Three-dimensional simulations of Bingham plastic flows with the multiple-relaxation-time lattice Boltzmann model

Chen, Songgui; Zhang, Chuan-Hu; Feng, Y. T.; Sun, Qiang; Feng, Jian

doi:10.1080/19942060.2016.1169946

Cited by 17 publications

(12 citation statements)

References 37 publications

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“…No. Besides experimental studies, several numerical models have been developed to simulate the filling process of RFC, such as Distinct Element Method (DEM) 5 , Lattice Boltzmann Method (LBM) 6,7 , Smoothed Particle Hydrodynamics (SPH) method 8 and LBM-DEM hybrid model 9 . HSCC was modelled as a two-phase Bingham fluid in the last hybrid model, where coarse aggregates were simulated by DEM and motor was considered to be Bingham fluid modelled by LBM.…”

Section: Workability Of Hscc and Compactness Of Rfcmentioning

confidence: 99%

Research on Rock-Filled Concrete Dams: a Review

Feng¹,

Zhou²,

Huang³

2018

EasyChair Preprints

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Rock-Filled Concrete (RFC) is an innovative mass concrete technology. To date, RFC technology has been used to build a great number of gravity dams and arch dams. Since it was invented in 2003, many experimental and numerical research works have been conducted. During the construction process of RFC, an assembly of large rocks with more than 300 mm in grain size, called rockfill, can be cemented with a high-performance self-compacting concrete (HSCC). The RFC technology combines the advantages of masonry and concrete, in that it decreases cement consumption, lowers temperature rise of cement hydration, and reduces shrinkage of concrete. This paper aims at acquainting readers with a timely review of state-of-the-art research on RFC technology, including (1) workability of HSCC and compactness of RFC, (2) thermal and mechanical properties of RFC, (3) structures of an RFC dam and (4) construction and quality control measurements.

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Section: Workability Of Hscc and Compactness Of Rfcmentioning

confidence: 99%

Research on Rock-Filled Concrete Dams: a Review

Feng¹,

Zhou²,

Huang³

2018

EasyChair Preprints

Self Cite

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“…More recently, Chai et al proposed the other formula to compute the strain rate tensor with non-equilibrium parts of density distribution functions (Chai formula) for simulation of non-Newtonian fluid flows by using MRT LB model with nine discrete velocities in two dimensions (D2Q9) [12]. After this work, Chai formula was widely used to compute the strain rate tensor in many studies on non-Newtonian fluid flows by MRT-LB model [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

The computation of strain rate tensor in multiple-relaxation-time lattice Boltzmann model

Zhang

Huang

Wang

et al. 2018

Computers & Mathematics with Applications

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Multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is an important class of LB model with lots of advantages over traditional singlerelaxation-time (SRT) LB model. In addition, the computation of strain rate tensor is crucial in MRT-LB simulations of some complex flows. Up to now, there are only two formulas to compute the strain rate tensor in the MRT LB model. One is to compute the strain rate tensor by using nonequilibrium parts of macroscopic moments (Yu formula). The other is to compute the strain rate tensor by using non-equilibrium parts of density distribution functions (Chai formula). The mathematical expressions of these two formulas are so different that we do not know which formula to choose for computing the strain rate tensor in MRT LB model. In this paper, we study the relationship of these two formulas. It is found that Yu formula can be deduced from Chai formula in a particular procedure. However, these two * Corresponding author, Tel and Fax: +86 574 87608744.

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“…Since VOF simulation strongly depends on the grid resolution, a grid refinement should be prepared in the studied domains (i.e. The abrasive waterjet flow and waterjet grinding space), to improve its accuracy and decrease the computational effort (Chen, Zhang, & Feng, 2016). It is noteworthy to point out that the VOF method is an interface-resolving method and has become a popular methodology for solving two-phase flow phenomena.…”

Section: Cfd Simulations and Actual Awj Grindingmentioning

confidence: 99%

Fuzzy prediction of AWJ turbulence characteristics by using typical multi-phase flow models

Liang

Shan

Liu

et al. 2017

Engineering Applications of Computational Fluid Mechanics

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For the purpose of improving the working performance of AWJ (Abrasive waterjet) grinding in actual machining, and revealing the unknown influence mechanism of waterjet machining prediction, this research conducted a theoretical and experimental investigation concerning with the influences caused by multi-phase flow models, on the fuzzy prediction of turbulence characteristics. First, typical flow models describing the abrasive waterjet were presented and enunciated; Second, a series of turbulence characteristics were defined to quantitatively demonstrate the waterjet flow, which are responsible for the actual performances of AWJ grinding in the contact zone; Then a new fuzzy prediction system equipped with logic protocols was established and introduced to predict turbulence characteristics based upon the machining parameters by employing different flow models, therefore a set of quantified prediction results generated from the CFD (Computational Fluid Dynamics) simulation, orthogonal experiments and actual measurements can be obtained and distinguished systematically. Through a detailed performance analysis with benchmark indexes and prediction comparisons, the theoretical superiorities and specific applications of these flow models were fully discussed and then an integrated conclusion assessing their inherent influence mechanism was acquired. Based on these innovative achievements, the instantaneous machining inspection or parameter optimization in AWJ grinding process can be facilitated, simultaneously the new research ideas aimed at waterjet monitoring or grinding improvements can be presented as well. ARTICLE HISTORY

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Three-dimensional simulations of Bingham plastic flows with the multiple-relaxation-time lattice Boltzmann model

Cited by 17 publications

References 37 publications

Research on Rock-Filled Concrete Dams: a Review

Research on Rock-Filled Concrete Dams: a Review

The computation of strain rate tensor in multiple-relaxation-time lattice Boltzmann model

Fuzzy prediction of AWJ turbulence characteristics by using typical multi-phase flow models

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