A5103005993- Lattice Boltzmann Simulation Studies
- Coal Properties and Utilization
- Heat and Mass Transfer in Porous Media
- Groundwater flow and contamination studies
- Hydraulic Fracturing and Reservoir Analysis
- Hydrocarbon exploration and reservoir analysis
- Complex Systems and Time Series Analysis
- Theoretical and Computational Physics
- Human Pose and Action Recognition
- Anomaly Detection Techniques and Applications
- Gait Recognition and Analysis
- Enhanced Oil Recovery Techniques
- Methane Hydrates and Related Phenomena
- Hydrology and Sediment Transport Processes
- Geochemistry and Geologic Mapping
- Geoscience and Mining Technology
- Advanced Thermodynamic Systems and Engines
- Fractal and DNA sequence analysis
- Advanced Thermodynamics and Statistical Mechanics
- Dam Engineering and Safety
- Remote-Sensing Image Classification
- Hydrology and Watershed Management Studies
- Geomechanics and Mining Engineering
- Rock Mechanics and Modeling
- Stochastic processes and statistical mechanics
Henan Polytechnic University
2013-2025
Xi'an Jiaotong University
2021-2024
Naval University of Engineering
2001
Abstract Pores among particles provide the main space for storage and migration of deep underground fluids (such as oil, gas, groundwater, unconventional natural gas). The pores form a pore structure with complex morphology which is mainly dominated by shape distribution particles. Therefore, reconstruction or granular porous media evaluation particle roundness have become an important foundation study fluid flow through rock mass. This research proposes novel approach multi‐scale model...
Abstract The pore structure in a coal matrix is dual‐porosity system where fractures and pores coexist feature scale‐invariance properties, which would affect the occurrence migration of coalbed methane (CBM) significantly. Therefore, it fundamental importance to well define complexity types effectively characterize their assembly mechanism matrix. Here we identify as dual‐complexity consisting original behavioral independent each other, former determines scaling single‐ or structure, while...
Permeability of porous reservoirs plays a significant role in engineering and scientific applications. In this study, we investigated the relationship between pore size fractal dimension (D f ) its porosity, as well that D structure parameters, consequentially developed an algorithm to generate spaces with arbitrary characterizing distribution. Using series–parallel flow resistance model lattice Boltzmann method (LBM) combination, then systematically analyzed effects physical properties on...
Multifractals are the general form of scale invariances, where a fractal behavior is repeated by similar object or pattern. Although multifractal spectrum has been accepted as measure behavioral complexity, it cannot solely determine behavior, thus leaving control mechanisms multifractality unclarified. Here, we reexamine multifractality, and discover two key features scaling behaviors in i.e. multiplicity repetition. Afterwards, establish topography to unify scale-invariance definition...
In this paper, the power density, defined as ratio of output to maximum specific volume in cycle, is taken objective for performance optimization an irreversible regenerated closed Brayton cycle coupled constant-temperature heat reservoirs viewpoint finite time thermodynamics (FTT) or entropy generation minimization (EGM). The analytical formulae about relations between density and pressure are derived with resistance losses hot- cold-side exchangers regenerator, compression expansion...
Abstract Objectives This study aims to enhance supervised human activity recognition based on spatiotemporal graph convolutional neural networks by addressing two key challenges: (1) extracting local spatial feature information from implicit joint connections that is unobtainable through standard convolutions natural alone. (2) Capturing long-range temporal dependencies extend beyond the limited receptive fields of conventional convolutions. Methods To achieve these objectives, we propose...
The parameters of coalbed methane reservoirs have large differences, and the precise values cannot represent resource production characteristics whole block. In order to address these problems, an index system for evaluating potential blocks was constructed, weights evaluation were determined, a model preferential selection based on subjective–objective combination method established. main coal seams (No. 2-1 No. 4-2) Pingdingshan-Shoushan I Mine Block taken as research objects rank...
Abstract Fractional Brownian motion (FBM) and the Weierstrass-Mandelbrot (W-M) function are two important methods for constructing self-affine objects. Accurately characterizing their features, such as morphology fractal geometry, is fundamental follow-up applications. However, due to differences between self-similar properties, dimension evaluation difficult sometimes unconvincing. In addition, sampling length diversity of calculation both lead non-uniqueness dimension. This study compared...
Graph structure is an important part of convolutional networks (GCNs), which can reflect the connection between each nodes non-Euclidean data. A feature hidden in graph structure, provide additional spatial features that represent relationship human joints. However many GCNs-based methods ignore these features. We put forward a extraction module, obtain implicit joints, and extract from structural In order to enhance temporal representation, we propose long-range frame-difference module....
As a multi-scale system featuring fractal hierarchical branching structure, the quantitative characterization of natural river networks is fundamental significance for assessment hydrological and ecological issues. However, as already evidenced, behavior cannot be uniquely inverted by dimension, which induces challenge in accurately describing arbitrary scale-invariance properties networks. In this work, per topography theory, an open mathematical framework description proposed clarifying...