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A Facility for Simulating the Dynamic Response of Materials

1. A Facility for Simulating the Dynamic Response of Materials. Materials Properties William A. Goddard, III Caltech ASCI Academic Strategic Alliances Program Site Visit October 8, 1998. 2. STAGE 2. STAGE 3. INTERACTION OF STRONG SHOCK WAVES WITH SOLID MATERIALS. SHOCK INDUCED

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A Facility for Simulating the Dynamic Response of Materials

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  1. 1 A Facility for Simulating the Dynamic Response of Materials Materials Properties William A. Goddard, III Caltech ASCI Academic Strategic Alliances Program Site Visit October 8, 1998

  2. 2 STAGE 2 STAGE 3 INTERACTION OF STRONG SHOCK WAVES WITH SOLID MATERIALS SHOCK INDUCED COMRESSIBLE TURBULENCE AND MIXING STAGE 1 DETONATION OF HIGH EXPLOSIVES Integration and Parallelism Continuum Modeling Turbulence Modeling Binder and Grain Interactions Compressible Mixing Length and Time Scales Integration and Parallelism Equation of State Shock-Contact Interaction Reaction Rates Reaction Pathways Equation of State Molecular Processes Simulation Development Roadmap PROBLEM SOLVING ENVIRONMENT Mesh Generation Solid Modeling MP Fracture and Fragmentation MicroMechanics Constitutive Relations Phase Transitions Materials Science Solid Mechanics Fluid Mechanics Computational Science

  3. 3 Goals of the proposed research • Provide the Parameters Describingthe Materials Properties required for a Full Physics, Full Chemistry 3-D Description of: • Detonation of High Explosives (HE), • Solids Subjected to Severe Dynamic Loading (SD), • Compressible Turbulence and Mixing (CT). • Develop the Technology Required to Predict These Properties Solely from First Principles. • Validate the Accuracy of the Properties by Comparison toExperiments Under Conditions Relevant to HE, SD and CT Applications. • Implement the Technology in the Most Efficient Manner for Massively Parallel Computers.

  4. 4 Roadmap for Materials Properties

  5. Materials Properties Milestones • 5 Year 1 Year 2 Year 3 Year 4 Year 5 Relevant discipline Metal FFs MP(core), SD QM based FFs Properties from MD simulations EoS database New functionals for metals QM on metals MP(core), SD Expansion of QM capabilities for HE MP(core), HE, SD Parallel DFT DFT-MD on Large Scale models Ceramic FFs and EoS Properties of brittle ceramics MP(core), SD,new QM based FFs Metal-ceramic interface FF MP(core), SD QMC in ab initio QM codes Parallelization of QMC codes MD simulations of HE with polymer MD simulations with reactive FF NEMD using reactive FF DB: Transport properties MP(core), HE Integration of atomistic simulation and 2D EoS models (Cij (T,P)) Cij at interfaces; heterogeneous systems at high T and P MP(core), SD NEMD, parallelization of NEMD MP(core), HE,CT Integration Viscosities of heavy metals Transport properties MP(core), CT Property database Hypervelocity impact and planar shock wave simulations MP(core), HE, SD,CT,new Reaction rates for HE’s from QM RR database MP(core), HE

  6. 6 Simulation Development Roadmap MPHE • High Explosives Applications • Binder and Grain Interactions • Kel-F, Estane • Equation of State • HMX, TATB • Reaction Dynamics and Molecular Processes • Shocked HMX, TATB • Vibrational Analysis of Rapid Post-Shock Events • Shock Compression MD

  7. 7 Simulation Development Roadmap MPSD • Solid Dynamics Applications • Equations of State • Ta, Fe, Oxides, and Ceramics • Phase Transitions • Ta, Carbon, Ceramics • Constitutive Equations • Elastic properties of metals, alloys, and ceramics • Thermodynamic properties • Plasticity and behavior under large strain rates

  8. 8 Simulation Development Roadmap MPCT • Compressive Turbulence and Fluid Dynamics Applications Determine material properties for fluids • Equation of state of Dense Fluids (P,V,T) • Transport Properties of Dense Fluids (at elevated T and P) • Viscosity of dense fluids under large shear rates • Mass transport in dense fluids (diffusion at high P & T) • Heat transport (thermal conductivity at high P & T) Shock propagation in fluids Negative pressure properties

