic fluids, exhibiting both elastic and viscous properties, play a fundamental role in various industrial and biological applications. Accurate modeling of their rheological behavior requires constitutive equations that capture the complex interplay between these properties. The present study focuses on the analysis of incompressible, isothermal, two-dimensional, planar, laminar, submerged jet flow of viscoelastic fluids. A computational methodology is adopted to determine the polymer stress-tensor distribution for different viscoelastic models, including Oldroyd-B, UCM, Giesekus, Phan-Thien-Tanner (PTT), and finitely extensible nonlinear elastic (FENE). These models are chosen to represent a diverse range of viscoelastic behaviors. The Navier–Stokes equations, coupled with the appropriate constitutive model, are solved numerically. The proposed method allows one to access the distribution of the polymer stress-tensor components with very low computational cost. Results demonstrate the accuracy of the computational method for various models and their parameter values. The findings provide valuable insights into the fundamental behavior of viscoelastic jets and can serve as a foundation for subsequent linear and nonlinear stability investigations.
A new framework based on vortex dynamics has been developed for bidirectional FSI simulations to analyze open and closed saddle-shaped membrane structures. Leveraging the framework's vortex tracking capability, wind pressure and flow velocity characteristics of both structures were compared. Wind tunnel tests validated simulation accuracy, and combined with wind-induced response analysis, the risk differences between the two structural types were clarified.
The strong fluid–structure interaction (FSI) between the membrane structure and the surrounding airflow directly impacts the wind pressure distribution and structural stability, which are concerned with structural safety. This paper comparatively investigates the FSI of open and closed-type saddle-shaped membrane structures under wind loads, in terms of wind pressure distribution and flow field characteristics. First, a bidirectional FSI numerical simulation, integrated into this vortex dynamics-based framework, was implemented for the spatial membrane structure in laminar flows. The accuracy of the simulation was verified based on previous wind tunnel tests, from the perspective of both structural vibration and flow field. Subsequently, leveraging the framework's ability to track vortex evolution, a comparative analysis of wind pressure distribution and velocity trajectories was conducted for both configurations. Finally, the framework enabled a deep analysis of how vortex structures–their formation, development, and dissipation–influence structural vibration. The results indicate that the peak wind pressure coefficients of the open membrane structure at the leading edge under 0° and 90° wind directions reach 0.5 and 0.7, respectively. At a 45° wind direction, the flange area becomes a risk focus due to conical vortices. For closed membrane structures, the minimum average wind pressure coefficients under 0° and 90° wind directions were −0.52 and −1.0, respectively, with significant overall wind suction force. The open-type membrane structures exhibit both positive and negative pressure zones at all wind directions. Airflow separation results in wind pressure peaks at the leading edge of the windward side. Wind direction obviously affects the type of vortex structure, and the more sufficient vortex development would lead to increased trailing edge amplitude. Then, the local dynamic response of open-type membrane structures should be paid more attention. However, closed-type membrane structures experience upward lifting at all wind directions. The enhanced stiffness of the internal gas would reduce pulsations, and therefore the risk of structural overall instability should be considered as priorities.
We introduce a novel mesh-free method for steady incompressible flow by combining a Weighted Least Squares approximation with a High-Order Continuation Method. The approach solves the Navier–Stokes equations without mesh generation or numerical integration, using only discrete domain points. It improves accuracy and reduces computational cost compared to MLS-based formulations by avoiding weight-function derivative evaluation. Results show superior precision and efficiency relative to classical and recent mesh-free methods.
In this study, we present a novel mesh-free approach for solving incompressible fluid flow problems, which is introduced here for the first time. Our approach solves the steady-state Navier–Stokes equations without requiring traditional mesh generation. For this purpose, we adopt a discrete framework in which variables are defined at specific points within the domain, thereby eliminating the need for numerical integration. The proposed approach combines a weighted least squares (WLS) approximation with a high-order continuation method (HOCM). This approach significantly enhances the accuracy of steady-state incompressible flow simulations, offering both improved precision and reduced computation time compared to classical methods. Our results indicate that this approach holds substantial potential for expanding practical applications across various engineering fields. In contrast to the coupling of the moving least squares (MLS) method with the HOCM, our approach avoids computing derivatives of the weight function within the influence domain, which reduces the computational cost and enhances accuracy. This original combination highlights the novelty of our work compared to research conducted in recent years. A comparison is presented between the results obtained using the HOCM with MLS approximation and those reported in the literature.
A 2D/axisymmetric meshless ALE solver was developed for interior ballistics, with a 1-DOF shell model incorporating shot start pressure, engraving resistance, and bore friction. Validated on multiple benchmark test cases, the solver reproduced 155 mm shell acceleration, velocity, and displacement in close agreement with experiments. Spectral analysis revealed dominant frequencies (160–300 Hz) but no resonance with the 1316 Hz modal frequency. Pressure-wave amplitudes (3.52–14.24 MPa) stayed below failure.
