Numerical Simulation Data Research Articles

A response surface equation for the drag polar for an airplane flying in the vicinity of wavy sea surface

The drag polar equation is the key issue to calculate the performance-based parameters during various flight phases and determine the optimum conditions. This is an essential feature to be included in airplane flight control system to manage the flight. The aircraft under certain emergency conditions are instructed to land on sea water. This underlines the combinational role of ground effect and the surface wave shape on airplane aerodynamic responses. Up to now, many investigations have described the airfoil and wing aerodynamic behaviors near the ground but none was devoted to an airplane flying near a wavy surface. In this paper, intensive numerical simulations have been carried out on a general aviation airplane flying near the water wavy surface. The effects of ground proximity as well as the wave amplitude have been investigated on airplane 2D longitudinal forces and moment. Some limited wind tunnel tests have also been performed on the same model, in the vicinity of water surface to validate the numerical calculations. A statistical quadratic equation based on Response Surface Model, RSM, has been proposed for the airplane flying in the vicinity of the wavy water in which, the wave shape deterioration due to both the airplane flowfield and the viscous dissipation has been taken into account. The statistical measures approve the model quality and accuracy in comparison to the numerical simulation data. The results show that the oscillations in aerodynamic forces are strong functions of the wave amplitude. The time variations of both CL and CD follow the shape of the surface wave while it does not have any remarkable effect on their mean values.

Data-Guided Low-Reynolds-Number Corrections for Two-Equation Models

Abstract The baseline Launder–Spalding k−ε model cannot be integrated to the wall. This paper seeks to incorporate the entire law of the wall into the model while preserving the original k−ε framework structure. Our approach involves modifying the unclosed dissipation terms in the k and ε equations specifically within the wall layer according to direct numerical simulation (DNS) data. The resulting model effectively captures the mean flow characteristics in both the buffer layer and the logarithmic layer, resulting in robust predictions of skin friction for zero-pressure-gradient (ZPG) flat-plate boundary layers and plane channels. To further validate our formulation, we apply our model to boundary layers under varying pressure gradients, channels experiencing sudden deceleration, and flow over periodic hills, with highly favorable results. Although not the focus of this study, the methodology here applies equally to the k–ω formulation and yields improved predictions of the mean flow in the viscous sublayer and buffer layer.

Dynamics of non-Newtonian fluid–fiber interactions and void formation mechanism based on fused filament fabrication

Due to the presence of internal defects such as voids in the composites manufactured by material extrusion additive manufacturing (MEX AM), the mechanical properties of the composites are significantly below the theoretical optimum. Under this circumstance, this paper is intended to investigate the effects of nozzle feeding angles and to analyze the void formation and evolution of multiphase flow, in which systematic computational fluid dynamics numerical simulations are conducted. The volume of fluid model and overset grid method are used to simulate the extrusion deposition process of carbon fiber-reinforced polymer composites, and the Carreau model is used to represent the shear-thinning behavior of molten polymer. The numerical method is validated against previously experimental and numerical simulation data. The numerical results show that the key factor leading to void formation is the vortices caused by fiber oscillation. The intense vortex at the front end of the fibers disrupts the interface between molten polymer and air, creating a beneficial condition for air to enter. Nozzle tilting can effectively reduce the probability of void formation by decreasing the fiber oscillation velocity. The results of the present study provide insights into the development and optimization of printer nozzles to enable the printing of longer fibers with less probability of potential void formation.

Dynamic characteristics and prediction and control models of subsonic exhaust from a container

This study combines experimental measurements, numerical simulations, and theoretical analysis to investigate the subsonic discharge process in a container under normal temperature and pressure conditions. Experimental data captured the internal pressure dynamics during exhaust at the atmospheric environmental pressure. Numerical simulations using OpenFOAM validated the isothermal exhaust model against the experimental results. Under the assumption of ideal gas and isothermal processes, a nonlinear differential equation was derived to describe the evolution of the container's internal pressure. This equation was simplified for a specific range of pressure ratios, yielding analytical solutions for the internal pressure of the container under both constant and variable external pressures. The effectiveness of the expressions of pressure inside the container was verified by comparing them with experimental and numerical simulation data. We further developed a formula for predicting exhaust mass flow rate, with a prediction error within 9%. An improved formula was subsequently proposed to reduce the error to below 0.4%, enhancing prediction accuracy. For containers with variable external pressure, a method for controlling the exhaust mass flow rate by predicting external pressure changes was proposed, demonstrating its effectiveness in achieving precise control.

