The regularized lattice Boltzmann method (RLBM) has the advantage of improving accuracy numerical simulations without increasing computational overhead. RLBM usually uses standard Cartesian grid in simulation. This paper introduces multi-layer technique, different resolutions, which is also more consistent with physical laws flow field. Based on this, a (ML-RLBM) for solving complex problems proposed. proposed performs local refinement to achieve grid, can reduce In order realize easily,...

Authorship detection has played an important role in social information science. In this study, we propose a support vector machine (SVM)-based authorship model for classical Chinese texts. Term frequency-inverse document frequency (TF-IDF) feature extraction technique is combined with the SVM-based method. The linguistic features used are based on TF-DIF calculations of different function words, including literary end-function vernacular and transitional words. Furthermore, bidirectional...

The traditional multi-level grid multiple-relaxation-time lattice Boltzmann method (MRT-LBM) requires interpolation calculations in time and space. It is a complex computationally intensive process. By using the buffer technique, this paper proposes new MRT-LBM which only spatial calculations. proposed uses center point format to store information. type determination flow field calculation domain done axis aligned bounding box (AABB) triangle overlap test. According characteristics of...

The dynamic processes of NO reduction by coals and char at different O2 concentrations have been investigated under the suspension conditions a precalciner. effects cement raw meal, temperature, concentration on formation were studied. results show that there are two stages in process presence O2. first stage is early homogeneous volatiles, second heterogeneous oxidation N. coal with higher volatiles content more significant. At this stage, quantities Datong Chenzhou found to be 1.08 × 10−6...

The Physics-Informed Neural Networks (PINNs) improve the efficiency of data utilization by combining physical principles with neural network algorithms and ensure that predictions are consistent stable laws. PINNs opens up a new approach to address inverse problems in fluid mechanics. Based on single-relaxation-time lattice Boltzmann method (SRT-LBM) Bhatnagar-Gross-Krook (BGK) collision operator, PINN-SRT-LBM model is proposed this paper for solving problem consists three components. first...

As an improved method of the lattice Boltzmann (LBM), regularized (RLBM) has been widely used to simulate fluid flow. For solving high Reynolds number problems, large eddy simulation (LES) and RLBM can be combined. The computation flow problems often requires a computational grids large-scale parallel clusters. Therefore, scalability algorithm with LES on cluster proposed in this paper. solve complex Cartesian numbers. In order achieve load balancing, domain decomposition (DDM) mesh...

Mesh quality is a major factor affecting the structure of computational fluid dynamics (CFD) calculations. Traditional mesh evaluation based on geometric factors cells and does not effectively take into account defects caused by integrity mesh. Ensuring generated meshes are sufficient for numerical simulation requires considerable intervention CFD professionals. In this paper, Transformer-based network automatic (Gridformer), which translates an image classification problem, proposed. By...

In the fields of physics and engineering, it is crucial to understand phase transition dynamics. This field involves fundamental partial differential equations (PDEs) such as Allen–Cahn, Burgers, two-dimensional (2D) wave equations. alloys, evolution interface described by Allen–Cahn equation. Vibrational phenomena during transitions are modeled using Burgers 2D The combination these gives comprehensive information about dynamic behavior a transition. Numerical modeling methods finite...

A flexible method for modulating the Casimir force is proposed by combining graphene and hyperbolic materials (HMs). The structure employs two candidates other than graphene. One hexagonal boron nitride (hBN), a natural HM. porous silicon carbide (SiC), which can be treated as an artificial HM effective medium theory. between graphene-covered hBN (porous SiC) bulks presented at zero temperature. results show that covering with increases monotonically. Furthermore, modulated varying Fermi...

Abstract As an improved method of lattice Boltzmann (LBM), regularized (RLBM) has been applied to simulate fluid flow. Nevertheless, the performance RLBM needs be considered when simulating actual problems. The rise multicore platforms, especially popularity graphics processor units (GPUs), provided possible implementation solutions for parallel computing. In this article, model on CPU/GPU heterogeneous platforms is proposed. To solve problem GPU memory shortage, CPU controls startup kernel...

