System identification for nonlinear maneuvering of large tankers using artificial neural network

This paper deals with the application of nonparametric system identification to a nonlinear maneuvering model for large tankers using artificial neural network method. The three coupled maneuvering equations in this model for large tankers contain linear and nonlinear terms and instead of attempting to determine the parameters (i.e. hydrodynamic derivatives) associated with nonlinear terms, all nonlinear terms are clubbed together to form one unknown time function per equation which are sought to be represented by the neural network coefficients. The time series used in training the network are obtained from simulated data of zigzag maneuvers and the proposed method has been applied to these data. The neural network scheme adopted in this work has one middle or hidden layer of neurons and it employs the Levenberg–Marquardt algorithm. Using the best choices for the number of hidden layer neurons, length of training data, convergence tolerance etc., the performance of the proposed neural network model has been investigated and conclusions drawn.     

“Trends” and variations of global oceanic evaporation data sets from remote sensing

The variability in global oceanic evaporation data sets was examined for the period 1988-2000. These data sets are satellite estimates based on bulk aerodynamic formulations and include the NASA/Goddard Space Flight Center Satellite-based Surface Turbulent Flux version 2 （ GSSTF2）, the Japanese-ocean flux using remote sensing observations （J-OFURO）, and the Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite version 2 （HOAPS2）. The National Center for Environmental Prediction （NCEP） reanalysis is also included for comparison. An increase in global average surface latent heat flux （SLHF） can be observed in all the data sets. Empirical mode decomposition （EMD） shows long-term increases that started around 1990 for all remote sensing data sets. The effect of Mt. Pinatubo eruption in 1991 is clearly evident in HOAPS2 but is independent of the longterm increase. Linear regression analyses show increases of 9.4%, 13.0%, 7. 3%, and 3.9% for GSSTF2, J-OFURO, HOAPS2 and NCEP, for the periods of the data sets. Empirical orthogonal function （EOF） analyses show that the pattern of the first EOF of all data sets is consistent with a decadal variation associated with the enhancement of the tropical Hadley circulation, which is supported by other satellite observations. The second EOF of all four data sets is an ENSO mode, and the correlations between their time series and an SO1 are 0.74, 0.71,0.59, and 0.61 for GSSTF2, J-OFURO, HOAPS2, and NCEP in that order. When the Hadley modes are removed from the remote sensing data, the residue global increases are reduced to 2.2% , 7. 3%, and 〈 1% for GSSTF2, J-OFURO and HOAPS, respectively. If the ENSO mode is used as a calibration standard for the data sets, the Hadley mode is at least comparable to, if not larger than, the ENSO mode during our study period.     

Influence of chemical composition and microstructure on the hygroscopic growth of pyrogenic aerosol

The hygroscopic properties of a model smoke aerosol series including ammonium sulfate, levoglucosan, and oxalic and humic acids were investigated. The condensation growth of particles and the relative humidity of direct and inverse particle-droplet phase transitions were measured with a tandem differential mobility analyzer. The data were obtained in the range of relative humidity from 4 to 95% at 298 K. Experimental growth factors were compared to the results of Koehler theory by using contemporary models of water activity in particles. It was shown that the hygroscopic properties of the aerosols were substantially different from the hygroscopic properties of the corresponding bulk phases. It was found that a complex microstructure of nanoparticles resulted in excess volume absorption of water, in some cases causing their full deliquescence at lower relative humidities than in macrosystems of identical composition. From the measurement data, a parametrization of hygroscopic particle growth was performed. The results of parametrization can be used to construct refined models of a smoke aerosol.     

Integrated Geological–Geophysical and Oceanographic Research in the South China Sea: Cruise 88 of the R/V “Akademik M.A. Lavrentyev”

Oceanology - Abstract—The paper gives brief results of comprehensive studies in the South China Sea obtained from a joint Russian–Vietnamese expedition in November 2019 (cruise 88 of...     

Field Research in the Baltic Sea on Cruise 55 of the P/V Akademik Ioffe

Oceanology - New data on the structure of the water column, upper layer of bottom sediments, and biological communities of the Gdansk and Gotland deeps and the Gulf of Finland in the Baltic Sea...     

Vertical Variability of Primary Production and Chlorophyll a in the Kara Sea in the Middle of Summer: Contribution of Subsurface Maxima to the Water Column Values

Oceanology - Spatial and vertical variability of primary production (PP) and Chl a were studied in the framework of the 76th cruise of R/V Akademik Mstislav Keldysh to the Kara Sea from July 7 to...     

Tuning a physically-based model of the air–sea gas transfer velocity

Air–sea gas transfer velocities are estimated for one year using a 1-D upper-ocean model (GOTM) and a modified version of the NOAA–COARE transfer velocity parameterization. Tuning parameters are evaluated with the aim of bringing the physically based NOAA–COARE parameterization in line with current estimates, based on simple wind-speed dependent models derived from bomb-radiocarbon inventories and deliberate tracer release experiments. We suggest that A = 1.3 and B = 1.0, for the sub-layer scaling parameter and the bubble mediated exchange, respectively, are consistent with the global average CO₂ transfer velocity k. Using these parameters and a simple 2nd order polynomial approximation, with respect to wind speed, we estimate a global annual average k for CO₂ of 16.4 ± 5.6 cm h^?1 when using global mean winds of 6.89 m s^?1 from the NCEP/NCAR Reanalysis 1 1954–2000. The tuned model can be used to predict the transfer velocity of any gas, with appropriate treatment of the dependence on molecular properties including the strong solubility dependence of bubble-mediated transfer. For example, an initial estimate of the global average transfer velocity of DMS (a relatively soluble gas) is only 11.9 cm h^?1 whilst for less soluble methane the estimate is 18.0 cm h^?1.