A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

Analysis of jacking forces during pipe jacking in granular materials using particle methods

Trenchless technology is often used in congested urban areas or river crossings to install underground pipelines to minimize disturbance to surface traffic or other activities.Pipe jacking is a typical technique applied to jack pipe segments between two working shafts.However,the design of the jacking force is usually implemented using empirical methods.It should be emphasized that the jacking force will change for each site,depending on the magnitude of overcut,lubricants,work stoppages,geology and misalignment.A particle method is proposed to estimate the jacking force along the pipe.The microparameters are calibrated for sandy soils in Shenyang,so that the macroscale material behavior can be reproduced using the particle model.Hence,the normal force around the pipe circumference can be derived in the particle model,after which the interface friction coefficient is applied to evaluate the friction resistance mobilized at the soil-pipe interface.A modified Protodyakonov’s arch model can be used to assess the magnitude of earth pressure acting on the shield face.In the end,the combination of friction resistance and face pressure provides the jacking force.The efficacy of the proposed particle method is demonstrated by comparing calculated jacking forces with those measured in the field for three types of jacking machines in sandy soils under the Hun River,Shenyang.

Computing Multivalued Solutions of Pressureless Gas Dynamics by Deterministic Particle Methods

We compute multivalued solutions of one-and two-dimensional pressureless gas dynamics equations by deterministic particle methods.Point values of the computed solutions are to be recovered from their singular particle approximations using some smoothing procedure.We study several recovery strategies and demonstrate ability of the particle methods to achieve high resolution.

PARTICLE METHODS FOR COMPLEX FLOWS IN CHEMICAL ENGINEERING ——THE PSEUDO-PARTICLE APPROACH

The multi-scale structures of complex flows in chemical engineering have been great challenges to the design and scaling of such systems, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constituents and powerful tools of multi-scale models, owing to their physical fidelity and computational simplicity. Especially, pseudo-particle modeling (PPM, Ge & Li, 1996; Ge & Li, 2003) is most suitable for molecular scale flow prediction and exploration of the origin of multi-scale structures; macro-scale PPM (MaPPM, Ge & Li, 2001) and similar models are advantageous for meso-scale simulations of flows with complex and dynamic discontinuity, while the lattice Boltzmann model is more competent for homogeneous media in complex geometries; and meso-scale methods such as dissipative particle dynamics are unique tools for complex fluids of uncertain properties or flows with strong thermal fluctuations. All these methods are favorable for seamless interconnection of models for different scales. However, as PMs are not originally designed as either tools for complexity or constituents of multi-scale models, further improvements are expected. PPM is proposed for microscopic simulation of particle-fluid systems as a combination of molecular dynamics (MD) and direct simulation Monte-Carlo (DSMC). The collision dynamics in PPM is identical to that of hard-sphere MD, so that mass, momentum and energy are conserved to machine accuracy. However, the collision detection procedure, which is most time-consuming and difficult to be parallelized for hard-sphere MD, has been greatly simplified to a procedure identical to that of soft-sphere MD. Actually, the physical model behind such a treatment is essentially different from MD and is more similar to DSMC, but an intrinsic difference is that in DSMC the collisions follow designed statistical rules that are reflection of the real physical processes only in very limited cases such as dilute gas. PPM is ideal for exploring the mechanism of complex flows ab initio. In final analysis, the complexity of flow behavior is shaped by two components on the micro-scale: the relative displacements and interactions of the numerous molecules. Adding to the generality of the characteristics of complex system as described by Li and Kwauk (2003), we notice that complex structures or behaviors are most probably observed when these two components are competitive and hence they must compromise, as in the case of emulsions and the so-called soft-matter that includes most bio-systems. When either displacement or interaction is dominant, as in the case of dilute gas or solid crystals, respectively, complexity is much less spectacular. Most PMs consist explicitly of these two components, which is operator splitting in a numerical sense, but it is physically more meaningful and concise in PPM. The properties of the pseudo-particle fluid are in good conformance to typical simple gas (Ge et al., 2003; Ge et al., 2005). The ability of PPM to describe the dynamic transport process on the micro-scale in heterogeneous particle-fluid systems has been demonstrated in recent simulations (Ge et al., 2005). Especially, the method has been employed to study the temporal evolution of the stability criterion in the energy minimization multi-scale model (Li & Kwauk, 1994), which confirms its monotonously asymptotic decreasing as the model has assumed (Zhang et al., 2005). Massive parallel processing is also practiced for simulating particle-fluid systems in PPM, indicating an optimistic prospect to elevate the computational limitations on their wider applications, and exploring deeper underlying mechanism in complex particle-fluid systems.