  9. 9 Personnel — Materials Properties • Postdoctoral staff • Daniel Mainz (non-ASCI) • Gregg Caldwell (non-ASCI) • Alejandro Strachan (non-ASCI) • John Che (non-ASCI) • Ersan Demiralp (non-ASCI) • Oguz Gulseren (CIW) • Hideki Ikeda (non-ASCI) • Don Frasier (non-ASCI) • Enrique Pifarre (LANL, Feb ‘99) • Professional support staff • Darryl Willick (MSC) • J. Kendall (MSC) • Senior researchers • William A. Goddard (MSC) • Ronald Cohen (CIW) • Tahir Cagin (MSC) • Siddharth Dasgupta (MSC) • Richard P. Muller (MSC) • Graduate students (ASCI) • Lu Sun (Materials Sci.) • Hao Li (Materials Sci.) • Yue Qi (Materials Sci.) • Georgios Zamanakos (Physics) • Ryan Martin (Materials Sci.) • Guofeng Wang (Materials Sci.)

  10. 10 Organization - Materials Properties • External Collaborators • Carnegie Institute Washington • University of Tennessee • Materials Properties Meeting — Annual • LANL, SNL, LLNL National Laboratories • Utah and Illinois Alliance Centers • November 10, 1997 • January 28, 1999 (HE); January 29, 1999 (SD) • Interactions • HE: Weekly Meetings, (daily email/phone) • SD: Monthly Meetings • MP: Monthly Meetings • SI: Biweekly Meetings

  11. 11 External Meetings - Materials Properties • Energetic Materials GRC (Dasgupta, Sun) • 11th Detonation Symposium (Dasgupta) • NATO ASI on QMC (Cohen, Muller) • 2 Visits to SNL: PBC QM Quest (Muller) • 1 Visit to LANL: QM ECP (Muller) • Dislocations Workshop, LLNL (Cagin, Gulseren) • 1 Visit to LLNL: MP, HE, SD (Goddard) • 1 Visit to SNL: Multi-length scale, Polymers (Goddard) • 1 Visit to LLNL: HE Aging (Goddard) • MRS, APS, ACS meeting presentations (~11)

  12. 12 November 10, 1997, Caltech Laboratory Presentations LLNL Mailhiot, Ree, King, Fried SNL Heffelfinger, Melius LANL Kress ASAP Center Presentations Caltech Goddard, Tombrello, Cagin, Muller, Dasgupta, Ortiz, Shepherd, Meiron CIW Cohen Utah Voth, Wight, Boyd Illinois Martinez, Mitas ASCI Materials Properties Workshop

  13. 13 Milestones, MP Software Integration • MSC QM Software (Jaguar, QM/MSC) Port to ASCI Machines Optimize parallelization • MSC MD Software (MPSim) Port to ASCI Machines Optimize parallelization • MSC Semi-empirical QM Software (MSC-INDO) Improve scaling for large systems • Integration of QM and MD Software use Caltech Integration Platform

  14. 14 Role of Computer Science (CSMP) • ScaLAPACK workshop, January 1998 • Use of math libraries to parallelize code • Software Integration • MP integration framework integrates with Caltech ASCI framework • New Algorithmic work • Shock dynamics for HE and SD • Improved matrix diagonalization work for QM • Virtual Test facility • HE Database Project

  15. 15 Quantum Mechanics Periodic Systems High Accuracy for Large Systems Fast Results for Large Systems Solvation (Poisson-Boltzmann) Force Fields Polarizable, Charge Transfer Variable Bond Orders Phase Transitions Mixed Metal, Ceramic, Polymer MesoScale Dynamics Coarse Grained FF Diffusion Hybrid MD and Meso Dynamics Friction Physics-based gridpoints for Finite Element Analysis Molecular Dynamics Large Systems (CMM, Parallel) Non-Equilibrium Viscosity, Friction Solvation (Poisson-Boltzmann) Hybrid QM/MD Hierarchical NEIMO Plasticity, Twin Formation, Crack Initiation Interfacial Energies Hildebrand Solubilities Process Simulation Vapor-Liquid Equilibria Reaction Networks Current Research in Methods for MP

