Inviscid Euler Equations Research Articles

A new open-source library based on novel high-resolution structure-preserving convection schemes

This work develops a new finite volume convection scheme and open-source library for convection-dominated problems on unstructured grids. The formulated reconstruction operators can realize high-resolution and structure-preserving properties by adjusting numerical dissipation and anti-dissipation errors in a unified normalized-variable diagram. Then, this work develops a new open-source library based on the devised schemes within one of the most widely used general-purpose open-source software whose solution quality is intrinsically limited by the low accuracy of the conventional total variation diminishing schemes. The performance of the new library is first verified by some fundamental problems including pure advection and inviscid Euler equations. The numerical results of the accuracy tests show that the developed interpolation library can significantly reduce numerical errors with a minor increased computational cost compared with the conventional second-order schemes. The complex profile advection test demonstrates that the new library can offer an improved structure-preserving property that gives essentially oscillation-free solutions and preserves the structures of the passive transported scalar. Furthermore, the robustness of the new library is validated by compressible high-speed flow simulations with irregular geometries. Thus, this work presents a new library of high-resolution structure-preserving schemes for the accurate and efficient discretization of the convection term which plays an essential role in a wide range of computational fluid dynamics. The source code of the new scheme and library are released via DOI:10.5281/zenodo.8399000.

Two-Dimensional Geometrical Shock Dynamics for Blast Wave Propagation and Post-Shock Flow Effects

Geometrical shock dynamics (GSD) is a model capable of efficiently predicting the position, shape, and strength of a shock wave. Compared to the traditional Euler method that solves the inviscid Euler equations, GSD is a reduced-order model derived from the method of characteristics which results in a more computationally efficient approach since it only considers the motion of the shock front instead of the entire flow field. Here, a study of post-shock flow effects in two dimensions has been performed. These post-shock flow effects become increasingly important when modeling blast wave propagation over extended times or distances, i.e., a shock front that decays in speed and that has decaying properties behind it. A comparison between the first-order complete, fully complete and point-source GSD (PGSD) models reveals the importance of preserving an intact post-shock flow term, which is truncated by the original GSD model, in predicting blast motion. Lagrangian simulations were performed for the case of interaction between two cylindrical blast waves and the results were compared to prior experimental work. The results showed an agreement in attenuation of the maximum pressure at the Mach stem, but an overestimation of the Mach stem growth at its early stage was observed using PGSD. To address this issue, another model was developed that combines the PGSD model with shock–shock approximate theory (PGSDSS), but it excessively attenuates Mach stem evolution.

Investigation of aspect ratio effects on flow characteristics and vorticity generation in shock-induced rectangular bubble

In shock-induced Richtmyer–Meshkov instability, the polygonal bubbles, including the rectangular interface can offer favorable circumstances for shock refraction research. Also, the aspect ratio is crucial in characterizing the physics behind this instability. Therefore, the aspect ratio effects on the flow characteristics and vorticity generation in the shock-induced rectangular light gas bubbles are investigated numerically in this study. This investigation is performed for a wide range of aspect ratios varying from 0.25 to 3.0. These effects are highlighted in the interface morphology, wave paradigms, vorticity generation, enstrophy evolution, and a qualitative examination of interface deformation. For simulating two-component gas flows, a high-order explicit modal discontinuous Galerkin approach is employed to solve a two-dimensional system of compressible inviscid Euler equations. Existing experimental results for shock-induced square and cylindrical light bubbles are used to validate the numerical model and solver. The results indicate that the effects of aspect ratio are critical in characterizing the interface morphology during the interaction between the shock wave and rectangular bubble. The interface morphology evolves faster as the aspect ratio increases, and the process of transverse jet formation is observed to be significantly different. The aspect ratio effects result in a substantial change in the flow field with bubble deformation, vortex development, vorticity generation, and transverse jet formation. The effects of aspect ratio are further investigated in detail through the mechanism of vorticity generation and enstrophy evolution. Finally, these effects on shock trajectories and interface characteristics over time are thoroughly explored.

