Long-Term Wave Measurement by an Onboard Radar Wave Meter and Prediction of Ship Motions Based on the Onboard Wave Measurements

2015 ◽  
Author(s):  
Hisafumi Yoshida ◽  
Hideo Orihara ◽  
Keiichi Yamasaki
Keyword(s):  
Ship Motions ◽  
Observation Data ◽  
Wave Direction ◽  
Motion Data ◽  
Safe Navigation ◽  
Wave Data ◽  
Wave Measurements ◽  
Short Term Prediction ◽  
Radar Wave

Continuous measurement of waves, ship motions (roll and pitch), and so on has been carried out for about five years by onboard monitoring system installed ocean-going vessel. Measured wave data, including wave height, wave period and wave direction, are thoroughly evaluated with corresponding onboard weather observation data by comparing directly in terms of time series and statistical values. Then, short term prediction of ship motions (roll and pitch) based on the measured wave data are compared with onboard motion data measured by vertical gyro. From the results described, good accuracy and effectiveness of wave measurements by an onboard radar wave meter for safe navigation are demonstrated.

Defining the Long-Term Wave Resource at Wave Hub: The Role of Measurements and Models

2008 ◽  
Author(s):  
Joseph Phillips ◽  
Joao Cruz ◽  
Rob Holbrow ◽  
Jeremy Parkes ◽  
Rob Rawlinson-Smith
Keyword(s):  
Wave Energy ◽  
Resource Assessment ◽  
Wave Climate ◽  
Short Term ◽  
Wave Data ◽  
Wave Measurements ◽  
Operations And Maintenance ◽  
South West Coast ◽  
Short Term Forecasting

Wave measurements made on the site of a potential wave energy project can be of high value to developers. Such data can be used to define both long-term and short-term wave energy resources available to devices as well as the optimal operations and maintenance strategy which should be employed for the project. All three of these applications are addressed in an ongoing study commissioned by the npower Juice Fund for the Wave Hub project which is planned off the South West coast of England. The aim of this work is to extract best value from the historical and future wave measurements from the project site. The programme of this project is outlined here with a technical description of activity in the three parallel strands of the study; wave resource assessment, short-term forecasting and O&M modelling. The focus of this paper is on a key aspect of the ongoing work programme - that relates to the use of measured and modelled wave data to derive a prediction of the long-term wave climate at the Wave Hub site. In particular, various candidate methodologies for correlating short-term measured wave data and long-term modelled data are explored in the context of a Measure-Correlate-Predict (MCP) analysis. This work has also included consideration of the inter-annual variability of wave resource in order to examine the uncertainty associated with assuming that a finite historical reference period is representative of the long-term wave climate.

Study on a Method for Estimating Fuel Consumption in a Seaway

2013 ◽  
Author(s):  
Toshio Iseki ◽  
Ulrik D. Nielsen
Keyword(s):  
Fuel Consumption ◽  
Fuel Efficiency ◽  
Great Influence ◽  
Wave Direction ◽  
Motion Data ◽  
Wave Measurements ◽  
Navigation Support ◽  
Wave Angle ◽  
Scale Experiment ◽  
Main Engine

On-board measurement of fuel consumption of a ship has been carried out in a relatively severe sea condition. In the full scale experiment, the ship traveled on several courses to investigate the change of fuel consumption relative to the encounter wave angle. The result shows that the wave direction has a great influence on the main engine horse power and fuel consumption, and also shows a possibility of fuel efficiency prediction. In order to develop an eco-friendly navigation support system, results of Bayesian wave estimation are applied to fuel efficiency prediction. The Bayesian method does not require wave measurements but needs only ship motion data as input and the method is suitable for on-site wave estimation.

scholarly journals A Wave Measurements HF Radar Data Set in the Malta-Sicily Channel: Data Quality, Validation and Gap Filling

10.29007/wg8s ◽  
2018 ◽  
Author(s):  
Marco Picone ◽  
Arianna Orasi ◽  
Aldo Drago ◽  
Fulvio Capodici ◽  
Giuseppe Ciraolo ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Missing Values ◽  
Hf Radar ◽  
Data Set ◽  
Significant Wave ◽  
Wave Data ◽  
Wave Measurements ◽  
Sicily Channel ◽  
Radar Wave

The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR HF stations. The system is providing real- time hourly maps of sea surface currents and wave data in the Malta-Sicily Channel since 2012. Significant wave height derived from the HF radar wave measurements are confirmed to be a reliable source of wave information even in case of extreme events. However, it is noticed that the HF radar wave data are subject to differing interfering noise in the signal from unknown sources that may be competing with transmissions in the same frequency band. These interferences lead to frequent gaps and/or outliers that affect the continuity and reliability of the data set. The aim of this work is to estimate missing values and to detect possible outliers building and fitting a Markov chain mixture model on the significant wave height data collected at the four stations. It is verified that the proposed procedure is sufficiently robust since the model estimates succeed to classify radar observations with a high percentage of missing data and to equally highlight spikes and outliers.

