Skip to content
CFD Simulation

CFD Simulation

Analyze & Simulate anything !

  • Home
  • Simulation gallery
    • Spray Dryers : All studies
    • Case Studies
      • Covid-19 pandemic
      • Covid 19 – Keeping indoors safe
      • Covid-19 Dispersion Model
      • Surfside Champlain Towers
    • Learn Solid & Fluid Analysis
      • CFD of a Butterfly Valve
    • Human Space Flight
      • Space Shuttle CFD
      • Aircraft Aerodynamics Performance
      • Space Exploration
      • Rocket Science
  • CFD Tube gallery
    • Flow Simulation TCAE
      • Centrifugal Pump
      • Centrifugal Fan Optimization
      • Potsdam Propeller
    • Football
      • Simulation of head kick in football/ soccer
    • Simulation and Analysis of Car Crash
      • Dummy without seatbelt impacting airbag
      • Static Structural Simulation of a teleferic or telpher cable car
      • Car braking with dummy under 3 point seatbelt at 150g deceleration
      • Car bumper impacting hip on 2 directions at 36 km/h
      • Heavy truck impacting a concrete barrier
      • Static Structural Simulation of a teleferic or telpher cable car
      • Truck with loose cargo brakes with 100g deceleration
    • Covid 19 – Gama Platform
    • Brain and Blast Injuries
    • Nuclear Blast CFD Simulation
    • Spaced Armor Penetration
    • Armor Penetration Simulation
      • Ultra Porcelain Armor
      • Explaining mechanics – Armor penetration
      • Energetic Reactive Armor
      • Javelin Simulation
      • Concrete Armor | M4A3
      • Concrete Armor Comparison
      • Merkava I vs T-72A
        • Defeating Modern Armor
    • Anti Tank Simulation
      • 80mm Mortar grenade
      • RP-3 ROCKET vs TIGER
      • 152mm HE vs Tiger II
      • Panzer IV F2 vs Valentine V
      • T-72 vs M1 Abrams
      • T34 | Combat Analysis
      • T90 Third Generation Russian Tank
      • Multiple Impact Simulation
    • Hydraulic and Pneumatic Systems
      • Electric Turbo Innovation
  • Modeling and Computational Simulation
    • Simulation of Car Crash
    • Electrochemical Energy Storage
      • Lithium-sulfur batteries
      • Metal-Air batteries
      • Na based batteries
      • Supercapacitors
    • Covid-19 pandemic
  • FEA & CFD – MESH GALLERY
    • Catfish Drone CFD Simulation
    • CFD Analysis of Football
    • Computational Fliud dynamics
    • Cyclone Simulation
    • Eiffel tower CFD Simulation
    • Flow Simulation Ship Propeller
    • GRIDPRO
    • M113 – Combat Vehicle Mesh for FEA
    • Milling & Turning – CNC
    • NUSCALE POWER PLANT MESH
    • Patriot Car Bumper
    • University of Munich – Research & Methods
      • Gallery – CFD –
      • Tangible CFD
    • Unmanned Combat Vehicle Mesh
  • Human Health
    • EMBRYO TRANSFER
      • Outcome Measures
      • Ectopic and Early Pregnancy Loss
    • CFD SIMULATION SAVES LIVES
    • Virtual Surgery CFD Study
      • Glosary
    • Normozoospermia
    • Sperm Motility Scores
  • Submarine
    • CFD of Submarines
  • R&D – Innovation
    • Capabilities
    • Current
    • Past
    • Future
  • Armor Penetration
  • #CFD Simulation
  • #CFD Tube
  • #CFD learn
  • #CFD Simulation
  • E-mail
  • Twitter
  • Facebook
  • Get free meshing and request for Quote
  • User
  • Login
    • Password Reset
  • Register
  • Logout
  • Jobs
  • Toggle search form
Space X Hypersonic Vehicle

Simulation with US3D Using Unstructured Grids from Fidelity Pointwise

Posted on July 27, 2023August 29, 2023 By mechalab761691 No Comments on Simulation with US3D Using Unstructured Grids from Fidelity Pointwise

Abstract:
For hypersonic simulations, unstructured flow solvers typically have problems predicting surface heat fluxes when strong shocks are present. This article outlines a workflow that applies best practices for structured and unstructured grids. In addition, unstructured grid generation can significantly reduce the time required to create quality grids for complex geometries. Several examples are computed using DPLR, a structured grid flow solver, and US3Dflow, an unstructured flow solver.

Results from the two codes are compared and they show excellent agreement. The unstructured grid workflow offers a viable and attractive alternative for hypersonic simulations.

Introduction

It is desirable to run computational fl uid dynamic (CFD) simulations to predict the aerothermalenvironment of a spacecraft during atmospheric entry.

However, for complex geometries, the grid generation process for structured grids is often tedious and typically a bottleneck in the simulation workflow. During these times, unstructured grid generation offers a potential alternative by simplifying the grid generation process.

Popular Stories Right now
SOCIAL DISTANCING DURING PANDEMICS
A Year of Curiosity on Mars
FAILED JAVELIN SIMULATION

There are several instances when unstructured grid solvers have problems predicting surface heating, especially when strong shocks are present. These numerical issues can be mitigated by applying best practices developed for structured grids to unstructured grids. Proper shock alignment of unstructured grids can minimize numerical noise emanating from shocks, thereby reducing the spurious oscillations in computed surface quantities (such as pressure, temperature, and heat flux).

Workflow for Structured Grids

As shown in Figure 1, the CFD workflow for structured grids starts with generating a surface grid around the spacecraft. For a simple shape, such as an idealized smooth Orion capsule, a structured surface grid can be easily constructed on the capsule’s surface.

