SIMULATION SOLUTION FOR DIGITAL TWIN

Why NFLOW?

Sustainable Development through Simulation

VERSATILE
EASY TO USE
PRECISE

EARN CERTAINTY AND FLEXIBILITY THROUGH

SPH Theory

SPH (SMOOTHED PARTICLE HYDRODYNAMICS)

Unlike traditional mesh-based Eulerian numerical methods such as the finite element method (FEM), finite difference method (FDM), and finite volume method (FVM), SPH is a meshless method that analyzes fluid flow by tracking the motion of fluid particles.

These unique characteristics enable SPH to more easily and flexibly analyze physical phenomena that traditional numerical methods have difficulty simulating. SPH is particularly capable of analyzing complex steady and unsteady phenomena such as nonlinear free-surface flows, bubble dynamics, tire aquaplaning, gearbox oiling, and spraying. Furthermore, the ease with which SPH can be parallelized in multi-core architectures renders it favorable for implementations in GPU-based parallel computing.

SPH is a particle-based Lagrangian method developed by Lucy Gingold and Joseph Monaghan in 1977 to predict astrophysical phenomena. Since the 1990s, SPH has been used extensively in various engineering applications, and research has been actively conducted in both academia and industry. Applicability of SPH now extends to analyses of extremely deformable materials, fluid-solid interactions, in addition to those of incompressible and compressible flows.

NFLOW SPH CAPABILITIES

NFLOW SPH APPLICATIONS

Verification of Design Safety

  • Vehicle safety verification and design reliability
  • Analysis of fuel tank sloshing phenomenon
  • Evaluation of Aviation Engine Thermal Performance
  • Review of Safety and Efficiency in Marine Phenomenon

Heat

  • Analysis of engine heat and heat dissipation
  • Analysis of overheating phenomena in furnaces, nuclear reactors and furnaces
  • Verification of generator deheating efficiency for seawater inflow

Drainage/Piping

  • Review of vulnerable sections of road drainage and optimize design
  • Review of water stagnant phenomenon in drainage facilities
  • Review of the stagnant section of inflow and outflow inside the vessel

Verification of Design Safety

  • Vehicle safety verification and design reliability
  • Analysis of fuel tank sloshing phenomenon
  • Evaluation of Aviation Engine Thermal Performance
  • Review of Safety and Efficiency in Marine Phenomenon

Heat

  • Analysis of engine heat and heat dissipation
  • Analysis of overheating phenomena in furnaces, nuclear reactors and furnaces
  • Verification of generator deheating efficiency for seawater inflow

Drainage/Piping

  • Review of vulnerable sections of road drainage and optimize design
  • Review of water stagnant phenomenon in drainage facilities
  • Review of the stagnant section of inflow and outflow inside the vessel

FLEXIBILITY
ELABORATE
RAPIDITY

EXPERIENCE THE FUTURE WITH INFINITE POSSIBILITY

LBM Theory

LBM (LATTICE BOLTZMANN METHODS)

LBM is a numerical approach for analyzing fluid flow using particle distribution functions. These distribution functions represent the density distribution of particles in the physical space, each of which have a specific velocity and density. These distribution functions are used to calculate the macroscopic flow properties such as fluid density, velocity, and temperature. LBM numerically solves the Boltzmann transport equation to simulate the time-evolution of the particle distributions within the computational domain and is fundamentally different from the traditional finite volume method (FVM) which solves the Navier-Stokes equations. Because the LBM discretizes the computational domain with a Cartesian lattice, it requires a much simpler preprocessing step than traditional CFD methods do and can be easily applied to simulate flows with complex geometries. Furthermore, because it is a mesoscopic approach, it can be more easily applied to microscopic flows which traditional CFD tools have difficulty simulating.

Historically, the LBM originates from the lattice gas automata (LGA). In addition to its vastly simple preprocessing, the local nature of computations makes the LBM applicable for hugely parallelized computational architectures. This computational efficiency is a competitive advantage of the LBM compared to traditional CFD methods and has garnered much interest of the research community. LBM research has been very active during the last couple decades, and this research activity has enabled the LBM to overcome its traditional weak compressibility limit to be able to analyze compressible flows, and supersonic flows. Furthermore, LBM continues to expand its applicability with applications to heat transfer, multiphase flows, acoustics, aeroacoustics, as well as fluid-structure interactions via coupling with DEM and FEM solvers.

NFLOW LBM CAPABILITIES

NFLOW LBM APPLICATIONS

Noise Analysis

  • Analysis of noise caused by wind spots on car side mirrors and upper roofs
  • Analysis of marine propulsion blade underwater noise
  • Sound insulation material manufacturing and effect analysis

Medical Engineering

  • Prediction of cardiovascular disease
  • Analysis of colloidal systems
  • Analysis of the respiratory system

Analysis of Rotating Body

  • Simulation of refrigeration cycle
  • Analysis of the dynamics of rotating bodies such as fans
  • Simulation of wind turbines

Noise Analysis

  • Analysis of noise caused by wind spots on car side mirrors and upper roofs
  • Analysis of marine propulsion blade underwater noise
  • Sound insulation material manufacturing and effect analysis

Medical Engineering

  • Prediction of cardiovascular disease
  • Analysis of colloidal systems
  • Analysis of the respiratory system

Analysis of Rotating Body

  • Simulation of refrigeration cycle
  • Analysis of the dynamics of rotating bodies such as fans
  • Simulation of wind turbines

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