A5019678122- Combustion and Detonation Processes
- Energetic Materials and Combustion
- Ultrasound and Cavitation Phenomena
- Model Reduction and Neural Networks
- Fluid Dynamics and Turbulent Flows
- Structural Response to Dynamic Loads
- High-Velocity Impact and Material Behavior
- Photonic and Optical Devices
- Advanced Fiber Optic Sensors
- Laser-Plasma Interactions and Diagnostics
- Transportation Safety and Impact Analysis
- Energy Load and Power Forecasting
- Fluid Dynamics Simulations and Interactions
- Computational Fluid Dynamics and Aerodynamics
- Nuclear and radioactivity studies
- Mechanical and Optical Resonators
- Generative Adversarial Networks and Image Synthesis
- Lattice Boltzmann Simulation Studies
- Fluid Dynamics and Vibration Analysis
- Neural Networks and Applications
- Photonic Crystals and Applications
- Computational Physics and Python Applications
Beijing Institute of Technology
2021-2024
The development of analytical theory and experimental methods for understanding the correlation between explosive properties bubble dynamic characteristics in underwater explosions has important engineering application value weapons ships. Based on assumption an instantaneous detonation, we introduced Jones–Wilkins–Lee equation state to describe high-pressure explosion established initial conditions dynamics calculations. Considering high-Mach-number flow high pressure at boundary bubble,...
In this paper, the effects of water depth on overpressure (pressure difference between positive shock pressure and hydrostatic pressure) peak energy underwater explosion waves were analyzed. Two quantitative calculation models established that accounted for effect depth, which have theoretical practical engineering value. A simulated deepwater tank test was first conducted to obtain experimental data peaks energies generated by 10 30 g trinitrotoluene (TNT) explosives in a environment at...
Nowadays, the sensing of hazardous gases is urgent for consideration public safety and human health, especially in extreme conditions low temperatures. In this study, a photonic crystals (PhCs) sensor with water retention antifreezing properties was developed applied to visual at temperature, passively. The prepared by dip-coating poly(methyl methacrylate) (PMMA) colloidal microspheres followed embedding k-carrageenan/polyacrylamide-ethylene glycol (k-CA/PAM-EG) hydrogel. responded gases,...
The dynamic behaviors of underwater explosion bubbles differ for different explosives. explosive characteristic parameters will result in a greater impact on the motion characteristics bubbles. Based bubble dynamics equation established by Prosperetti and Lezzi [“Bubble compressible liquid. Part 1. First-order theory,” J. Fluid Mech. 168, 457âĂŞ-478 (1986); “Bubble 2. Second-order 185, 289âĂŞ-321 (1987)], we proposed an initial condition state (EOS) form applicable calculating With...
The shock wave characteristics within the near-field are one of most challenging aspects understanding an underwater explosion. latest numerical and experimental techniques were utilized to investigate pressure distribution decay features after a disturbance. governing equations in simulation discretized with fifth-order weighted essentially non-oscillatory scheme space third-order Runge–Kutta time, multi-medium interactions defined resolved via modified ghost fluid method. test system...
The NPCs sensor was fabricated for the ultra-fast real-time monitoring of large-range sharp pressure fluctuations in aqueous field, which provided a new strategy studying hydrodynamics and can be extended to air shockwave field.
To calculate the near-field shockwave propagation of underwater explosions for different explosives quickly and accurately, an improved calculation model, based on Kirkwood–Bethe theory, is proposed. Based detonation theory shock jump conditions, model establishes initial equilibrium conditions shockwave-front state explosion bubble interface. By incorporating a second-order Mach-precision dynamics equation, determines physical parameters enthalpy change functions at expanding stage in real...
Mode decomposition methods, such as proper orthogonal and dynamic mode (DMD), have introduced a novel data-driven approach for flow prediction. These methods aim to identify collection of modes that capture the essential features. Subsequently, field data are projected onto these reconstruct predict evolution field. However, due their inherent linearity, limited in effectively handling unsteady nonlinear exhibiting significant nonlinearities. In this study, we propose spectral graph...
The modified ghost fluid method (MGFM) has been one of the most popular and successful algorithms for coping with numerical calculation multi-medium flows, especially interaction between strong discontinuities material interfaces. To apply advanced algorithm to an underwater explosion simulation, first, uniform distribution state detonation products, which is generally used initial condition in replaced by analytic solution Taylor wave. Tait equation is, then, expanded a broader pressure...
Traditional computational fluid dynamics (CFD) techniques deduce the dynamic variations in flow fields by using finite elements or differences to solve partial differential equations. CFD usually involves several tens of thousands grid nodes, which entail long computation times and significant resources. Fluid data are irregular data, there will be turbulence field where physical quantities between adjacent nodes extremely nonequilibrium. We use a graph attention neural network build...
The turbulent flow characteristics, such as its multiscale and nonlinear nature, make the solution to problems complex. To simplify these problems, traditional methods have employed simplifications, RANS LES models for dealing with aspect linear approximation theories aspect. We designed a turbulence characteristic extraction model using graph neural network spatial convolutions fitting capabilities. Unlike methods, this computes data directly without resorting simplified formulas. problem...