Well Posedness and Characterization of Solutions to Non Conservative Products in Non Homogeneous Fluid Dynamics Equations

AbstractConsider a balance law where the flux depends explicitly on the space variable. At jump discontinuities, modeling considerations may impose the defect in the conservation of some quantities, thus leading to non conservative products. Below, we deduce the evolution in the smooth case from the jump conditions at discontinuities. Moreover, the resulting framework enjoys well posedness and solutions are uniquely characterized. These results apply, for instance, to the flow of water in a canal with varying width and depth, as well as to the inviscid Euler equations in pipes with varying geometry.

A constrained boundary gradient reconstruction method for unstructured finite volume discretization of the Euler equations

We propose a novel boundary gradient and solution reconstruction approach for the second-order cell-centered unstructured finite volume method for solving the inviscid Euler equations. The proposed constrained reconstruction method involving ghost cells is shown to be more accurate than several conventional boundary reconstruction methods and linear-exact in the near-boundary areas. In the present procedure, the solutions at the ghost cell centroids are given by solving constraint equations, which are established based on boundary conditions. At the same time, the solution gradients in boundary cells and the solutions in boundary surfaces are obtained altogether, while guaranteeing the compatibility of the boundary conditions with the reconstructed results. A variety of numerical test cases show that the new method effectively reduces the errors of near-boundary approximations and improves the overall numerical accuracy. Furthermore, because the constrained reconstruction is only used for the boundary cells, the extra computational cost barely changes the overall computational efficiency.

An improved fifth-order nonlinear spectral difference scheme for hyperbolic conservation laws

In previous work (Lin et al., 2021), a fifth-order nonlinear spectral difference scheme was proposed for hyperbolic conservation laws. Since the mentioned nonlinear shock-capturing scheme is cell-based, it keeps the compactness of the original linear one and hence the advantage in terms of parallel efficiency. However, it was shown that the scheme encountered defects in stability and computational cost. The current work attempts to address these two defects by employing a positivity preserving method originally developed for discontinuous Galerkin schemes and a trouble cell detecting method based on edge detection. Some numerical results are also presented to demonstrate the effectiveness of the positivity preserving method and the shock detecting method. To be more specific, this work focuses on one- and two-dimensional inviscid Euler equations to validate the algorithms. It is shown that the two aforementioned defects are effectively solved by the current improved scheme.

Surface gravity waves in the presence of vertically shearing current and eddy viscosity

Conventional models of surface gravity waves usually use potential theory in their calculations where the governing equations are the inviscid Euler equations. Nevertheless, turbulence may play a significant role for short waves or highly energetic sea or river conditions and, therefore, must be taken into account in the flow's formulation. This work extends the model of linear monochromatic waves in the presence of vertically shearing currents to account for turbulence in the form of eddy viscosity varying in depth. The boundary value problem is found to be governed by an augmented Orr–Sommerfeld(–Squire) equation(s) in two-(three-)dimensional with additional terms of viscosity derivatives. The free-surface conditions are extended to account for shearing currents with turbulent viscosity and external stress for the air layer. This provides a fundamental model for investigating the influence of the turbulent viscosity on the oscillatory wave flow. Examples of semi-analytical and numerical solutions show a fundamentally different dynamical behavior with respect to the known non-viscous solutions. These differences include two regimes in the dispersion relation with non-dispersive short waves and dispersive longer waves with a reduced celerity. They also include tilted stream function contours (i.e., a phase which is a function of depth), much deeper penetration depth, and more. These preliminary results show that turbulence potentially has great importance in wave generation mechanisms as well as in highly turbulent regions such as under strong storms or cyclones.

