Los Alamos National Laboratory

Los Alamos National Laboratory

Delivering science and technology to protect our nation and promote world stability

Los Alamos National Laboratory Advanced Scientific Computing Research Publications

Peer-reviewed publications sponsored by the DOE Office of Science, Office of Advanced Scientific Computing Research.

2018

  • Barlow, A., M. Klima, and M. Shashkov, 2018:  Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics.  J. Comp. Phys., 371, 914-944.  https://doi.org/10.1016/j.jcp.2018.03.034
  • Bujack, R. T. L. Turton, F. Samsel, C. Ware, D. H. Rogers, and J. Ahrens, 2018:  The Good, the Bad and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps.  IEEE Transactions on Visualization and Computer Graphics24, 923-933.  https://doi.org/10.1109/TVCG.2017.2743978 
  • Faizian, P., M. A. Mollah, X. Yuan, S. Pakin, and M. Lang, 2018:  Random Regular Graph and Generalized De Bruijin Graph with k-Shortest Path Routing.  IEES Trans. Parallel and Distributed Systems, 29, 144-155. https://doi.org/10.1109/TPDS.2017.2741492 
  • Hansan, S. K. and V. V. Vesselinov, 2018: Local Equilibrium and Retardation Revisited.  Groundwater56, 109-117.  https://doi.org/10.1111/gwat.12566 
  • Hoffman, M. J., et al., (LANL authors: S. F. Price) 2018:  Widespread Moulin formation During Supraglacial Lake Drainages in Greenland.  Geophysical Research Letters, 45http://dx.doi.org/10.1002/2017GL075659 
  • Iliev, F., L., V. G. Stanev, V. V. Vesselinov, and B. S. Alexandrov, 2018:  Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals.  PLoS ONE13, e0193974.  https://doi.org/10.1371/journal.pone.0193974 
  • Kucharik, M., G. Scovazzi, M. Shashkov, and R. Loubère, 2018:  A multi-scale residual-based anti-hourglass control for compatible staggered Lagrangian hydrodynamics.  J. Comp. Phys., 354, 1-25.  https://doi.org/10.1016/j.jcp.2017.10.050
  • Liu, X. Y., B. P. Uberuaga, D. Perez, and A. F. Voter, 2018:  New helium bubble growth mode at a symmetric grain-boundary in tungsten: Accelerated molecular dynamics study.  Mater. Res. Lett., 6, 522-530.  https://doi.org/10.1080/21663831.2018.1494637
  • Lonardoni, D., J. Carlson, S. Gandolfi, J. E. Lynn, K. E. Schmidt, A. Schwenk, and X. B. Wang, 2018:  Properties of Nuclei up to A = 16 using Local Chiral Interactions.  Phys. Rev. Lett., 120, 122502.  https://doi.org/10.1103/PhysRevLett.120.122502
  • Lovato, A., S. Gandolfi, J. Carlson, E. Lusk, S. C. Pieper, and R. Schiavilla, 2018: Quantum Monte Carlo calculation of neutral-current v-12C inclusive quasielastic scattering. Phys. Rev. C97, 022502.  https://doi.org/10.1103/PhysRevC.97.022502 
  • McDevitt, C. J., Z. Guo, and X-Z. Tang, 2017:   Relation of the runaway avalanche threshold to momentum space topology.  Plasma Phys. Control. Fusion, 60, 024004.  https://doi.org/10.1088/1361-6587/aa9b3f
  • Pastore, S., A. Baroni, J. Carlson, S. Gandolfi, S. C. Pieper, R. Schiavilla, and R. B. Wiringa, 2018:  Quantum Monte Carlo calculations of weak transitions in A = 6-10 nuclei. Phys. Rev. C97, 022501.  https://doi.org/10.1103/PhysRevC.97.022501 
  • Pastore, S., J. Carlson, V. Cirigliano, W. Dekens, E. Mereghetti, and R. B. Wiringa, 2018: Neutrinoless double-β decay matrix elements in light nuclei.  Phys. Rev. C, 97, 014606. https://doi.org/10.1103/PhysRevC.97.014606 
  • Qian, E., B. Peherstorfer, D. O'Malley, V. V. Vesselinov, and K. Wilcox, 2018: Multifidelity Monte Carlo estimation of variance and sensitivity indices. SIAM/ASA J. Uncertainty Quantification, 6, 683-706.  https://doi.org/10.1137/17M1151006
  • Stanev, V. G., F. L. Iliev, S. Hansen, V. V. Vesselinov, and B. S. Alexandrov, 2018: Identification of release sources in advection-diffusion system by machine learning combined with Green's function inverse method.  Appl. Math. Model.60, 64-76.  https://doi.org/10.1016/j.apm.2018.03.006  
  • Vesselinov, V. V., B. S. Alexandrov, and D. O'Malley, 2018: Contaminant source identification using semi-supervised machine learning.  J. Contaminant Hydrology, In press.  https://doi.org/10.1016/j.jconhyd.2017.11.002

