Hydrodynamics Algorithm Research Articles

VecDualSPHysics: A vectorized implementation of Smoothed Particle Hydrodynamics method for simulating fluid flows on multi-core processors

As one of the most promising mesh-free numerical approaches, the Smoothed Particle Hydrodynamics (SPH) algorithm can be used for simulating many engineering problems. However, it is necessary to fully exploit the performance of computing processors for realizing extremely large-scale parallel simulations. In this paper, we focused on maximizing the performance of a SPH program by vectorizing on modern multi-core processors. We summarize the general principles of vectorization including the branch vectorization, vector reduction and instruction set optimization approaches. Then, a vectorized version VecDualSPHysics was implemented based on these basic vectorization principles. Experiments show that VecDualSPHysics has a significant performance improvement over the original DualSPHysics. By using AVX2 instruction set combined with OpenMP, we obtained up to 4.3x speedups on a single multi-core processor, and the maximal speedup is 6.3x for AVX-512 instruction set, which is much faster than the pure OpenMP-based multi-threading version. The VecDualSPHysics shows the great potential of exploiting the performance of multi-core processors by vectorization and can further be used to optimize the massively parallel SPH simulations.

A New Updated Reference Lagrangian Smooth Particle Hydrodynamics algorithm for isothermal elasticity and elasto-plasticity

This paper presents a new Updated Reference Lagrangian Smooth Particle Hydrodynamics (SPH) algorithm for the analysis of large deformation isothermal elasticity and elasto-plasticity. Taking as point of departure a Total Lagrangian setting and considering as referential configuration an intermediate configuration of the deformation process, the equation of conservation of linear momentum and three geometric conservation laws (for the deformation gradient, its cofactor and its determinant) are re-written leading to a very generic system of first order conservation laws. The key feature of the formulation is a suitable multiplicative decomposition of the conservation variables, leading to a very simple final set of equations with striking similarities to the conventional Total Lagrangian system albeit re-written in terms of alternative Referential Updated conservation variables which are evolved in time. Taking advantage of this new Updated Reference Lagrangian formalism, a second order entropy-stable SPH upwinding stabilisation method will be introduced. With respect to previous publications by the group, a new three-stage Runge–Kutta time integration method is implemented in order to increase the CFL stability restriction. Finally, and to demonstrate the robustness and applicability of the methodology, a wide spectrum of challenging problems will be presented and compared, including some benchmark three-dimensional large deformation elasto-plasticity problems. To facilitate its ease of implementation, the paper explores the use of a series of novel expressions for the evaluation of kernels and the gradients of kernels to provide the SPH user the freedom to choose amongst various options, all leading to equally convincingly robust results.

Formation Behavior and Reaction Characteristic of a PTFE/Al Reactive Jet.

To reveal the expansion phenomenon and reaction characteristics of an aluminum particle filled polytetrafluoroethylene (PTFE/Al) reactive jet during the forming process, and to control the penetration and explosion coupling damage ability of the reactive jet, the temperature and density distribution of the reactive jet were investigated by combining numerical simulation and experimental study. Based on the platform of AUTODYN-3D code, the Smoothed Particle Hydrodynamics (SPH) algorithm was used to study the evolution behaviors and distribution regularity of the morphology, density, temperature, and velocity field during the formation process of the reactive composite jet. The reaction characteristic in the forming process was revealed by combining the distribution of the high-temperature zone in numerical simulation and the Differential Scanning Calorimeter/Thermo-Gravimetry (DSC/TG) experiment results. The results show that the distribution of the high-temperature zone of the reactive composite jet is mainly concentrated in the jet tip and the axial direction, and the reactive composite jet tip reacts first. Combining the density distribution in the numerical simulation and the pulsed X-ray experimental results, the forming behavior of the reactive composite jet was analyzed. The results show that the reactive composite jet has an obvious expansion effect, accompanied by a significant decrease in the overall density.