Random Batch Particle Methods for the Homogeneous Landau Equation

We consider in this paper randombatch particlemethods for efficiently solving the homogeneous Landau equation in plasma physics.The methods are stochastic variations of the particle methods proposed by Carrillo et al.[J.Comput.Phys.:X 7:100066,2020]using the random batch strategy.The collisions only take place inside the small but randomly selected batches so that the computational cost is reduced to O(N)per time step.Meanwhile,our methods can preserve the conservation of mass,momentum,energy and the decay of entropy.Several numerical examples are performed to validate our methods.

A dynamic large-deformation particle finite element method for geotechnical applications based on Abaqus

In this paper,the application of Abaqus-based particle finite element method(PFEM)is extended from static to dynamic large deformation.The PFEM is based on periodic mesh regeneration with Delaunay triangulation to avoid mesh distortion.Additional mesh smoothing and boundary node smoothing techniques are incorporated to improve the mesh quality and solution accuracy.The field variables are mapped from the old to the new mesh using the closest point projection method to minimize the mapping error.The procedures of the proposed Abaqus-based dynamic PFEM(Abaqus-DPFEM)analysis and its implementation in Abaqus are detailed.The accuracy and robustness of the proposed approach are examined via four illustrative numerical examples.The numerical results show a satisfactory agreement with published results and further confirm the applicability of the Abaqus-DPFEM to solving dynamic large-deformation problems in geotechnical engineering.

耦合拉格朗日-欧拉方法及其在海洋工程中的应用

Combining the strengths of Lagrangian and Eulerian descriptions,the coupled Lagrangian–Eulerian methods play an increasingly important role in various subjects.This work reviews their development and application in ocean engineering.Initially,we briefly outline the advantages and disadvantages of the Lagrangian and Eulerian descriptions and the main characteristics of the coupled Lagrangian–Eulerian approach.Then,following the developmental trajectory of these methods,the fundamental formulations and the frameworks of various approaches,including the arbitrary Lagrangian–Eulerian finite element method,the particle-in-cell method,the material point method,and the recently developed Lagrangian–Eulerian stabilized collocation method,are detailedly reviewed.In addition,the article reviews the research progress of these methods with applications in ocean hydrodynamics,focusing on free surface flows,numerical wave generation,wave overturning and breaking,interactions between waves and coastal structures,fluid–rigid body interactions,fluid–elastic body interactions,multiphase flow problems and visualization of ocean flows,etc.Furthermore,the latest research advancements in the numerical stability,accuracy,efficiency,and consistency of the coupled Lagrangian–Eulerian particle methods are reviewed;these advancements enable efficient and highly accurate simulation of complicated multiphysics problems in ocean and coastal engineering.By building on these works,the current challenges and future directions of the hybrid Lagrangian–Eulerian particle methods are summarized.

h-ADAPTIVITY ANALYSIS BASED ON MULTIPLE SCALE REPRODUCING KERNEL PARTICLE METHOD

An h-adaptivity analysis scheme based on multiple scale reproducing kernel particle method was proposed, and two node refinement strategies were constructed using searching-neighbor-nodes（SNN） and local-Delaunay-triangulation（LDT） techniques, which were suitable and effective for h-adaptivity analysis on 2-D problems with the regular or irregular distribution of the nodes. The results of multiresolution and h- adaptivity analyses on 2-D linear elastostatics and bending plate problems demonstrate that the improper high-gradient indicator will reduce the convergence property of the h- adaptivity analysis, and that the efficiency of the LDT node refinement strategy is better than SNN, and that the presented h-adaptivity analysis scheme is provided with the validity, stability and good convergence property.

