Viscous Compaction Waves Joseph M. Powers and Michael T. Cochran University of Notre Dame, Notre Dame, Indiana SIAM Annual Meeting New Orleans, Louisiana 12 July 2005
Compaction Wave Schematic 100 µ m D ~ 400 m/s u ~ 100 m/s p particles φ ~ 0.73 φ ~ 0.98 s s
Introduction • Heterogeneous energetic solids composed of 100 µm crystals in plastic binder. • Engineering length scales on the order of many cm . • Macrobehavior (ignition, etc.) strongly linked to microstructure. • Continuum mixture models with non-traditional constitutive theories needed to capture grain scale physics.
Review • Gokhale and Krier, Prog. Energy Combust. Sci. , 1982. • Baer and Nunziato, Int. J. Multiphase Flow , 1986. • Powers, Stewart, Krier, Combust. Flame , 1990. • Saurel and Abgrall, J. Comput. Phys. , 1999. • Bdzil, et al. Phys. Fluids , 1999, 2001. • Gonthier and Powers, J. Comput. Phys. , 2000. • Powers, Phys. Fluids , 2004.
Issues with Continuum Mixture Theories • Well-posedness not always straightforward. • Second law complicated. • Shock jumps not clearly defined for non-conservative equations. • Consequent numerical difficulties.
Inviscid Theory of Bdzil, et al. • First theory to unambiguously satisfy the second law. • Hyperbolic and well-posed for initial value problems. • Fundamentally non-conservative. • Some regularization needed for discontinuities. • No viscous cutoff mechanism for multidimensional instabilities. • Grid-dependent numerical viscosity problematic.
Viscous Extension ∂ ∂t ( ρ s φ s ) + ∇ · ( ρ s φ s u s ) = C , ∂ ∂t ( ρ g φ g ) + ∇ · ( ρ g φ g u g ) = −C , ∂ � � ρ s φ s u s u T ∂t ( ρ s φ s u s ) + ∇ · s + φ s ( p s I − τ s ) = M , � � ∂ ρ g φ g u g u T ∂t ( ρ g φ g u g ) + ∇ · g + φ g ( p g I − τ g ) = −M ,
Viscous Extension (cont.) � � �� ∂ e s + 1 ρ s φ s 2 u s · u s ∂t � � � � e s + 1 + ∇ · ρ s φ s u s + φ s u s · ( p s I − τ s ) + φ s q s = E , 2 u s · u s � � �� ∂ e g + 1 ρ g φ g 2 u g · u g ∂t � � � � e g + 1 + ∇ · ρ g φ g u g + φ g u g · ( p g I − τ g ) + φ g q g = −E , 2 u g · u g ∂ρ s ∂t + ∇ · ( ρ s u s ) = − ρ s F φ s , ∂ ∂t ( ρ s φ s η s + ρ g φ g η g ) � φ s q s � + φ g q g + ∇ · ( ρ s φ s u s η s + ρ g φ g u g η g ) ≥ −∇ · . T s T g
Constitutive Equations φ g + φ s = 1 , ψ s = ˆ ψ s ( ρ s , T s ) + B ( φ s ) , ψ g = ψ g ( ρ g , T g ) , � � ∂ψ s ∂ψ g � � p s = ρ 2 p g = ρ 2 , , � � s g ∂ρ s ∂ρ g � � T s ,φ s T g � � η s = − ∂ψ s η g = − ∂ψ g � � , , � � ∂T s ∂T g � � ρ s ,φ s ρ g � β s = ρ s φ s ∂ψ s � , � ∂φ s � ρ s ,T s e s = ψ s + T s η s , e g = ψ g + T g η g ,
Constitutive Equations (cont.) � ( ∇ u s ) T + ∇ u s � − 1 τ s = 2 µ s 3( ∇ · u s ) I , 2 � ( ∇ u g ) T + ∇ u g � − 1 τ g = 2 µ s 3( ∇ · u g ) I , 2 q s = − k s ∇ T s , q g = − k g ∇ T g , C = C ( ρ s , ρ g , T s , T g , φ s ) , M = p g ∇ φ s − δ ( u s − u g ) + 1 2( u s + u g ) C , � � e s − u s · u s E = H ( T g − T s ) − p g F + u s · M + C , 2 F = φ s φ g µ c ( p s − β s − p g ) .