Effect of scratches on the damage characteristics of fused silica optics under extremely-high impact load

Fused silica glass is widely used in aircraft portholes, space telescopes, solar panels, etc. due to its excellent properties. In such environments, dust and debris with extremely high speed can easily create high impact loads on the silica glass surfaces, which would incur impact damage on the fused silica components and shorten their service life. Machining-induced surface defects on fused silica components would aggravate their damage behaviors, but the influencing rules and the underlying mechanisms has not been fully revealed. This work focuses on the influence of surface scratch defects on the impact damage characteristics of fused silica optics under the extremely high impact load. An improved Johnson-Holmquist Ⅱ (JH-2) dynamic constitutive model of fused silica was established on basis of the stress-strain relationship obtained by the Split Hopkinson Pressure Bar (SHPB) experiments. Based on that constitutive model, a dynamic simulation model describing the impact damage process induced by scratch defects was established by combining the smoothed particle hydrodynamics (SPH) algorithm and arbitrary Lagrange-Euler (ALE) algorithms. Then, the influence of scratch defect size on the impact damage morphology and crack propagation behaviors under various impact angles was systematically analyzed. The results show that, the impact damage induced by scratches with depths of 5 μm and 25 μm is more serious than scratches with other sizes. And under the impact angles of 45° and 60°, the damage extent of the optical surface with 10 μm-depth scratch is significantly lower than the defect-free surface. Finally, the laser-driven flyer experiment was performed to validate the role of scratch defects in influencing the impact damage characteristics of fused silica components under extremely high impact loads. The deviation between simulation and experimental results is generally within 10% except for one specific case that could be well explained, thus verifying the reliability of the established constitutive model and dynamic simulation model. This work could offer theoretical guidance and parameter basis for controlling the surface defects introduced in the machining processes and resultantly improving the impact damage resistance of fused silica components.

A Smoothed Particle Hydrodynamics Algorithm for Elasticity Without Tensile Instabilities

A Smoothed Particle Hydrodynamics Algorithm for Elasticity Without Tensile Instabilities

Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics

The numerical solution of relativistic hydrodynamics equations in conservative form requires root-finding algorithms that invert the conservative-to-primitive variables map. These algorithms employ the equation of state of the fluid and can be computationally demanding for applications involving sophisticated microphysics models, such as those required to calculate accurate gravitational wave signals in numerical relativity simulations of binary neutron stars. This work explores the use of machine learning methods to speed up the recovery of primitives in relativistic hydrodynamics. Artificial neural networks are trained to replace either the interpolations of a tabulated equation of state or directly the conservative-to-primitive map. The application of these neural networks to simple benchmark problems shows that both approaches improve over traditional root finders with tabular equation-of-state and multi-dimensional interpolations. In particular, the neural networks for the conservative-to-primitive map accelerate the variable recovery by more than an order of magnitude over standard methods while maintaining accuracy. Neural networks are thus an interesting option to improve the speed and robustness of relativistic hydrodynamics algorithms.

Numerical Investigation of Surge Waves Generated by Submarine Debris Flows

Submarine debris flows and their generated waves are common disasters in Nature that may destroy offshore infrastructure and cause fatalities. As the propagation of submarine debris flows is complex, involving granular material sliding and wave generation, it is difficult to simulate the process using conventional numerical models. In this study, a numerical model based on the smoothed particle hydrodynamics (SPH) algorithm is proposed to simulate the propagation of submarine debris flow and predict its generated waves. This model contains the Bingham fluid model for granular material, the Newtonian fluid model for the ambient water, and a multiphase granular flow algorithm. Moreover, a boundary treatment technique is applied to consider the repulsive force from the solid boundary. Underwater rigid block slide and underwater sand flow were simulated as numerical examples to verify the proposed SPH model. The computed wave profiles were compared with the observed results recorded in references. The good agreement between the numerical results and experimental data indicates the stability and accuracy of the proposed SPH model.

