Grid Refinement Research Articles

Numerical simulation of pendant droplet behavior on plain and patterned surfaces using Surface Evolver: Applications to condensation heat transfer

In this work, pendant water droplet behavior on a plain surface was simulated using the Surface Evolver (SE) finite element program to study the three-dimensional shape of the droplet on the surface. The critical droplet volume (CDV) before detachment from the surface was measured and compared against experimental data for different plain surfaces. These computational predictions were shown to agree well with experimental data. Next, patterned surfaces were studied which consisted of a central wetting region 2 mm to 5 mm wide sandwiched between two outer non-wetting superhydrophobic stripes. These superhydrophobic stripes served as “bumpers” to confine the droplet to the wetting region during its simulated growth. For these simulations, the primary inputs to the program were the droplet volume V, stripe width w, and surface static contact angle θ which was varied from 30° to 150°. Water droplet contact angle measurements on the plain surfaces used for initial benchmarking were also reported which included polished aluminum, mill finish aluminum, glass, plastic (acrylic), stainless steel, and copper. The idea of this study was to see if the superhydrophobic borders could be used to effectively “pinch off” a droplet in the wetting region, thereby reducing the critical droplet volume needed for detachment and drainage. The motivation for this work was condensation heat transfer which is common to many HVAC&R applications. In these systems, increasing the droplet shedding frequency is often associated with increased heat transfer and improved system efficiency.Therefore, the baseline surface adopted in this study was aluminum with and without the use of superhydrophobic stripes. For these simulations, properties of water at 20 °C were used, and the droplet volume was gradually increased until the critical condition was reached and detachment was detected. Typically, more than 1000 iterations were performed before the droplet geometry converged and was ready for measurement. Grid refinement was also performed to make sure that the results were grid independent. According to Surface Evolver, the lowest predicted critical droplet volume on the plain surfaces was <5 μL for θ1 = 150°, whereas the highest CDV was >295 μL for θ1 = 30°. For θ1 = 90° which is typical of aluminum, the CDV on the plain surface was 74 μL for the fine mesh and 83 μL for the rough mesh. When a 3-mm wide θ1 = 90° wetting region was used, however, bordered by two superhydrophobic stripes with θ2 = 150°, this CDV was reduced to 71 μL for the rough mesh, and when a 2-mm wide wetting region was used, the CDV was reduced even further to 55 μL. This shows both the promise of the idea and the possibility of using a striped / patterned tube to reduce the critical droplet volume needed for droplet shedding in a condensation environment.

Optimising hydrofoils using automated multi-fidelity surrogate models

ABSTRACT Lifting hydrofoils are gaining importance, since they drastically reduce the wetted surface area of a ship, thus decreasing resistance. To attain efficient hydrofoils, the geometries can be obtained from an automated optimisation process. However, hydrofoil simulations are computationally demanding, since fine meshes are needed to accurately capture the pressure field and the boundary layer on the hydrofoil. Simulation-based optimisation can therefore be very expensive. To speed up the fully automated hydrofoil optimisation procedure, we propose a multi-fidelity framework which takes advantage of both an efficient low-fidelity potential flow solver dedicated to hydrofoils and a high-fidelity RANS solver enhanced with adaptive grid refinement and dedicated foil-aligned overset meshes, to attain high accuracy with a limited computational budget. Both solvers are shown to be reliable for automatic simulation, and remarkable correlation between potential-flow and RANS results is obtained. Two different multi-fidelity frameworks are compared for a realistic hydrofoil: only RANS based and potential-RANS based. According to the optimisation results, the drag is able to be reduced by 17% and 8% in these frameworks, within a realistic time frame. Thus, industrial optimisation of hydrofoils appears possible. Finally, critical areas of future improvement regarding the robustness and efficiency of the optimisation procedure are discussed in this study.

