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DOE OSTI2010

PEBBLES Mechanics Simulation Speedup

Pebble bed reactors contain large numbers of spherical fuel elements arranged randomly. Determining the motion and location of these fuel elements is required for calculating certain parameters of pebble bed reactor operation. These simulations involve hundreds of thousands of pebbles and involve determining the entire core motion as pebbles are recirculated. Single processor algorithms for this are insufficient since they would take decades to centuries of wall-clock time. This paper describes the process of parallelizing and speeding up the PEBBLES pebble mechanics simulation code. Both shared memory programming with the Open Multi-Processing API and distributed memory programming with the Message Passing Interface API are used in simultaneously in this process. A new shared memory lock-less linear time collision detection algorithm is described. This method allows faster detection of pebbles in contact than generic methods. These combine to make full recirculations on AVR sized reactors possible in months of wall clock time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

OceanWATERS Lander Robotic Arm Operation

Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) is an open-source simulator for developing onboard autonomy software for robotic exploration of ocean worlds, such as Europa, Enceladus, and Titan, built on the Robot Operating System (ROS) and Gazebo simulation environment. Inevitable ground communication delays increase demand for a high degree of autonomy during excavation, collection and transfer of samples to scientific instruments for in-situ analysis. This paper offers a detailed discussion of the robotic arm design and operation for such autonomous surface exploration, taking as reference the Europa Lander mission. The lander arm, which is designed primarily to acquire icy surface and subsurface samples within the arm’s workspace, is a 6-degree-of-freedom manipulator with two end effectors: a sample excavation tool and a trenching end-effector. The robotic arm’s modes and operations can be summarized as follows: stowed arm, intended as the lander arm default configuration characterized by zero-power consumption; un-stowed arm, target arm configuration after its first deployment; selection and deployment of the end-effector to use next; guarded move, to detect ground level at the desired trenching location; drill ice using the grinder; dig trench at a particular location using the scoop; deliver sample to the sample transfer dock; discard redundant samples. The motion planning tool used for the lander arm is MoveIt, a ROS package. MoveIt uses sampling-based planning and collision checking libraries to determine safe paths. The Rapidly Exploring Random Trees* (RRT*) has been chosen as default planning algorithm as it provides optimal plans with an exponential speed and is guaranteed to find a solution, if feasible solutions exist. Furthermore, this work quantifies and discusses the energy requirements for excavating and collecting samples. In OceanWATERS, force feedback from the terrain, which influences the arm dynamics, is modelled using a discrete element method (DEM) simulation. The DEM and Gazebo software run in parallel and communicate through a co-simulation plugin. This paper presents an analysis and comparison of three DEM open source software (YADE, ESyS-Particle, Project Chrono) for implementation in OceanWATERS and motivates the choice of YADE as most suitable candidate.

Damiana Catanoso↗

NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗

NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

Peter A Liever↗

DOE OSTI2011

Parallel-vector algorithms for particle simulations on shared-memory multiprocessors

Over the last few decades, the computational demands of massive particle-based simulations for both scientific and industrial purposes have been continuously increasing. Hence, considerable efforts are being made to develop parallel computing techniques on various platforms. In such simulations, particles freely move within a given space, and so on a distributed-memory system, load balancing, i.e., assigning an equal number of particles to each processor, is not guaranteed. However, shared-memory systems achieve better load balancing for particle models, but suffer from the intrinsic drawback of memory access competition, particularly during (1) paring of contact candidates from among neighboring particles and (2) force summation for each particle. Here, novel algorithms are proposed to overcome these two problems. For the first problem, the key is a pre-conditioning process during which particle labels are sorted by a cell label in the domain to which the particles belong. Then, a list of contact candidates is constructed by pairing the sorted particle labels. For the latter problem, a table comprising the list indexes of the contact candidate pairs is created and used to sum the contact forces acting on each particle for all contacts according to Newton's third law. With just these methods, memory access competition is avoided without additional redundant procedures. The parallel efficiency and compatibility of these two algorithms were evaluated in discrete element method (DEM) simulations on four types of shared-memory parallel computers: a multicore multiprocessor computer, scalar supercomputer, vector supercomputer, and graphics processing unit. The computational efficiency of a DEM code was found to be drastically improved with our algorithms on all but the scalar supercomputer. Thus, the developed parallel algorithms are useful on shared-memory parallel computers with sufficient memory bandwidth.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Three-Dimensional Evaluation of Sand Particle Fracture Using Discrete-Element Method and Synchrotron Microcomputed Tomography Images