  16. 16 Ab Initio (Exact Hamiltonian) Pseudospectral Techniques dealiasing, multigrid Improved scaling by factors of N to N2 First Principles Solvation Density Functional Theory Periodic Boundary Conditions New Functionals Tight Binding fit to accurate LAPW Semiempirical Tight Binding or INDO Fast Hamiltonian Construction Molecular Dynamics Quantum Monte Carlo Most accurate method (0.0004 eV for simple reactions) Scales exponentially with size Combine with DFT (Only simulate reacting electrons) Quantum Mechanics (HY=EY)

  17. 17 • Psuedospectral Technology (with Columbia U.) • Multigrids • Dealiasing functions • Replace N4 4-center Integrals with N3 potentials • Use Potentials to Form Euler-Lagrange Operator: • CURRENT STATUS: • Single processor speed 9 times faster than best alternate methodology • Scales a factor of N2 better than best alternate methodology QM Methodology (Jaguar) Gaussian CPU Time Jaguar Log (number basis functions) Collaboration with Columbia U. and Schrödinger Inc.

  18. 18 QM Parallelization (Jaguar) Collaboration with Columbia U. and Schrödinger Inc.

  19. 19 Quest: Sandia Software for PBC QM MP/ASCI: Incorporate MSC GUI, new ECP, Basis sets Port to other machines

  20. 20 CS/MP 1: Improved Matrix Acceleration Muller (MSC) - Ward (UTenn) Series of alkane chains, 276-552 basis functions, bandwidth ~80 basis functions • QM Scaling • N2 - N4 Hamiltonian Construction • N3 Diagonalization • Need both to scale as N Contour plot of Hamiltonian Matrix Band Diag: scales good (N2.3) but overhead too high Normal Diag: scales poorly (N3.3) but generally efficient Block Diag: scales best (<N2) but generalization problems

  21. 21 Progress Molecular Dynamics (F=MA) • Generalized Gibbs MD (Constant T and P/S ) • Cell Multipole Methods (Octree, Fast Multipoles) • Fast, accurate NB evaluations for millions of atom systems • NEIMO Dynamics • Fast internal coordinate dynamics • Hierarchical for coarse graining • Solvation • Poisson-Boltzmann solver (energy and forces) • Generalized Born • Optimization for Highly Parallel Computers • SGI Origin, HP Exemplar • Ported to Intel quad-Pro

  22. 22 MPSim with PB Solvation • Explicit Solvent • Accurate • Typically solvent molecules account for 90% of computation • polymer motions limited by diffusion rates in solvent • Continuum Solvent (Poisson-Boltzmann) • Solvent reduced to charges and forces on mesh points around molecule • Use realistic solvent accessible surface • Calculate energies and forces (for dynamics) • Dramatically increases simulation times • Protocol • Update PB Forces every N time steps (Forces Expensive) • Use mesh density sufficient for MD (coarser than for QM).

  23. 23 Integrate NEIMO in MPSim INTERNAL COORDINATE DYNAMICS: Problem: M is full N by N (N is number of int. coord.) Inversion scales as N3, too slow for every dynamics step Solution: NEIMO = Newton Euler Inverse Mass Operator Construct M-1 in terms of operators (scale as N=1) (collaboration with JPL Space Robotics) Hierarchical NEIMO - Treat segments as rigid clusters connected by flexible hinges, Allows successively coarser descriptions for Large time and spatial scales • Goals • Incorporate NEIMO dynamics into MPSim (Forces use CMM) • Include Poisson-Boltzmann solvers • Parallelize • Target Systems: HE grains in polymer binder.