A dynamic linearized wall model for turbulent flow simulation: Towards grid convergence in wall-modeled simulations

This paper addresses the common issue of (no-)grid convergence in wall-modeled numerical simulations and proposes a dynamic linearization technique applied to the Spalart-Allmaras wall model to achieve a proper behavior on fine grids and low-friction areas. A theoretical analysis of the numerical error committed on the shear stress balance close to the walls is performed. It shows that the error is due to the inappropriate imposition of too steep wall-normal velocity gradients that cannot be properly accounted for on the typical grids used for wall-modeled simulations. Based on this error quantification, a dedicated wall model linearization technique is proposed, following the approach developed by Tamaki, Harada and Imamura in 2017. In the proposed modified linearization method, the linearization distance is modified and adjusted dynamically. This is done according to the theoretical shear stress error estimate, in order to keep the numerical error below a user-defined threshold. The method is applied to well-referenced test cases of increasing complexity from the Turbulence Modeling Resource. Overall, the proposed wall model clearly exhibits appropriate grid convergence properties and is also able to predict accurately non-equilibrium boundary layers and flow separation using proper grid refinement.

Computational fluid dynamics for naval hydrodynamics

This article describes key issues which have to be addressed to apply Computational Fluid Dynamics to Naval Hydrodynamics. The specific aspects of Naval Hydrodynamics are discussed and illustrated by recent simulations and comparisons with available experiments. Free-surface flows with or without waves and even violent phenomena such as ventilation or cavitation can be modelled with mixture-fluid surface capturing. Turbulence modelling of thick boundary layers and vortical flows requires anisotropic RANS models or hybrid RANS/LES in case of strongly separated flows. Moreover, fluid–structure interaction in the form of rigid or flexible body motion and multi-body systems is crucial to represent ship manoeuvring and propulsion. Finally, the paper underlines the central role played by anisotropic adaptive grid refinement in the accurate simulation of marine flows.

Advantages of base isolation in reducing the reliability sensitivity to structural uncertainties of buildings

Base isolation is among the most effective techniques for safeguarding buildings against earthquakes. Similar to non-isolated buildings, the seismic performance of a base-isolated building can vary not only due to the inherent record-to-record variability in earthquake ground motions but also the non-negligible influence of uncertainties associated with structural properties. Introducing an isolation layer of isolation bearings and energy dissipators to the building further adds to the source of uncertainties, raising the question regarding the reliability of base isolated buildings. This study proposed a methodology that employs the probability density evolution method (PDEM) with local time grid refinement to evaluate the reliability of a base-isolated structure and its non-isolated counterpart under earthquakes of various magnitudes and fault distances. It allows for simultaneously considering the uncertainties of various sources in the reliability analyses with affordable computational cost, including those of the ground motions, of the structural nonlinearity, and of the ultimate states that define the reliability. The results show that the base-isolated building exhibits much higher reliability than its non-isolated counterpart in all cases even if the ultimate behavior such as the isolator fracture or the impact to the retaining wall is considered. The added source of uncertainties in the isolation layer does not exhibit a notable impact on the reliability. In contrast, the seismic reliability of base-isolated buildings is much less sensitive to structural uncertainties than that of their non-isolated counterparts.