Eddy viscosity enhanced temporal direct deconvolution model for temporal large-eddy simulation of turbulent channel flow

In this work, a novel eddy viscosity enhanced temporal direct deconvolution model (TDDM) is proposed for temporal large-eddy simulation (TLES) of turbulent channel flow at large filter widths. To improve the accuracy of the constant eddy viscosity (CEV) model, particularly in the near-wall region, a damping function is incorporated to refine its performance. Moreover, a spatial filtering strategy is introduced to reduce the aliasing errors associated with the computation of subfilter-scale (SFS) stress, thereby enhancing numerical stability. In the a posteriori study, the accuracy of the CEV model is assessed comprehensively by comparing the TLES results with corresponding temporally filtered direct numerical simulation data. The results demonstrate that the CEV-enhanced TDDM provides accurate predictions across various statistical properties of velocity, instantaneous flow structures, kinetic energy spectra, and SFS energy fluxes. The coefficient sensitivity analysis of the CEV model reveals that the model coefficient significantly influences low Reynolds number flows, while its impact on high Reynolds number flows is relatively small. TLES on coarse grids demonstrate that the CEV-enhanced TDDM exhibits strong robustness and accuracy at different grid resolutions. Additionally, the CEV-enhanced TDDM in high Reynolds number flows is stable and accurate at remarkably large filter widths.

A data-driven approach to analyze bubble deformation in turbulence

Bubble deformation and breakup from turbulence is present in many engineering applications and in nature, yet the physical mechanisms still remain poorly understood. Depending on the local turbulence intensity or Weber number, a bubble may either deform without breakup, suffer a violent breakup, or exhibit a resonant behavior, where the turbulent eddies excite the bubble's natural frequencies. Recent studies have used spherical harmonic decomposition to analyze bubble interaction with turbulence, quantifying the deformation energy of each eigenmode. However, this approach is only applicable for small levels of deformation (linear regime), while the bubble shape remains close to a sphere. In the present work, we present a novel data-driven approach combining large deformation diffeomorphic metric mapping and proper orthogonal decomposition, which is more robust for large deformations. The method is tested on a set of validation cases and applied to turbulent bubble deformation cases obtained from direct numerical simulations data.

Self-supervised learning for effective denoising of flow fields

In this study, we proposed an efficient approach based on a deep learning (DL) denoising autoencoder (DAE) model for denoising noisy flow fields. The DAE operates on a self-learning principle and does not require clean data as training labels. Furthermore, investigations into the denoising mechanism of the DAE revealed that its bottleneck structure with a compact latent space enhances denoising efficacy. Meanwhile, we also developed a deep multiscale DAE for denoising turbulent flow fields. Furthermore, we used conventional noise filters to denoise the flow fields and performed a comparative analysis with the results from the DL method. The effectiveness of the proposed DL models was evaluated using direct numerical simulation data of laminar flow around a square cylinder and turbulent channel flow data at various Reynolds numbers. For every case, synthetic noise was augmented in the data. A separate experiment used particle-image velocimetry data of laminar flow around a square cylinder containing real noise to test DAE denoising performance. Instantaneous contours and flow statistical results were used to verify the alignment between the denoised data and ground truth. The findings confirmed that the proposed method could effectively denoise noisy flow data, including turbulent flow scenarios. Furthermore, the proposed method exhibited excellent generalization, efficiently denoising noise with various types and intensities.