Investigating the winch performance in an ASV/ROV autonomous inspection system

Combined Autonomous Surface Vehicles (ASV) and remotely operated underwater vehicles (ROV) inspection and intervention systems can contribute to future asset management of offshore renewable energy. This paper presents the design and performance of the winch system which couples the ASV and ROV and deploys/recovers the ROV. The hydrodynamic models and control algorithms are developed and solved with analytical and numerical approaches. The winch performance needs to meet a range of operational profiles, including i) ASV following/not following the ROV ii) winch operating in speed control iii) winch operating in tension control iv) varying ROV distance and depths targets. For a representative ASV/ROV configuration, the work determines the required umbilical length for different ROV targets and suitable winch speeds. The results show that the strategy where the ASV follows the ROV can reduce the umbilical tension, but conditions of compression should be carefully managed. The umbilical tension can also be decreased by tension control and shows to be very effective in larger sea states. This study also models the accidental limit case, where a malfunctioning ROV is recovered. The estimated increase of umbilical tension during the recovery stage of a malfunctioning ROV can thus be incorporated into the design calculations.

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach.

The efficient and reliable monitoring of the flow of water in open channels provides useful information for preventing water slow-downs due to the deposition of materials within the bed of the channel, which might lead to critical floods. A reliable monitoring system can thus help to protect properties and, in the most critical cases, save lives. A sensing system capable of monitoring the flow conditions and the possible geo-environmental constraints within a channel can operate using still images or video imaging. The latter approach better supports the above two features, but the acquisition of still images can display a better accuracy. To increase the accuracy of the video imaging approach, we propose an improved particle tracking algorithm for flow hydrodynamics supported by a machine learning approach based on a convolutional neural network-evolutionary fuzzy integral (CNN-EFI), with a sub-comparison performed by multi-layer perceptron (MLP). Both algorithms have been applied to process the video signals captured from a CMOS camera, which monitors the water flow of a channel that collects rain water from an upstream area to discharge it into the sea. The channel plays a key role in avoiding upstream floods that might pose a serious threat to the neighboring infrastructures and population. This combined approach displays reliable results in the field of environmental and hydrodynamic safety.

Crack growth pattern analysis of monolithic glass ceramic on a titanium abutment for single crown implant restorations using smooth particle hydrodynamics algorithm.

Background Glass ceramic materials have multiple applications in various prosthetic fields. Despite the many advantages of these materials, they still have limitations such as fragility and surface machining and ease of repairing. Crack propagation has been a typical concern in fullceramic crowns, for which many successful numerical simulations have been carried out using the extended finite element method (XFEM). However, XFEM cannot correctly predict a primary crack growth direction under dynamic loading on the implant crown. Methods In this work, the dental implant crown and abutment were modeled in CATIA V5R19 software using a CT-scan technique based on the human first molar. The crown was approximated with 39514 spherical particles to reach a reasonable convergence in the results. In the present work, glass ceramic was considered the crown material on a titanium abutment. The simulation was performed for an impactor with an initial velocity of 25 m/s in the implant-abutment axis direction. We took advantage of smooth particle hydrodynamics (SPH) such that the burden of defining a primary crack growth direction was suppressed. Results The simulation results demonstrated that the micro-crack onset due to the impact wave in the ceramic crown first began from the crown incisal edge and then extended to the margin due to increased stress concentration near the contact region. At 23.36 µs, the crack growth was observed in two different directions based on the crown geometry, and at the end of the simulation, some micro-cracks were also initiated from the crown margin. Moreover, the results showed that the SPH algorithm could be considered an alternative robust tool to predict crack propagation in brittle materials, particularly for the implant crown under dynamic loading. Conclusion The main achievement of the present study was that the SPH algorithm is a helpful tool to predict the crack growth pattern in brittle materials, especially for ceramic crowns under dynamic loading. The predicted crack direction showed that the initial crack was divided into two branches after its impact, leading to the crown fracture. The micro-crack initiated from the crown incisal edge and then extended to the crown margin due to the stress concentration near the contact area.