Condensate Banking Analysis Optimizes Reservoir Development in Permian Basin

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 4044947, “Numerical Analysis of Condensate Banking and Development Optimization in the Deep Formation of the Permian Basin,” by Jichao Han, SPE, Sunil Lakshminarayanan, and Jiasen Tan, SPE, Oxy, et al. The paper has not been peer reviewed. _ In the context of unconventional reservoir development, the issue of condensate banking—a factor contributing to reduced productivity in gas condensate reservoirs when the reservoir pressure falls below the dewpoint pressure—poses a constant concern. Before implementation of any mitigation strategies, it is prudent to assess the potential of condensate banking in the future, based on the limited early production data. A specialized workflow was devised for a deep formation in the Permian Basin. This workflow aims to quantify the severity of condensate banking and subsequently optimize reservoir development strategies. Introduction Well A represents a single appraisal well situated within deep formations of the Permian Basin. With only 5 months of production data available, pressure/volume/temperature analysis and modeling identified it as a gas condensate reservoir, with the dewpoint very close to the critical point. This prompts two critical business inquiries: Are there any concerns regarding condensate banking for this well? And what are the optimal drawdown strategies tailored to this specific format surrounding the appraisal well? Model Setup and Calibration Modeling Workflow. This study uses the comprehensive simulation workflow derived from Hydraulic Fracturing Test Site 2, which can effectively handle integrated models to provide valuable insight for condensate banking analysis and reservoir development optimization (Fig. 1). Hydraulic fracture and reservoir simulations were conducted using GOHFER 3D and Navigator software, respectively. The integration of fracture and reservoir models poses a significant challenge in accurately transferring fracture geometry and conductivity information from fracture simulators to reservoir simulators. To address this challenge, an in‑house preprocessor was developed, designed to project results from the fracture simulator into the reservoir simulator seamlessly, ensuring the fidelity of complex fracture geometries. This preprocessor enables the extension or contraction of fracture geometries in proportion to reduce uncertainties imposed by production data. Additionally, fracture conductivity is determined through regional correlations among proppant concentration, net closure stress, and fracture conductivity. Model Introduction. The geological model has been simplified to enhance modeling efficiency while still meeting the project requirements. The 3D geological model adopts a layer-cake structure with a flat geostructure. To ensure accuracy, the well trajectory is adjusted to align with the desired formation. The reservoir model measures 4,000×10,000×330 ft, with a grid resolution of 200×25×10 ft. Fracture geometry is imported from the fracture simulator, while fracture conductivity is primarily determined based on proppant concentration data exported from the fracture simulator. Fracture height remains unaltered in the reservoir simulator, reflecting available geochemical measurements. A compositional simulation approach is adopted instead of a black-oil model. To improve the accuracy of pressure drop and condensate dropout predictions, the local grid refinement (LGR) approach is selected, resulting in denser grids. This approach proves superior to the dual-porosity, dual-permeability (DPDP) method.

Magnetic dissipation in short gamma-ray-burst jets

Aims. Short gamma-ray bursts originate when relativistic jets emerge from the remnants of binary neutron star (BNS) mergers, as observed in the first multi-messenger event GW170817–GRB 170817A, which coincided with a gravitational wave signal. Both the jet and the remnant are believed to be magnetized, and the presence of magnetic fields is known to influence the jet propagation across the surrounding post-merger environment. In the magnetic interplay between the jet and the environment itself, effects due to a finite plasma conductivity may be important, especially in the first phases of jet propagation. We aim to investigate these effects, from jet launching to its final breakout from the post-merger environment. Methods. We used the PLUTO numerical code to perform 2D axisymmetric and full 3D resistive relativistic magnetohydrodynamic (MHD) simulations, employing spherical coordinates with spatial radial stretching. We considered and compared different models for physical resistivity, which must be small but still dominating over the intrinsic numerical dissipation (which yields unwanted smearing of structures in any ideal MHD code). Stiff terms in the current density are treated with IMplicit-EXplicit Runge Kutta algorithms for time-stepping. A Synge-like gas (Taub equation of state) is also considered. All simulations were performed using an axisymmetric analytical model for both the jet propagation environment and the jet injection; we leave the case of jet propagation in a realistic environment (i.e., imported from an actual BNS merger simulation) to a future study. Results. As expected, no qualitative differences are detected due to the effect of a finite conductivity, but significant quantitative differences in the jet structure and induced turbulence are clearly seen in 2D axisymmetric simulations, and we also compare different resistivity models. We see the formation of regions with a resistive electric field parallel to the magnetic field, and nonthermal particle acceleration may be enhanced there. The level of dissipated Ohmic power is also dependent on the various recipes for resistivity. Most of the differences arise before the breakout from the inner environment, whereas once the jet enters the external weakly magnetized environment region, these differences are preserved during further propagation despite the lower grid refinement. Finally, we show and discuss the 3D evolution of the jet within the same environment in order to highlight the emergence of nonaxisymmetric features.