This study presents a meshless computational framework for simulating unsteady fluid dynamics in interior ballistic applications. The proposed meshless method eliminates the need for grid generation and deformation by utilizing a cloud of dynamically moving points, based on the Arbitrary Lagrangian–Eulerian (ALE) formulation. The key novelty of this work is integrating the meshless solver with a moving points system, which makes it highly suitable for ballistics applications involving complex geometries. Furthermore, the combustion process has been simplified, streamlining the simulation by avoiding the need for fully modeling propellant combustion, as required in multiphase solvers. The framework discretizes the unsteady axisymmetric Euler equations using local weighted least-squares approximations to calculate derivatives. Numerical fluxes are computed using a modified Harten, Lax, van Leer, Contact (HLLC) scheme, which is essential for achieving high accuracy and effectively capturing complex flow features. Temporal evolution is handled using the Explicit Strong Stability Preserving (ESSP) Runge–Kutta method, ensuring stability and accuracy under unsteady flow conditions. The method is applied to interior ballistic simulations, such as the motion of an M107–155 mm shell launched through an M185 cannon, achieving excellent agreement with experimental observations, particularly in predicting muzzle velocity and peak pressure. The simplified setup of this framework enables it to handle large grid deformations and complex geometries, and makes it an efficient, high-fidelity solution for dynamic flow problems in ballistics and aerospace, serving as a reliable predictive and assessment tool for interior ballistics studies. Further, the pressure wave analysis conducted within this framework provides valuable insights for optimizing shell design and propellant combustion characteristics, while also enhancing its role as a predictive tool for assessing shell integrity and mitigating resonance-induced structural risks in interior ballistics applications.
This study investigates the impact of uncertain parameters on Navier–Stokes equations coupled with heat transfer using the Intrusive Polynomial Chaos Method (IPCM). Sensitivity equations are formulated for key input parameters, such as viscosity and thermal diffusivity, and solved numerically using the Finite Element-Volume method. The Rayleigh–Bénard convection test validates the approach, demonstrating its relevance to applications in solar energy, materials processing, and energy storage.
Performing sensitivity analysis in computational fluid dynamics is essential for assessing model robustness and reliability, since it determines how parameter variations or boundary conditions affect the simulation results. Specifically, this study focuses on the Navier–Stokes equations coupled with heat transfer, relevant to scenarios where temperature affects fluid flow behavior. Our sensitivity analysis is based on the Intrusive Polynomial Chaos Method (IPCM), which uses Probability Density Functions (PDFs) to describe stochastic variables. We extend previous work on uncertain initial or boundary conditions by focusing on input parameters such as viscosity and thermal diffusivity. We show that the sensitivity equations are well-posed and solve them numerically using the Finite Element Volume (FEV) method. The Rayleigh–Bénard convection test is used to validate the approach. This test is particularly relevant to applications in solar energy, materials processing, and energy storage, making it an excellent choice for demonstrating the effectiveness of our method.
The change in temperature distribution has the same pattern in section B in the case of all fins structure. From section A, it is observed that the difference in temperature distribution near the inlet for the two Re is maximum for triangular fins and least for rectangular fins. The difference in temperature distribution is in between these two fin structures in the case of circular fins.
Microchannels are used for thermal exchange because of their precise volume and higher heat dissipation capacity due to its surface to volume ratio. The thermal performance of microfluidic systems is greatly influenced by the dynamics of Newtonian and non-Newtonian fluid flows inside microchannels. In the current study, the regulation of temperature fluctuations within the working fluid is evaluated by executing the thermo-fluid coupling effects in micro-channels. For a combination of Newtonian–Newtonian and Newtonian–non-Newtonian influx fluid, the impact of flowing fluid on heat distributions with regards to micro-fins heat element sources within a microchannel was investigated numerically. Three micro-fins shape, viz., rectangular, triangular, and circular fin structures were used in the study. Rectangular fins had the largest as well as lowest heat transfer to the fluid flow for the combination of Newtonian–Newtonian fluids. It is also evaluated that for rectangular fins, the maximum Nu value obtained was 18.42 and the minimum Nu value obtained was 1.04. In addition, for triangular fins, the maximum Nu value obtained was 16.16 and the minimum Nu value obtained was 1.13. Finally, for circular fins, the maximum Nu value obtained was 9.82 and the minimum Nu value obtained was 1.22.
A one-dimensional shallow water model is coupled with a floating boat, which is assumed to be in hydrostatic equilibrium with the underlying water. Numerically, a semi-implicit discretization of the shallow water equations also includes the Archimedes' floating conditions in such a fashion that the boat's vertical position and pitch slope are simultaneously adjusted to the computed flow field. The resulting algorithm is well posed, physically consistent, numerically stable, extremely efficient, and fully conservative. A few numerical tests are included for illustrative purposes.