  24. 24 CS/MP 2: Lightweight Threads in MD HRV-1 Rhinovirus - 500,000 Atoms Intel QuadPentium, 2 GB RAM Cagin, Li (MP), Thornley (CS) • Parallelized MPSim • Efficient on KSR, Intel Delta • Other platforms less efficient • Lightweight Threads • Inexpensive intialization • Parallelization on commodity microprocessors • Speedup of 3.6 on 4 processors for a real problem • Next year, Expand to • QM • QM/MM

  25. 25 Accomplishments, Overview • High Explosives • MD Simulation of TATB, HMX, and Kel-F • Simulation of post-shock energy redistribution • Solid Dynamics • MD Simulation of Metals and Oxides • QM Simulation of HCP, FCC, and BCC Metals • FF for BCC Metals • Algorithms • Shock MD Simulator • Phase transitions in Oxides and Metals • Bond-order-dependent FF for Carbon

  26. 26 Milestones, HE • TATB/HMX Molecular Structure • MD of inert and reactive explosives • Reaction Mechanism for TATB/HMX

  27. 27 MD and Force Field Development for HMX • Level 0 - Generic Force Field (Dreiding) - Can Do Any Combination Of Main Group Atoms • Density of States • Pressure Loading • Phase transitions • Level 1 - Vibrationally accurate force field Develop for specific systems DMN, HMX & RDX • DFT (B3LYP) calculations on isolated monomers • QUEST calculations on condensed phase systems • FFOPT parameterization of FF to fit QM • Vibrational Energy Transfer (VET): Intra-, inter-molecular, phonon - phonon couplings • H-bond interactions

  28. 28 Crystallographic Forms of HMX Impact Energy E = 0.20 kg/cm2 Sensitive Impact Energy E = 0.10 kg/cm2 Most sensitive 429 K - to melting point r = 1.58 r = 1.78 r = 1.894 r = 1.839 Impact Energy E = 0.75 kg/cm2 Least sensitive Impact Energy E = 0.20 kg/cm2 Sensitive Stable @ 300K 377 - 429 K

  29. 29 Correlation of Density of States (from MD) with Sensitivity (h50 measurement) b-HMX h50 = 0.33m TATB h50 = 3.2m a-HMX h50 = N/A g-HMX h50 = 0.14m 0 200 400 600 cm-1 d-HMX h50 = N/A most sensitive Conclusion: Impact sensitivity correlates with density of modes between 0-200 cm-1

  30. 30 Compare Vibrational Frequencies QM (DFT-B3LYP/6-31G**) with FF (Dreiding) 0-200cm-1

  31. 31 Pressure Dependence of Crystallographic Cell Parameters for b-HMX (Theory using Dreiding, open symbols) with Experiments from Cady & Ollinger (filled symbols) B C A

  32. 32 Elastic Constants and Bulk Modulus of b-HMX Experimental Data (Joe Zaug, LANL), Theory (Dreiding)

  33. 33 HMX Cold Compression Curves for the 4 crystal morphologies • a form is the least compressible followed closely by the g form • d form is the most compressible • stable b form is intermediate in compressibility a g d b

  34. 34 Isothermal P-V curves for b-HMX • Procedure • Minimize at 0K • Increase T by 300K increments • 20ps MD at each T • Results • Evidence of melting or phase transition above 600K • Compressibility similar for P > 25GPa Melting behavior?

  35. 35 Calculation of Shock Adiabat intersection with P-V isotherms 0K Tang’s Adiabat • PV Isotherm from Simulations Allows the T for the Adiabat to be calculated from intersection points 600K

  36. 36 b-HMX Cv from Phonon Dispersion Curves of Crystal 27 K points 343 K points • 125 K points in Brillouin zone adequate • 90% of asymptotic high T limit reached at 1400K 125 K points

  37. 37 Convergence of Gruneissen Parameter from 50ps (0.5fs step) MD of 4x3x2 supercell of b-HMX • Gruneissen parameter converged by 40ps of MD

  38. 38 TATB (1,3,5-triamino-2,4,6-trinitrobenzene) Overview • planar structure, compact packing and high density • Experimental density at STP is 1.9374 g/cc. • TATB crystal has low symmetry: triclinic (P-1). density (g/cc) a (A) b (A) c (A) Expt. 300K 9.01 9.028 6.812 1.9374 Dreiding Exp6 8.986 8.976 6.883 1.8852 error 0.27% 0.58% 1.04% 2.69%

  39. 39 TATB Isothermal Equation of State Expt. MD 300K MD Dreiding FF Expt. (Cady)

  40. 40 TATB Isothermal EOS, Dreiding Force Field

  41. 41 TATB Future Work • Shock Hugoniot from isotherms • Gruneissen Parameter • Further Force Field Improvement • Surfaces, Defects • Interaction with Kel-F • MD Fast Loading with surfaces & Kel-F

  42. 42 Kel-F800 Overview • Kel-F 800 is a random copolymer of chlorotrifluoroethylene and vinylidene fluoride monomer units in a 3:1 ratio. • The presence of the vinylidene fluoride disrupts the the crystallinity of the chlorotrifluroethylene to form an essentially amorphous polymer • Although amorphous, the polymer is very dense due to the presence of the Cl and F atoms • It is used in composites and as a binder for many plastic-bonded explosive systems • First atomistic/molecular study of Kel-F 800 system.