Comparative Analysis and Application of Mass and Heat Transfer Simulation in Fractured Reservoirs Based on Two Fracture Models

The projection-based embedded discrete fracture model (pEDFM) and its counterpart, the embedded discrete fracture model (EDFM), have become standard tools for the depiction of the fractures in reservoir simulations. Despite their widespread use, there are still some unclear areas in modeling the complex processes of mass and heat transfer within fractured reservoirs, particularly in both single-phase and multiphase flow scenarios. Our research introduces a numerical methodology for simulating the mass and heat transfer in fractured reservoirs which is developed by extending the framework of the pEDFM and EDFM. To gauge the effectiveness of these models, we devised two cases which were designed to evaluate the adaptability of the pEDFM and EDFM in scenarios involving an ultra-low permeability fracture or a high permeability fracture under single-phase and multiphase conditions. By using local grid refinement (LGR) as a reference, the results of the pEDFM were in reasonably good agreement with the LGR in terms of pressure, temperature, and saturation distributions. This comparison suggests that the pEDFM has a significant advantage in depicting the mass and heat transfer at the matrix–fracture interface compared to the EDFM. Furthermore, a comprehensive analysis of the flow trajectories in both the pEDFM and EDFM provided a reasonable explanation for their differences. Furthermore, the numerical applications involving the heat extraction of Enhanced Geothermal Systems (EGSs) and the water flooding in fractured reservoirs illustrate the adaptability of the pEDFM in the numerical simulation for complex geological conditions. The insights and conclusions obtained in this paper can enhance our understanding of the distinctions between the pEDFM and EDFM, aiding in the selection of the most suitable method for characterizing the fractures in numerical simulations.

A novel energy-bounded Boussinesq model and a well balanced and stable numerical discretisation

Many Boussinesq models suffer from nonlinear instabilities, especially in the context of rapid variations in the bed topography. In this work, a Boussinesq system is put forward which is derived in such a way as to be both linearly and nonlinearly energy-stable.The proposed system is designed to be robust for coastal simulations with sharply varying bathymetric features while maintaining the dispersive accuracy at any constant depth. For constant bathymetries, the system has the same linear dispersion relation as Peregrine's system ([22]). Furthermore, the system transitions smoothly to the shallow-water system as the depth goes to zero.In the one-dimensional case, we design a stable finite-volume scheme and demonstrate its robustness, accuracy and stability under grid refinement in a suite of test problems including Dingemans's wave experiment.Finally, we generalise the system to the two-dimensional case.

A two‐way coupling approach for simulating bouncing droplets

AbstractThis article presents a two‐way coupling approach to simulate bouncing droplet phenomena by incorporating the lubricated thin aerodynamic gap between fluid volumes. At the heart of our framework lies a cut‐cell representation of the thin air film between colliding liquid fluid volumes. The air pressures within the thin film, modeled using a reduced fluid model based on the lubrication theory, are coupled with the volumetric liquid pressures by the gradient across the liquid–air interfaces and solved in a monolithic two‐way coupling system. Our method can accurately solve liquid–liquid interaction with air films without adaptive grid refinements, enabling accurate simulation of many novel surface‐tension‐driven phenomena such as droplet collisions, bouncing droplets, and promenading pairs.

Shock-driven three-fluid mixing with various chevron interface configurations

When a shock wave crosses a density interface, the Richtmyer–Meshkov instability causes perturbations to grow. Richtmyer–Meshkov instabilities arise from the deposition of vorticity from the misaligned density and pressure gradients at the shock front. In many engineering applications, microscopic surface roughness will grow into multi-mode perturbations, inducing mixing between the fluid on either side of an initial interface. Applications often have multiple interfaces, some of which are close enough to interact in the later stages of instability growth. In this study, we numerically investigate the mixing of a three-layer system with periodic zigzag (or chevron) interfaces, calculating the dependence of the width and mass of mixed material on properties such as the shock timing, chevron amplitude, multi-mode perturbation spectrum, density ratio, and shock mach number. The multi-mode case is also compared with a single-mode perturbation. The Flash hydrodynamic code is used to solve the Euler equations in three dimensions with adaptive grid refinement. Key results include a significant increase in mixed mass when changing from a single-mode to a multi-mode perturbation on one of the interfaces. The mixed width is mainly sensitive to the density ratio and chevron amplitude, whereas the mixed mass also depends on the multi-mode spectrum. Steeper initial perturbation spectra have lower mixed mass at early times but a greater mixed mass after the reflected shock transits back across the layer.

