An MPI parallel DEM-IMB-LBM framework for simulating fluid-solid interaction problems

The high-resolution DEM-IMB-LBM model can accurately describe pore-scale fluid-solid interactions,but its potential for use in geotechnical engineering analysis has not been fully unleashed due to its prohibitive computational costs.To overcome this limitation,a message passing interface(MPI)parallel DEM-IMB-LBM framework is proposed aimed at enhancing computation efficiency.This framework utilises a static domain decomposition scheme,with the entire computation domain being decomposed into multiple subdomains according to predefined processors.A detailed parallel strategy is employed for both contact detection and hydrodynamic force calculation.In particular,a particle ID re-numbering scheme is proposed to handle particle transitions across sub-domain interfaces.Two benchmarks are conducted to validate the accuracy and overall performance of the proposed framework.Subsequently,the framework is applied to simulate scenarios involving multi-particle sedimentation and submarine landslides.The numerical examples effectively demonstrate the robustness and applicability of the MPI parallel DEM-IMB-LBM framework.

A particle-resolved heat-particle-fluid coupling model by DEM-IMB-LBM

Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering.In this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level.In this extended technique,an immersed moving boundary(IMB)scheme is used to couple the discrete element method(DEM)and lattice Boltzmann method(LBM),while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid particles.The resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal flows.To facilitate the understanding and implementation of this coupled model for non-isothermal problems,a complete list is given for the conversion of relevant physical variables to lattice units.Then,benchmark tests,including a single-particle sedimentation and a two-particle drafting-kissing-tumbling(DKT)simulation with heat transfer,are carried out to validate the accuracy of our coupled technique.To further investigate the role of heat transfer in particle-laden flows,two multiple-particle problems with heat transfer are performed.Numerical examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Editorial for Multiscale&Multifield Coupling in Geomechanics

We are delighted to serve as guest editors for this special issue in the Journal of Rock Mechanics and Geotechnical Engineering.The purpose of this special issue is dedicated to gathering the latest research work on Multiscale&Multifield Coupling in Geomechanics,where we delve into the intricate interplay of various fields and scales that govern the behavior of geomaterials.In total,30 manuscripts from USA,China,UK,Germany,Canada,India and United Arab Emirates are selected to be included in this issue.

振动轨迹对钻井振动筛固相运移的影响

基于考虑颗粒表面粘附力的JKR（Johnson-Kendall-Roberts）理论接触模型,建立钻井振动筛的离散元分析模型,针对固相颗粒群在直线和椭圆轨迹筛面上的运移过程进行对比仿真研究。结果表明：直线振动筛颗粒的运移速度略大于椭圆型的;颗粒碰撞次数呈现周期性变化,并且椭圆振动筛的碰撞次数大于直线振动筛的;不同颗粒呈现明显的分层,粒径大的颗粒容易运动到上层,粒径小的颗粒容易运动到底层;受颗粒表面钻井液黏滞阻力的影响,颗粒粒径与筛孔孔径比为0.4~0.6的颗粒透筛率最大,颗粒粒径与筛孔孔径比小于0.4的小颗粒更容易形成颗粒团,阻碍这类颗粒的透筛。

PARALLEL ANALYSIS OF COMBINED FINITE/DISCRETE ELEMENT SYSTEMS ON PC CLUSTER

A computational strategy is presented for the nonlinear dynamic analysis of large- scale combined finite/discrete element systems on a PC cluster.In this strategy,a dual-level domain decomposition scheme is adopted to implement the dynamic domain decomposition.The domain decomposition approach perfectly matches the requirement of reducing the memory size per processor of the calculation.To treat the contact between boundary elements in neighbouring subdomains,the elements in a subdomain are classified into internal,interfacial and external elements.In this way,all the contact detect algorithms developed for a sequential computation could be adopted directly in the parallel computation.Numerical examples show that this implementation is suitable for simulating large-scale problems.Two typical numerical examples are given to demonstrate the parallel efficiency and scalability on a PC cluster.

Deep Learning Predicts Stress–Strain Relations of Granular Materials Based on Triaxial Testing Data

This study presents an AI-based constitutive modelling framework wherein the prediction model directly learns from triaxial testing data by combining discrete element modelling(DEM)and deep learning.A constitutive learning strategy is proposed based on the generally accepted frame-indifference assumption in constructing material constitutive models.The low-dimensional principal stress-strain sequence pairs,measured from discrete element modelling of triaxial testing,are used to train recurrent neural networks,and then the predicted principal stress sequence is augmented to other high-dimensional or general stress tensor via coordinate transformation.Through detailed hyperparameter investigations,it is found that long short-term memory(LSTM)and gated recurrent unit(GRU)networks have similar prediction performance in constitutive modelling problems,and both satisfactorily predict the stress responses of granular materials subjected to a given unseen strain path.Furthermore,the unique merits and ongoing challenges of data-driven constitutive models for granular materials are discussed.

Discrete Element Modelling of Dynamic Behaviour of Rockfills forResisting High Speed Projectile Penetration

This paper presents a convex polyhedral based discrete element method for modelling the dynamic behaviour ofrockfills for resisting high speed projectile penetration. The contact between two convex polyhedra is defined by theMinkowski overlap and determined by the GJK and EPA algorithm. The contact force is calculated by a Minkowskioverlap based normal model. The rotational motion of polyhedral particles is solved by employing a quaternionbased orientation representation scheme. The energy-conserving nature of the polyhedral DEM method ensures arobust and effective modelling of convex particle systems. The method is applied to simulate the dynamic behaviourof a rockfill system under impact of a high speed projectile. The rockfill sample is generated by a three-dimensionalVoronoi meso method with a specific particle size distribution. The penetrating process of the projectile strikingthe rockfill target is simulated. Some physical quantities associated with the projectile such as the residual velocity,penetration resistance, and deflection angle are monitored which can reflect the influence of the characteristics ofthe rockfill target on its anti-penetration performance. It can be concluded that the developed polyhedral DEMmethod is a very promising numerical approach in analysing the dynamic behaviour of rockfill systems subject tohigh speed projectile impact.

