Type Ia supernova bolometric light curves and ejected mass estimates from the nearby supernova factory

We present a sample of normal Type Ia supernovae (SNe Ia) from the Nearby Supernova Factory data set with spectrophotometry at sufficiently late phases to estimate the ejected mass using the bolometric light curve.Wemeasure Ni masses from the peak bolometric luminosity, then compare the luminosity in the Co-decay tail to the expected rate of radioactive energy release from ejecta of a given mass. We infer the ejected mass in a Bayesian context using a semi-analytic model of the ejecta, incorporating constraints from contemporary numerical models as priors on the density structure and distribution of Ni throughout the ejecta. We find a strong correlation between ejected mass and light-curve decline rate, and consequently Ni mass, with ejected masses in our data ranging from 0.9 to 1.4 M. Most fast-declining (SALT2 x <-1) normal SNe Ia have significantly sub-Chandrasekhar ejected masses in our fiducial analysis.

Synthetic light curves and spectra for three-dimensional delayed-detonation models of type ia supernovae

In a companion paper, Seitenzahl et al. have presented a set of three-dimensional delayed detonation models for thermonuclear explosions of near-Chandrasekhar-mass white dwarfs (WDs). Here,we present multidimensional radiative transfer simulations that provide synthetic light curves and spectra for those models. The model sequence explores both changes in the strength of the deflagration phase (which is controlled by the ignition configuration in our models) and the WD central density. In agreement with previous studies, we find that the strength of the deflagration significantly affects the explosion and the observables. Variations in the central density also have an influence on both brightness and colour, but overall it is a secondary parameter in our set of models. In many respects, the models yield a good match to the observed properties of normal Type Ia supernovae (SNe Ia): peak brightness, rise/decline time-scales and synthetic spectra are all in reasonable agreement. There are, however, several differences. In particular, the models are systematically too red around maximum light, manifest spectral line velocities that are a little too high and yield I-band light curves that do not match observations. Although some of these discrepancies may simply relate to approximations made in the modelling, some pose real challenges to the models. If viewed as a complete sequence, our models do not reproduce the observed light-curve width- luminosity relation (WLR) of SNe Ia: all our models show rather similar B-band decline rates, irrespective of peak brightness. This suggests that simple variations in the strength of the deflagration phase in Chandrasekhar-mass deflagration-to-detonation models do not readily explain the observed diversity of normal SNe Ia. This may imply that some other parameter within the Chandrasekhar-mass paradigm is key to the WLR, or that a substantial fraction of normal SNe Ia arise from an alternative explosion scenario.

A smart load appliance application using a single compressor fridge-freezer to support grid operations

This paper describes a fridge-freezer smart load model, which responds to external signals from the wholesale electricity market to support grid operations while switching the fridge-freezer on and off to maintain optimum operations for the owner. The key parameters of the model are the appliance dimensions, thermal mass, the fridge and freezer thermal time constants and the compressor power consumption. The model demonstrates that control strategies help to minimise load at times when the grid is under stress from high demand, and shift some load to a lower wholesale price or when there is excess renewable power. Three control strategies are proposed, based on peak shaving and valley filling, price signals and wind availability.

Assessment of Domestic Load Suitable for Smart Consumer Load Participation

This study characterizes the domestic loads suitable to participate in the load participation scheme to make the power system more carbon and economically efficient by shifting the electricity demand profile towards periods when there is plentiful renewable in-feed.

A series of experiments have been performed on a common fridge-freezer, both completely empty and half full. The results presented are ambient temperature, temperature inside the fridge, temperature inside the drawer of the fridge, temperature inside the freezer, thermal time constants, power consumption and electric energy consumed.

The thermal time constants obtained clearly demonstrate the potential of such refrigeration load for Smart Customer Load Participation.