Recent research showed that fracture of sand particles plays a significant role in determining the plastic bulk volumetric changes of granular materials under different loading conditions. One of the major tools used to better understand the influence of particle fracture on the behavior of granular materials is discrete-element modeling (DEM). This paper employed the bonded block model (BBM) to simulate the fracture behavior of sand. Each sand particle is modeled as an agglomerate of rigid blocks bonded at their contacts using the linear-parallel contact model, which can transmit both moment and force. DEM simulated particles closely matched the actual three-dimensional (3D) shape of sand particles acquired using high-resolution 3D synchrotron microcomputed tomography (SMT). Results from unconfined one-dimensional (1D) compression of a single synthetic silica cube were used to calibrate the model parameters. Particle fracture was investigated for specimens composed of three sand particles that were loaded under confined 1D compression. Breakage energy measured from DEM models matched well with that measured experimentally. The paper studied the effects of contact loading condition and particle interaction on the fracture mode of particles using BBM that can closely capture the 3D shape of real sand particles.

58 GEOSCIENCES↗

DOE OSTI2022

CFD-DEM Simulations of Reacting Fluidized Beds with MFIX-Exa

SIAM Conference on Parallel Processing for Scientific Computing, Virtual, February 23-26, 2022

Porcu, Roberto↗

NASA NTRSDate not supplied

Implementation of Charged Particle Behavior in Discrete Element Method (DEM) Simulations

Lunar landers will agitate the surface of the Moon with an exhaust plume during descent which will, due to the particulate nature of the lunar regolith, loosen and eject grains from the surface. This ejection is not only coupled with the charged plume gas, but also results in significant particle-particle interactions. Settling of these grains after plume effects have subsided takes much longer than expected in a ballistic trajectory. The prevailing hypothesis attributes this behavior to the accumulated charge on the particles. We are thus developing a discrete element method (DEM) approach to explore these charged particle interactions on the lunar surface. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) Improved for General Granular and Granular Heat Transfer Simulations (LIGGGHTS) software package provides a DEM modeling framework for granular interactions. It includes many complexities such as non-spherical particle shapes, cohesion and frictional forces, and heat transfer, but has no provision for inter-particle electrostatic forces and charge transfer that are important to examine in the lunar environment. In this work, a standard Coulomb potential and a Yukawa potential are integrated into the LIGGGHTS framework to provide a basis for particle-particle electrostatic interactions, as well as a gravitational potential to enable inter-grain gravitational interactions. A preliminary approach to charge transfer between grains incorporating properties such as work function and electrical conductivity to the library of available material characteristics will be presented. Several scenarios have been simulated that include charged particle interactions within a diffuse granular gas, settling of charged grains into a regolith bed, sliding of granular material along an incline, and vibration of settled grains to produce a behavior similar to fluidization. There are numerous challenges to incorporate realistic interactions between complex lunar particles. Currently, grains are modeled to behave as if the entirety of the charge acts at the center of mass, such as conductors with spherical symmetry and insulators with homogeneously distributed charge. We are developing improvements that will include the use of non-spherical particle geometries, as well as reasonable approximations of insulating/dielectric materials that have non-uniform charge distributions. The cases simulated thus far will be examined in a relevant environment within a vacuum chamber to validate the simulations. These simulations will be bounded by experiments utilizing high-speed camera observations of the motion for validation. The grains in the experiment will exchange charge during their motion and this can be quantified by collection within a charge measurement device such as a Faraday cup. Such a device may be modeled within the software by defining an integration region and computing the contained charge as a function of simulation time, allowing for side-by-side comparison of simulated and measured bulk charging results. Any differences will be reconciled by updating the mathematical mechanisms described within the simulation suite. Successfully combining results from experiments within a relevant environment into the LIGGGHTS framework will improve modeling of the charged grain dynamics experienced on the Moon to provide insights into dust behavior for future lunar exploration missions.