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

Analysis of ansys fluent for Wall-Modeled Large-Eddy Simulation of Turbulent Channel Flow

Abstract This study assesses the accuracy of ansysfluent 19.2, a commonly employed general-purpose finite volume solver, in the context of wall-modeled large-eddy simulation for turbulent channel flow at a moderate Reynolds number, Reτ=2000. The sensitivity of the solution to variations in grid resolution, aspect ratio, grid arrangement (collocated versus staggered), and subgrid-scale (SGS) model is analyzed and contrasted to results from a corresponding direct numerical simulation (DNS) and a mixed pseudospectral and finite differences solver. Results indicate good convergence of first- and second-order statistics from the staggered grid setups as the grid is refined, whereas no clear trend is observed in cases with collocated grid setups. Velocity spectra show a lack of an apparent inertial range trend and rapid decay of energy density at high wavenumbers, with a spurious energy pile-up near the cutoff wavenumber indicating the presence of unphysical oscillations in the velocity fields. Grid refinement strengthens such oscillations in collocated grid setups and reduces them in staggered grid setups. Two-point streamwise velocity autocorrelation maps reveal an underprediction of turbulent structure size. In contrast, cross-stream autocorrelations agree with corresponding curves from direct numerical simulation, showing signatures of alternating high- and low-momentum streaks in the logarithmic layer.

A Highly Efficient Compressive Sensing Algorithm Based on Root-Sparse Bayesian Learning for RFPA Radar

Off-grid issues and high computational complexity are two major challenges faced by sparse Bayesian learning (SBL)-based compressive sensing (CS) algorithms used for random frequency pulse interval agile (RFPA) radar. Therefore, this paper proposes an off-grid CS algorithm for RFPA radar based on Root-SBL to address these issues. To effectively cope with off-grid issues, this paper derives a root-solving formula inspired by the Root-SBL algorithm for velocity parameters applicable to RFPA radar, thus enabling the proposed algorithm to directly solve the velocity parameters of targets during the fine search stage. Meanwhile, to ensure computational feasibility, the proposed algorithm utilizes a simple single-level hierarchical prior distribution model and employs the derived root-solving formula to avoid the refinement of velocity grids. Moreover, during the fine search stage, the proposed algorithm combines the fixed-point strategy with the Expectation-Maximization algorithm to update the hyperparameters, further reducing computational complexity. In terms of implementation, the proposed algorithm updates hyperparameters based on the single-level prior distribution to approximate values for the range and velocity parameters during the coarse search stage. Subsequently, in the fine search stage, the proposed algorithm performs a grid search only in the range dimension and uses the derived root-solving formula to directly solve for the target velocity parameters. Simulation results demonstrate that the proposed algorithm maintains low computational complexity while exhibiting stable performance for parameter estimation in various multi-target off-grid scenarios.

Predicting Oil Recovery Under Uncertainty for Huff ‘n’ Puff Gas Injection: A Field Case Study in the Permian Basin

Summary The extent and size of the fracture network connected to the wellbore are among the most uncertain parameters for multifractured horizontal wells. The uncertainty has a profound impact on production under primary depletion and has an even bigger impact on the recovery during huff ‘n’ puff (HnP) gas injection. In this paper, we quantify the uncertainty in reservoir properties and enhanced oil recovery (EOR) for a pair of wells in the Permian basin. In addition, we report on the lessons learned from modeling a field pilot HnP project involving four cycles using reservoir simulation. We create a base sector model for two wells completed in Wolfcamp B and C formations, where fractures are incorporated using an embedded discrete fracture model. For each well, we identify 13 uncertain parameters (describing fracture properties and compaction, initial conditions, and relative permeability). We use a Bayesian assisted-history-matching (AHM) method to match primary production data. Our study emphasizes the critical role of grid refinement for the accurate depiction of the gas-injection process by comparing three models with varying grid sizes. Additionally, we study the impact of molecular diffusion on oil and gas recovery using different diffusion coefficients. Another significant factor is the dynamic nature of the fracture network during cyclic injection, as indicated by evidence of communication between the wells. This makes the accessible fracture area during injection highly uncertain. To address interwell interference, we incorporate an additional fracture network activated during injection. To manage the uncertainty of active fracture area, we created four scenarios within the literature range, approximately 0.5, 1, 2, and 4 million ft² per stage, and tuned their properties to match historical HnP data. The production predictions from the AHM solutions were extended beyond the initial four HnP cycles to provide probabilistic forecasts. We demonstrate that grid refinement has a minimal effect on production under primary depletion but significantly influences HnP recovery. We attribute this disparity to numerical dispersion, which causes the artificial mixing of gas in the large gridblocks, leading to an overly optimistic recovery. Activating the molecular-diffusion mechanism results in a negligible impact on the recovery in our case. The contribution of molecular diffusion becomes noticeable only when diffusion coefficients exceed ten times the reported values. This leads us to conclude that molecular diffusion is of second-order importance compared with advection and can generally be neglected in our case. This finding should not be generalized to all shale formations. In reservoirs characterized by lower permeability and fluids with higher diffusion coefficients, molecular diffusion could still play a crucial role. We highlight that the contacted-fracture area, which is often underestimated in the reservoir simulation practice, is a critical factor for accurate modeling. Production for 37 filtered AHM solutions is extended under the four scenarios with variable fracture surface areas. Based on our analysis, we report that the HnP results in an average of 76% improvement in oil recovery compared with natural depletion.