As an important economic fish resource, germplasm resources and phenotypic measurements of tilapia are great importance in the direction culture genetic improvement. Furthermore, accurate identification precise localization body parts crucial for enabling key technologies such as automated capture cutting. However, there some problems semantic segmentation fish, including accuracy target edge ambiguity segmenting small targets. To improve real farming environments, improved Deeplabv3+...

Physics-Informed Neural Networks (PINNs) improve the efficiency of data utilization by combining physical principles with neural network algorithms and thus ensure that their predictions are consistent stable laws. PINNs open up a new approach to address inverse problems in fluid mechanics. Based on single-relaxation-time lattice Boltzmann method (SRT-LBM) Bhatnagar–Gross–Krook (BGK) collision operator, PINN-SRT-LBM model is proposed this paper for solving problem The consists three...

Immersed boundary-lattice Boltzmann method (IB-LBM) has become a popular for studying fluid-structure interaction (FSI) problems. However, the performance issues of IB-LBM have to be considered when simulating practical The Graphics Processing Units (GPUs) from NVIDIA offer possible solution parallel computing, while CPU is multicore processor that can also improve performance. This paper proposes algorithm on CPU-GPU heterogeneous platform, in which not only controls launch kernel function...

The lattice Boltzmann method (LBM) is a potent numerical technique based on kinetic theory. It can effectively simulate the steady-state and unsteady-state flow problems. A multi-domain decomposition strategy developed for LBM in order to accelerate rate of convergence different domains by relative error regions flow. In addition, proposed reduce amount calculations required improve stability. Numerical experiments involving both two- three-dimensional flows demonstrate drastically improved...

Combined with the intelligent manufacturing equipment operating characteristics, this paper proposes a reliability assessment method based on regression model. We first determine evaluation object and its components, give components formal description. Then we use model theory to build an At last confidence level judge results of assessment. An application shows that can effectively evaluate equipment.

The lattice Boltzmann method (LBM) is a computational based on kinetic description of fluid mechanics. Intel Many Integrated Core (MIC) architecture designed for highly parallel computing has not been fully evaluated LBM. This paper proposes hybrid MPI/OpenMP model LBM CPU+MIC heterogeneous architecture, using the two-dimensional partitioning data division and offload, MPI, OpenMP. Furthermore, we use various methods to optimize algorithm. By numerical experiments in cluster Shanghai...

Based on the double distribution function Boltzmann-BGK equations, a cell-centered finite volume lattice Boltzmann method unstructured grids for high-speed viscid compressible flows is presented. In particle introduced basis of D2Q17 circular function, and its corresponding total energy adopted. proposed method, advective term evaluated by Roe’s flux-difference splitting scheme, limiter used to prevent generation oscillations. The functions interface are calculated piecewise linear...

The large-scale numerical simulation of complex flows has been an important research area in scientific and engineering computing. lattice Boltzmann method (LBM) as a mesoscopic for solving flow field problems become relatively new direction computational fluid dynamics. multi-layer grid-refinement strategy deals with different-level computing complexity through multi-scale grids, which can be used to solve the non-uniform grid LBM without destroying parallelism standard LBM. It also avoids...

The regularized lattice Boltzmann method (RLBM) is an improvement of the (LBM). advantage RLBM improved accuracy without increasing computational overheads. paper introduces multi-layer grids, grids have different resolutions which can accurately solve problems in fluid dynamics (CFD) destroying parallelism RLBM. Simulating flow usually requires a large number grid simulations. Therefore, it necessary to design parallel algorithm for based on grids. In this paper, load-balancing-based...

The Boltzmann equation with multiple-relaxation-time (MRT) collision operators has been widely employed in kinetic theory to describe the behavior of gases and liquids at macro-level. Given successful development deep learning availability data analytic tools, it is a feasible idea try solve Boltzmann-MRT using neural network-based method. Based on canonical polyadic decomposition, new physics-informed network describing equation, named for MRT (NMRT), proposed this paper solving equation....