83,411 research outputs found
O&M Models for Ocean Energy Converters: Calibrating through Real Sea Data
Of the cost centres that combine to result in Levelised Cost of Energy (LCOE), O&M costs play a significant part. Several developers have calculated component costs, demonstrating how they can become commercially competitive with other forms of renewable energy. However, there are uncertainties relating to the O&M figures that can only be reduced through lessons learned at sea. This work presents an O&M model calibrated with data from real sea experience of a wave energy device deployed at the Biscay Marine energy Platform (BiMEP): the OPERA O&M Model. Two additional case studies, utilising two other O&M calculation methodologies, are presented for comparison with the OPERA O&M Model. The second case study assumes the inexistence of an O&M model, utilising a Simplified Approach. The third case study applies DTOcean’s (a design tool for ocean energy arrays) O&M module. The results illustrate the potential advantages of utilising real sea data for the calibration and development of an O&M model. The Simplified Approach was observed to overestimate LCOE when compared to the OPERA O&M Model. This work also shows that O&M models can be used for the definition of optimal maintenance plans to assist with OPEX reduction.The authors are grateful to the European commission for funding the OPERA and EnFAIT projects as part of the Horizon 2020 framework. The authors also thankful to Oceantec-Idom for providing feedback to OPERA model’s inputs. A special thanks to Shona Pennock and Donald Noble for their diligent proofreading of this paper
Predicting reference points and associated uncertainty from life histories for risk and status assessment
To assess status of fish populations and the risks of overexploitation, management bodies compare fishing mortality rates and abundance estimates with reference points (RP). Generic, “data-poor” methods for estimating RP are garnering attention because they are faster and cheaper to implement than those based on extensive life history data. Yet data-poor RP are subject to many unquantified uncertainties. Here, we predict fishing mortality RP based on five levels of increasingly comprehensive data, to quantify effects of parameter and structural uncertainty on RP. Level I RP (least data) are estimated solely from species' maximum size and generic life history relationships, while level V RP (most data) are estimated from population-specific growth and maturity data. By estimating RP at all five data levels, for each of 12 North Sea populations, we demonstrate marked changes in the median RP values, and to a lesser extent uncertainty, when growth parameters come from data rather than life history relationships. As a simple rule, halving the median level I RP gives almost 90% probability that a level V median RP is not exceeded. RP and uncertainty were substantially affected by assumed gear selectivity; plausible changes in selectivity had a greater effect on RP than adding level V data. Calculations of RP using data for successive individual years from 1984 to 2014 showed that the median RP based on data for any given year would often fall outside the range of uncertainty for RP based on data from earlier or later years. This highlighted the benefits of frequent RP updates when suitable data are available. Our approach provides a quantitative method to inform risk-based management and decisions about acceptable targets for data collection and quality. Ultimately, however, the utility and extent of adoption of data-poor methods for estimating RP will depend on the risk aversion of managers
Altimetry, gravimetry, GPS and viscoelastic modeling data for the joint inversion for glacial isostatic adjustment in Antarctica (ESA STSE Project REGINA)
The poorly known correction for the ongoing deformation of the solid Earth caused by glacial isostatic adjustment (GIA) is a major uncertainty in determining the mass balance of the Antarctic ice sheet from measurements of satellite gravimetry and to a lesser extent satellite altimetry. In the past decade, much progress has been made in consistently modeling ice sheet and solid Earth interactions; however, forward-modeling solutions of GIA in Antarctica remain uncertain due to the sparsity of constraints on the ice sheet evolution, as well as the Earth's rheological properties. An alternative approach towards estimating GIA is the joint inversion of multiple satellite data – namely, satellite gravimetry, satellite altimetry and GPS, which reflect, with different sensitivities, trends in recent glacial changes and GIA. Crucial to the success of this approach is the accuracy of the space-geodetic data sets. Here, we present reprocessed rates of surface-ice elevation change (Envisat/Ice, Cloud,and land Elevation Satellite, ICESat; 2003–2009), gravity field change (Gravity Recovery and Climate Experiment, GRACE; 2003–2009) and bedrock uplift (GPS; 1995–2013). The data analysis is complemented by the forward modeling of viscoelastic response functions to disc load forcing, allowing us to relate GIA-induced surface displacements with gravity changes for different rheological parameters of the solid Earth. The data and modeling results presented here are available in the PANGAEA database (https://doi.org/10.1594/PANGAEA.875745). The data sets are the input streams for the joint inversion estimate of present-day ice-mass change and GIA, focusing on Antarctica. However, the methods, code and data provided in this paper can be used to solve other problems, such as volume balances of the Antarctic ice sheet, or can be applied to other geographical regions in the case of the viscoelastic response functions. This paper presents the first of two contributions summarizing the work carried out within a European Space Agency funded study: Regional glacial isostatic adjustment and CryoSat elevation rate corrections in Antarctica (REGINA)
Uncertainties in grid-based estimates of stellar mass and radius. SCEPtER: Stellar CharactEristics Pisa Estimation gRid
Some aspects of the systematic and statistical errors affecting grid-based
estimation of stellar masses and radii have still not been investigated well.