Prediction–correction projection immersed interface method for interfacial stress-induced flows and applications to electrohydrodynamics

We propose a robust, high-resolution prediction–correction projection immersed interface method (IIM) for solving the unsteady incompressible Navier–Stokes equations with traction boundary conditions, which arise from free surface flows driven by capillary, electric, and elastic forces. This method combines the advantages of traditional body-fitted moving mesh methods and immersed boundary methods (IBM), allowing for the accurate imposition of boundary conditions on free surfaces using Cartesian grids and providing detailed interface information that is typically smoothed out in traditional IBM. The irregular liquid-phase domain is embedded within a square region and discretized using a dynamically adaptive Cartesian mesh. The free surface is captured using a narrow-band level set with hybrid reinitialization. A prediction–correction projection scheme is constructed, incorporating additional pressure predictions and corrections to enhance robustness. The resulting Helmholtz/Poisson equations are solved using the augmented IIM for boundary value problems. Grid refinement analysis demonstrates second-order convergence of the L∞ error, even in challenging cases such as the oscillating drop test with low viscosity. We further apply this method to electrohydrodynamic (EHD) problems, constructing an implicit augmented IIM to solve the equations governing the electric field and charge conservation. Numerical experiments demonstrate that this method accurately addresses highly intense EHD phenomena, such as the formation of Taylor cones, highlighting its robustness.

High-Resolution Identification of Sound Sources Based on Sparse Bayesian Learning with Grid Adaptive Split Refinement

Sound source identification technology based on a microphone array has many application scenarios. The compressive beamforming method has attracted much attention due to its high accuracy and high-resolution performance. However, for the far-field measurement problem of large microphone arrays, existing methods based on fixed grids have the defect of basis mismatch. Due to the large number of grid points representing potential sound source locations, the identification accuracy of traditional grid adjustment methods also needs to be improved. To solve this problem, this paper proposes a sound source identification method based on adaptive grid splitting and refinement. First, the initial source locations are obtained through a sparse Bayesian learning framework. Then, higher-weight candidate grids are retained, and local regions near them are split and updated. During the iteration process, Green’s function and the source strength obtained in the previous iteration are multiplied to get the sound pressure matrix. The robust principal component analysis model of the Gaussian mixture separates and replaces the sound pressure matrix with a low-rank matrix. The actual sound source locations are gradually approximated through the dynamically adjusted sound pressure low-rank matrix and optimized grid transfer matrix. The performance of the method is verified through numerical simulations. In addition, experiments on a standard aircraft model are conducted in a wind tunnel and speakers are installed on the model, proving that the proposed method can achieve fast, high-precision imaging of low-frequency sound sources in an extensive dynamic range at long distances.