Numerical Simulation of Jet Forming Characteristics of Energetic Liner Based on Smoothed Particle Hydrodynamics Algorithm

To study the jet forming characteristics of energetic material liner, in this paper, using AUTODYN simulation software and smoothed particle hydrodynamics (SPH) algorithm, the jet forming process of traditional metal Al liner and PTFE/Al energetic liner with different shapes, different cone angles and different thickness was simulated. The results show that the morphologies of PTFE/Al energetic jet and Al inert jet are significantly different, PTFE/Al jet has divergence compared with Al jet. With the increase of cone angle of liner, the velocity of jet tail increases, the velocity of jet head and the length of penetrator decrease. As the liner thickness increases, the head and tail velocity of the jet decrease, and the length of the penetrator increases.

An entropy-stable Smooth Particle Hydrodynamics algorithm for large strain thermo-elasticity

This paper presents a novel Smooth Particle Hydrodynamics computational framework for the simulation of large strain fast solid dynamics in thermo-elasticity. The formulation is based on the Total Lagrangian description of a system of first order conservation laws written in terms of the linear momentum, the triplet of deformation measures (also known as minors of the deformation gradient tensor) and the total energy of the system, extending thus the previous work carried out by some of the authors in the context of isothermal elasticity and elasto-plasticity (Lee et al., 2016; Lee et al., 2017; Lee et al., 2019). To ensure the stability (i.e. hyperbolicity) of the formulation from the continuum point of view, the internal energy density is expressed as a polyconvex combination of the triplet of deformation measures and the entropy density. Moreover, and to guarantee stability from the spatial discretisation point of view, consistently derived Riemann-based numerical dissipation is carefully introduced where local numerical entropy production is demonstrated via a novel technique in terms of the time rate of the so-called ballistic free energy of the system. For completeness, an alternative and equally competitive formulation (in the case of smooth solutions), expressed in terms of the entropy density, is also implemented and compared. A series of numerical examples is presented in order to assess the applicability and robustness of the proposed formulations, where the Smooth Particle Hydrodynamics scheme is benchmarked against an alternative in-house Finite Volume Vertex Centred implementation.

Thornado-hydro: A Discontinuous Galerkin Method for Supernova Hydrodynamics with Nuclear Equations of State*

Abstract This paper describes algorithms for nonrelativistic hydrodynamics in the toolkit for high-order neutrino radiation hydrodynamics (thornado), which is being developed for multiphysics simulations of core-collapse supernovae (CCSNe) and related problems with Runge–Kutta discontinuous Galerkin (RKDG) methods. More specifically, thornado employs a spectral-type nodal collocation approximation, and we have extended limiters—a slope limiter to prevent nonphysical oscillations and a bound-enforcing limiter to prevent nonphysical states—from the standard RKDG framework to be able to accommodate a tabulated nuclear equation of state (EoS). To demonstrate the efficacy of the algorithms with a nuclear EoS, we first present numerical results from basic test problems in idealized settings in one and two spatial dimensions, employing Cartesian, spherical-polar, and cylindrical coordinates. Then, we apply the RKDG method to the problem of adiabatic collapse, shock formation, and shock propagation in spherical symmetry, initiated with a 15 M ⊙ progenitor. We find that the extended limiters improve the fidelity and robustness of the RKDG method in idealized settings. The bound-enforcing limiter improves the robustness of the RKDG method in the adiabatic collapse application, while we find that slope limiting in characteristic fields is vulnerable to structures in the EoS—more specifically, in the phase transition from nuclei and nucleons to bulk nuclear matter. The success of these applications marks an important step toward applying RKDG methods to more realistic CCSN simulations with thornado in the future.