Proper orthogonal decomposition of wall-bounded high-pressure transcritical fluids

This study explores the principal modes of high-pressure transcritical channel flow from direct numerical simulation data. The four cases investigated correspond to CO2 at high-pressure conditions (P/Pc=1.5) confined between a cold/bottom wall (T/Tc=0.8−0.95) and a hot/top wall (T/Tc=1.1−1.4); Pc and Tc correspond, respectively, to the pressure and temperature of the critical point. The bulk velocity ranges between Ub=0.5−1.0 m/s with corresponding bulk Reynolds numbers of Reb≈1000−2500. The four cases considered are first characterized into laminar and turbulent regimes, followed by an analysis of energy decay using singular value decomposition. This method allows us to identify the most energetic modes of velocity, temperature, and specific isobaric heat capacity for the laminar and turbulent cases considered. The results reveal that fewer modes are needed to represent the hydrodynamics compared to the thermodynamics of the system. The findings also highlight that the pseudo-boiling region, prevalent in high-pressure transcritical systems, disrupts the coherent structures formed (especially) in the hotter region of the flow. Finally, a correlation analysis between the most energetic modes shows an interdependence between velocity and specific isobaric heat capacity modes when conditioned to focus solely on the pseudo-boiling affected regions. This correlation underscores the complex interplay between hydrodynamic and thermodynamic variables in such high-pressure transcritical environments.

Calculation of thermodynamic properties and transport coefficients of Ar/N2–H2–Si plasma

Abstract The composition, thermodynamic properties and transport coefficients of Ar – H 2 – Si and N 2 – H 2 – Si plasma within a temperature range of 300–30 000 K and pressure range of 0.1–10 atm are calculated under the assumptions of local thermal equilibrium (LTE) and local chemical equilibrium (LCE). Taking Debye–Hückel corrections into account, the chemical equilibrium composition and thermodynamic properties of these two plasma systems are derived using the mass action law and classical statistical thermodynamics respectively. The transport coefficients, including viscosity, conductivity, and thermal conductivity, are calculated using the Chapman–Enskog (C–E) method extended to a third-order approximation (second-order for viscosity and heavy particle translational thermal conductivity). Some of the results have been compared with those of other researchers, and there is a good level of agreement. The slight difference arises from the selection of interaction potential. The final calculation reveals that the introduction of silicon vapor significantly alters the thermodynamic properties and transport coefficients of Ar / N 2 – H 2 – Si plasma, even at a small concentration of silicon vapor (1%), the effect on the electrical conductivity cannot be ignored. Furthermore, our calculation results provide the fundamental data for numerical simulations of magnetohydrodynamics (MHD) for the synthesis of silicon nanoparticles and silicon composites.

A volume‐averaging and stochastic turbulence modeling framework for homogeneous roughness‐induced drag in turbulent flows

AbstractThe goal of this work is the formulation of a model for the parameterization of homogeneous roughness‐induced drag in turbulent flow simulations. We characterize rough surfaces using their surface‐area moments of roughness‐peaks. Additionally, we consider a probabilistic self‐similar power law distribution for the roughness heights, in such a way that an assumed set of discrete roughness elements can behave as a probabilistic fractal set. Upon these assumptions, the surface characterization is complete and yields wall‐normal profiles of porosity, average roughness element diameter, and equivalent pore diameter of the roughness affected porous flow. The profiles are supplied to a (pore‐based) Reynolds number and porosity‐based drag parameterization for staggered cylinder arrays available in the literature, as well as a one‐dimensional map‐based turbulence model, the one‐dimensional turbulence (ODT) model. The purpose of the latter is a way to provide the missing effects of the equivalent dispersion tensor in the porous flow close to the rough surface, as well as that of the nonlinear turbulent transport away from the wall. Simulations are then carried out in order to evaluate the effects of two different rough surfaces on a turbulent channel flow, comparing results with existing direct numerical simulation (DNS) data. Overall, reasonable agreement is obtained, which suggests that, by using the proposed model, it is possible to model the effects of rough surfaces on wall‐bounded turbulent flows, without the explicit need of the full topological representation of the surface on the numerical domain. To that extent, one clear flow control application for the suggested approach would be that of drag‐based surface optimization.