Zero-viscosity-capillarity limit to the planar rarefaction wave for the 2D compressible Navier–Stokes–Korteweg equations

We shall consider the two-dimensional (2D) isentropic Navier–Stokes–Korteweg equations which are used to model compressible fluids with internal capillarity. Formally, the 2D isentropic Navier–Stokes–Korteweg equations converge, as the viscosity and the capillarity vanish, to the corresponding 2D inviscid Euler equations, and we do justify this for the case that the corresponding 2D inviscid Euler equations admit a planar rarefaction wave solution. More precisely, it is proved that there exists a family of smooth solutions for the 2D isentropic compressible Navier–Stokes–Korteweg equations converging to the planar rarefaction wave solution with arbitrary strength for the 2D Euler equations. A uniform convergence rate is obtained in terms of the viscosity coefficient and the capillarity away from the initial time. The key ingredients of our proof are the re-scaling technique and energy estimate, in which we also introduce the hyperbolic wave to recover the physical viscosities and capillarity of the inviscid rarefaction wave profile.

A new strategy for solving store separation problems using OpenFOAM

The ability of OpenFOAM to solve the problem of a store separating from an air vehicle (store separation problem) has been evaluated using a dynamic mesh (Overset/Chimera) technique for an industry-class (transonic and generic) benchmark test case. The major limitations of the standard libraries have been determined. To tackle these challenges, a new strategy has been proposed and implemented using only open-source libraries and tools. The strategy combines porting, modifying, and adapting an overset library from the OpenFOAM fork platform (foam-extend) to the standard OpenFOAM platform (ESI). Furthermore, in order to overcome the well-known weakness of the standard OpenFOAM compressible solvers, the newly adapted overset library was integrated with an open-source, density-based, and coupled solver ( HiSA), which uses the OpenFOAM technology. Additionally, a force restrained model was developed to consider the externally applied forces on the store by the store ejectors. The accuracy of the developed strategy has been compared with wind tunnel tests and the solutions of two well-known commercial codes, showing good agreements with them. While the study has focused on simulations with inviscid Euler equations (typical of the test case considered here), the viscosity effect on the solution has also been studied with Navier–Stokes equations and compared with other results in the literature, showing minor differences. To the best of the authors’ knowledge, this is the first work which studies and validates the store separation problem in transonic regime with OpenFOAM.

Plasma transport simulations of Rayleigh–Taylor instability in near-ICF deceleration regimes

Rayleigh–Taylor (R–T) instability between plasma species is examined in a kinetic test and near-inertial confinement fusion (ICF) regimes. A transport approximation to the plasma species kinetics is used to represent viscosity and species mass transport within a hydrodynamic fluid code (xRage). R–T simulation results are compared in a kinetic test regime with a fully kinetic particle-in-cell approach [vectorized particle-in-cell (VPIC)] and with an analytic model for the growth rate of R–T instability. Single-mode growth rates from both codes and the analytic model are in reasonable agreement over a range of initial wavelengths including the wavenumber of maximum growth rate. Both codes exhibit similar diffusive mixing fronts. Small code-to-code differences arise from the kinetics, while simulation-analytic model differences arise from several sources dominated by the choice of gradients establishing the hydrostatic equilibrium initial conditions. After demonstrating code agreement in the kinetic test regime, which is practically accessible to the VPIC code, then the xRage code, with the fluid plasma transport approximation, is applied to single mode R–T instability under deceleration conditions closer to an ICF implosion, approximated with a carbon (C) shell imploding on a deuterium (D) fuel. The analytic wavelength of maximum instability is limited by the kinetics, primarily in the viscosity, and is found to be ≈10 μm for an ion temperature near 1 keV at this C–D interface, with the most unstable wavelength increasing as temperature increases. The analytic viscous model agrees with simulation results over a range of initial perturbation wavelengths, provided the simulation results are analyzed over a sufficiently short duration (⪅0.2 ns in this case). Details of the fluid structure evolution during this R–T deceleration are compared between the inviscid Euler equations and cases, which include plasma transport over a range in initial wavelengths and initial perturbation amplitudes. The inviscid Euler solutions show a grid-dependent cascade to smaller scale structures often seen in the R–T instability, while simulations with plasma transport in this deceleration regime develop a single vortex roll-up, as the plasma transport smoothes all hydrodynamic fluid structures smaller than several micrometers. This leads to a grid-converged transient solution for the R–T instability when kinetic effects are included in the simulations, and thus represents a direct numerical simulation of the thermal ions during R–T unstable mixing in ICF relevant conditions.