  43. 43 Kel-F 800 Atomistic Simulations Strategy for building amorphous polymers • Assume infinite solid with periodic supercell • Choose a molecular weight and a number of chains per unit cell • Use torsional potential and nonbond interactions to evaluate energy of growing system • Build each chain simultaneously monomer by monomer using Monte Carlo sampling. • anneal structure with MD at various Temperatures and Pressures (or volumes) • Standard techniques lead to density too low • The MSC Cohesive Energy Density Module uses a strategy that leads to excellent density and cohesive energy

  44. 44 Kel-F 800 Atomistic Simulations 20 Angstroms 24 monomers - 2 chains 50 Angstroms 24 monomers - 16 chains

  45. 45 Kel-F800 Cohesive Energy Density COMPASS PCTFE 75 Validation • Due to the lack of experimental data for the pure Kel-F 800 polymer system, poly(chlorotrifluorethlene-co-vinylidene fluoride) Some validation work was done by calculating Cohesive Energy Densities and Solubility parameters using a MSC “in-house” developed code. • Initial studies and choice of force field were conducted on pure PCTFE, poly(chlorotrifluoroethylene) for which some experimental data is known. • Dreiding-EXP6 force field is consistent with experiment. 70 Upper limit of Experiment 65 |CED| (cal/cm^3) 60 Experimental Range 55 50 lowerlimit of Experiment 45 Dreiding-EXP6 40 2 5 16 No of "Polymer" chains in cell Cohesive Energy Density Kel-F 800 100 80 |CED| (cal/cm^3) Dreiding-EXP6 60 40 COMPASS 20 0 2 5 16 No of "Polymer"chains in cell

  46. 46 Kel-F800 Future work • Determine how properties depend on number of chains • find compromise between accuracy and speed. • Calculate GRUNEISSEN parameters and other physical properties • as a function of temperature and pressure • from longer Molecular Dynamics runs • Repeat for Estane binder • Use binder with finite crystals of HE, apply shear loading

  47. Large scale MD simulations of HE 47 • High explosives: HMX,TATB grains in a polymeric binder (kelF, estane) • Model HE System • periodic in all 3 directions • x- and y-direction extent (10 nm) • z-direction extent (1-10 mm) • Allow axial compressive loading using new steady state algorithms (Cagin, Goddard) polymer grains polymer 10 nm 1-10 mm

  48. Milestones, Solid Dynamics 48 • Equation of State for Metals and Alloys • Many body FF for fcc metals • Many body FF for bcc metals • Force fields for oxides and ceramics • Phase transformations in metals and ceramics • Equation of state for metals and ceramics • Mechanical and thermodynamic properties of metals • Energetics for Dislocation Models (from QM and MD)

  49. Accomplishments, QM Metals 49 • Simulation of BCC Metals (Cohen) • EOS of Ta • LAPW LDA, GGA, Spin-Orbit Curves • Mixed Basis Code, scales very well on ASCI machines • Simulation of HCP metals (Cohen) • Results for Co (magnetic) and Re (non-magnetic) are in good agreement with experiment. • Theory consistent with behavior of other metals except Fe. • Problem with Fe: theory not agree with recent experiments on Fe

  50. 50 DFT Simulation of Ta EOS • Local Density Approximation • Available in all codes • Quest, Mixed Basis, LAPW • Underestimates EOS curves • Generalized Gradient Approximation • Now Available in fast codes • Greatly improves EOS • Spin Orbit Coupling • Important for Ta EOS • Can Effective Core Potential Simulate These Effect? • Find FF to fit QM Exper LDA Exper GGA

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