Comparative DEM-CFD study of binary interaction and acoustic agglomeration of aerosol microparticles at low frequencies

Kačianauskas, Rimantas; Rimša, Vytautas; Kačeniauskas, Arnas; Maknickas, Algirdas; Vainorius, Darius; Pacevič, Ruslan

doi:10.1016/j.cherd.2018.06.006

Cited by 22 publications

(7 citation statements)

References 59 publications

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“…The discrete element or discrete particle method is considered a powerful numerical technique to understand and model granular materials [37]. However, advanced DEM models can be effectively applied to study heat transfer [38], acoustic agglomeration [39], and coupled multi-physical problems [40].…”

Section: Discrete Element Methods Softwarementioning

confidence: 99%

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021

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The pervasive use of cloud computing has led to many concerns, such as performance challenges in communication- and computation-intensive services on virtual cloud resources. Most evaluations of the infrastructural overhead are based on standard benchmarks. Therefore, the impact of communication issues and infrastructure services on the performance of parallel MPI-based computations remains unclear. This paper presents the performance analysis of communication- and computation-intensive software based on the discrete element method, which is deployed as a service (SaaS) on the OpenStack cloud. The performance measured on KVM-based virtual machines and Docker containers of the OpenStack cloud is compared with that obtained by using native hardware. The improved mapping of computations to multicore resources reduced the internode MPI communication by 34.4% and increased the parallel efficiency from 0.67 to 0.78, which shows the importance of communication issues. Increasing the number of parallel processes, the overhead of the cloud infrastructure increased to 13.7% and 11.2% of the software execution time on native hardware in the case of the Docker containers and KVM-based virtual machines of the OpenStack cloud, respectively. The observed overhead was mainly caused by OpenStack service processes that increased the load imbalance of parallel MPI-based SaaS.

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Section: Discrete Element Methods Softwarementioning

confidence: 99%

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021

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“…19 Recent studies have employed three-dimensional Computational Fluid Dynamics and the Discrete Element Method (CFD-DEM) to simulate acoustic agglomeration, focusing on flow pattern influences. 23,98,104…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, the Monte Carlo model currently does not account for agglomeration in turbulent flows, , necessitating the inclusion of a turbulent agglomeration kernel function in future Monte Carlo simulations . Recent studies have employed three-dimensional Computational Fluid Dynamics and the Discrete Element Method (CFD-DEM) to simulate acoustic agglomeration, focusing on flow pattern influences. ,, This approach is particularly suitable for turbulent flow conditions, yielding superior results compared to those obtained under simple laminar flow conditions. Currently, within the algorithms utilizing the Population Balance (PB) model, the simulation method employing the adaptive Monte Carlo technique exhibits the highest degree of fit with experimental values, with an approximate error of 1%.…”

Section: Discussionmentioning

confidence: 99%

“…Unlike the population balance model (PBM), DEM calculates actual particle motion without utilizing an agglomeration kernel function and eschews the assumptions inherent in PBM. This method is perceived as a highly accurate agglomeration simulation technique. ,− However, due to its requirement for minute time steps, it is computationally intensive, both in terms of time and cost, rendering it less suitable for large-scale particle flow agglomeration simulations. To address the issue of extended computation times, some researchers have adopted multitime step algorithms to expedite simulations.…”

Section: Comments On Research Related To Acoustic Agglomerationmentioning

confidence: 99%

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Review of Acoustic Agglomeration Technology Research

Zhang,

Deng,

Luo

et al. 2024

ACS Omega

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Acoustic agglomeration is employed as a precursor technique that modifies the sound field of fine particles to increase their size, thereby facilitating more efficient emission control. This paper reviews progress in the field of acoustic agglomeration technology, clarifies the mechanisms at play within the acoustic agglomeration process, and outlines its applicability in both gas−liquid and gas−solid phases. Furthermore, it analyzes the factors impacting the efficacy of acoustic agglomeration, summarizes the numerical simulation research of acoustic agglomeration, and proposes directions for technological enhancement.

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“…Thus, DEM can simulate the transition process from the continuum to discontinuum by changing the bond types between the particles without the need for specialized elements or remeshing lattices. Now, various DEM models are not limited to the analysis of granular materials [4,5], but can be effectively applied to studying rock cutting [6], coupled multi-physical problems [7], sea ice failure [8] and the fracture of reinforced concrete [9].…”

Section: Introductionmentioning

confidence: 99%

The Performance Analysis of the Thermal Discrete Element Method Computations on the GPU

Pacevič

Kačeniauskas

2022

cai

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The paper presents a GPU implementation of the thermal discrete element method (TDEM) and the comparative analysis of its performance. Several discrete element models for granular flows, the bonded particle model and the TDEM are considered for quantitative comparison of computational performance. The performance measured on NVIDIA ® Tesla™ P100 GPU is compared with that attained by running the same OpenCL code on Intel ® Xeon™ E5-2630 CPU with 20 cores. The presented GPU implementation of the TDEM increases the computing time of the bonded particle model only up to 30.6 % of the computing time of the simplest DEM model, which is an acceptable decrease in the performance required for solving coupled thermomechanical problems.

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Comparative DEM-CFD study of binary interaction and acoustic agglomeration of aerosol microparticles at low frequencies

Cited by 22 publications

References 59 publications

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

Review of Acoustic Agglomeration Technology Research

The Performance Analysis of the Thermal Discrete Element Method Computations on the GPU

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