1,720,984 research outputs found
Interaction of swell and sea waves with partially reflective structures for possible engineering applications
No full textIn this work, we investigate the interaction between the combination of wind-driven and regular waves and a chamber defined by a rigid wall and a thin vertical semi-submerged barrier. A series of laboratory experiments were performed with different values of incident wave height, wave period, and wind speed. The analysis focuses on the effect of the geometry of the system characterized in terms of its relative submergence d/h and relative width B/L. Results show that for the case of d/h = 0.58 a resonant effect takes place inside the chamber regardless of the wind speed. Wind-driven waves have a higher influence on the variation of the wave period of the waves seaward and leeward of the plate, as well as on the phase lag. Results show that the amplification or reduction of the wave energy inside the chamber is closely related to the wave period as compared to the 1st order natural period of the chamber
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
On the role of wave climate temporal variability in bias correction of GCM-RCM wave simulations
No full textThis work presents the performance analysis of a multi-model ensemble of wave climate projections in the Mediterranean Sea against hindcast data. The wave projections were developed with the numerical model Wavewatch III forced by surface wind fields of 17 EURO-CORDEX GCM-RCMs providing time series of the main wave parameters on a 3-h and 10-km resolution. The performance of the wave GCM-RCM simulations during the baseline period (1979–2005) was assessed by means of the deterministic metrics RMSE and Bias. Different bias correction methodologies were analyzed by means of the application of the widespread Empirical Quantile Mapping method considering different time periods of significant wave height in order to analyze the ability of the bias-correcting methods to capture the different wave climate temporal scales ranging from storm events, monthly, seasonal and interannual variability. The results show that the use of the EQM method for the full-time series without taking into account other timescales, can lead to increased biases in some regions and seasons and that the use of time-dependent bias-correction techniques leads to an improved accurate characterization of biases considering the interannual temporal variability of significant wave height. More specifically the use of the EQM method for monthly data provides a good performance in capturing the correlation and interannual temporal variability of wave climate
Projected wave climate temporal variability due to climate change
No full textThis work proposes a new general procedure to stochastically analyze multi-model multivariate wave climate time series projections at different temporal scales. For every projection, it characterizes significant wave height, peak period and mean direction by means of univariate non-stationary distributions capable of capturing cyclic climate behavior over a reference time interval duration. The temporal dependence between the values at a given sea state and previous short-term wave climate is described with a vector autoregressive model (VAR). The multi-model ensemble wave climate characterization is based on a compound distribution of the individual non-stationary distributions and a weighted averaged VAR model. The methodology is applied to bias-adjusted wave climate projections derived using WaveWatch III forced by wind field data from EURO-CORDEX models at a location close to the Mediterranean Spanish coast. Results are compared to hindcast data which shows a clear bi-seasonal behavior. Different temporal references were considered, starting with a 1-year reference period to analyze overall changes in wave climate at scales ranging from days, months and seasons with respect to historic conditions. The results show that the projected wave climate has a very different temporal behavior than hindcast data, delaying and widening/shortening the start and duration of the two main seasons and including shorter term variations. Regarding the energetic content of the sea states, the compound variable highest percentiles of the significant wave height present lower values than the hindcast (≈3−10%) during the traditionally more severe period (November–March) but higher values (≈10−35%) during the calmer months. The projected peak period presents a similar temporal pattern to the hindcast data, while the mean wave direction shows a significant change from the historical bi-modal behavior towards more likely easterly waves throughout the year. Additionally, a 10-year analysis is done to find larger temporal variabilities such as decadal variations associated with the North Atlantic Oscillation. The observed temporal variability in the yearly seasonal pattern throughout the century is addressed by analysing 20-year rolling windows in all the model projections and in the compound variable. The compound distribution shows significant temporal variabilities throughout the century with the most severe periods and more likely severe waves during summer at the end of the century
Storm characterization and simulation for damage evolution models of maritime structures
No full textThis paper presents a new approach to statistically characterize and simulate the wave climate under storm conditions. The methodology includes the joint selection of the parameters that identify storm events (significant wave height threshold, minimum storm duration and minimum interarrival time between consecutive storms) by means of hypothesis testing on the distribution functions of the number of storm events and the elapsing time between storms, providing an improved characterization of the parameters that define storm events. The main wave variables and their temporal dependence are characterized by non-stationary mixture distribution functions and a vector autoregressive model. This allows to adequately reproduce the random temporal evolution of storm events, crucial for the study of damage progression in maritime structures without the use of predefined geometries. The long-term time series of storm events and calm periods is obtained using copula functions which analyze the joint dependence of storm duration and interarrival time for separate climate intervals. The model is applied to hindcast data at a location of the Mediterranean sea close to the Granada coast in Spain to show its ability to reproduce wave storm conditions accounting for the time variability of the storminess. An example of application, using a large number of simulations and a damage progression model in a maritime structure, is presented
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