A one-dimensional shallow water model is coupled with a floating boat which is assumed to be in hydrostatic equilibrium with the underlying water. Numerically, a semi-implicit discretization of the shallow water equations also includes the Archimedes' floating conditions in such a fashion that the boat's vertical position and pitch slope are simultaneously adjusted to the computed flow field. The resulting algorithm is well-posed, physically consistent, numerically stable, extremely efficient, and fully conservative. A few numerical tests are included to confirm the model's accuracy and performance.
This study proposes a locally adaptive non-hydrostatic model, which is based on the non-hydrostatic extension of the shallow water equations (SWE) with a quadratic pressure relation, and applies it to wave propagation generated by a moving bottom. To obtain the locally adaptive model, we investigate several potential adaptivity criteria based on the hydrostatic SWE solution. The adaptive model yields similar accuracy as the global application of the non-hydrostatic extension while reducing the computational time by more than 50%.
We propose a locally adaptive non-hydrostatic model and apply it to wave propagation generated by a moving bottom. This model is based on the non-hydrostatic extension of the shallow water equations (SWE) with a quadratic pressure relation, which is suitable for weakly dispersive waves. The approximation is mathematically equivalent to the Green-Naghdi equations. Applied globally, the extension requires solving an elliptic system of equations in the whole domain at each time step. Therefore, we develop an adaptive model that reduces the application area of the extension, thereby reducing the computational time. The elliptic problem is only solved in the area where the dispersive effect might play a crucial role. To define the non-hydrostatic area, we investigate several potential criteria based on the hydrostatic SWE solution. We validate and illustrate how our adaptive model works by first applying it to simulate a simple propagating solitary wave, where exact solutions are known. Following that, we demonstrate the accuracy and efficiency of our approach in more complicated cases involving moving bottom-generated waves, where measured laboratory data serve as reference solutions. The adaptive model yields similar accuracy as the global application of the non-hydrostatic extension while reducing the computational time by more than 50%$$ 50\% $$.
This study utilized the delayed detached eddy simulation (DDES) technique to simulate the detailed flow field around a NACA0021 airfoil under two common flow control strategies: The Gurney flap and the combined leading- and trailing-edge flaps, both tested at a stall angle of attack of 20°. Subsequently, dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) were employed to analyze the flow structure characteristics derived from velocity field data. This analysis exposed the distinct patterns and mechanisms through which these two methods modulate the unsteady flow field on the airfoil surface during stall conditions and clarified the intrinsic differences in their impact on the airfoil's aerodynamic properties.
In aerospace engineering and wind turbine applications, flow control technologies improve the behavior of separated flows around airfoils by employing diverse methods. However, the effectiveness of these methods varies significantly. Therefore, it is necessary to conduct an in-depth analysis of the flow structure over the airfoil surface after applying flow control. This helps to gain a deeper understanding of the underlying physical mechanisms, thereby providing a theoretical basis for optimizing flow control techniques and guiding the selection of the most appropriate flow control strategies according to specific requirements. This study utilized the delayed detached eddy simulation (DDES) technique to simulate the detailed flow field around a NACA0021 airfoil under two common flow control strategies: The Gurney flap and the combined leading- and trailing-edge flaps, both tested at a stall angle of attack of 20°. Subsequently, dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) were employed to analyze the flow structure characteristics derived from velocity field data. This analysis exposed the distinct patterns and mechanisms through which these two methods modulate the unsteady flow field on the airfoil surface during stall conditions and clarified the intrinsic differences in their impact on the airfoil's aerodynamic properties. Highly instructive for in-depth study of flow control methods.
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Beibei Li
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Namkyeong Cho, Junseung Ryu, Hyung Ju Hwang
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Xupeng Cheng, Lijin Wang, Yanzhao Cao, Chen Chen
Publication date: Available online 20 January 2026
Source: Journal of Computational Physics
Author(s): Cagatay Guventurk, Mehmet Sahin
Publication date: Available online 19 January 2026
Source: Journal of Computational Physics
Author(s): Arnaud Colaïtis, Sébastien Guisset, Jérôme Breil
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Aviral Prakash, Ben S. Southworth, Marc L. Klasky
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Andrea Lamperti, Laura De Lorenzis
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Bo-Lin Wei, Jie Zhang, Ming-Jiu Ni
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Shuaihao Zhang, Jidong Zhao, Honghu Zhu, Xiangyu Hu
Publication date: 1 April 2026
Source: Journal of Computational Physics, Volume 550
Author(s): Antonio Ghidoni, Edoardo Mantecca, Gianmaria Noventa, David Pasquale