Equations of State Modified Tait equation for solid (correction courtesy D. W. Schwendeman) � T s � ρ s � � �� + 1 ρ s 0 ψ s ( ρ s , T s , φ s ) = c vs T s 1 − ln + ( γ s − 1) ln ρ s ε s + q T s 0 ρ s 0 γ s � 2 − φ s 0 � (1 − φ s ) 1 − φs +( p s 0 − p g 0 ) (2 − φ s 0 ) 2 2 − φs ln � � 1 − φs 0 2 − φ s 1 ρ s 0 φ s 0 ln (1 − φ s 0 ) 2 − φs 0 1 − φ s 0 Virial equation for gas � T g � ρ g � � � � �� ψ g ( ρ g , T g ) = c vg T g 1 − ln + ( γ g − 1) ln + b g ( ρ g − ρ g 0 ) T g 0 ρ g 0
Viscous Dissipation Function ∇ u s + ( ∇ u s ) T 1 Φ s = 2 µ s − 3( ∇ · u s ) : I 2 � �� � � �� � strain rate mean strain rate � �� � deviatoric strain rate ∇ u s + ( ∇ u s ) T 1 − 3( ∇ · u s ) . I 2 � �� � � �� � strain rate mean strain rate � �� � deviatoric strain rate • similar expression for Φ g .
Dissipation: Clausius-Duhem Equation � β s � ρ s T s + e s − e g − p g (1 /ρ g − 1 /ρ s ) I ≡ ( −C ) + η g − η s T g + δ ( u s − u g ) · ( u s − u g ) T g + H ( T g − T s ) 2 T g T s ( p s − β s − p g ) 2 + φ s φ g µ c T s + φ s Φ s + φ g Φ g T s T g + k s φ s ∇ T s · ∇ T s + k g φ g ∇ T g · ∇ T g ≥ 0 . T 2 T 2 s g
Characteristics • Three real characteristics u s , u s , u g , • Three associated eigenvectors, • Not enough eigenvectors for eleven equations: parabolic, • Eight additional conditions from boundary conditions on T s , T g , u s , u g .
Numerical Method • One-Dimensional: Fortran 90 code – Second order central spatial discretization – High order implicit integration in time with DLSODE • Two-Dimensional: FEMLAB software tool – Finite element method for the form ∂ q ∂t + ∇ · f ( q ) = s ( q ) . – Unstructured mesh
1D Verification: Shock Tube T (K) inviscid L (K) 310 T g 1 analytical 1 slope=0.75 viscous 305 T s numerical 0.1 300 0.01 slope=1.95 295 A2 A1 290 0.001 ∆ x (m) 0.5 x (m) 0.1 0.2 0.3 0.4 0.0001 0.001 0.01 0.1
1D Verification: Piston-Driven Shock T (K) 340 solid 330 gas 320 310 B1 300 x (m) 0.1 0.2 0.3 0.4 0.5 T (K) T (K) g s viscous shock in solid viscous shock in gas 340 325 steady solution steady solution 330 320 time-dependent time-dependent 315 solution 320 solution 310 B2 310 B3 305 300 0.39 x (m) 0.28 x (m) 0.36 0.37 0.38 0.18 0.20 0.22 0.24 0.26
1D Subsonic Piston-Driven Compaction φ s p (MPa) 1 50 p β s s 0.8 10 0.6 5 0.4 p 1 g E1 0.2 E2 0.5 x (m) x (m) 0 0.1 0.2 0.3 0.4 0.5 0.1 0.2 0.3 0.4 0.5 T (K) u (m/s) 304 100 80 303 T , T u , u g s s g 60 302 40 301 E3 20 0.5 x (m) x (m) 0.1 0.2 0.3 0.4 0.1 0.2 0.3 0.4 0.5
1D Dissipation: Subsonic Case 3 I (MW/m /K) 200 Total Compaction 150 100 E 50 Solid Momentum Diffusion x (m) 0.1 0.2 0.3 0.4 0.5
FEMLAB vs. F90 Verification: 1D Shock Tube 1.4 x 10 -3 310 305 1.0 r o r r E T [K] e 300 v i g t a l 0.5 e R 295 0 290 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 x [m] x [m]
Narrow 2D Shock Tube vs. 1D Shock Tube 300 K 292 K 310 K 300 K 2 D 0 0.1 0.2 0.3 0.4 0.5 x (m) 310 1 D t = 50 µ s T (K) 300 g 290 0.0 0.1 0.2 0.3 0.4 0.5 x (m)
Small Energy Pulse: 2D Response . t = 18 μ s small temperature perturbation . radial pressure wave at ~ 2000 m/s . t = 0 μ s reflection at wall Solid Pressure
Large Energy Pulse: 2D Response Max = 0.867 φ s (x,y) 0.040 y (m) 0.000 -0.015 0 0.035 0.05 Min=0.730 x (m)
Conclusions • Diffusion enables use of simple numerical techniques. • Diffusion suppresses short wavelength instabilities, e.g. Kelvin-Helmholtz. • Diffusion suppresses subgranular length scales. • Compaction dominates the dissipation. • Rigorous subscale physical justification for diffusion models presently lacking. • Such justification necessary for a validated model.
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