2017

  • Bakarji, J., D. O’Malley, and V. V. Vesselinov, 2017: Agent-based socio-hydrological hybrid modeling for water resource management.  Water Resour. Res., 31, 3881-3898.  https://doi.org/10.1007/s11269-017-1713-7
  • Canik, J. M. and X-Z. Tang, 2017: Sensitivity of the boundary plasma to the plasma-material interface.  Fusion Sci. Technol., 71, 103-109.  http://dx.doi.org/10.13182/FST16-124
  • Carlson, J., S. Gandolfi, U. van Kolck, and S. A. Vitiello, 2017:  Ground-state properties of unitary bosons: From clusters to matter.  Phys. Rev.  Lettrs, 119, 223002. https://doi.org/10.1103/PhysRevLett.119.223002
  • Chacon, L., et al., (LANL authors: G. Chen, D. A. Knoll, C. Newman, H. Park, W. Taitano, G. Womeldorff) 2017:  Multiscale high-order/low-order (HOLO) algorithms and applications.  J. Comput. Phys., 330, 21-45.  https://doi.org/10.1016/j.jcp.2016.10.069
  • Guo, Z., C. J. McDevitt, and X-Z. Tang, 2017: Phase-space dynamics of runaway electrons in magnetic fields. Plasma Phys. Controlled Fusion, 59, 044003. https://doi.org/10.1088/1361-6587/aa5952
  • Hahn, E. N., T. C. Germann, R. Ravelo, J. E. Hammerberg, and M. A. Meyers, 2017: On the ultimate tensile strength of tantalum. Acta. Mater., 126, 313-328. https://doi.org/10.1016/j.actamat.2016.12.033
  • Kikinzon, E., Y. Kuznetsov, K. Lipnikov, and M. Shashkov, 2017: Approximate static condensation algorithm for solving multi-material diffusion problems on meshes non-aligned with material interfaces.  J. Comp. Phys., 347, 416-436.  https://doi.org/10.1016/j.jcp.2017.06.048
  • Klima, M., M. Kucharik, and M. Shashkov, 2017: Combined swept region and intersection-based single-material remapping method.  Int. J. Numer. Meth. Fluids, 85, 363-382.  https://doi.org/10.1002/fld.4384
  • Klima, M., M. Kucharik, and M. Shashkov, 2017: Local error analysis and comparison of the swept-and intersection-based remapping methods.  Commun. Comput. Phys., 21, 526-558.  https://doi.org/10.4208/cicp.OA-2015-0021
  • Kucharik, N. and M. Shashkov, 2017:  Bound-preserving remapping of staggered quantities for multi-material ALE methods.  AIP Conf. Proc., 1863, 030025.  https://doi.org/10.1063/1.4992178 
  • Lin, Y., E. B. Le, D. O’Malley, V. V. Vesselinov, and T. Bui-Thanh, 2017: Large-scale inverse model analyses employing fast randomized data reduction.  Water Resour. Res., 53, 6784-6081.  http://dx.doi.org/10.1002/2016WR020299