scholarly journals A Method to Reduce the Calculation Time of Sediment Simulation by Controlling the Number of Long-term Wave Data

2021 ◽  
Vol 8 (4) ◽  
pp. 307-314
Author(s):  
Gweon-su Kim ◽  
Ha-sang Ryu ◽  
Sang-hoon Kim
Keyword(s):  
Numerical Simulation ◽  
Time Series ◽  
Numerical Model ◽  
Real Time ◽  
Wave Direction ◽  
Wave Data ◽  
Simulation Results ◽  
The Difference ◽  
Reduced Time

In order to solve the difficulty of performing a numerical model using a long-term wave time series, a method of reducing wave time series was considered. And Numerical simulation of the sediment by the Delft3d model at the Maengbang Beach was conducted to verify the validity of the method. NOAA wave data were collected for about 40 years from January 1979 to May 2019. Among them, waves, which are judged to have insignificant effect on the beach, were removed and the wave time series was reduced. To this end, the entire wave time series was graded at intervals of 0.5m, period 2sec, and wave direction 10° to generate a total of 749 representative waves, and a numerical simulation of sediment was performed for each representative wave for 1 day. When the maximum sediment height was less than 0.01m/day, it was assumed that the influence of the representative wave on the area was negligible. As a result of conducting numerical simulation of the sediment using the 23-month real-time waves and the wave by the reduced time series, the difference between the two simulation results indicates a local sedimentation difference of 0.1 to 0.5 m near Deokbongsan. There is a difference in sedimentation of 0.01 to 0.1m overall, and the pattern of repeated erosion and sedimentation along the entire coast is very similar to both real-time waves and reduced time series waves.

scholarly journals Quality Assessment and Practical Interpretation of the Wave Parameters Estimated by HF Radars in NW Spain

2020 ◽  
Vol 12 (4) ◽  
pp. 598 ◽  
Author(s):  
Ana Basañez ◽  
Pablo Lorente ◽  
Pedro Montero ◽  
Enrique Álvarez-Fanjul ◽  
Vicente Pérez-Muñuzuri
Keyword(s):  
Hf Radar ◽  
Wave Direction ◽  
Nw Spain ◽  
Wave Regime ◽  
Wave Data ◽  
Wave Parameters ◽  
Range Cell ◽  
Wave Reanalysis ◽  
Radar Wave ◽  
Sampling Times

High-frequency (HF) radars are efficient tools for measuring vast areas and gathering ocean parameters in real-time. However, the accuracy of their wave estimates is under analysis. This paper presents a new methodology for analyzing and validating the wave data estimated by two CODAR SeaSonde radars located on the Galician coast (NW Spain). Approximately one and a half years of wave data (January, 2014–April, 2015) were obtained for ten range cells employing two different sampling times used by the radar software. The resulting data were screened by an updated method, and their abundance and quality were described for each radar range cell and different wave regime; the latter were defined using the spectral significant wave height (Hm0) and mean wave direction (Dm) estimated by two buoys and three SIMAR points (SImulación MARina in Spanish, from the wave reanalysis model by Puertos del Estado (PdE)). The correlation between the results and the particularities of the different sea states (broadband or bimodal), the wind and the operation of the devices are discussed. Most HF radar wave parameters’ errors occur for waves from the NNE and higher than 6 m. The best agreement between the Vilán radar and the Vilano-Sisargas buoy wave data was obtained for the dominant wave regime (from the northwest) and the southwest wave regime. However, relevant contradictions regarding wave direction were detected. The possibilities of reducing the wave parameters’ processing time by one hour and increasing the numbers of range cells of the radars have been validated.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Evaluations of Surface PM10 Concentration and Chemical Compositions in MERRA-2 Aerosol Reanalysis over Central and Eastern China

2021 ◽  
Vol 13 (7) ◽  
pp. 1317
Author(s):  
Xiaodan Ma ◽  
Peng Yan ◽  
Tianliang Zhao ◽  
Xiaofang Jia ◽  
Jian Jiao ◽  
...  
Keyword(s):  
Eastern China ◽  
Mainland China ◽  
Chemical Components ◽  
Chemical Compositions ◽  
Observation Data ◽  
Causative Factors ◽  
Routine Sampling ◽  
Aerosol Compositions ◽  
Modern Era