Electrostatics↗

DOE OSTI2021

MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)

The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2015

Simulation of Powder Layer Deposition in Additive Manufacturing Processes Using the Discrete Element Method

This document serves as a final report to a small effort where several improvements were added to a LLNL code GEODYN-L to develop Discrete Element Method (DEM) algorithms coupled to Lagrangian Finite Element (FE) solvers to investigate powder-bed formation problems for additive manufacturing. The results from these simulations will be assessed for inclusion as the initial conditions for Direct Metal Laser Sintering (DMLS) simulations performed with ALE3D. The algorithms were written and performed on parallel computing platforms at LLNL. The total funding level was 3-4 weeks of an FTE split amongst two staff scientists and one post-doc. The DEM simulations emulated, as much as was feasible, the physical process of depositing a new layer of powder over a bed of existing powder. The DEM simulations utilized truncated size distributions spanning realistic size ranges with a size distribution profile consistent with realistic sample set. A minimum simulation sample size on the order of 40-particles square by 10-particles deep was utilized in these scoping studies in order to evaluate the potential effects of size segregation variation with distance displaced in front of a screed blade. A reasonable method for evaluating the problem was developed and validated. Several simulations were performed to show the viability of the approach. Future investigations will focus on running various simulations investigating powder particle sizing and screen geometries.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A PIC Bootstrapping Strategy for Exascale CFD-DEM Simulation

The exascale computing era comes with the release of MFIX-Exa, a new code for studying gas-particle fluidization using CFD-DEM and PIC models on massively parallel, heterogeneous high-performance computing architectures. However, as compute resources continue to grow in scale and complexity, so too does the impetus to use them efficiently. Here, we propose a novel bootstrapping method to minimize neglected simulation time and cast the approach more broadly among a growing field of multi-fidelity methods.

Porcu, Roberto↗

NASA NTRSDate not supplied

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗

NASA NTRS1993

The differential emission measure of nested hot and cool magnetic loops

The detailed thermal structure of the magnetized solar transition region, as measured by its differential emission measure (DEM(T)), is poorly known. Building on the fact that the solar surface is strongly magnetized and thereby structured, proposals have been made that envision a significant lower-temperature contribution to the energy balance from (ion) heat flux across an arcade of different temperature loops. In this paper, we describe a self-consistent 2D MHD simulation, which includes the full thermal effects of parallel stability and anisotropic conduction, of a nested-loop model of the thermal and magnetic structure of the transition region. We then demonstrate that the predicted DEM agrees with observations in the conceptually elusive T less than 10 exp 5 K regime.

Van Hoven, G.↗

DOE OSTI2013

Development of parallel DEM for the open source code MFIX

The paper presents the development of a parallel Discrete Element Method (DEM) solver for the open source code, Multiphase Flow with Interphase eXchange (MFIX) based on the domain decomposition method. The performance of the code was evaluated by simulating a bubbling fluidized bed with 2.5 million particles. The DEM solver shows strong scalability up to 256 processors with an efficiency of 81%. Further, to analyze weak scaling, the static height of the fluidized bed was increased to hold 5 and 10 million particles. The results show that global communication cost increases with problem size while the computational cost remains constant. Further, the effects of static bed height on the bubble hydrodynamics and mixing characteristics are analyzed.

42 ENGINEERING↗

DOE OSTI2010

A convex complementarity approach for simulating large granular flows.