Generated by extruding the surface grid outward using a hyperbolic PDE extrusion algorithm available in Cadence® Fidelity™ Pointwise® Mesh Generation. The surface grid, volume grid, and initial flow solution computed using DPLR—a structured grid, Navier-Stokes flow solver for reacting flows—are illustrated in Figure 2.

Figure 2. Surface grid, volume grid, and centerline Mach contours on the initial grid

The next step in the workflow is to align the grid with the bow shock and adjust the wall spacing, so there is sufficient grid resolution to resolve the boundary layer in a viscous simulation properly. The tedious tasks of shock detection, shock smoothing, grid alignment, and updating the volume grid can all be handled automatically using the built-in grid adaption tool within DPLR. It usually takes approximately three to five CPU minutes to generate a new grid using the grid adaption subroutine.

Workflow for Unstructured Grids

As an alternative to structured grids, a workflow using unstructured grids (see Figure 3) can simplify the grid generation process and produce faster turnaround times for hypersonic simulation.

  1. Initial grid
    To start the simulation, an initial grid needs to be generated. One option in Fidelity Pointwise is to utilize the T-Rex algorithm, an advancing front method. This technique is conceptually similar to the PDE-based hyperbolic method in that both involve extrusion of the volume grid from a surface grid. One key difference is that T-Rex tests each extrusion step for grid quality and potential collisions with other parts of the extrusion. If either test fails, the extrusion process is stopped locally for that point. The marching front continues for the remaining points until all tests fail, a specified maximum number of layers is reached, or the volume grid achieves isotropy.
    When the marching front stops, the remaining volume is filled by a Delaunay-based isotropic grid algorithm. Once these parameters are set, the algorithm can be initialized to run without any user interactions.
  2. Initial solution
    After the unstructured grid is generated, US3D—an unstructured grid, Navier-Stokes fl ow solver for reacting flows—simulates the flow on the initial grid. The computational domain is initialized using freestream conditions and an artificial boundary layer at the surface. A second-order implicit Euler-time integration and line relaxation method is selected to solve the governing equations. Line relaxation is active in the prismatic layers at the wall surface for a hybrid grid. Outside of this region, the solver switches to a point implicit method.
  3. Shock detection and extraction
Figure 4. Mach iso-surface from Tecplot (left) and smoothed iso-surface using MeshLab (right)

4. Generate new surface and volume grids

Although the new iso-surface is smooth, it may contain triangles with very small areas, whichcould result in the generation of poor-quality volume cells. This problem can be resolved bycreating a new unstructured surface via the Fidelity Pointwise tool’s “On Database Entities”command. By selecting the “isotropic” option for unstructured domains, the new surface shouldbe quite uniform in cell size. If desired, the user can change the cell size distribution by addingsource terms. The plot of a new grid representing the bow shock surface is shown in Figure 5.

Figure 7. Space Shuttle CAD geometry (left) and adapted structured grid (right)

To test the unstructured workflow, the structured surface grids of the shuttle were used to create a hybrid volume grid. However, unlike the structured grid, the unstructured grid includes the exhaust nozzle details. Mesh generation for this case required one eight-hour workday, quite a reduction versus the structured grid. Further, comparing the heat flux shows excellent agreement between the two codes. Figure 8 illustrates the normalized heat flux contours on the wind side (left) and leeside (middle), and a plot of the centerline heat flux down the length of the vehicle (right). The peak centerline heat flux predicted by US3D is about 2% lower than the DPLR estimate. These results indicate that an unstructured flow solver can produce heating estimates comparable to a structured flow solver if best practices are applied.

Figure 8. Normalized heat fl ux contours on windside (left), leeside (right), and centerline (right)

Conclusion
A workflow using an unstructured grid has been developed and tested. As demonstrated by the Space Shuttle example, the new process can quickly produce accurate heating estimates for a complex geometry, proving to be a viable and promising alternative to traditional structured grid methods. In particular, the T-Rex meshing algorithm is shown to be fast, robust, and easy to implement. While an unstructured workflow does not off er a speed advantage over a structured workflow for simple geometries, the difference is significant for complex geometries.
Unstructured grid generation also offers great flexibility in modifying existing surface and volume grids because grid points can be easily added or deleted without the need to adhere to a particular grid topology. Overall, the current unstructured workflow offers a fast and straightforward process to model hypersonic flows for complex geometries.

Modelling and Computational Simulation Tags:Fidelity Pointwise, heat fluxes, hypersonic simulations, POINTWISE, unstructured flow solvers, US3Dflow

Post navigation

Previous Post: Fluid dynamics during embryo transfer
Next Post: Computational Fluid Dynamics Analysis of Butterfly Valve – ChatGPT Generated

More Related Articles

What Every Design Engineer Needs to Know
about Computational Fluid Dynamics
Learn Solid & Fluid Analysis
Finite Element Modeling and Simulation of Car Crash Finite Element Modeling and Simulation of Car Crash Modelling and Computational Simulation
Volcano Simulation – Phoenix Fluid Simulation CFD Tube gallery

Leave a Reply Cancel reply

You must be logged in to post a comment.

About Mechalab

Mechalab Limited is a UK-registered company trading in England and Wales. By Post : Mechalab Ltd 49 Station road - BN26 6EA Polegate - East Sussex - United Kingdom Phone : 07 342 212 398

By email : info@mechalab.co.uk

Copyright © 2025 CFD Simulation.

Powered by PressBook Blog WordPress theme