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Marius Stan Computational Physics Group Los Alamos National Laboratory Atomistic and Continuum Simulations of Phase Stability of Alloys - Advanced Models.

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Presentation on theme: "Marius Stan Computational Physics Group Los Alamos National Laboratory Atomistic and Continuum Simulations of Phase Stability of Alloys - Advanced Models."— Presentation transcript:

1 Marius Stan Computational Physics Group Los Alamos National Laboratory Atomistic and Continuum Simulations of Phase Stability of Alloys - Advanced Models and Simulations of Nuclear Fuel Materials UNCLASSIFIED Characterization of Advanced Materials under Extreme Environments for the Next Generation Energy Systems Workshop Brookhaven National Laboratory, Sept , 2009

2 Outline Multi-scale methods and simulations can qualitatively predict phase stability of alloys… …and nuclear fuel performance In the future, experiment, theory and computation will work hand in hand to create materials with spectacular properties.

3 1 M. Stan, J. Nucl. Eng. Techn., 41 (2009) M. Stan, et al., J. Alloys Comp., 444–445 (2007) 415–423 Multi-scale theoretical and computational methods 1

4 Phase Stability of Pu-Ga Alloys Will  -Pu decompose into  -Pu and Pu 3 Ga, at room temperature and 1 atm.? N. T. Chebotarev, E. S. Smotriskaya, M. A. Adrianov, and O. E. Kostyuk, in Plutonium 1975 and Other Actinides, Proc. of the Fifth International Conference on Plutonium and Other Actinides, Baden Baden, Germany, September 10-13, 1975, Edited by North-Holland Publishing Company, New York, 1976, p F. H. Ellinger, C. C. Land, and V. O. Strebing, The Plutonium-Gallium System, J. Nucl. Mat., 12 (1964) p No, δ-phase will not decompose at room temp.Yes, δ-phase will (eventually) decompose at room temp.

5 Ga atoms Molecular Dynamics simulations 1 Molecular Dynamics simulations 1 MEAM potential 2 MEAM potential 2 Melting of gallium at 1 atm. Liquid Solid (A11) 1 Courtesy of S. M. Valone 2 M.I. Baskes et al., Phys. Rev. B, 66 (2002), p. 104–107.

6 Distorted-  Pu Interstitial Pu Initial atom (010) view direction Radiation damage in plutonium at 1 atm. Molecular Dynamics simulations 1 Molecular Dynamics simulations 1 Distorted  -Pu structure at 300 K Distorted  -Pu structure at 300 K MEAM potential 2 MEAM potential 2 1 S. M. Valone et al., J. Nucl. Mater., 324 (2004) M. I. Baskes, Phys. Rev. B 62, (2000).

7 Multi-scale method for alloys 1 1 M. I. Baskes and M. Stan, Metall. Mater. Trans. 34A (2003) M. I. Baskes, et al. JOM, 55 (2003) N. T. Chebotarev, et al. Proc. Fifth International Conf. on Plutonium and Other Actinides, Baden Baden, Germany, Sept , 1975, North-Holland Publishing, NY, 1976, p Phase diagram Free energy of all phases Chemical potentials Thermodynamic equilibrium Electronic Structure Atomistic Predicted Pu-Ga diagram. 2 Experimental Pu-Ga diagram. 3

8 Irradiation Effects on Fission Reactor Materials 1 From Donald R. Olander, "Fundamental Aspects of Nuclear Reactor Fuel Elements," TID P1, Technical Information Service, U.S. Department of Commerce, Springfield, Virginia. Fuel restructuring, changes in chemistry 1 Issues: Fission products accumulation, gas bubbles formation Formation of dislocations, cracks. Localized melting, phase transformations Fuel-cladding chemical Interactions Consequences: Fuel and clad swelling, deformation Loss of mechanical integrity Decrease in heat release, overheating. Fuel element replacement.