Aiming at the simulation of dense granular flows, we propose and test a numerical method based on successive convex complementarity problems. This approach originates from a multibody description of the granular flow: all the particles are simulated as rigid bodies with arbitrary shapes and frictional contacts. Unlike the discrete element method (DEM), the proposed approach does not require small integration time steps typical of stiff particle interaction; this fact, together with the development of optimized algorithms that can run also on parallel computing architectures, allows an efficient application of the proposed methodology to granular flows with a large number of particles. We present an application to the analysis of the refueling flow in pebble-bed nuclear reactors. Extensive validation of our method against both DEM and physical experiments results indicates that essential collective characteristics of dense granular flow are accurately predicted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Plate motion in sheared granular fault system

Plate motion near the fault gouge layer, and the elastic interplay between the gouge layer and the plate under stick-slip conditions, is key to understanding the dynamics of sheared granular fault systems. Here, a two-dimensional implementation of the combined finite-discrete element method (FDEM), which merges the finite element method (FEM) and the discrete element method (DEM), is used to explicitly simulate a sheared granular gouge fault system. In this work we focus on investigating the influence of normal load, driving shear velocity and plate stiffness on the velocities and displacements in the direction parallel to the shear direction (x-direction) measured at locations on the upper and lower plates just adjacent to the gouge. The simulations show that during slip phases the magnitudes of the measured velocities on the upper and lower plates are proportional to the normal load and may be inversely proportional to the square root of the plate's shear modulus. Whereas, the driving shear velocity does not show distinct influence on the measured velocities. Additionally, large slip velocities are generally associated with large macroscopic friction coefficient drops. For the models subjected to smaller normal loads, larger shear velocities and with stiffer shear plates, the same magnitude of slip velocity could cause a larger drop of macroscopic friction coefficient. During stick phases, the velocities of the upper and lower plates are respectively slightly greater and slightly smaller than half of the driving shear velocity and are both in the same direction of shear. The shear strain rate of the gouge is calculated from this velocity difference between the upper and lower plate during stick phases and thus the gouge effective shear modulus can be calculated. The results show that the gouge effective shear modulus increases proportionally with normal load, while the influence of shear velocity and plate stiffness on gouge effective shear modulus is minor. The simulations address the dynamics of a laboratory-scale fault gouge system and may aid in revealing the complexities of earthquake frictional dynamics.

58 GEOSCIENCES↗

DOE OSTI2024

A High-Performance Discrete-Element Framework for Simulating Flow and Jamming of Moisture Bearing Biomass Feedstocks

We developed and verified a high-performance open-source discrete element method (DEM) solver with simultaneously-supported feedstock-specific interaction models, including bonded-sphere, liquid bridge, cohesion, and non-linear contact models. Our solver uses parallel data structures on hybrid central and graphics processing unit (CPU/GPU) architectures, with favorable strong scaling performance observed for large problem sizes comprised of (100 M particles), and 4X single-node GPU speedup. The particles for corn stover feedstock were conceptualized and calibrated based on experimental measurements and results. Sensitivity analyses demonstrate that the mass flow rate from a wedge hopper is governed primarily by moisture content, friction coefficient, and cohesion energy density. The model is used to reproduce experimentally observed hopper jamming results, highlighting that the experimental no-flow trends can only be achieved by using non-spherical particles, liquid bridge and cohesion models, highlighting the importance of using concurrent feedstock specialized models for the effective representation of biomass material handling problems.

bioenergy↗

DOE OSTI2015

Application of parallel distributed Lagrange multiplier technique to simulate coupled Fluid-Granular flows in pipes with varying Cross-Sectional area

Fluid-granular flows are common phenomena in nature and industry. Here, an efficient computational technique based on the distributed Lagrange multiplier method is utilized to simulate complex fluid-granular flows. Each particle is explicitly resolved on an Eulerian grid as a separate domain, using solid volume fractions. The fluid equations are solved through the entire computational domain, however, Lagrange multiplier constrains are applied inside the particle domain such that the fluid within any volume associated with a solid particle moves as an incompressible rigid body. The particle–particle interactions are implemented using explicit force-displacement interactions for frictional inelastic particles similar to the DEM method with some modifications using the volume of an overlapping region as an input to the contact forces. Here, a parallel implementation of the method is based on the SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