We study the impact on mass and radius determination of the uncertainty in the
input physics, in the mixing-length value, in the initial helium abundance, and
in the microscopic diffusion efficiency adopted in stellar model computations.
We consider stars with mass in the range [0.8 - 1.1] Msun and evolutionary
stages from the zero-age main sequence to the central hydrogen exhaustion.
Stellar parameters were recovered by a maximum-likelihood technique, comparing
the observations constraints to a grid of stellar models. Synthetic grids with
perturbed input were adopted to estimate the systematic errors arising from the
current uncertainty in model computations. We found that the statistical error
components, owing to the current typical uncertainty in the observations, are
nearly constant in all cases at about 4.5% and 2.2% on mass and radius
determination, respectively. The systematic bias on mass and radius
determination due to a variation of 1 in Delta Y/Delta Z is 2.3%
and 1.1%; the one due to a change of 0.24 in the value of the
mixing-length is 2.1% and 1.0%; the one due to a variation of
5% in the radiative opacity is 1.0% and 0.45%. An important bias
source is to neglect microscopic diffusion, which accounts for errors of about
3.7% and 1.5% on mass and radius. The cumulative effects of the considered
uncertainty sources can produce biased estimates of stellar characteristics.
Comparison of the results of our technique with other grid techniques shows
that the systematic biases induced by the differences in the estimation grids
are generally greater than the statistical errors involved.Comment: Accepted for publication in A&A. Abstract shortene
Affine arithmetic-based methodology for energy hub operation-scheduling in the presence of data uncertainty
In this study, the role of self-validated computing for solving the energy hub-scheduling problem in the presence of multiple and heterogeneous sources of data uncertainties is explored and a new solution paradigm based on affine arithmetic is conceptualised. The benefits deriving from the application of this methodology are analysed in details, and several numerical results are presented and discussed
Revised Stellar Properties of Kepler Targets for the Quarter 1-16 Transit Detection Run
We present revised properties for 196,468 stars observed by the NASA Kepler
Mission and used in the analysis of Quarter 1-16 (Q1-Q16) data to detect and
characterize transiting exoplanets. The catalog is based on a compilation of
literature values for atmospheric properties (temperature, surface gravity, and
metallicity) derived from different observational techniques (photometry,
spectroscopy, asteroseismology, and exoplanet transits), which were then
homogeneously fitted to a grid of Dartmouth stellar isochrones. We use
broadband photometry and asteroseismology to characterize 11,532 Kepler targets
which were previously unclassified in the Kepler Input Catalog (KIC). We report
the detection of oscillations in 2,762 of these targets, classifying them as
giant stars and increasing the number of known oscillating giant stars observed
by Kepler by ~20% to a total of ~15,500 stars. Typical uncertainties in derived
radii and masses are ~40% and ~20%, respectively, for stars with photometric
constraints only, and 5-15% and ~10% for stars based on spectroscopy and/or
asteroseismology, although these uncertainties vary strongly with spectral type
and luminosity class. A comparison with the Q1-Q12 catalog shows a systematic
decrease in radii for M dwarfs, while radii for K dwarfs decrease or increase
depending on the Q1-Q12 provenance (KIC or Yonsei-Yale isochrones). Radii of
F-G dwarfs are on average unchanged, with the exception of newly identified
giants. The Q1-Q16 star properties catalog is a first step towards an improved
characterization of all Kepler targets to support planet occurrence studies.Comment: 20 pages, 14 figures, 5 tables; accepted for publication in ApJS;
electronic versions of Tables 4 and 5 are available as ancillary files (see
sidebar on the right), and an interactive version of Table 5 is available at
the NASA Exoplanet Archive (http://exoplanetarchive.ipac.caltech.edu/
Sound and Automated Synthesis of Digital Stabilizing Controllers for Continuous Plants
Modern control is implemented with digital microcontrollers, embedded within
a dynamical plant that represents physical components. We present a new
algorithm based on counter-example guided inductive synthesis that automates
the design of digital controllers that are correct by construction. The
synthesis result is sound with respect to the complete range of approximations,
including time discretization, quantization effects, and finite-precision
arithmetic and its rounding errors. We have implemented our new algorithm in a
tool called DSSynth, and are able to automatically generate stable controllers
for a set of intricate plant models taken from the literature within minutes.Comment: 10 page
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