Symplectic algorithm for constant-pressure molecular dynamics using a Nose-Poincare thermostat

We present a new algorithm for isothermal-isobaric molecular-dynamics simulation. The method uses an extended Hamiltonian with an Andersen piston combined with the Nos'e-Poincar'e thermostat, recently developed by Bond, Leimkuhler and Laird [J. Comp. Phys., 151, (1999)]. This Nos'e-Poincar'e-Andersen (NPA) formulation has advantages over the Nos'e-Hoover-Andersen approach in that the NPA is Hamiltonian and can take advantage of symplectic integration schemes, which lead to enhanced stability for long-time simulations. The equations of motion are integrated using a Generalized Leapfrog Algorithm and the method is easy to implement, symplectic, explicit and time reversible. To demonstrate the stability of the method we show results for test simulations using a model for aluminum.Comment: 7 page

Adjusting the melting point of a model system via Gibbs-Duhem integration: application to a model of Aluminum

Model interaction potentials for real materials are generally optimized with respect to only those experimental properties that are easily evaluated as mechanical averages (e.g., elastic constants (at T=0 K), static lattice energies and liquid structure). For such potentials, agreement with experiment for the non-mechanical properties, such as the melting point, is not guaranteed and such values can deviate significantly from experiment. We present a method for re-parameterizing any model interaction potential of a real material to adjust its melting temperature to a value that is closer to its experimental melting temperature. This is done without significantly affecting the mechanical properties for which the potential was modeled. This method is an application of Gibbs-Duhem integration [D. Kofke, Mol. Phys.78, 1331 (1993)]. As a test we apply the method to an embedded atom model of aluminum [J. Mei and J.W. Davenport, Phys. Rev. B 46, 21 (1992)] for which the melting temperature for the thermodynamic limit is 826.4 +/- 1.3K - somewhat below the experimental value of 933K. After re-parameterization, the melting temperature of the modified potential is found to be 931.5K +/- 1.5K.Comment: 9 pages, 5 figures, 4 table

Interlaboratory study for coral Sr/Ca and other element/Ca ratio measurements

The Sr/Ca ratio of coral aragonite is used to reconstruct past sea surface temperature (SST). Twentyone laboratories took part in an interlaboratory study of coral Sr/Ca measurements. Results show interlaboratory bias can be significant, and in the extreme case could result in a range in SST estimates of 7°C. However, most of the data fall within a narrower range and the Porites coral reference material JCp- 1 is now characterized well enough to have a certified Sr/Ca value of 8.838 mmol/mol with an expanded uncertainty of 0.089 mmol/mol following International Association of Geoanalysts (IAG) guidelines. This uncertainty, at the 95% confidence level, equates to 1.5°C for SST estimates using Porites, so is approaching fitness for purpose. The comparable median within laboratory error is <0.5°C. This difference in uncertainties illustrates the interlaboratory bias component that should be reduced through the use of reference materials like the JCp-1. There are many potential sources contributing to biases in comparative methods but traces of Sr in Ca standards and uncertainties in reference solution composition can account for half of the combined uncertainty. Consensus values that fulfil the requirements to be certified values were also obtained for Mg/Ca in JCp-1 and for Sr/Ca and Mg/Ca ratios in the JCt-1 giant clam reference material. Reference values with variable fitness for purpose have also been obtained for Li/Ca, B/Ca, Ba/Ca, and U/Ca in both reference materials. In future, studies reporting coral element/Ca data should also report the average value obtained for a reference material such as the JCp-1

BB: Symplectic algorithm for constant-pressure molecular dynamics using a Nose-Poincare thermostate

We present a new algorithm for isothermal-isobaric molecular-dynamics simulation. The method uses an extended Hamiltonian with an Andersen piston combined with the Nosé-Poincaré thermostat, recently developed by Bond, Leimkuhler and Laird [J. Comp. Phys., 151, xxxx (1999)]. This Nosé-Poincaré-Andersen (NPA) formulation has advantages over the Nosé-Hoover-Andersen approach in that the NPA is Hamiltonian and can take advantage of symplectic integration schemes, which lead to enhanced stability for long-time simulations. The equations of motion are integrated using a Generalized Leapfrog Algorithm and the method is easy to implement, symplectic, explicit and time reversible. To demonstrate the stability of the method we show results for test simulations using a model for aluminum.

The Computational Fluid Dynamics Rupture Challenge 2013—Phase II: variability of hemodynamic simulations in two intracranial aneurysms

With the increased availability of computational resources, the past decade has seen a rise in the use of computational fluid dynamics (CFD) for medical applications. There has been an increase in the application of CFD to attempt to predict the rupture of intracranial aneurysms, however, while many hemodynamic parameters can be obtained from these computations, to date, no consistent methodology for the prediction of the rupture has been identified. One particular challenge to CFD is that many factors contribute to its accuracy; the mesh resolution and spatial/temporal discretization can alone contribute to a variation in accuracy. This failure to identify the importance of these factors and identify a methodology for the prediction of ruptures has limited the acceptance of CFD among physicians for rupture prediction. The International CFD Rupture Challenge 2013 seeks to comment on the sensitivity of these various CFD assumptions to predict the rupture by undertaking a comparison of the rupture and blood-flow predictions from a wide range of independent participants utilizing a range of CFD approaches. Twenty-six groups from 15 countries took part in the challenge. Participants were provided with surface models of two intracranial aneurysms and asked to carry out the corresponding hemodynamics simulations, free to choose their own mesh, solver, and temporal discretization. They were requested to submit velocity and pressure predictions along the centerline and on specified planes. The first phase of the challenge, described in a separate paper, was aimed at predicting which of the two aneurysms had previously ruptured and where the rupture site was located. The second phase, described in this paper, aims to assess the variability of the solutions and the sensitivity to the modeling assumptions. Participants were free to choose boundary conditions in the first phase, whereas they were prescribed in the second phase but all other CFD modeling parameters were not prescribed. In order to compare the computational results of one representative group with experimental results, steady-flow measurements using particle image velocimetry (PIV) were carried out in a silicone model of one of the provided aneurysms. Approximately 80% of the participating groups generated similar results. Both velocity and pressure computations were in good agreement with each other for cycle-averaged and peaksystolic predictions. Most apparent "outliers" (results that stand out of the collective) were observed to have underestimated velocity levels compared to the majority of solutions, but nevertheless identified comparable flow structures. In only two cases, the results deviate by over 35% from the mean solution of all the participants. Results of steady CFD simulations of the representative group and PIV experiments were in good agreement. The study demonstrated that while a range of numerical schemes, mesh resolution, and solvers was used, similar flow predictions were observed in the majority of cases. To further validate the computational results, it is suggested that time-dependent measurements should be conducted in the future. However, it is recognized that this study does not include the biological aspects of the aneurysm, which needs to be considered to be able to more precisely identify the specific rupture risk of an intracranial aneurysm