The chemical composition dataset of Aerosol Reanalysis of NASA’s Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRAero) has not been thoroughly evaluated with observation data in mainland China due to the lack of long-term chemical components data. Using the 5-year data of PM10 mass concentrations and chemical compositions obtained from the routine sampling measurements at the World Meteorological Organization the Global Atmosphere Watch Programme regional background stations, Jing Sha (JS) and Lin’An (LA), in central and eastern China, we comprehensively evaluate the surface PM10 concentrations and chemical compositions such as sulfate (SO42−), organic carbon (OC) and black carbon (BC) derived from MERRAero. Overall, the concentrations of PM10, SO42−, OC and BC from the MERRAero agreed well with the measurements, despite a slight and consistent overestimation of BC concentrations and a moderate and persistent underestimation of PM10 concentrations throughout the study period. The MERRAero reanalysis of aerosol compositions performs better during the summertime than wintertime. By considering the nitrate particles in PM10 reconstruction, MERRAero performance can be significantly improved. The unreasonable seasonal variations of PM10 chemical compositions at station LA by MERRAero could be causative factors for the larger MERRAero discrepancies during 2016–2017 than the period of 2011–2013.

scholarly journals Novel robust time series analysis for long-term and short-term prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroshi Okamura ◽  
Yutaka Osada ◽  
Shota Nishijima ◽  
Shinto Eguchi
Keyword(s):  
Robust Regression ◽  
Simulated Data ◽  
New Method ◽  
Short Term ◽  
Least Absolute Deviations ◽  
Term Prediction ◽  
Regression Approach ◽  
Short Term Prediction ◽  
Long Term Prediction

AbstractNonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-term prediction by estimating autocorrelation, whereas it has weakness to outliers and consequently worse long-term prediction. In contrast, a traditional robust regression approach, such as the least absolute deviations method, alleviates the influence of outliers and has potentially better long-term prediction, whereas it makes accurately estimating autocorrelation difficult and possibly leads to worse short-term prediction. We propose a new robust regression approach that estimates autocorrelation accurately and reduces the influence of outliers. We then compare the new method with the conventional least squares and least absolute deviations methods by using simulated data and real ecological data. Simulations and analysis of real data demonstrate that the new method generally has better long-term and short-term prediction ability for nonlinear estimation problems using spawner–recruitment data. The new method provides nearly unbiased autocorrelation even for highly contaminated simulated data with extreme outliers, whereas other methods fail to estimate autocorrelation accurately.

scholarly journals Wearable Wireless Physiological Monitoring System Based on Multi-Sensor

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 986
Author(s):  
Hongru Li ◽  
Guiling Sun ◽  
Yue Li ◽  
Runzhuo Yang
Keyword(s):  
Monitoring System ◽  
Health Management ◽  
Wearable Technology ◽  
Physiological Monitoring ◽  
Motion Data ◽  
Low Load ◽  
Measure Heart Rate ◽  
Body Surface Temperature ◽  
Continuous Work

The purpose of wearable technology is to use multimedia, sensors, and wireless communication to integrate specific technology into user clothes or accessories. With the help of various sensors, the physiological monitoring system can collect, process, and transmit physiological signals without causing damage. Wearable technology has been widely used in patient monitoring and people’s health management because of its low-load, mobile, and easy-to-use characteristics, and it supports long-term continuous work and can carry out wireless transmissions. In this paper, we established a Wi-Fi-based physiological monitoring system that can accurately measure heart rate, body surface temperature, and motion data and can quickly detect and alert the user about abnormal heart rates.

scholarly journals Long-Term Observations of Beach Variability at Hasaki, Japan

2020 ◽  
Vol 8 (11) ◽  
pp. 871
Author(s):  
Masayuki Banno ◽  
Satoshi Nakamura ◽  
Taichi Kosako ◽  
Yasuyuki Nakagawa ◽  
Shin-ichi Yanagishima ◽  
...  
Keyword(s):  
Morphological Change ◽  
High Frequency ◽  
Climate Changes ◽  
Wave Climate ◽  
Time Interval ◽  
Observation Data ◽  
Beach Profile ◽  
Water Level Variations ◽  
Monthly Variations

Long-term beach observation data for several decades are essential to validate beach morphodynamic models that are used to predict coastal responses to sea-level rise and wave climate changes. At the Hasaki coast, Japan, the beach profile has been measured for 34 years at a daily to weekly time interval. This beach morphological dataset is one of the longest and most high-frequency measurements of the beach morphological change worldwide. The profile data, with more than 6800 records, reflect short- to long-term beach morphological change, showing coastal dune development, foreshore morphological change and longshore bar movement. We investigated the temporal beach variability from the decadal and monthly variations in elevation. Extremely high waves and tidal anomalies from an extratropical cyclone caused a significant change in the long-term bar behavior and foreshore slope. The berm and bar variability were also affected by seasonal wave and water level variations. The variabilities identified here from the long-term observations contribute to our understanding of various coastal phenomena.

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