Energy levels, wavefunction compositions and electric dipole transitions in neutral Ca

A configuration-interaction approach, based on the use of B-spline basis sets combined with a model potential including monoelectronic and dielectronic core polarization effects, is employed to calculate term energies and wavefunctions for neutral Ca. Results are reported for singlet and triplet bound states, and some quasi-bound states above the lowest ionization limit, with angular momentum up to L = 4. Comparison with experiment and with other theoretical results shows that this method yields the most accurate energy values for neutral Ca obtained to date. Wavefunction compositions, necessary for labelling the levels, and the effects of semi-empirical polarization potentials on the wavefunctions are discussed, as are some recent identifications of doubly-excited states. It is shown that taking into account dielectronic core polarization changes the energies of the lowest terms in Ca significantly, in general by a few hundred cm(-1), the effect decreasing rapidly for the higher bound states. For Rydberg states with n approximate to 7 the accuracy of the results is often better than a few cm(-1). For series members (or perturbers) with a pronounced 3d character the error can reach 150 cm(-1). The wavefunctions are used to calculate oscillator strengths and lifetimes for a number of terms and these are compared with existing measurements. The agreement is good but points to a need for improved measurements.

Determining the regional potential for a grass biomethane industry

Grass biogas/biomethane has been put forward as a renewable energy solution and it has been shown to perform well in terms of energy balance, greenhouse gas emissions and policy constraints. Biofuel and energy crop solutions are country-specific and grass biomethane has strong potential in countries with temperate climates and a high proportion of grassland, such as Ireland. For a grass biomethane industry to develop in a country, suitable regions (i.e. those with the highest potential) must be identified. In this paper, factors specifically related to the assessment of the potential of a grass biogas/biomethane industry are identified and analysed. The potential for grass biogas and grass biomethane is determined on a county-by-county basis using multi-criteria decision analysis. Values are assigned to each county and ratings and weightings applied to determine the overall county potential. The potential for grass biomethane with co-digestion of slaughter waste (belly grass) is also determined. The county with the highest potential (Limerick) is analysed in detail and is shown to have ready potential for production of gaseous biofuel to meet either 50% of the vehicle fleet or 130% of the domestic natural gas demand, through 25 facilities at a scale of ca. 30ktyr of feedstock. The assessment factors developed in this paper can be used in other resource studies into grass biomethane or other energy crops. © 2010 Elsevier Ltd.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

Surface energy and surface proton order of the ice Ih basal and prism surfaces

Density-functional theory (DFT) is used to examine the basal and prism surfaces of ice Ih. Similar surface energies are obtained for the two surfaces; however, in each case a strong dependence of the surface energy on surface proton order is identified. This dependence, which can be as much as 50% of the absolute surface energy, is significantly larger than the bulk dependence (< 1%) on proton order, suggesting that the thermodynamic ground state of the ice surface will remain proton ordered well above the bulk order-disorder temperature of about 72 K. On the basal surface this suggestion is supported by Monte Carlo simulations with an empirical potential and solution of a 2D Ising model with nearest neighbor interactions taken from DFT. Order parameters that define the surface energy of each surface in terms of nearest neighbor interactions between dangling OH bonds (those which point out of the surface into vacuum) have been identified and are discussed. Overall, these results suggest that proton order-disorder effects have a profound impact on the stability of ice surfaces and will most likely have an effect on ice surface reactivity as well as ice crystal growth and morphology. S Supplementary data are available from stacks.iop.org/JPhysCM/22/074209/mmedia