  • Liska, R. and M. Shashkov, 2017: Divergence preserving reconstruction of the nodal components of a vector field from its normal components to edges.  Int. J. Numer. Meth, Fluids, 83, 798-809.  https://doi.org/10.1002/fld.4289
  • Lynn, J. E., I. Tews, J. Carlson, S. Gandolfi, A. Gezerlis, K. E. Schmidt, and A. Schwenk, 2017:  Quantum Monte Carlo calculations of light nuclei with local chiral two- and three-nucleon interactions.  Phys. Rev. C, 96, 054007.  https://doi.org/10.1103/PhysRevC.96.054007
  • Martinez, E., B. P. Uberuaga, and B. D. Wirth, 2017: Atomistic modeling of helium segregation to grain boundaries in tungsten and its effect on de-cohesion.  Nucl. Fusion, 57, 086044.  https://doi.org/10.1088/1741-4326/aa6e15
  • Price, S. F., et al., (LANL authors:  M. J. Hoffman, W. H. Lipscomb) 2017:  An ice sheet model validation framework for the Greenland ice sheet.  Geosci. Model Dev., 10, 255-270.  https://doi.org/10.5194/gmd-10-255-2017
  • Ringler, T., J. A. Saenz, P. J. Wolfram, and L. Van Roekel, 2017: A thickness-weighted average perspective of force balance in an idealized circumpolar current. J. Phys. Oceanography, 47, 285-305. https://doi.org/10.1175/JPO-D-16-0096-1
  • Sandoval, L., D. Perez, B. P. Uberuaga, and A. F. Voter, 2017: Growth rate effects on the formation of dislocation loops around deep helium bubbles in tungsten.  Fusion Sci. Technol., 71, 1-6.  http://dx.doi.org/10.13182/FST16-116
  • Stanier, A., et al., (LANL authors: W. Daughton, A. N. Simakov, L. Chacon, A. Le) 2017:  The role of guide field in magnetic reconnection driven by island coalescence.  Phys. Plasmas, 24, 022124.  http://dx.doi.org/10.1063/1.4976712
  • Tang, X-Z. and Z. Guo, 2017: Plasma power recycling at the divertor surface.  Fusion Sci Technol., 71, 110-121.  http://dx.doi.org/10.13182/FST16-119
  • Zhang, T., S. Price, L. Ju, W. Leng, J. Brondex, G. Durand, and O. Gagliardini, 2017: A comparison of two Stokes ice sheet models applied to the Marine Ice Sheet Model Intercomparison Project for plan view models (MISMIP3d).  The Cryosphere, 11, 179-190.  https://doi.org/10.5194/tc-11-179-2017
  • Zhang, X., A. Y. Sun, I. J. Duncan, and V. V. Vesselinov, 2017: Two-stage fracturing wastewater management in shale gas development.  Ind. Eng. Chem. Res., 56, 1570-1579.  http://dx.doi.org/10.1021/acs.iecr.6b03971