Study on Wind Farm Flow Field Characteristics Based on Boundary Condition Optimization of Complex Mountain Numerical Simulation

The accurate prediction of the flow field characteristics of complex mountains is of great practical significance for the development and construction of wind farms, but it is not yet fully understood. The main purpose of this study is to propose a method for the study of flow field characteristics under complex mountain conditions, which can optimize the boundary conditions required for numerical simulation through the wind acceleration ratio and, at the same time, couple the numerical simulation and wind measurement data to reflect the real mountain flow field distribution. The results show that the proposed method has good applicability in complex mountain wind farms, can reproduce the real flow field distribution, and has a certain practical value. Wind speed distribution and turbulence intensity are greatly affected by boundary conditions such as wind speed and wind direction and are also affected by the shielding effect brought by terrain changes. The contrast between 120° and 150° wind direction is more obvious. When the incoming wind moves to the top of a mountain or the ridgeline, it will form a low-speed wake area behind it, resulting in reduced wind speed, increased turbulence intensity, and an unstable flow field.

An explicit multilevel power turbulent wall function based on the de-thresholding Douglas–Peucker algorithm

Wall functions are extensively applied in engineering simulations with turbulence. They facilitate a significant increase in the scale of the grids next to the wall, which in turn reduces the total number of grids needed. This optimization enhances computational efficiency, making the simulation process more effective and streamlined. However, the current commonly used wall functions, such as the Spalding wall function, are an implicit expression that needs to be solved iteratively, which affects the computational efficiency, and the multilayer segmented wall function is not smoothly articulated, which affects the fidelity. In this study, based on flat plate direct numerical simulation (DNS) data, combined with structural ensemble dynamics theory, the de-thresholding Douglas–Peucker algorithm is introduced to construct an explicit wall function expression in the form of multilevel power exponential concatenated multiplication. The comparison of the new wall function against DNS data reveals that it demonstrates superior fitting accuracy in contrast to the traditional ones, and eliminates the need for manual calibration, reduces subjective influence, and enhances reliability. The numerical simulation outcomes for the flat plate boundary layer and a series of airfoils showcase the new wall function's exceptional accuracy, which not only meets but also surpasses the demanding standards of engineering practice.

An improved viscoelastic k- ε -v2-f turbulence model for intermediate and high drag reduction regimes

In this work, an improved anisotropic k-ε-v2-f model based on the finite extensible nonlinear elastic model with the Peterlin approximation for viscoelastic channel flows is proposed. This model is tested using direct numerical simulation (DNS) data for friction Reynolds numbers (Reτ) in the range of 120–1000, friction Wiesenberg numbers (Wiτ) in the range of 25–116, viscosity ratios (β) in the range of 0.6–0.9, and maximum polymer extensibility values (L2) in the range of 900–14 400. The flow characteristics of viscoelastic fluids with various parameters obtained from the new model agree well with existing DNS results. By adding closures for the flow, shear, and transverse components, the incomplete prediction of nonlinear terms from interactions between the fluctuating components of the conformation and velocity gradient tensors is improved. Compared with DNS results, these closures can fully obtain each component and significantly improve the accuracy of the flow direction component in the intermediate and high drag reduction regimes. Furthermore, the model in this paper retains the advantages of an anisotropic model, does not require a damping function, is simple to construct, and is easily extended to a variety of bounded flows.

The Diagnostic Analysis of the Thermodynamic Characteristics of Typhoon “Maysak” during Its Transformation Process

This study utilized high-resolution numerical simulation data from the WRF model to conduct a thermodynamic diagnosis of the process by which Typhoon “Maysak” transformed and merged with the Northeast Cold Vortex. The results indicated that the continuous intrusion of cold vortex air and the relative cold advection formed by the typhoon’s movement led to the demise of the typhoon’s warm core structure. The low-level low-pressure convergence and upper-level high-pressure divergence structure disappeared. After the transformation and merging with the Northeast Cold Vortex, the cyclone became cold throughout the entire layer, with a cold center appearing at low levels. During the process of the typhoon’s transformation and merging with the Northeast Cold Vortex, cold air accumulated near the low levels of the cyclone, causing the pseudo-adiabatic potential temperature lines to tilt and resulting in the slanted development of vertical vorticity in the mid-levels of the cyclone. After the typhoon transformed and merged with the Northeast Cold Vortex, the positive vertical vorticity advection at the bottom of the upper-level cold vortex trough promoted the cyclone’s development directly from the mid-levels to the upper levels, while the jet stream at the bottom of the cold vortex trough facilitated the maintenance of the positive vertical vorticity advection. Concurrently, the thermodynamic shear vorticity parameter could describe the typical vertical structure characteristics of the dynamic and thermodynamic fields above the rain area during the typhoon transformation process. In terms of temporal evolution trends, there was a certain correspondence with the development and movement of the ground rain area, and the perturbation thermodynamic divergence parameter had a good indicative effect on the area of heavy rainfall.