ANALYSIS OF THREE-DIMENSIONAL UPSETTING PROCESS BY THE RIGID-PLASTIC REPRODUCING KERNEL PARTICLE METHOD

A meshless approach, called the rigid-plastic reproducing kernel particle method （RKPM）, is presented for three-dimensional （3D） bulk metal forming simulation. The approach is a combination of RKPM with the flow theory of 3D rigid-plastic mechanics. For the treatments of essential boundary conditions and incompressibility constraint, the boundary singular kernel method and the modified penalty method are utilized, respectively. The arc-tangential friction model is employed to treat the contact conditions. The compression of rectangular blocks, a typical 3D upsetting operation, is analyzed for different friction conditions and the numerical results are compared with those obtained using commercial rigid-plastic FEM （finite element method） software Deform^3D. As results show, when handling 3D plastic deformations, the proposed approach eliminates the need of expensive meshing and remeshing procedures which are unavoidable in conventional FEM and can provide results that are in good agreement with finite element predictions.

The complex variable reproducing kernel particle method for two-dimensional elastodynamics

On the basis of the reproducing kernel particle method （RKPM）, a new meshless method, which is called the complex variable reproducing kernel particle method （CVRKPM）, for two-dimensional elastodynamics is presented in this paper. The advantages of the CVRKPM are that the correction function of a two-dimensional problem is formed with one-dimensional basis function when the shape function is obtained. The Galerkin weak form is employed to obtain the discretised system equations, and implicit time integration method, which is the Newmark method, is used for time history analysis. And the penalty method is employed to apply the essential boundary conditions. Then the corresponding formulae of the CVRKPM for two-dimensional elastodynamics are obtained. Three numerical examples of two-dimensional elastodynamics are presented, and the CVRKPM results are compared with the ones of the RKPM and analytical solutions. It is evident that the numerical results of the CVRKPM are in excellent agreement with the analytical solution, and that the CVRKPM has greater precision than the RKPM.

Parallelized Implementation of the Finite Particle Method for Explicit Dynamics in GPU

As a novel kind of particle method for explicit dynamics,the finite particle method(FPM)does not require the formation or solution of global matrices,and the evaluations of the element equivalent forces and particle displacements are decoupled in nature,thus making this method suitable for parallelization.The FPM also requires an acceleration strategy to overcome the heavy computational burden of its explicit framework for time-dependent dynamic analysis.To this end,a GPU-accelerated parallel strategy for the FPM is proposed in this paper.By taking advantage of the independence of each step of the FPM workflow,a generic parallelized computational framework for multiple types of analysis is established.Using the Compute Unified Device Architecture(CUDA),the GPU implementations of the main tasks of the FPM,such as evaluating and assembling the element equivalent forces and solving the kinematic equations for particles,are elaborated through careful thread management and memory optimization.Performance tests show that speedup ratios of 8,25 and 48 are achieved for beams,hexahedral solids and triangular shells,respectively.For examples consisting of explicit dynamic analyses of shells and solids,comparisons with Abaqus using 1 to 8 CPU cores validate the accuracy of the results and demonstrate a maximum speed improvement of a factor of 11.2.

An interpolating reproducing kernel particle method for two-dimensional scatter points

An interpolating reproducing kernel particle method for two-dimensional （2D） scatter points is introduced. It elim- inates the dependency of gridding in numerical calculations. The interpolating shape function in the interpolating repro- ducing kernel particle method satisfies the property of the Kronecker delta function. This method offers a mathematics basis for recognition technology and simulation analysis, which can be expressed as simultaneous differential equations in science or project problems. Mathematical examples are given to show the validity of the interpolating reproducing kernel particle method.

Combining the complex variable reproducing kernel particle method and the finite element method for solving transient heat conduction problems

In this paper, the complex variable reproducing kernel particle （CVRKP） method and the finite element （FE） method are combined as the CVRKP-FE method to solve transient heat conduction problems. The CVRKP-FE method not only conveniently imposes the essential boundary conditions, but also exploits the advantages of the individual methods while avoiding their disadvantages, then the computational efficiency is higher. A hybrid approximation function is applied to combine the CVRKP method with the FE method, and the traditional difference method for two-point boundary value problems is selected as the time discretization scheme. The corresponding formulations of the CVRKP-FE method are presented in detail. Several selected numerical examples of the transient heat conduction problems are presented to illustrate the performance of the CVRKP-FE method.

