An in-medium full-folding model approach to quasielastic (p,n) charge-exchange reactions

A microscopic description of the quasielastic (p,n) charge-exchange reaction (here, charge-exchange scattering between analogue states) is presented and discussed. Emphasis is focused on the spin-isospin structure of the projectile-target coupling. The model is a coupled-channel extension of the full-folding optical model approach (OMP) developed for nucleon elastic scattering, where emphasis is placed on retaining the genuine off-shell behavior of realistic effective interactions in the nuclear medium. The resulting non-local optical potentials are applied to the calculation of (p,n) differential cross sections, with particular emphasis on small-angle Fermi ($\Delta S=0$) cross-sections to isobaric analog states. These parameter-free results provide a reasonable description of the $^{14}$C(p,n)-data at proton energies above $\sim$100 MeV, but deteriorate for heavier targets. These shortcomings are analyzed and possible ways to correct them are discussed.Comment: 20 pages plus 10 figures. Accepted for publication in Phys. Rev.

Nuclear halo structure from quasielastic charge-exchange reactions

Neutron and proton densities in the nuclear periphery are investigated within (p,n) charge-exchange isobar transitions. For this purpose we have developed parameter-free optical potentials with a detailed treatment of the in-medium $t_{\tau}$ part of the effective interaction. Non local coupled-channel Lane equations are solved to obtain the scattering observables. The use of conventional proton and neutron densities significantly underestimates Fermi (forward-angle) cross-sections in agreement with findings by various other groups. However, we have found model-independent densities which provide a remarkable improvement in the description of the quasielastic scattering data.The densities obtained are consistent with recent measurements at CERN in studies of the neutron-to-proton halo factor f(r)=Z$\rho_n/N\rho_p$ with antiprotons. These findings provide an alternative way to investigate the nuclear periphery, and may also help to solve the long-standing puzzle of the underestimated Fermi cross section in (p,n) charge-exchange phenomena.Comment: 5 pages and 2 figs. Presented at the Baryons-04 Conference (Palaiseau, France, Oct 2004). To appear in Nucl. Phys.

Credit Frictions and 'Sudden Stops' in Small Open Economies: An Equilibrium Business Cycle Framework for Emerging Markets Crises

Financial frictions are a central element of most of the models that the literature on emerging markets crises has proposed for explaining the Sudden Stop' phenomenon. To date, few studies have aimed to examine the quantitative implications of these models and to integrate them with an equilibrium business cycle framework for emerging economies. This paper surveys these studies viewing them as ability-to-pay and willingness-to-pay variations of a framework that adds occasionally binding borrowing constraints to the small open economy real-business-cycle model. A common feature of the different models is that agents factor in the risk of future Sudden Stops in their optimal plans, so that equilibrium allocations and prices are distorted even when credit constraints do not bind. Sudden Stops are a property of the unique, flexible-price competitive equilibrium of these models that occurs in a particular region of the state space in which negative shocks make borrowing constraints bind. The resulting nonlinear effects imply that solving the models requires non-linear numerical methods, which are described in the survey. The results show that the models can yield relatively infrequent Sudden Stops with large current account reversals and deep recessions nested within smoother business cycles. Still, research in this area is at an early stage and this survey aims to stimulate further work.

Prediction of jet engine parameters for control design using genetic programming

The simulation of a jet engine behavior is widely used in many different aspects of the engine development and maintenance. Achieving high quality jet engine control systems requires the iterative use of these simulations to virtually test the performance of the engine avoiding any possible damage on the real engine. Jet engine simulations involve the use of mathematical models which are complex and may not always be available. This paper introduces an approach based on Genetic Programming (GP) to model different parameters of a small engine for control design such as the Exhaust Gas Temperature (EGT). The GP approach has no knowledge of the characteristics of the engine. Instead, the model is found by the evolution of models based on past measurements of parameters such as the pump voltage. Once the model is obtained, it is used to predict the behaviour of the jet engine one step ahead. The proposed approach is successfully applied for the simulation of a Behotec j66 jet engine and the results are presented

Surface and boundary layer exchanges of volatile organic compounds, nitrogen oxides and ozone during the GABRIEL campaign