Denoising graph neural network based on zero-shot learning for Gibbs phenomenon in high-order DG applications

With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engineering. As one of the high-precision representative algorithms, the high-order Discontinuous Galerkin Method (DGM) has not only attracted widespread attention from scholars in the CFD research community, but also received strong development. However, when DGM is extended to high-speed aerodynamic flow field calculations, non-physical numerical Gibbs oscillations near shock waves often significantly affect the numerical accuracy and even cause calculation failure. Data driven approaches based on machine learning techniques can be used to learn the characteristics of Gibbs noise, which motivates us to use it in high-speed DG applications. To achieve this goal, labeled data need to be generated in order to train the machine learning models. This paper proposes a new method for denoising modeling of Gibbs phenomenon using a machine learning technique, the zero-shot learning strategy, to eliminate acquiring large amounts of CFD data. The model adopts a graph convolutional network combined with graph attention mechanism to learn the denoising paradigm from synthetic Gibbs noise data and generalize to DGM numerical simulation data. Numerical simulation results show that the Gibbs denoising model proposed in this paper can suppress the numerical oscillation near shock waves in the high-order DGM. Our work automates the extension of DGM to high-speed aerodynamic flow field calculations with higher generalization and lower cost.

Low Stress Level and Low Stress Amplitude Fatigue Loading Simulation of Concrete Components Containing Cold Joints under Fatigue Loading

Concrete linings containing cold joint defects may crack or detach under the aerodynamic fatigue loading generated by high-speed train operation, which posing a serious threat to the normal operation of high-speed trains. However, there is currently no simulation method specifically for fatigue damage of concrete linings containing cold joints. Based on the Roe-Siegmund cycle cohesive force model, a cohesive force fatigue damage elements were developed. A large dataset was constructed through numerical simulation software to build a BP neural network for back-calculated parameter of cohesive force fatigue damage elements. By combining experimental data, fatigue damage parameters corresponding to different pouring interval cold joints were back-calculated. These back-calculated parameters were then incorporated into the numerical model to compare simulation results with experimental results to validate the applicability of cohesive force fatigue damage elements and back propagation neural networks (BP neural network). The research results show that the difference between the fatigue life and fracture process calculated by numerical simulation and experimental data is small, verifying the applicability of the method proposed in this paper. The pouring interval directly affects the initial strength of the cold joint interface and the starting conditions of fatigue damage. The possibility of fatigue damage and fracture of concrete components containing cold joints increases with the increase of pouring interval, while the variability of fatigue life decreases with the increase of pouring interval. Interface strength and thickness are the main factors affecting the possibility of fatigue damage occurrence and the variability of fatigue life. The research results can be used to analyze the damage and cracking status of concrete linings containing cold joints under aerodynamic fatigue loading.

High-Fidelity Simulation of the Light-to-Dense Stratification Transient in the HiRJET Facility

Density stratification in a large enclosure is a crucial phenomenon to heat transfer and sustainable passive heat removal of a sodium fast reactor during reactivity transients. However, engineering turbulence models were identified to have unsatisfactory performance in predicting propagation of a stratified front. Yet, the scarcity of high-resolution data for stratification hampers the development of models. To explor e applications of leveraging direct numerical simulation (DNS) data to support turbulence model development, this work conducted DNS using NekRS to study a long stratification transient in the High-Resolution Jet (HiRJET) experimental facility. This work considers an experiment run where light fluid is injected into a tank containing a denser fluid with a relative density difference of 1.5%. Formation of the stratified layer is identified as impingement of the buoyant jet promoting mixing of the two fluids. Based on the transient statistics, transport of the concentration can be characterized by regions with dominating effects of turbulent mixing, buoyant dissipation, and molecular diffusion, respectively, as moving away from the elevation of jet impingement. Concentration near the stratified front also exhibits oscillation at Brunt-Väisälä frequency. Preliminary validation of the simulation showed encouraging agreement of the concentration distribution with the reference experiment.