Characterization of Wormhole Growth and Propagation Dynamics during CHOPS Processes by Integrating Rate Transient Analysis and a Pressure-Gradient-Based Sand Failure Criterion in the Presence of Foamy Oil Behavior

Summary Characterization of wormhole growth and propagation dynamics has been made possible with the semi-analytical models developed in this work by integrating both rate transient analysis (RTA) and a pressure-gradient-based (PGB) sand failure criterion in the presence of foamy oil behavior. The nonlinearity caused by the foamy oil properties is linearized using pseudofunctions, while the source function and finite difference methods are applied to obtain the solutions for the linearized models in the matrix and wormhole subsystems, respectively. A sequential method is adopted to solve the coupling fluid-solid problem, where new wormhole segments can be generated once the PGB sand failure criterion has been achieved, while their updated petrophysical properties can be sent back to obtain the solutions for the fluid flow in the next time interval. Furthermore, the influence of sand failure/fluidizing and foamy oil properties on the dynamic wormhole network can be investigated with the generated type curves. Both wormhole growth and foamy oil flow dictate an upward fluid production at the early times, while the production-induced pressure depletion dominates the declining production at the late times. The fractal wormhole networks can be dynamically characterized by history matching the field fluid and sand production profiles. Both the sand failure degree and foamy oil properties dictate the effective wormhole coverage and intensity. Sand production is found to be influenced by both the breakdown pressure gradient and wormhole conductivities, while oil production rate can be dominated by the wormhole coverage and intensity. Foamy oil flow can increase the oil production rate and increase the wormhole coverage compared with the conventional oil. The newly developed method in this work has been validated and then applied at field scale to dynamically characterize the wormhole growth and propagation by considering both the sand failure phenomenon and foamy oil properties within a unified, consistent, and accurate framework. Compared to the conventional numerical simulations, the novelty of such a semi-analytical method can not only allow us to characterize the growth and propagation dynamics of the fractal-like wormholes without the need for grid refinement near the wormhole grids but also take the complex sand failure and foamy oil behavior into account. In addition, it can minimize the impact of grid orientation effects in numerical simulations, enabling the growth and propagation of the wormholes in arbitrary directions rather than orthogonal directions conditioned to the largest pressure gradient.

High-fidelity fluid-structure interaction applied to static aeroelasticity in transonic flows

Transonic flows at high Reynolds numbers can lead to high dynamic pressures and, consequently, to aerostructural deflections of aircraft structures. This study aims to develop and validate a high-fidelity static aeroelastic analysis environment that is efficient and that can be used in an industrial setting. The aerodynamics is represented by numerical solutions of the Reynolds-averaged Navier-Stokes equations with appropriate turbulence closures. The load transfer process uses finite element shape functions in order to distribute the aerodynamic loads into the structural discretization. The structural analysis employs a modal basis approach, and a wingtip deflection convergence study is performed to find an adequate modal basis size. Radial basis functions are used for the fluid mesh displacement, and the influence of the support radius is evaluated to determine the optimal values relative to the wing mean aerodynamic chord. The capability is tested using the static aeroelastic benchmarks of the High Reynolds Aerostructural Dynamics Project (HIRENASD) and NASA's Common Research Model (CRM). The static aeroelastic results demonstrate robustness and consistency for the aerodynamic coefficients, pressure distributions, and structural deflection predictions at different normalized dynamic pressure values and grid refinement levels.

Verification and validation of a coupled CFD–FEM approach with overset structured grid through free decay and regular wave tests

This paper presents a comprehensive verification and validation study applied to the hydrodynamic analysis of a semi-submersible Floating Offshore Wind Turbine (FOWT) platform. The numerical simulation is conducted using a coupled Computational Fluid Dynamics-Finite Element Method (CFD–FEM) approach. The CFD program incorporates an overset grid interpolation method, facilitating a more systematic grid refinement in the estimation of discretization uncertainties. A mooring analysis program, based on the FEM scheme, is integrated with the CFD program to simulate the dynamic responses of mooring system. The necessity of the nonlinear mooring model is demonstrated by comparing solutions with a comparative test using a linear mooring model. The verification study, based on a least-squares-based extrapolation method, quantifies the spatial and temporal discretization errors of the numerical model. The numerical solutions based on the baseline model are further validated against the model test measurements. A pitch free decay model test and a regular wave model test conducted within the OC5 project are utilized for the verification and validation study. Results from both tests demonstrate the reliability and accuracy of the coupled method.