DEM simulation of particle flow on a single deck banana screen

A mathematical study of particle flow on a banana screen deck using the discrete element method (DEM) was presented in this paper. The motion characteristics and penetrating mechanisms of particles on the screen deck were studied. Effects of geometric parameters of screen deck on banana screening process were also investigated. The results show that when the values of inclination of discharge and increment of screen deck inclination are 10° and 5° respectively, the banana screening process get a good screening performance in the simulation. The relationship between screen deck length and screening efficiency was further confirmed. The conclusion that the screening efficiency will not significantly increase when the deck length L≥430 mm (L/B ≥ 3.5) was obtained, which can provide theoretical basis for the optimization of banana screen.

A GPU-Based Parallel Algorithm for 2D Large Deformation Contact Problems Using the Finite Particle Method

Large deformation contact problems generally involve highly nonlinear behaviors,which are very time-consuming and may lead to convergence issues.The finite particle method(FPM)effectively separates pure deformation from total motion in large deformation problems.In addition,the decoupled procedures of the FPM make it suitable for parallel computing,which may provide an approach to solve time-consuming issues.In this study,a graphics processing unit(GPU)-based parallel algorithm is proposed for two-dimensional large deformation contact problems.The fundamentals of the FPM for planar solids are first briefly introduced,including the equations of motion of particles and the internal forces of quadrilateral elements.Subsequently,a linked-list data structure suitable for parallel processing is built,and parallel global and local search algorithms are presented for contact detection.The contact forces are then derived and directly exerted on particles.The proposed method is implemented with main solution procedures executed in parallel on a GPU.Two verification problems comprising large deformation frictional contacts are presented,and the accuracy of the proposed algorithm is validated.Furthermore,the algorithm’s performance is investigated via a large-scale contact problem,and the maximum speedups of total computational time and contact calculation reach 28.5 and 77.4,respectively,relative to commercial finite element software Abaqus/Explicit running on a single-core central processing unit(CPU).The contact calculation time percentage of the total calculation time is only 18%with the FPM,much smaller than that(50%)with Abaqus/Explicit,demonstrating the efficiency of the proposed method.

Robust airfoil optimization based on improved particle swarm optimization method

A robust airfoil optimization platform is constructed based on the modified particle swarm optimization method （i.e., the second-order oscillating particle swarm method）, which consists of an efficient optimization algorithm, a precise aerodynamic analysis program, a high accuracy surrogate model, and a classical airfoil parametric method. There are two improvements for the modified particle swarm method compared with the standard particle swarm method. First, the particle velocity is represented by the combination of the particle position and the variation of position, which makes the particle swarm algorithm a second-order precision method with respect to the particle po- sition. Second, for the sake of adding diversity to the swarm and enlarging the parameter searching domain to improve the global convergence performance of the algorithm, an oscillating term is introduced to the update formula of the particle velocity. At last, tak- ing two airfoils as examples, the aerodynamic shapes are optimized on this optimization platform. It is shown from the optimization results that the aerodynamic characteristic of the airfoils is greatly improved in a broad design range.

Effect of curing time on the mesoscopic parameters of cemented paste backfill simulated using the particle flow code technique

Several special mechanical properties,such as dilatancy and compressibility,of cemented paste backfill(CPB)are controlled by its internal microstructure and evolution.The mesoscopic structure changes of CPB during the development process were investigated.On the basis of the scanning electron microscopy(SEM)and mechanical test results of CPB,the particle size information of CPB was extracted,and a two-dimensional particle flow code(PFC)model of CPB was established to analyze the evolution rule of mesoscopic parameters during CPB development.The embedded FISH language in PFC was used to develop a program for establishing a PFC model on the basis of the SEM results.The mesoscopic parameters of CPB samples at different curing times,such as coordination number(C_(n)),contact force chain,and rose diagram,were obtained by recording and loading and used to analyze the intrinsic relationship between mesoscopic parameter variations and macroscopic mechanical response during CPB development.It is of considerable significance to establish the physical model of CPB using the PFC to reveal the mesoscopic structure of CPB.