Study on non-uniform circumferential temperature distribution of annular fuel in the tight lattice configuration of a lead-bismuth cooled fast reactor

To guarantee the safe operation of nuclear reactors and protect fuel elements from being damaged under long-term thermal stress, analyzing the circumferential temperature distribution of the outer cladding of nuclear fuel rods in reactors with tight lattice structures is crucial. In this work, a mathematical and physical model was established through theoretical analysis to calculate the circumferential temperature distribution of the outer cladding of an annular fuel rod. The proposed model provides an analytical expression for the circumferential temperature distribution, and the key factors influencing this distribution are determined. The results of the mathematical-physical model and numerical simulation are then combined through numerical fitting. Consequently, a numerical fitting equation is obtained under the steady-state condition of the lead-bismuth reactor using annular fuel and compared with the numerical simulation data acquired via computational fluid dynamics. The results demonstrate that the proposed numerical fitting equation has high accuracy and can serve as a valuable computational tool for analyzing the circumferential temperature of fuel claddings during the operation of lead-bismuth reactors with annular fuels.

Data-informed characterization of spatio-temporal scales in experiments of microconfined high-pressure transcritical turbulence

The spatio-temporal scales of microconfined high-pressure transcritical turbulence are characterized in relation to the resolution capabilities of present time-resolved two-dimensional μPIV technology. Utilizing CO2 as the working fluid, the physical scales are examined by considering the main dimensionless groups of the problem, which correspond to the Reynolds, Brinkman, and Stokes numbers and the mass fraction of particles in the fluid. In detail, the methodology employed leverages direct numerical simulation data to inform the estimation of hydrodynamic, thermophysical, and particle-related scales, and selects a state-of-the-art μPIV setup to describe the optical performance of the current technology. The results indicate that the temporal scales can be experimentally captured for a wide range of operating conditions. However, the scenario becomes much more complex when trying to capture the spatial scales of microconfined high-pressure transcritical turbulent flow. Particularly, the Kolmogorov and Batchelor spatial scales can be captured for bulk Reynolds numbers below O(103). Otherwise, the spatial scales can only be partially captured and/or remain completely masked due to insufficient resolution, like for example in the case of boundary layer viscous scales and fluid density variations. This limitation is not imposed by the tracer behavior of microparticles, as the Stokes number remains significantly low for all the system configurations studied. Instead, the limitation is mainly a result of the optical capabilities of present μPIV systems. Finally, given the generalizable properties of dimensionless numbers, the results and insight obtained can be extended to other experiments of μPIV-based visualization/quantification of microconfined multiscale flows involving large thermophysical variations.

Numerical and experimental studies of a novel compact sandwich-type plate reactor for thermochemical energy storage

In this work, a novel compact sandwich-type plate reactor (CSPR) for thermochemical energy storage (TCES) with Ca(OH)2/CaO is proposed, where the essential unit is symmetrically comprised of steam channel in the center, orderly sandwiched by metal gauzes, reaction cavities, plates and heat transfer channels at both sides. Firstly, the flow-heat-reaction multi-field coupled modelling is conducted to comparatively investigate the flat, baffled and dimpled plates, where the dimpled plate (DP) stands out. Then, the entire CSPR comprised of three essential units with DPs is modelled to numerically predict its comprehensive performance and characteristics. Afterwards, the prototype of CSPR is manufactured based on the above numerical studies and experimentally evaluated on our exothermic and endothermic cycling performance test bench with loading of 1.667 kg of Ca(OH)2 pellets. The experimental data confirm that the charging stage takes 330 min with the final conversion up to 97.74 %, while the discharging stage takes 200 min with the maximal heat transfer fluid (HTF) output temperature reaching 385 ℃ and the duration for the HTF output temperature above 350 ℃ lasting for 130 min. Based on energy balance analysis, the energy storage efficiency for charging stage is 74.92 % and the round-trip energy efficiency for cycle is 60.24 % (including 2 h of buffering period) without heat recovery of product steam. Technically, these efficiencies can be respectively promoted to be 76.35 % and 71.59 % with heat recovery. The numerical simulation and experimental data are found to be mutually verified. We hope this work can provide a novel insight of reactor design for development of TCES technology.