Derivation of a Viscous Serre–Green–Naghdi Equation: An Impasse?

In this article, we present the current status of the derivation of a viscous Serre–Green–Naghdi system. For this goal, the flow domain is separated into two regions. The upper region is governed by inviscid Euler equations, while the bottom region (the so-called boundary layer) is described by Navier–Stokes equations. We consider a particular regime binding the Reynolds number and the shallowness parameter. The computations presented in this article are performed in the fully nonlinear regime. The boundary layer flow reduces to a Prandtl-like equation that we claim to be irreducible. Further approximations are necessary to obtain a tractable model.

A high‐order WENO‐limited finite‐volume algorithm for atmospheric flow using the ADER‐differential transform time discretization

AbstractA high‐order‐accurate weighted essentially non‐oscillatory (WENO) limited upwind finite‐volume scheme is detailed for the compressible, nonhydrostatic, inviscid Euler equations using an arbitrary derivatives (ADER) time‐stepping scheme based on differential transforms (DTs). A second‐order‐accurate alternating Strang dimensional splitting is compared against multidimensional simulation with 2D transport using solid body rotation of various data. The two were found to give nearly identical accuracy in orthogonal, Cartesian coordinates. Orders of convergence are demonstrated at up to ninth‐order accuracy with 2D transport. 1D transport is used to confirm that error decreases monotonically with increasing order of accuracy with WENO limiting even for discontinuous data. Further, WENO limiting always decreased the error compared with simulation without limiting in the L1 norm. A series of standard 2D compressible nonhydrostatic Euler equation test cases were validated against previous results from literature. Finally, it was demonstrated that increasing the order of accuracy led to better resolved features and increased power for kinetic energy at small wavelengths.

Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamics scheme

Lagrangian methods to solve the inviscid Euler equations produce numerical oscillations near shock waves. A common approach to reducing these oscillations is to add artificial viscosity (AV) to the discrete equations. The AV term acts as a dissipative mechanism that attenuates oscillations by smearing the shock across a finite number of computational cells. However, AV introduces several control parameters that are not determined by the underlying physical model, and hence, in practice are tuned to the characteristics of a given problem. We seek to improve the standard quadratic-linear AV form by replacing it with a learned neural function that reduces oscillations relative to exact solutions of the Euler equations, resulting in a hybrid numerical-neural hydrodynamic solver. Because AV is an artificial construct that exists solely to improve the numerical properties of a hydrodynamic code, there is no offline ‘viscosity data’ against which a neural network can be trained before inserting into a numerical simulation, thus requiring online training. We achieve this via differentiable programming, i.e. end-to-end backpropagation or adjoint solution through both the neural and differential equation code, using automatic differentiation of the hybrid code in the Julia programming language to calculate the necessary loss function gradients. A novel offline pre-training step accelerates training by initializing the neural network to the default numerical AV scheme, which can be learned rapidly by space-filling sampling over the AV input space. We find that online training over early time steps of simulation is sufficient to learn a neural AV function that reduces numerical oscillations in long-term hydrodynamic shock simulations. These results offer an early proof-of-principle that online differentiable training of hybrid numerical schemes with novel neural network components can improve certain performance aspects existing in purely numerical schemes.

Molecular viscosity and diffusivity effects in transitional and shock-driven mixing flows.

