A Deeper Look Inside the Furnace - Thermochemistry

A Deeper Look Inside the Furnace Thermochemistry in Multiphysics Models Willem Roos 2018-11-21 Mintek Supervisor: Dr J.H. Zietsman

Contents: Thermochemistry in multiphysics models     

Background Current applications Implementation Accelerating calculations References

Background

Macroscopic

Microscopic

(Pistorius and Coetsee, 2003)

Combine these factors

Heat Transfer Fluid Flow

Thermochemistry

Current Applications Where has thermochemistry been used in multiphysics models?

Refractory design

New (top) and worn (bottom) oxide bonded SiC-based tile. Progressive swelling during service due to oxidation. Blond et al. 2014

Oxidation at the hotface increases matrix density and reduces oxigen transportation into the refractory. This slows down the oxidation of the rest of the refractory.

Long term oxidation under thermal gradient. Blue: Numerical results. Red and Violet: Experimental results, measured along two perpendicular centre lines. Blond et al. 2014

Refractory design

Effect of tile geometry on oxidation extent [mol/mm3] after one year in service under steady state temperature. Blond et al. 2014

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Vertical component of stress tensor after one year in service of tile A. a) Chemical strain not taken into account. b) Chemical strain taken into account. Blond et al. 2014

Tile geometry plays an important role in crack localisation and different designs can be compared to find most suitable design. Chemical strain needs to be incorporated if a worst case is to be considered. High stress locations correlate to crack positions in refractory.

Freeze lining

Velocity, temperature, and solid fraction of a hot liquid flowig over a cold surface. Marin-Alvarado 2015

The inclusion of phase change can have a noticable influence on the flow and temperature distribution inside a system.

Chemical potential

Chemical potential distribution [J/g] of components in irradiated nuclear fuel. Corcoran et al. 2016

 Chemical potential has been used in the nuclear industry to simulate feul depletion.  Can be used to simulate the slag-alloy reduction interaction in furnaces.

Casting

Temperature distribution during solidification. Agelet de Saracibar 2006

Solid-liquid interface as steel solidifies Agelet de Saracibar 2006

Srinkage and Von -Misses stress. Agelet de Saracibar 2006

Other Applications:  Alloy design for improved strength and fracture toughness – control inclusions.  Combustion.  Thermochemical biomass conversion.  Characterization of energy storage materials.  Silicone production for photo-voltaic component coatings.  Reentry vehicle refractory ablation.

Implementation How to incorporate thermochemistry in multiphysics models

Thermochemical Calculations:   

Minimization problem to find equilibrium. Can become very computationally expensive. More components lead to longer solving time:

Model Domains:  

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Can become large and complex. Solve thermochemical equilibrium;  for each element,  for each iteration,  for each time step of transient model. Infeasible to solve large complex systems:  1 Million cells.  1000 iterations.  0.2 seconds per termochemical calculation.  Would take more than 6 years to solve. (Pope 1997). This is just the thermochemistry. There are even more equations to solve.

Model equations:   

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Conservation of energy – Temperature. 3 Momentum equations – Flow and velocity. Mass conservation – Reactions or solidification:  Each phase.  Each phase constituent. (Ommit for simplicity)  Each system component. Normal CFD has 5 equations to solve. 5 Component system can have 21 or more. 16 Component system can have 142 or more.

Accelerating calculations Making the calculations faster and solving time more feasible.

Multiphysics Solver (OpenFOAM)

Heat transfer Fluid flow Mass transfer Electromagnetics  

Thermochemistry Accelerator

Thermochemistry Calculator (FactSage, ChemApp)

Equilibrium calculation Heat capacity Enthalpy Viscosity Density

My PhD focus is the accelerator. Ex Mente is working on the PDE implementation.

What accelerators are there:    

Multi-component databases. In situ adaptive tabulation. Neural Networks. Geometrical approach.

Discretising of a phase region ten Cate et al. 2008 Pb-Sn phase diagram ten Cate et al. 2008

From literature:   

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Geometrical approach can be very efficient. Phase diagrams describe thermochemical behaviour. Phase diagrams consist of geometrical objects:  Points  Phase region boundaries  Phase regions Multicomponent systems can be described by multidimensional phase diagrams. Use Geometrical Algebra and Calculus to efficiently describe multidimensional objects.

Can use thermochemistry theory to our advantage: 

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Gibbs Phase Rule.  Classify phase regions.  Determine minimum amount of data needed to describe phase region. Lever Rule.  Reduces dimensionality.  Use to calculate phase fractions.  Cayley-Menger Determinant: generic algorithm that can be used for c-components.

Accelerator Performance:

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Binary system (Al2O3-CaO):  Initially 20x faster than ChemApp.  Currently 3,000x faster.  Negligible deviations from ChemApp results.  Very coarse discretization resulted in errors less than 1.5%. Ternary (Al2O3-CaO-SiO2):  First implementation was 15x faster than ChemApp.  Negligible deviations.

Visit to Germany:

Prof. Markus Reuter

Tanai Marin

Dr Thomas Echterhof

2019: Establish the best method that can be used to provide multiphysics solvers with the needed thermochemistry information as fast as possible, regardless of the complexity and dimensionality of the multi-component system.

2019:   

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5 component accelerator. Simplified steelmaking system: Fe, O, C, Si, Ca. Send to Thomas Echterhof:  Aachen University in Germany.  Electric Arc Furnace process model. Send to Tanai Marin:  M4Dynamics in Canada.  Freeze lining simulation in COMSOL.

2020:  

Generic accelerator. 16+ components:  Steelmaking system: Fe, O, C, Si, Ca, Al, Cr, H, K, Mg, Mn, N, Na, P, S, V.  Thomas Echterhof: Electric Arc Furnace model.

Post PhD: 

Dive deep and swim around inside the furnace; look at everything that is happening to gain insight into processes and equipment. “Yes! I understand how it works.”

Thank You

References

Blond, Eric et al. (2014). “Multiphysics Modelling Applied to Refractory Behaviour in Severe Environments”. In: Advances in Science and Technology 92, pp. 301–309 Cate, Andreas, Bernard J Geurts, and K Daniel (2008). “Modeling and simulation of phase-transitions in multicomponent aluminum alloy casting” Contino, Francesco et al. (2012). “Simulations of Advanced Combustion Modes Using Detailed Chemistry Combined with Tabulation and Mechanism Reduction Techniques”. In: SAE International Journal of Engines 5.2, pp. 2012–01–0145. Corcoran, E. C., M. H. Kaye, and M. H.A. Piro (2016). “An overview of thermochemical modelling of CANDU fuel and applications to the nuclear industry”. In: Calphad: Computer Coupling of Phase Diagrams and Thermochemistry 55, pp. 52–62. Drake, M. C. and D. C. Haworth (2007). “Advanced gasoline engine development using optical diagnostics and numerical modeling”. In: Proceedings of the Combustion Institute 31 I, pp. 99–124. Marin-alvarado, Tanai L (2015). “Combining Multiphysics Modeling and Solution Thermodynamics Using M4Dlib, an External Library”. Pope, S.B. (1997). “Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation”. In: Combustion Theory and Modelling 1.1, pp. 41–63.