STCF conceptual design report (Volume 1): Physics & detector

The superτ-charm facility(STCF)is an electron–positron collider proposed by the Chinese particle physics community.It is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of 0.5×10^(35) cm^(–2)·s^(–1) or higher.The STCF will produce a data sample about a factor of 100 larger than that of the presentτ-charm factory—the BEPCII,providing a unique platform for exploring the asymmetry of matter-antimatter(charge-parity violation),in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions,as well as searching for exotic hadrons and physics beyond the Standard Model.The STCF project in China is under development with an extensive R&D program.This document presents the physics opportunities at the STCF,describes conceptual designs of the STCF detector system,and discusses future plans for detector R&D and physics case studies.

Amplitude analysis of the decays D^(0)→π^(+)π^(−)π^(+)π^(−)and D^(0)→π^(+)π^(−)π^(0)π^(0)

Using e^(+)e^(−)annihilation data corresponding to an integrated luminosity of 2.93 fb^(−1)taken at the center-of-mass energy√s=3.773 GeV with the BESIII detector,a joint amplitude analysis is performed on the decays D^(0)→π^(+)π^(−)π^(+)π^(−)and D^(0)→π^(+)π^(−)π^(0)π^(0)(non-η).The fit fractions of individual components are obtained,and large interferences among the dominant components of the decays D^(0)→a_(1)(1260)π,D^(0)→π(1300)π,D^(0)→ρ(770)ρ(770),and D^(0)→2(ππ)_(S)are observed in both channels.With the obtained amplitude model,the CP-even fractions of D^(0)→π^(+)π^(−)π^(+)π^(−)and D^(0)→π^(+)π^(−)π^(0)π^(0)(non-η)are determined to be(75.2±1.1_(stat).±1.5_(syst.))%and(68.9±1.5_(stat).±2.4_(syst.))%,respectively.The branching fractions of D^(0)→π^(+)π^(−)π^(+)π^(−)and D^(0)→π^(+)π^(−)π^(0)π^(0)(non-η)are measured to be(0.688±0.010_(stat.)±0.010_(syst.))%and(0.951±0.025_(stat.)±0.021_(syst.))%,respectively.The amplitude analysis provides an important model for the binning strategy in measuring the strong phase parameters of D^(0)→4πwhen used to determine the CKM angleγ(ϕ_(3))via the B^(−)→DK^(−)decay.

Determination of the number ofψ(3686)events taken at BESⅢ

The number ofψ(3686)events collected by the BESⅢdetector during the 2021 run period is determined to be(2259.3±11.1)×10~6 by counting inclusiveψ(3686)hadronic events.The uncertainty is systematic and the statistical uncertainty is negligible.Meanwhile,the numbers ofψ(3686)events collected during the 2009 and 2012run periods are updated to be(107.7±0.6)×10~6 and(345.4±2.6)×10~6,respectively.Both numbers are consistent with the previous measurements within one standard deviation.The total number ofψ(3686)events in the three data samples is(2712.4±14.3)×10~6.

一种用于结构动态过程数值模拟的广义有限元法

提出了一种能同时处理连续体和离散体动态过程的有限元法.该法通过构造接触力模型,将传统的离散元当做标准的一节点有限单元来看待.新构造的一节点单元与常规有限单元具有同样物理特征,包括应力和应变.从而,将离散元算法与有限元算法紧密结合在一起,形成了统一的、与现有有限元系统兼容的广义有限元计算模型.这种模型不仅简化了计算过程,还可最大限度地发挥现有有限元代码的功能.数值算例表明,新方法可以更加有效地模拟大量离散体与连续体相互作用的复杂动力学过程.

Modeling of alkali-silica reaction in concrete:a review

This paper presents a comprehensive review of modeling of alkali-silica reaction(ASR)in concrete.Such modeling is essential for investigating the chemical expansion mechanism and the subsequent influence on the mechanical aspects of the material.The concept of ASR and the mechanism of expansion are first outlined,and the stateof-the-art of modeling for ASR,the focus of the paper,is then presented in detail.The modeling includes theoretical approaches,meso-and macroscopic models for ASR analysis.The theoretical approaches dealt with the chemical reaction mechanism and were used for predicting pessimum size of aggregate.Mesoscopic models have attempted to explain the mechanism of mechanical deterioration of ASR-affected concrete at material scale.The macroscopic models,chemomechanical coupling models,have been generally dcveloped by combining the chemical reaction kinetics with linear or nonlinear mechanical constitutive,and were applied to reproduce and predict the long-term behavior of struetures suffering from ASR.Finally,a conclusion and discussion of the modcling are given.

Modelling of Magnetorheological Fluids with Combined Lattice Boltzmann and Discrete Element Approach

A combined lattice Boltzmann and discrete element approach is proposedfor numerical modelling of magnetorheological fluids. In its formulation, the particledynamics is simulated by the discrete element method, while the fluid field is resolvedwith the lattice Boltzmann method. The coupling between the fluid and the particlesare realized through the hydrodynamic interactions. Procedures for computing magnetic, contact and hydrodynamic forces are discussed in detail. The applicability ofthe proposed solution procedure is illustrated via a two-stage simulation of a MR fluidproblem with four different particle volume fractions. At the first stage, simulationsare performed for the particle chain formation upon application of an external magnetic field;and at the second stage, the rheological properties of the MR fluid underdifferent shear loading conditions are investigated with the particle chains establishedat the first stage as the initial configuration.