987 resultados para Energy constraints


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Aims. We calculate the theoretical event rate of gamma-ray bursts (GRBs) from the collapse of massive first-generation (Population III; Pop III) stars. The Pop III GRBs could be super-energetic with the isotropic energy up to E(iso) greater than or similar to 10(55-57) erg, providing a unique probe of the high-redshift Universe. Methods. We consider both the so-called Pop III.1 stars (primordial) and Pop III.2 stars (primordial but affected by radiation from other stars). We employ a semi-analytical approach that considers inhomogeneous hydrogen reionization and chemical evolution of the intergalactic medium. Results. We show that Pop III.2 GRBs occur more than 100 times more frequently than Pop III.1 GRBs, and thus should be suitable targets for future GRB missions. Interestingly, our optimistic model predicts an event rate that is already constrained by the current radio transient searches. We expect similar to 10-10(4) radio afterglows above similar to 0.3 mJy on the sky with similar to 1 year variability and mostly without GRBs (orphans), which are detectable by ALMA, EVLA, LOFAR, and SKA, while we expect to observe maximum of N < 20 GRBs per year integrated over at z > 6 for Pop III.2 and N < 0.08 per year integrated over at z > 10 for Pop III.1 with EXIST, and N < 0.2 for Pop III.2 GRBs per year integrated over at z > 6 with Swift.

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The kinematic approach to cosmological tests provides direct evidence to the present accelerating stage of the Universe that does not depend on the validity of general relativity, as well as on the matter-energy content of the Universe. In this context, we consider here a linear two-parameter expansion for the decelerating parameter, q(z)=q(0)+q(1)z, where q(0) and q(1) are arbitrary constants to be constrained by the union supernovae data. By assuming a flat Universe we find that the best fit to the pair of free parameters is (q(0),q(1))=(-0.73,1.5) whereas the transition redshift is z(t)=0.49(-0.07)(+0.14)(1 sigma) +0.54-0.12(2 sigma). This kinematic result is in agreement with some independent analyses and more easily accommodates many dynamical flat models (like Lambda CDM).

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We analyze the interaction between dark energy and dark matter from a thermodynamical perspective. By assuming they have different temperatures, we study the possibility of occurring a decay from dark matter into dark energy, characterized by a negative parameter Q. We find that, if at least one of the fluids has nonvanishing chemical potential, for instance mu(x)< 0 and mu(dm)=0 or mu(x)=0 and mu(dm)> 0, the decay is possible, where mu(x) and mu(dm) are the chemical potentials of dark energy and dark matter, respectively. Using recent cosmological data, we find that, for a fairly simple interaction, the dark matter decay is favored with a probability of similar to 93% over the dark energy decay. This result comes from a likelihood analysis where only background evolution has been considered.

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For Au + Au collisions at 200 GeV, we measure neutral pion production with good statistics for transverse momentum, p(T), up to 20 GeV/c. A fivefold suppression is found, which is essentially constant for 5 < p(T) < 20 GeV/c. Experimental uncertainties are small enough to constrain any model-dependent parametrization for the transport coefficient of the medium, e. g., <(q) over cap > in the parton quenching model. The spectral shape is similar for all collision classes, and the suppression does not saturate in Au + Au collisions.

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The PHENIX experiment has measured the suppression of semi-inclusive single high-transverse-momentum pi(0)'s in Au+Au collisions at root s(NN) = 200 GeV. The present understanding of this suppression is in terms of energy loss of the parent (fragmenting) parton in a dense color-charge medium. We have performed a quantitative comparison between various parton energy-loss models and our experimental data. The statistical point-to-point uncorrelated as well as correlated systematic uncertainties are taken into account in the comparison. We detail this methodology and the resulting constraint on the model parameters, such as the initial color-charge density dN(g)/dy, the medium transport coefficient <(q) over cap >, or the initial energy-loss parameter epsilon(0). We find that high-transverse-momentum pi(0) suppression in Au+Au collisions has sufficient precision to constrain these model-dependent parameters at the +/- 20-25% (one standard deviation) level. These constraints include only the experimental uncertainties, and further studies are needed to compute the corresponding theoretical uncertainties.

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We investigate the effect of an interaction between dark energy and dark matter upon the dynamics of galaxy clusters. This effect is computed through the Layser-Irvine equation, which describes how an astrophysical system reaches virial equilibrium and was modified to include the dark interactions. Using observational data from almost 100 purportedly relaxed galaxy clusters we put constraints on the strength of the couplings in the dark sector. We compare our results with those from other observations and find that a positive (in the sense of energy flow from dark energy to dark matter) nonvanishing interaction is consistent with the data within several standard deviations.

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We propose a field theory model for dark energy and dark matter in interaction. Comparing the classical solutions of the field equations with the observations of the CMB shift parameter, baryonic acoustic oscillations, lookback time, and the Gold supernovae sample, we observe a possible interaction between dark sectors with energy decay from dark energy into dark matter. The observed interaction provides an alleviation to the coincidence problem.

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Cosmological analyses based on currently available observations are unable to rule out a sizeable coupling between dark energy and dark matter. However, the signature of the coupling is not easy to grasp, since the coupling is degenerate with other cosmological parameters, such as the dark energy equation of state and the dark matter abundance. We discuss possible ways to break such degeneracy. Based on the perturbation formalism, we carry out the global fitting by using the latest observational data and get a tight constraint on the interaction between dark sectors. We find that the appropriate interaction can alleviate the coincidence problem.

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Evidence suggests that women who are mothers of young children have lower levels of physical activity than women of similar age who do not have children (Brown, Lee, Mishra, & Bauman, 2000). The purposes of this study were to explore the factors that constrain mothers of young children from being more physically active, and the relationship between physical activity and levels of social support available to the women. The empirical basis for this examination was provided through a study of activity levels and barriers to physical activity experienced by a sample of 543 mothers of young children from differing socioeconomic backgrounds. The data indicate that: (a) more than two-thirds of the mothers were inadequately active in their leisure time for health benefit; (b) while the vast majority of mothers expressed a desire to be more active, they were inhibited in their ability to act out their leisure preferences by a combination of structural (e.g., lack of time, money, energy) and ideological influences (e.g., sense of commitment to others); (c) access to social support (from partners, family, and friends) was seen to place some women in a better position than others to negotiate constraints that inhibit leisure participation; and (d) within groups of varying socioeconomic status (SES) there was wide variation in the amount of time spent each week in active leisure.

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This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

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The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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In this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

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Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

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This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

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This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.