We present an evaluation of sources, sinks and turbulent transport of nitrogen oxides, ozone and volatile organic compounds (VOC) in the boundary layer over French Guyana and Suriname during the October 2005 GABRIEL campaign by simulating observations with a single-column chemistry and climate model (SCM) along a zonal transect. Simulated concentrations of O3 and NO as well as NO2 photolysis rates over the forest agree well with observations when a small soil-biogenic NO emission flux was applied. This suggests that the photochemical conditions observed during GABRIEL reflect a pristine tropical low-NOx regime. The SCM uses a compensation point approach to simulate nocturnal deposition and daytime emissions of acetone and methanol and produces daytime boundary layer mixing ratios in reasonable agreement with observations. The area average isoprene emission flux, inferred from the observed isoprene mixing ratios and boundary layer height, is about half the flux simulated with commonly applied emission algorithms. The SCM nevertheless simulates too high isoprene mixing ratios, whereas hydroxyl concentrations are strongly underestimated compared to observations, which can at least partly explain the discrepancy. Furthermore, the model substantially overestimates the isoprene oxidation products methlyl vinyl ketone (MVK) and methacrolein (MACR) partly due to a simulated nocturnal increase due to isoprene oxidation. This increase is most prominent in the residual layer whereas in the nocturnal inversion layer we simulate a decrease in MVK and MACR mixing ratios, assuming efficient removal of MVK and MACR. Entrainment of residual layer air masses, which are enhanced in MVK and MACR and other isoprene oxidation products, into the growing boundary layer poses an additional sink for OH which is thus not available for isoprene oxidation. Based on these findings, we suggest pursuing measurements of the tropical residual layer chemistry with a focus on the nocturnal depletion of isoprene and its oxidation products

Forecasting wind power for the day-ahead market using numerical weather prediction models and computational intelligence techniques

Wind power forecasting is essential for the integration of large amounts of wind power into the electric grid, especially during large rapid changes of wind generation. These changes, known as ramp events, may cause instability in the power grid. Therefore, detailed information of future ramp events could potentially improve the backup allocation process during the Day Ahead (DA) market (12 to 36 hours before the actual operation), allowing the reduction of resources needed, costs and environmental impact. It is well established in the literature that meteorological models are necessary when forecasting more than six hours into the future. Most state-of-the-art forecasting tools use a combination of Numerical Weather Prediction (NWP) forecasts and observations to estimate the power output of a single wind turbine or a whole wind farm. Although NWP systems can model meteorological processes that are related to large changes in wind power, these might be misplaced i.e. in the wrong physical position. A standard way to quantify such errors is by the use of NWP ensembles. However, these are computationally expensive. Here, an alternative is to use spatial fields, which are used to explore different numerical grid points to quantify variability. This strategy can achieve comparable results to typical numerical ensembles, which makes it a potential candidate for ramp characterisation

Skewed Factor Models Using Selection Mechanisms

Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-t, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset

Flux estimates of isoprene, methanol and acetone from airborne PTR-MS measurements over the tropical rainforest during the GABRIEL 2005 campaign

Tropical forests are a strong source of biogenic volatile organic compounds (BVOCs) to the atmosphere which can potentially impact the atmospheric oxidation capacity. Here we present airborne and ground-based BVOC measurements representative for the long dry season covering a large area of the northern Amazonian rainforest (6-3° N, 50-59° W). The measurements were conducted during the October 2005 GABRIEL (Guyanas Atmosphere-Biosphere exchange and Radicals Intensive Experiment with the Learjet) campaign. The vertical (35 m to 10 km) and diurnal (09:00-16:00) profiles of isoprene, its oxidation products methacrolein and methyl vinyl ketone and methanol and acetone, measured by PTR-MS (Proton Transfer Reaction Mass Spectrometry), have been used to empirically estimate their emission fluxes from the forest canopy on a regional scale. The mixed layer isoprene emission flux, inferred from the airborne measurements above 300 m, is 5.7 mg isoprene m-2 h-1 after compensating for chemistry and ~6.9 mg isoprene m-2 h-1 taking detrainment into account. This surface flux is in general agreement with previous tropical forest studies. Inferred methanol and acetone emission fluxes are 0.5 mg methanol m¿2 h¿1 and 0.35 mg acetone m-2 h-1, respectively. The BVOC measurements were compared with fluxes and mixing ratios simulated with a single-column chemistry and climate model (SCM). The inferred isoprene flux is substantially smaller than that simulated with an implementation of a commonly applied BVOC emission algorithm in the SCM

Sensitivity of nucleon-nucleus scattering to the off-shell behavior of on-shell equivalent NN potentials

The sensitivity of nucleon-nucleus elastic scattering to the off-shell behavior of realistic nucleon-nucleon interactions is investigated when on-shell equivalent nucleon-nucleon potentials are used. The study is based on applications of the full-folding optical model potential for an explicit treatment of the off-shell behavior of the nucleon-nucleon effective interaction. Applications were made at beam energies between 40 and 500 MeV for proton scattering from 40Ca and 208Pb. We use the momentum-dependent Paris potential and its local on-shell equivalent as obtained with the Gelfand-Levitan and Marchenko inversion formalism for the two nucleon Schroedinger equation. Full-folding calculations for nucleon-nucleus scattering show small fluctuations in the corresponding observables. This implies that off-shell features of the NN interaction cannot be unambiguously identified with these processes. Inversion potentials were also constructed directly from NN phase-shift data (SM94) in the 0-1.3 GeV energy range. Their use in proton-nucleus scattering above 200 MeV provide a superior description of the observables relative to those obtained from current realistic NN potentials. Limitations and scope of our findings are presented and discussed.Comment: 17 pages tightened REVTeX, 8 .ps figures, submitted to Phys. Rev.