 2016

  • Bauer, A. C., et al., (LANL author: J. Ahrens) 2016:  In situ methods, infrastructures, and applications on high performance computing platforms.  Comput. Graph. Forum, 35, 577-597.  https://doi.org/10.1111/cgf.12930
  • Barlow, A. J., P-H. Marie, W. J. Rider, R. N. Rieben, and M. J. Shashkov, 2016: Arbitrary Lagrangian-Eulerian methods for modeling high-speed compressible multimaterial flows.  J. Comput. Phys., 322, 603-665.  https://doi.org/10.1016/j.jcp.2016.07.001
  • Chacon, L. and G. Chen, 2016: A curvilinear, fully implicit, conservative electromagnetic PIC algorithm in multiple dimensions.  J. Comput. Phys., 316, 578-597.  https://doi.org/10.1016/j.jcp.2016.03.070
  • Chacon, L. and A. Stanier, 2016: A scalable, fully implicit algorithm for the reduced two-field low-β extended MHD model. J. Comput. Phys., 326, 763-772.  https://doi.org/10.1016/j.jcp.2016.09.007
  • Chen, Q., T. Ringler, and P. R. Gent, 2016: Extending a potential vorticity transport eddy closure to include a spatially-varying co-efficient.  Comput. Math. Appl., 71, 2206-2217.  https://doi.org/10.1016/j.camwa.2015.12.041
  • D’Elia, M., D. Ridzal, K. J. Peterson, P. Bochev, and M. Shashkov, 2016: Optimization-based mesh correction with volume and convexity constraints.   J. Comput. Phys., 313, 455-477.  https://doi.org/10.1016/j.jcp.2016.02.050
  • Gekelman, W., et al., (LANL authors: W. Daughton, T. Intrator) 2016: Pulsating magnetic reconnection driven by three- dimensional flux-rope interactions. Phys. Rev. Lett., 116, 235101.  http://dx.doi.org/10.1063/1.4976712
  • Grasinger, M., D. O’Malley, V. Vesselinov, and S. Karra, 2016: Decision analysis for robust CO2 injection:  Application of Bayesian-Information-Gap decision theory.  Int. J. Greenh. Gas Con., 49, 73-80.  https://doi.org/10.1016/j.ijggc.2016.02.017
  • Hahn, E. N., J. Fensin, T. C. Germann, and M. A. Meyers, 2016: Symmetric tilt boundaries in body-centered cubic tantalum.  Scr. Mater., 116, 108-111.  https://doi.org/10.1016/j.scriptamat.2016.01.038
  • Lin, Y., D. O’Malley, and V. Vesselinov, 2016: A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses.  Water Resour. Res., 52, 6948-6977.  http://dx.doi.org/10.1002/2016WR019028
  • Lipnikov, K., D. Moulton, and D. Svyatskiy, 2016: New preconditioning strategy for Jacobian-free solvers for variably saturated flows with Richards’ equation.  Water Res., 94, 11-22.  https://doi.org/10.1016/j.advwatres.2016.04.016
  • Lipnikov, K., G. Manzini, J. D. Moulton, and M. Shashkov, 2016: The mimetic finite difference method for elliptic and parabolic problems with a staggered discretization of diffusion coefficient.  J. Comp. Phys., 305, 111-126.  https://doi.org/10.1016/j.jcp.2015.10.031
  • Lynn, J. E., I. Tews, J. Carlson, S. Gandolfi, A. Gezerlis, K. E. Schmidt, and A. Schwenk, 2016: Chiral three-nucleon interactions in the light nuclei, neutron-α scattering, and neutron matter.  Phys. Rev. Lett. 116, 062501.  http://dx.doi.org/10.1103/PhysRevLett.116.062501   
  • Moreland, K., et al., (LANL authors: C. Sewell, L-T. Lo) 2016:  VTK-m: Accelerating the visualization toolkit for massively threaded architectures.  IEEE Computer Graphics and Applications, 36, 48-58.  https://doi.org/10.1109/MCG.2016.48
  • O’Leary, P., J. Ahrens, S. Jourdain, S. Wittenburg, D. H. Rodgers, and M. Peterson, 2016: Cinema image-based in situ analysis and visualization of MPAS-ocean simulations.  Parallel Comput., 55, 43-48.  https://doi.org/10.1016/j.parco.2015.10.005
  • Tang, X-Z. and Z. Guo, 2016: Critical role of electron heat flux on Bohm criterion.  Phys. Plasmas, 23, 120701.  http://dx.doi.org/10.1063/1.4971808
  • Tang, X-Z. and Z. Guo, 2016: Kinetic model for the collisionless sheath of a collisional plasma.  Phys. Plasmas, 23, 083503.  http://dx.doi.org/10.1063/1.4960321