This paper investigates the importance of molecular viscosity and diffusivity for the prediction of transitional and shock-driven mixing flows featuring high and low Reynolds and Mach number regions. Two representative problems are computed with implicit large-eddy simulations using the inviscid Euler equations (EE) and viscous Navier-Stokes equations (NSE): the Taylor-Green vortex at Reynolds number Re=3000 and initial Mach number Ma=0.28, and an air-SF_{6}-air gas curtain subjected to two shock waves at Ma=1.2. The primary focus is on differences between NSE and EE predictions due to viscous effects. The outcome of the paper illustrates the advantages of utilizing NSE. In contrast to the EE, where the effective viscosity decreases upon grid refinement, NSE predictions can be assessed for simulations of flows with transition to turbulence at prescribed constant Re. The NSE can achieve better agreement between solutions and reference data, and the results converge upon grid refinement. On the other hand, the EE predictions do not converge with grid refinement, and can only exhibit similarities with the NSE results at coarse grid resolutions. We also investigate the effect of viscous effects on the dynamics of the coherent and turbulent fields, as well as on the mechanisms contributing to the production and diffusion of vorticity. The results show that nominally inviscid calculations can exhibit significantly varying flow dynamics driven by changing effective resolution-dependent Reynolds number, and highlight the role of viscous processes affecting the vorticity field. These tendencies become more pronounced upon grid refinement. The discussion of the results concludes with the assessment of the computational cost of inviscid and viscous computations.

Modeling thermodynamic trends of rotating detonation engines

The formation of a number of co- and counter-rotating coherent combustion wave fronts is the hallmark feature of the Rotating Detonation Engine (RDE). The engineering implications of wave topology are not well understood nor quantified, especially with respect to parametric changes in combustor geometry, propellant chemistry, and injection and mixing schemes. In this article, a modeling framework that relates the time and spatial scales of the RDE to engineering performance metrics is developed and presented. The model is built under assumptions of backpressure-insensitivity and nominally choked gaseous propellant injection. The Euler equations of inviscid, compressible fluid flow in one dimension are adapted to model the combustion wave dynamics along the circumference of an annular-type RDE. These adaptations provide the necessary mass and energy input and output channels to shape the traveling wave fronts and decaying tails. The associated unit processes of injection, mixing, combustion, and exhaust are all assigned representative time scales necessary for successful wave propagation. We find that the separation, or lack, of these time scales is responsible for the behavior of the system, including wave co- and counter-propagation and bifurcations between these regimes and wave counts. Furthermore, as there is no imposition of wave topology, the model output is used to estimate the net available mechanical work output and thermodynamic efficiency from the closed trajectories through pressure–volume and temperature–entropy spaces. These metrics are investigated with respect to variation in the characteristic scales for the RDE unit physical processes.

Parallel discontinuous Galerkin finite element method for computing hyperbolic conservation law on unstructured meshes

PurposeThe discontinuous Galerkin finite element method (DGFEM) is very suited for realizing high order resolution approximations on unstructured grids for calculating the hyperbolic conservation law. However, it requires a significant amount of computing resources. Therefore, this paper aims to investigate how to solve the Euler equations in parallel systems and improve the parallel performance.Design/methodology/approachDiscontinuous Galerkin discretization is used for the compressible inviscid Euler equations. The multi-level domain decomposition strategy was used to deal with the computational grids and ensure the calculation load balancing. The total variation diminishing (TVD) Runge–Kutta (RK) scheme coupled with the multigrid strategy was employed to further improve parallel efficiency. Moreover, the Newton Block Gauss–Seidel (GS) method was adopted to accelerate convergence and improve the iteration efficiency.FindingsNumerical experiments were implemented for the compressible inviscid flow problems around NACA0012 airfoil, over M6 wing and DLR-F6 configuration. The parallel acceleration is near to a linear convergence. The results indicate that the present parallel algorithm can reduce computational time significantly and allocate memory reasonably, which has high parallel efficiency and speedup, and it is well-suited to large-scale scientific computational problems on multiple instruction stream multiple data stream model.Originality/valueThe parallel DGFEM coupled with TVD RK and the Newton Block GS methods was presented for hyperbolic conservation law on unstructured meshes.

