Simulations and experimental study of ddt behind a single obstacle
This presentation is the property of its rightful owner.
Sponsored Links
1 / 29

Simulations and experimental study of DDT behind a single obstacle PowerPoint PPT Presentation


  • 30 Views
  • Uploaded on
  • Presentation posted in: General

Simulations and experimental study of DDT behind a single obstacle. André Vagner Gaathaug Knut Vaagsaether Dag Bjerketvedt Faculty of Technology Telemark University College Norway. Setup of study. 100 x 100 m 2 quadratic cross sectional area, 3000 mm long

Download Presentation

Simulations and experimental study of DDT behind a single obstacle

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Simulations and experimental study of ddt behind a single obstacle

Simulations and experimental study of DDT behind a single obstacle

André Vagner Gaathaug

Knut Vaagsaether

Dag Bjerketvedt

Faculty of Technology

Telemark University College

Norway


Setup of study

Setup of study

  • 100 x 100 m2quadratic cross sectional area, 3000 mm long

  • One obstacle with variable blockage ratio BR=0.5 to BR=0.9

  • Spark ignition at the closed end, open at the other

  • 5 and 6 pressure trancducers

  • 15% to 40% Hydrogen in air mixture


Why this work

Why this work?

  • Not smooth channel

  • Not obstructed channel

  • Not unconfined jet

  • Earlier work by Vaagsaether and Knudsen

    • Circular geometry

    • Various blockage ratio

    • BR=Blocked area / open area

  • Investigated where DDT occur, a possibly why.

  • Challenges related to the problem

    • Driving section, the first meter

    • Investigated earlier by the authors


Experimental study

Experimental study

Focus


Experimental results

Experimental results

High speed frames with sketches of their phenomena. BR=0.84, H2 conc. 30%, 30000 fps


Experimental results1

Experimental results

High speed film. BR=0.84, H2 conc. 28%, 30000 fps


Simulations and experimental study of ddt behind a single obstacle

1.


Simulations and experimental study of ddt behind a single obstacle

2.


Simulations and experimental study of ddt behind a single obstacle

3.


Simulations and experimental study of ddt behind a single obstacle

4.


Simulations and experimental study of ddt behind a single obstacle

5.


Simulations and experimental study of ddt behind a single obstacle

6.


Simulations and experimental study of ddt behind a single obstacle

7.


Simulations and experimental study of ddt behind a single obstacle

8.


Numerical methods

Numerical methods

  • In house code by K. Vaagsaether – FLIC

    • Flux LImited Centered scheme

    • 2D TVD method

    • Details by K. Vaagsaether and E.F. Toro

  • Euler equation with ideal gas equation of state

    • Conservation of mass

    • Conservation of momentum

    • Conservation of energy

    • Conservation of turbulent kinetic energy

1.Toro, E.F., Riemann Solvers and Numerical Methods for Fluid Dynamics:

A Practical Introduction, 1999, Springer-Verlag, Berlin, Heidelberg.

2.Vaagsaether, K., Modelling of Gas Explosions, PhD thesis, 2010,

Telemark University College – NTNU, 2010:221.


Combustion model

Combustion model

  • Progress variable β is conserved and can represent a concentration.

  • β =1 are products, while β =0 are reactants

  • Progress variable α is conserved and represents induction time

  • α<1 ”not hot enough”, while α=1 auto ignite


Combustion model1

Combustion model

  • The reaction rate is a maximum of two rates.

  • One turbulent reaction rate and one kinetic reaction rate.

  • Turbulent burning velocity from Flohr and Pitsch. Original from Zimont (1979), model constant A = 0.52 from Zimont and Lipatnikov (1995).

  • Flohr, P. and Pitsch, H., Centre for Turbulent Research, Proceedings

  • of the Summer Program, 2000.

  • Zimont, V. L. 1979 The theory of turbulent combustion at high

  • Reynolds numbers. Combust. Expl. and Shock Waves. 15.

  • Zimont, V. L., & Lipatnikov, A. N. 1995 A numerical model of

  • premixed turbulent combustion of gases. Chem. Phys. Reports. 14(7).


Combustion model2

Combustion model

  • The kinetic model is given by Korobeinikov et.al. 2002

  • Then α is linked to the induction time τ by

  • Need model for induction time.

Korobeinikov, M.S., Levin, V.A., Markov, V.V. and Chernyi, G.G,

Propagation of Blast in a Combustible Gas, Astronautica Acta,

17, 1972, pp. 529-537.


Induction time

Induction time

  • Sichel et.al. model

  • Del Alamo et.al. model

1.Sichel, M., Tonello, N.A., Oran, E.S. and Jones, D.A.,

A Two–Step Kinetics Model for Numerical Simulation

of Explosions and Detonations in H2-O2 Mixtures,

Proc. R. Soc. Lond. A, 458, 2002, pp. 49-82.

2.Del Alamo, G., Williams, F.A. and Sanchez, A.L.,

Hydrogen–Oxygen Induction Times Above Crossover

Temperatures, Combustion Science and Technology,

176, 2004, pp. 1599–1626.


Reaction rates

Reaction rates

  • Turbulent reaction rate ωT is relevant for deflagrations, where diffusion and mixing is the dominante mechanism.

  • Kinetic reaction rate ωK is relevant for detonations, where shock compression/heating is the dominante mechanism.

1

0

1.Vaagsaether, K., Modelling of Gas Explosions, PhD thesis, 2010,

Telemark University College – NTNU, 2010:221.


Numerical simulations

Numerical simulations


Numerical results

Numerical results

  • Focus on the combustion behind the obstacle

  • Driver section (0 -> 1000 mm) challenge to reproduce

  • Several small explosions along the walls add up to DDT

    • Small scale mixing

    • Pockets of hot reactants

  • Very dependant on induction time model

  • Kinetic reaction rate is important


Numerical results1

Numerical results

Numerical schlieren pictures from the simulation case with BR=0.84 and 35% H2 in air.

Frames are not equidistant in time. Induction model: del Alamo.


Numerical results2

Numerical results

Numerical schlieren pictures from the simulation case with BR=0.84 and 30% H2 in air.

Frames are not equidistant in time. Induction model: del Alamo.


Simulations and experimental study of ddt behind a single obstacle

Film

Case with BR=0.75 and 30% H2 in air. Induction model: del Alamo.


Numerical results3

Numerical results

Density gradient along top wall

  • Comparison of one case with two induction time models

  • One DDT, one without

  • Need to create large enough volume to explode.

  • Not too long and not too short induction time

  • “Draw to bow”


Conclusion

Conclusion

  • Total run up distance from 1.1 m to 1.6 m in experiments.

  • Small explosions behind the flame front.

  • Onset of detonation at the walls, mostly top wall.

  • Simulations with two step combustion model.

    • Turbulent reaction rate for deflagrations.

    • Kinetic reaction rate for detonations.

  • Several small explosions along the walls.

  • Dependant on induction time model.


Thank you

Thank you


  • Login