Development of hybrid optimization algorithm for structures furnished with seismic damper devices using the particle swarm optimization method and gravitational search algorithm

Previous studies about optimizing earthquake structural energy dissipation systems indicated that most existing techniques employ merely one or a few parameters as design variables in the optimization process,and thereby are only applicable only to simple,single,or multiple degree-of-freedom structures.The current approaches to optimization procedures take a specific damper with its properties and observe the effect of applying time history data to the building;however,there are many different dampers and isolators that can be used.Furthermore,there is a lack of studies regarding the optimum location for various viscous and wall dampers.The main aim of this study is hybridization of the particle swarm optimization(PSO) and gravitational search algorithm(GSA) to optimize the performance of earthquake energy dissipation systems(i.e.,damper devices) simultaneously with optimizing the characteristics of the structure.Four types of structural dampers device are considered in this study:(ⅰ) variable stiffness bracing(VSB) system,(ⅱ) rubber wall damper(RWD),(ⅲ) nonlinear conical spring bracing(NCSB) device,(iv) and multi-action stiffener(MAS) device.Since many parameters may affect the design of seismic resistant structures,this study proposes a hybrid of PSO and GSA to develop a hybrid,multi-objective optimization method to resolve the aforementioned problems.The characteristics of the above-mentioned damper devices as well as the section size for structural beams and columns are considered as variables for development of the PSO-GSA optimization algorithm to minimize structural seismic response in terms of nodal displacement(in three directions) as well as plastic hinge formation in structural members simultaneously with the weight of the structure.After that,the optimization algorithm is implemented to identify the best position of the damper device in the structural frame to have the maximum effect and minimize the seismic structure response.To examine the performance of the proposed PSO-GSA optimization method,it has been applied to a three-story reinforced structure equipped with a seismic damper device.The results revealed that the method successfully optimized the earthquake energy dissipation systems and reduced the effects of earthquakes on structures,which significantly increase the building’s stability and safety during seismic excitation.The analysis results showed a reduction in the seismic response of the structure regarding the formation of plastic hinges in structural members as well as the displacement of each story to approximately 99.63%,60.5%,79.13% and 57.42% for the VSB device,RWD,NCSB device,and MAS device,respectively.This shows that using the PSO-GSA optimization algorithm and optimized damper devices in the structure resulted in no structural damage due to earthquake vibration.

Particle path tracking method in two- and three-dimensional continuously rotating detonation engines

The particle path tracking method is proposed and used in two-dimensional（2D） and three-dimensional（3D） numerical simulations of continuously rotating detonation engines（CRDEs）. This method is used to analyze the combustion and expansion processes of the fresh particles, and the thermodynamic cycle process of CRDE. In a 3D CRDE flow field, as the radius of the annulus increases, the no-injection area proportion increases, the non-detonation proportion decreases, and the detonation height decreases. The flow field parameters on the 3D mid annulus are different from in the 2D flow field under the same chamber size. The non-detonation proportion in the 3D flow field is less than in the 2D flow field. In the 2D and 3D CRDE, the paths of the flow particles have only a small fluctuation in the circumferential direction. The numerical thermodynamic cycle processes are qualitatively consistent with the three ideal cycle models, and they are right in between the ideal F–J cycle and ideal ZND cycle. The net mechanical work and thermal efficiency are slightly smaller in the 2D simulation than in the 3D simulation. In the 3D CRDE, as the radius of the annulus increases, the net mechanical work is almost constant, and the thermal efficiency increases. The numerical thermal efficiencies are larger than F–J cycle, and much smaller than ZND cycle.

Simulation of random mixed packing of different density particles

This paper presents the effects of density difference on the three-dimensional （3D） distribution of random mixed packing. The random mixed packing dynamics of particles of two different densities are simulated. The initial state is homogeneous, but the final packing state is inhomogeneous. The segregation phenomenon （inhomogeneous distribution） is also observed. In the final state, the top layers are composed of mostly light particles. The several layers beneath the top contain more heavy particles than light particles. At the bottom, they also contain more heavy particles than light particles. Furthermore, at both the top and the bottom, particle clustering is observed. The current study also analyses the cause of this inhomogeneity in detail. The main cause of this phenomenon is the velocity difference after collision of these two types of particles induced by the density difference. The present study reveals that even if particles were perfectly mixed, the packing process would lead to the final inhomogeneous mixture. It suggests that special treatment may be required to get the true homogeneous packing.