Toward Characterization Of The Type IIP Supernova Progenitor Population: A Statistical Sample Of Light Curves From Pan-STARRS1

In recent years, wide-field sky surveys providing deep multi-band imaging have presented a new path for indirectly characterizing the progenitor populations of core-collapse supernovae (SN): systematic light curve studies. We assemble a set of 76 grizy-band Type IIP SN light curves from Pan-STARRS1, obtained over a constant survey program of 4 years and classified using both spectroscopy and machine learning-based photometric techniques. We develop and apply a new Bayesian model for the full multi-band evolution of each light curve in the sample. We find no evidence of a sub-population of fast-declining explosions (historically referred to as "Type IIL" SNe). However, we identify a highly significant relation between the plateau phase decay rate and peak luminosity among our SNe IIP. These results argue in favor of a single parameter, likely determined by initial stellar mass, predominantly controlling the explosions of red supergiants. This relation could also be applied for supernova cosmology, offering a standardizable candle good to an intrinsic scatter of 0.2 mag. We compare each light curve to physical models from hydrodynamic simulations to estimate progenitor initial masses and other properties of the Pan-STARRS1 Type IIP SN sample. We show that correction of systematic discrepancies between modeled and observed SN IIP light curve properties and an expanded grid of progenitor properties, are needed to enable robust progenitor inferences from multi-band light curve samples of this kind. This work will serve as a pathfinder for photometric studies of core-collapse SNe to be conducted through future wide field transient searches.

Domestic fridge-freezer load aggregation to support ancillary services

Grid operators and electricity retailers in Ireland manage peak demand, power system balancing and grid congestion by offering relevant incentives to consumers to reduce or shift their load. The need for active consumers in the home using smart appliances has never been greater, due to increased variable renewable generation and grid constraints. In this paper an aggregated model of a single compressor fridge-freezer population is developed. A price control strategy is examined to quantify and value demand response savings during a representative winter and summer week for Ireland in 2020. The results show an average reduction in fridge-freezer operating cost of 8.2% during winter and significantly lower during summer in Ireland. A peak reduction of at least 68% of the average winter refrigeration load is achieved consistently during the week analysed using a staggering control mode. An analysis of the current ancillary service payments confirms that these are insufficient to ensure widespread uptake by the small consumer, and new mechanisms need to be developed to make becoming an active consumer attractive. Demand response is proposed as a new ancillary service called ramping capability, as the need for this service will increase with more renewable energy penetration on the power system.

Electric vehicles and opportunities to displace tailgate emissions using Smart Charging controls

Under the European Union Renewable Energy Directive each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. This paper investigates the impact of the 10% electric vehicle target in Ireland in 2020 using a dynamic programming based long term generation expansion planning model. The model developed optimizes power dispatch using hourly electricity demand curves up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. Two distinct scenarios are analysed based on a peak and off-peak charging regimes in order to simulate the effects of the electric vehicles charging in 2020. The importance and influence of the charging regimes on the amount of energy used and tailgate emissions displaced is then determined.

Electric vehicle capacity forecasting model with application to load levelling

There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.

Finite element modelling of composite structures under crushing load

This paper details the theory and implementation of a composite damage model, addressing damage within a ply (intralaminar) and delamination (interlaminar), for the simulation of crushing of laminated composite structures. It includes a more accurate determination of the characteristic length to achieve mesh objectivity in capturing intralaminar damage consisting of matrix cracking and fibre failure, a load-history dependent material response, an isotropic hardening nonlinear matrix response, as well as a more physically-based interactive matrix-dominated damage mechanism. The developed damage model requires a set of material parameters obtained from a combination of standard and non-standard material characterisation tests. The fidelity of the model mitigates the need to manipulate, or "calibrate", the input data to achieve good agreement with experimental results. The intralaminar damage model was implemented as a VUMAT subroutine, and used in conjunction with an existing interlaminar damage model, in Abaqus/Explicit. This approach was validated through the simulation of the crushing of a cross-ply composite tube with a tulip-shaped trigger, loaded in uniaxial compression. Despite the complexity of the chosen geometry, excellent correlation was achieved with experimental results.

Refinements to the IntCal09 and Marine09 radiocarbon calibration curves

Radiocarbon dating forms the basis for many Late Quaternary chronologies but, due to the fluctuations in atmospheric levels of 14C, radiocarbon dates require calibration before they can be compared and/or combined with date estimates derived from other dating techniques. New and recently published 14C measurements on independently dated material, such as speleothems, foraminifera, coral and tree-rings, allow the IntCal Working Group to make new estimates of the radiocarbon calibration curves and provide the opportunity to evaluate the offsets observed between records. In addition floating tree-ring 14C chronologies, which are not absolutely dendro-dated, provide evidence for the magnitude of atmospheric 14C variations in different time periods which can be used to refine the calibration curves.