Acceleration of high-order combined compact finite difference scheme for simulating three-dimensional flow and heat transfer problems in GPUs

In this article, the high-order upwinding combined compact difference scheme developed in a three-point grid stencil is applied to solve the incompressible Navier-Stokes (NS) and energy equations in three dimensions. The time integrator with symplectic property is employed to approximate the temporal derivative term in inviscid Euler equation so as to numerically retain the embedded Hamiltions and Casimir to get long-time accurate solutions. For the sake of computational efficiency in solving the three-dimensional NS equations, all the calculations will be accelerated using the hybrid CUDA and OpenAcc GPU programing models. The parallel speedup performance compared to the multicore of an Intel Xeon E5-2690V5 CPU is reported.

Scaling laws in turbulence.

Following the idea that dissipation in turbulence at high Reynolds number is dominated by singular events in space-time and described by solutions of the inviscid Euler equations, we draw the conclusion that in such flows, scaling laws should depend only on quantities appearing in the Euler equations. This excludes viscosity or a turbulent length as scaling parameters and constrains drastically possible analytical pictures of this limit. We focus on the drag law deduced by Newton for a projectile moving quickly in a fluid at rest. Inspired by this Newton's drag force law (proportional to the square of the speed of the moving object in the limit of large Reynolds numbers), which is well verified in experiments when the location of the detachment of the boundary layer is defined, we propose an explicit relationship between the Reynolds stress in the turbulent wake and quantities depending on the velocity field (averaged in time but depending on space). This model takes the form of an integrodifferential equation for the velocity which is eventually solved for a Poiseuille flow in a circular pipe.

The neural particle method – An updated Lagrangian physics informed neural network for computational fluid dynamics

Today numerical simulation is indispensable in industrial design processes. It can replace cost and time intensive experiments and even reduce the need for prototypes. While products designed with the aid of numerical simulation undergo continuous improvement, this must also be true for numerical simulation techniques themselves. Up to date, no general purpose numerical method is available which can accurately resolve a variety of physics ranging from fluid to solid mechanics including large deformations and free surface flow phenomena. These complex multi-physics problems occur for example in Additive Manufacturing processes. In this sense, the recent developments in Machine Learning display promise for numerical simulation. It has recently been shown that instead of solving a system of equations as in standard numerical methods, a neural network can be trained solely based on initial and boundary conditions. Neural networks are smooth, differentiable functions that can be used as a global ansatz for Partial Differential Equations (PDEs). While this idea dates back to more than 20 years (Lagaris et al., 1998), it is only recently that an approach for the solution of time dependent problems has been developed (Raissi et al., 2019). With the latter, implicit Runge–Kutta schemes with unprecedented high order have been constructed to solve scalar-valued PDEs. We build on the aforementioned work in order to develop an Updated Lagrangian method for the solution of incompressible free surface flow subject to the inviscid Euler equations. The method is straightforward to implement and does not require any specific algorithmic treatment which is usually necessary to accurately resolve the incompressibility constraint. Due to its meshfree character, we will name it the Neural Particle Method (NPM). It will be demonstrated that the NPM remains stable and accurate even if the location of discretization points is highly irregular.

Scale invariance of the homentropic inviscid Euler equations with application to the Noh problem.

We investigate the inviscid compressible flow (Euler) equations constrained by an "isentropic" equation of state (EOS), whose functional form in pressure is an arbitrary function of density alone. Under the aforementioned condition, we interrogate using symmetry methods the scale-invariance of the homentropic inviscid Euler equations. We find that under general conditions, we can reduce the inviscid Euler equations into a system of two coupled ordinary differential equations. To exemplify the utility of these results, we formulate two example scale-invariant, self-similar solutions. The first example includes a shock-free expanding bubble scenario, featuring a modified Tait EOS. The second example features the classical Noh problem, coupled to an arbitrary isentropic EOS. In this case, to satisfy the conditions set forth in the classical Noh problem, we find that the solution for the flow is given by a transcendental algebraic equation in the shocked density.