9 grain boundary (GB) Xe 1 M. Stan, et al., J. Alloys Comp., 444–445 (2007) 415– P. Cristea et al., J. Optoelectr. Adv. Mater, 9 (2007) Courtesy of John Wills Understand and control atomic-scale phenomena: defect formation and fission products migration Schematic representation of grain boundary defect formation from MD 3. To meso-scale - GB structure, orientation, and energy - FPs mobility at GBs and in the bulk - Nucleation sites - Free energy model From ES Defect formation time = ps Recombination time = 1-10 ps Defects (clusters) size 1-10 nm. - Defect formation energy - Diffusion energy barriers To experiment - Chemical potentials - Nucleation sites From experiment - Grain size, orientation - FPs diffusivity (bulk) Fission products (FP) migrate in the grain and at the grain boundary (GB). At high doses (burnup) point defects interact and form clusters 1-2 Point defect and clusters are nucleation centers for FP gas bubbles and cracks.

10 Understand and control meso-scale phenomena: microstructure evolution 1 M. Stan, J. Nucl. Eng. Technology, 41 (2009) S.Y. Hu et al., J. Nucl. Mater. 392 (2009) 292– I. Zacharie et. al., J. Nucl. Mater. 255 (1998), Phase Field simulation using empirical free energy model 2 10  m Experiment: Irradiated UO 2 in PWR 3 Fission products migrate in the nuclear fuel and form gas bubbles. The gas bubbles can lead to formation of “tunnels” (channels) that release the gas into the gap (fuel-clad) region. Radiation induced changes in microstructure decrease the effective thermal conductivity 1. Nucleation times = ps Coalescence times = µs Size distributions of gas bubbles 1nm-10µm. From atomisticTo continuum - GB structure, orientation, and energy - FPs mobility at GBs and in the bulk - Nucleation sites - Free energy model From experiment - Grain size, orientation - FPs diffusivity (bulk) To experiment - Pore distribution - FPs distribution -Thermal cond. model - Thermal exp. model -Crack nucleation and evolution model

11 Understand and control continuum phenomena : heat and chemical transport 1 J. C. Ramirez et al, J. Nucl. Mater, 359 (2006) B. Mihaila et al., J. Nucl. Mater (2009) in press. Radial profile of properties 2 Finite Element Method (FEM) simulations of coupled heat transport, oxygen diffusion and thermal expansion in a UO 2 fuel element with steel clad are show that including the dependence of thermal conductivity on defects and local oxygen content can lead to changes in the predicted centerline temperature and displacements of 5% or more 1,2. Following a power excursion of 1 ms: Thermal time to steady state = seconds Displacement time to steady state = seconds Composition time to steady state = weeks! To reactor level To experiment - Temp. distribution - Chemical species distribution (O, FPs). - Centerline temp. - Fuel pin deformation From meso-scale From experiment -Crack distribution -Burnup effects -Thermal cond. model - Thermal exp. model -Crack nucleation and evolution model

12 The Future: Institutes for Materials Discovery and Design (IMDD) The institutes will integrate experiment, theory, and computation. The scientists will be trained in all areas and experts in one of them 1,2. State of the art laboratories for small-scale experiments A computational materials science hub for model development and small-scale simulations Meeting rooms equipped with visualization capabilities for discussions Offices for staff, guest scientists and students IMDD Computational Materials Science Hub Meeting/Visualization rooms Laboratories Offices 1 M. Stan and S. Yip, white paper DOE workshop on Advanced Modeling and Simulation for Nuclear Fission Energy Systems, Washington DC, May 11-2, 2009: https://www.cels.anl.gov/events/workshops/extremecomputing/nuclearenergy/agenda.php. https://www.cels.anl.gov/events/workshops/extremecomputing/nuclearenergy/agenda.php 1 M. Stan, Materials Today, Nov. (2009) accepted. Experimental and computational data Models (mathematical) Simulations (pictures, movies) Fully searchable International knowledge base for fuels and materials

13 Meetings of potential interest Materials Models and Simulations for Nuclear Fuels Workshop, Albuquerque, NM, Oct , See: From Basic Concepts to Real Materials Conference, Santa Barbara, CA, Nov. 2-6, See: The Nuclear Materials Congress, Karlsruhe, Germany, 4-8 October 2010, Contact: Marius Stan,


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