Effects of Swell on Wave Height Distribution of Energy-Conserved Bimodal Seas

An understanding of the wave height distribution of a sea state is important in forecasting extreme wave height and lifetime fatigue predictions of marine structures. In bimodal seas, swell can be present at different percentages and different frequencies while the energy content of the sea state remains unaltered. This computational study investigates how the wave height distribution is affected by different swell percentages and long swell periods in an energy-conserved bimodal sea both near a wave maker and in shallow water. A formulated energy-conserved bimodal spectrum was created from unimodal sea states and converted into random waves time series using the Inverse Fast Fourier Transform (IFFT). The resulting time series was used to drive a Reynolds-Averaged Navier Stokes computational (RANS) model. Wave height values were then extracted from the model results (both away near and near the structure) using down-crossing analysis to inspect the non-linearity imposed by wave-wave interactions and through transformations as they propagate into shallow waters near the structure. It is concluded that the kurtosis and skewness of the wave height distribution very inversely with the swell percentage and peak periods. Non-linearities are greater in the unimodal seas compared to the bimodal seas with the same energy content. Also, non-linearities are greater structure side than at wave maker and are more dependent on the phases of the component waves at different frequencies

Small Scale Field Experiment on Breaking Wave Pressure on Vertical Breakwaters

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Experimental investigation of different geometries of fixed oscillating water column devices

publisher: Elsevier articletitle: Experimental investigation of different geometries of fixed oscillating water column devices journaltitle: Renewable Energy articlelink: http://dx.doi.org/10.1016/j.renene.2016.11.061 content_type: article copyright: © 2016 Elsevier Ltd. All rights reserved

Comparative diagnostic performance of rapid antigen detection tests for COVID-19 in a hospital setting

Background: The availability of accurate and rapid diagnostic tools for COVID-19 is essential for tackling the ongoing pandemic. Our study aimed to quantify the performance of available antigen-detecting rapid diagnostic tests (Ag-RDTs) in a real-world hospital setting. Methods: In this retrospective analysis, the diagnostic performance of 7 Ag-RDTs was compared with real-time reverse transcription quantitative polymerase chain reaction assay in terms of sensitivity, specificity and expected predictive values. Results: A total of 321 matched Ag-RDTreal-time reverse transcription quantitative polymerase chain reaction samples were analyzed retrospectively. The overall sensitivity and specificity of the Ag-RDTs was 78.7% and 100%, respectively. However, a wide range of sensitivity estimates by brand (66.0%–93.8%) and cycle threshold (Ct) cut-off values (Ct <25: 96.2%; Ct 30–35: 31.1%) was observed. The optimal Ct cut-off value that maximized sensitivity was 29. Conclusions: The routine use of Ag-RDTs may be convenient in moderate-to-high intensity settings when high volumes of specimens are tested every day. However, the diagnostic performance of the commercially available tests may differ substantially

Storm Energy Flux Characterization along the Mediterranean Coast of Andalusia (Spain)

This paper investigates wave climate and storm characteristics along the Mediterranean coast of Andalusia, for the period 1979–2014, by means of the analysis of wave data on four prediction points obtained from the European Centre for Medium-RangeWeather Forecasts (ECMWF). Normally, to characterize storms, researchers use the so-called “power index”. In this paper, a different approach was adopted based on the assessment of the wave energy flux of each storm, using a robust definition of sea storm. During the investigated period, a total of 2961 storm events were recorded. They were classified by means of their associated energy flux into five classes, from low- (Class I) to high-energetic (Class V). Each point showed a different behavior in terms of energy, number, and duration of storms. Nine stormy years, i.e., years with a high cumulative energy, were recorded in 1980, 1983, 1990, 1992, 1995, 2001, 2008, 2010, and 2013

Effect of the 2020/21 season influenza vaccine on SARS-CoV-2 infection in a cohort of Italian healthcare workers

Objectives: Healthcare workers (HCWs) are a priority group for seasonal influenza vaccination (SIV). The 2020/21 SIV campaign was conducted during the second wave of the COVID-19 pandemic. Vaccines, including SIV, may exert non-specific protective effects on other infectious diseases which may be ascribable to the concept of trained immunity. The aim of this study was to explore the association between 2020/21 SIV and SARS-CoV-2 positivity in a cohort of Italian HCWs. Methods: In this observational study, a cohort of HCWs employed by a large (ca 5000 employees) referral tertiary acute-care university hospital was followed up retrospectively until the start of the COVID-19 vaccination campaign. The independent variable of interest was the 2020/21 SIV uptake. Both egg-based and cell culture-derived quadrivalent SIVs were available. The study outcome was the incidence of new SARS-CoV-2 infections, as determined by RT-PCR. Multivariable Cox regression was applied in order to discern the association of interest. Results: The final cohort consisted of 2561 HCWs who underwent ≥1 RT-PCR test and accounted for a total of 94,445 person-days of observation. SIV uptake was 35.6%. During the study period, a total of 290 new SARS-CoV-2 infections occurred. The incidence of new SARS-CoV-2 was 1.62 (95% CI: 1.22–2.10) and 3.91 (95% CI: 3.43–4.45) per 1000 person-days in vaccinated and non-vaccinated HCWs, respectively, with an adjusted non-proportional hazard ratio of 0.37 (95% CI: 0.22–0.62). E-values suggested that unmeasured confounding was unlikely to explain the association. Conclusions: A lower risk of SARS-CoV-2 infection was observed among SIV recipients

Storm evolution characterization for analysing stone armour damage progression

Storm evolution is fundamental for analysing the damage progression of the different failure modes and establishing suitable protocols for maintaining and optimally sizing structures. However, this aspect has hardly been studied and practically the whole of the studies dealing with the subject adopt the Equivalent triangle storm. As against this approach, two new ones are proposed. The first is the Equivalent Triangle Magnitude Storm model (ETMS), whose base, the triangular storm duration, D, is established such that its magnitude (area describing the storm history above the reference threshold level which sets the storm condition),HT, equals the real storm magnitude. The other is the Equivalent Triangle Number of Waves Storm (ETNWS), where the base is referred in terms of the real storm's number of waves,Nz. Three approaches are used for estimating the mean period, Tm, associated to each of the sea states defining the storm evolution, which is necessary to determine the full energy flux withstood by the structure in the course of the extreme event. Two are based on the Jonswap spectrum representativity and the other uses the bivariate Gumbel copula (Hs, Tm), resulting from adjusting the storm peaks. The representativity of the approaches proposed and those defined in specialised literature are analysed by comparing the main armour layer's progressive loss of hydraulic stability caused by real storms and that relating to theoretical ones. An empirical maximum energy flux model is used for this purpose. The agreement between the empirical and theoretical results demonstrates that the representativity of the different approaches depends on the storm characteristics and point towards a need to investigate other geometrical shapes to characterise the storm evolution associated with sea states heavily influenced by swell wave components