Bleeding Simulation With Improved Visual Effects for Surgical Simulation Systems

In surgical simulation, the Navier–Stokes (N–S) equation is commonly employed to imitate the physical characteristics of bleeding and the smooth particle hydrodynamics (SPHs) algorithm is applied to solve the numerical solution of the N–S equation. However, blood is viscous, incompressible and non-Newtonian fluid whose physical properties cannot be fully incorporated by the simple N–S equation, and the kernel approximation of the SPH algorithm may lead to both edge and volume distortions plus high computational cost. In this paper, both the tension force and the effect of platelets on the viscous force of bleeding particles are incorporated into the N–S equation in order to render more realistic visual effect and biological features of bleeding in surgical simulation. Constant core radius of the kernel function of the SPH algorithm is substituted with a function of particle density, avoiding potential edge distortions in simulating bleeding area. A repulsive force between particles is introduced, which effectively prevents volume distortions. Besides, accelerated search for particles based on the cube mesh improves the computational efficiency. The simulation results show that the presented simulation method leads to smooth bleeding surface and improves the visual effects of edge and volume in comparison with existing methods, and relatively high computational efficiency can be achieved as well.

A parameter-free total Lagrangian smooth particle hydrodynamics algorithm applied to problems with free surfaces

This paper presents a new Smooth Particle Hydrodynamics computational framework for the solution of inviscid free surface flow problems. The formulation is based on the Total Lagrangian description of a system of first-order conservation laws written in terms of the linear momentum and the Jacobian of the deformation. One of the aims of this paper is to explore the use of Total Lagrangian description in the case of large deformations but without topological changes. In this case, the evaluation of spatial integrals is carried out with respect to the initial undeformed configuration, yielding an extremely efficient formulation where the need for continuous particle neighbouring search is completely circumvented. To guarantee stability from the SPH discretisation point of view, consistently derived Riemann-based numerical dissipation is suitably introduced where global numerical entropy production is demonstrated via a novel technique in terms of the time rate of the Hamiltonian of the system. Since the kernel derivatives presented in this work are fixed in the reference configuration, the non-physical clumping mechanism is completely removed. To fulfil conservation of the global angular momentum, a posteriori (least-squares) projection procedure is introduced. Finally, a wide spectrum of dedicated prototype problems is thoroughly examined. Through these tests, the SPH methodology overcomes by construction a number of persistent numerical drawbacks (e.g. hour-glassing, pressure instability, global conservation and/or completeness issues) commonly found in SPH literature, without resorting to the use of any ad-hoc user-defined artificial stabilisation parameters. Crucially, the overall SPH algorithm yields equal second order of convergence for both velocities and pressure.

ISPH modeling and investigation of the effect of viscosity variations on the fluids mixing in a micro-channel due to oscillation of a circular cylinder

In the present study, an improved Incompressible Smoothed Particle Hydrodynamics algorithm (ISPH) is proposed to model the mixing flow in an active micromixer in which an oscillating cylinder cusses to enhance the mixing rate. The mass transport is investigated for the case that the inlet fluids can have different viscosities. First, the numerical procedure is explained. Then it is validated against analytical results and other numerical results. Last, the main problem is modeled and investigated. For the channel, the entering fluids have different concentration and viscosity. The effect of viscosity differences is investigated for different Forced-Strouhal and Reynolds numbers. The results show that these two non-dimensional parameters have an essential role in the behavior of the cases with different viscosity. The present results also indicate that the viscosity differences have major effects on the mixing rate.

A New Method for Ice–Ice Aggregation in the Adaptive Habit Model

Abstract A novel methodology for modeling ice–ice aggregation is presented. This methodology combines a modified hydrodynamic collection algorithm with bulk aggregate characteristic information from an offline simulator that collects ice particles, namely, the Ice Particle and Aggregate Simulator, and has been implemented into the Adaptive Habit Microphysics scheme in the Weather Research and Forecasting Model. Aggregates, or snow, are formed via collection of cloud ice particles, where initial ice characteristics and the resulting geometry determine aggregate characteristics. Upon implementation, idealized squall-line simulations are performed to examine the new methodology in comparison with commonly used bulk microphysics schemes. It is found that the adaptive habit aggregation parameterization develops snow and reduces ice mass and number concentrations compared to other schemes. The development of aggregates through the new methodology cascades into other interesting effects, including enhancements in ice and snow growth, as well as homogeneous freezing. Further microphysical analyses reveal varying sensitivities, where snow processes are most sensitive to the new parameterization, followed by ice, then cloud, rain, and graupel processes. Further, the new scheme results in enhancements in surface precipitation due to the persistence of snow at lower altitudes. This persistence is a result of shape-dependent melting and sublimation, increasing the residence time. Moreover, these low-level enhancements are reflected in increases in radar reflectivity at the surface and its spatial distribution. Finally, the ability to predict snow shape and density allows for the simulation of polarimetric radar quantities, resulting in signature enhancements compared to schemes that do not consider spatial and temporal variations in snow shape and density.

A smoothed particle hydrodynamics algorithm for multigrain dust with separate sets of particles

ABSTRACT We present a method for simulating the dynamics of a mixture of gas and multiple species of large Stokes number dust grains, typical of evolved protoplanetary discs and debris discs. The method improves upon earlier methods, in which only a single grain size could be represented, by capturing the differential backreaction of multiple dust species on the gas. This effect is greater for large dust-to-gas ratios that may be expected in the later stages of the protoplanetary disc life. We benchmark the method against analytic solutions for linear waves, drag, and shocks in dust–gas mixtures, and radial drift in a protoplanetary disc showing that the method is robust and accurate.

Analysis of Movement Law and Influencing Factors of Hill-Drop Fertilizer Based on SPH Algorithm

Studying the movement law and influencing factors of fertilizer in soil and controlling fertilizer distribution can improve the quality of fertilization, which is of great significance for promoting crop yield. In this paper, a 3D simulation model of the hill-drop fertilizer device and soil was established by the Smoothed Particle Hydrodynamics (SPH) algorithm, and the simulation model was modified using the Mohr–Coulomb criterion, and fertilizer movement in the soil under the disturbance of the cover was simulated and analyzed by the SPH algorithm. Orthogonal simulation experiments and the range analysis method were used to study the overall displacement and deformation of fertilizer, and the key factors affecting fertilizer movement were analyzed. After fertilization, the soil was layered with a soil sampler, and a digital image processing method was used to detect the fertilizer distribution in different soil depths; then, the fertilizer movement was inferred. The results of the field experiment showed that the trend of fertilizer movement was consistent with the results of the simulation experiment, which provides a reference for studying the movement and distribution of fertilizer in soil.

Coarse grained simulation of convectively driven turbulent mixing, transition, and turbulence decay

Accurate predictions with quantifiable uncertainties are essential to many practical turbulent flow applications exhibiting extreme geometrical complexity and broad ranges of length and time scales. Under-resolved computer simulations are typically unavoidable in such applications, and implicit large-eddy simulation (ILES) often becomes the effective strategy. We focus on assessing ILES initialized with well-characterized 2563 homogeneous isotropic turbulence datasets generated with direct numerical simulation (DNS). ILES solutions based on the LANL xRAGE code are studied as function of resolution for 643, 1283, 2563, and 5123 grids. ILES performance of new directionally-unsplit high-order numerical hydrodynamics algorithms in xRAGE is examined in this context. Compared to the initial 2563 DNS, we find longer inertial subranges and higher turbulence Reynolds number (Re) for 2563 and 5123 xRAGE — attributed to having linked DNS (Navier–Stokes based) solutions to nominally inviscid (higher Re) Euler based ILES solutions. For fixed 2563 resolution, we find that significantly larger simulated turbulence Re can be achieved with the higher-order unsplit (vs. split) discretizations.