Our work aims to investigate the vcBLMPE in
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-dimensions (3D-vcBLMPE) that characterizes wave propagation in incompressible fluids. In real-world issues, nonlinear partial differential ...equations containing time-dependent coefficients are more relevant than those with constant coefficients owing to inhomogeneities of media and nonuniformities of boundaries. In shallow water, linearization of the wave formation needs more critical wave capacity criteria than in water depths, and the strongly nonlinear aspects are readily visible. By using symbolic computation, several nonautonomous wave solutions with different geometric structures are obtained. Each of the gained solutions is presented graphically based on various arbitrary coefficients to demonstrate and better comprehend their dynamical properties. As a comparison between the new results and the results previously reported, we have presented several completely new findings in this study.
The mooring systems give stability to the floating platforms against environmental conditions, stabilizing the platform with mooring lines attached to the seabed. The mooring systems are among the ...main components that guarantee the safety of the staff and the various operations carried out on the platforms. The current approaches used to monitor mooring lines are inefficient as line tension sensors are expensive to install, maintain, and have durability problems. This article presents the development of two neural network-based machine learning systems: a Multilayer Perceptron (MLP) and a Long Short-Term Memory (LSTM). They are able to detect mooring line failure in near real-time based on the comparison between measured and predicted motion. The implemented systems were trained and evaluated with simulated motion data generated using real environmental conditions measured in the Campos Basin, in Rio de Janeiro, Brazil. The results showed the MLP and LSTM models were able to detect a failure in the mooring lines, with increasing difference between the predicted and the measured motions when there is a line breakage. A comparison between the two machine learning models revealed the LSTM model performed better at predicting the motions of the platform.
The current design process of mooring systems for Floating Production, Storage, and Offloading units (FPSOs) depends on the availability of the platform's mathematical model and the accuracy of ...dynamic simulations. These simulations then provide the FPSO's time series motion which is evaluated according to design constraints. This process can be time-consuming and present inaccurate results due to the mathematical model's limitations and the overall complexity of the vessel's dynamics. We propose a Neural Simulator, called NeuroSim, a set of data-based surrogate models with environmental data as input, each model specialized in predicting different motion statistics relevant to mooring system design: Maximum Roll, Platform Offset, and Fairlead Displacements. The surrogate models are trained by current, wind, and wave data given in 3 hours periods at a Brazilian Offshore Basin from 2003 to 2010, and the associated dynamic response of a spread-moored FPSO is obtained through time-domain simulations using the Dynasim software. Hyperparameter Optimization techniques are performed to obtain optimal Artificial Neural Network (ANN) models specialized in different platform drafts. Finally, the proposed models are shown to correctly capture platform dynamics, providing good results when compared to motion statistics obtained from Dynasim. We conclude that an ANN surrogate model can be trained directly on actual measured metocean conditions and corresponding FPSO motion statistics to provide increased accuracy and reduced computational time over traditional methods based on dynamic simulation. Moreover, the proposed architecture can be integrated into an automated learning framework: The data-based surrogate models can be continuously fine-tuned and updated with newly measured data, improving accuracy over time.
Polarized radio emission from PSR J1745−2900 has already been used to investigate the strength of the magnetic field in the Galactic center (GC), close to Sagittarius A*. Here we report how ...persistent radio emission from this magnetar, for over four years since its discovery, has revealed large changes in the observed Faraday rotation measure (RM), by up to 3500 rad m−2 (a 5% fractional change). From simultaneous analysis of the dispersion measure, we determine that these fluctuations are dominated by variations in either the projected magnetic field or the free electron content within the GC, along the changing line of sight to the rapidly moving magnetar. From a structure function analysis of RM variations, and a recent epoch of rapid change of RM, we determine a minimum scale of magneto-ionic fluctuations of size ∼2 au at the GC distance, inferring PSR J1745−2900 is just ∼0.1 pc behind an additional scattering screen.
Earth's nearest candidate supermassive black hole lies at the centre of the Milky Way. Its electromagnetic emission is thought to be powered by radiatively inefficient accretion of gas from its ...environment, which is a standard mode of energy supply for most galactic nuclei. X-ray measurements have already resolved a tenuous hot gas component from which the black hole can be fed. The magnetization of the gas, however, which is a crucial parameter determining the structure of the accretion flow, remains unknown. Strong magnetic fields can influence the dynamics of accretion, remove angular momentum from the infalling gas, expel matter through relativistic jets and lead to synchrotron emission such as that previously observed. Here we report multi-frequency radio measurements of a newly discovered pulsar close to the Galactic Centre and show that the pulsar's unusually large Faraday rotation (the rotation of the plane of polarization of the emission in the presence of an external magnetic field) indicates that there is a dynamically important magnetic field near the black hole. If this field is accreted down to the event horizon it provides enough magnetic flux to explain the observed emission--from radio to X-ray wavelengths--from the black hole.
Hematite (α-Fe2O3) polycrystalline thin films of different thicknesses were produced by thermal oxidation in air atmosphere from Fe metallic thin-films deposited by radio frequency (RF) sputtering ...technique. X-ray diffraction (XRD) patterns confirm the formation of hematite phase in all samples and indicate that the mean grain size decreases as the film thickness becomes thinner. Conversion electron Mössbauer spectroscopy (CEMS) spectra at room temperature show magnetic splitting (six line patterns). It is determined that the resonance peaks become broader and asymmetric as the film thickness decreases. This finding was associated with the structural disorder introduced by the thickness reduction. Magnetization as a function of the magnetic field curve obtained at 300K shows the presence of a weak-ferromagnetic contribution, which was assigned to the large density of decompensated spins at the films surface. From the magnetization vs. temperature curves it has been determined that the Morin transition temperature (TM) is shifted from ~240K to ~196K, meanwhile it becomes more broadened as the film thickness decreases. X-ray photoelectron spectroscopy (XPS) measurements show the presence of Fe2+ ions coexisting with Fe3+ ions whose population increases as the film becomes thinner. The density of chemisorbed oxygen increases as the film thickness is reduced in agreement with the results obtained from the other measurements in this work.
•Hematite thin films with different thickness were deposited by RF sputtering technique.•X-ray diffraction patterns confirm the formation of hematite phase in all samples.•Hysteresis curve at 300K shows the presence of a weak-ferromagnetic phase.•XPS show the presence of Fe2+ ions coexisting with Fe3+ ions.
A total of 95 yeast strains were isolated from the microbiota of different grapes collected at vineyards in southern Brazil. The yeasts were screened for β-(1 → 3)-glucanases using a newly developed ...zymogram method that relies upon the appearance of clearance zones around growing colonies cultured on agar–botryosphaeran medium and also by submerged fermentation on nutrient medium containing botryosphaeran, a (1 → 3),(1 → 6)-β-d-glucan. Among 14 β-(1 → 3)-glucanase-positive yeasts identified, four strains produced the highest β-glucanolytic activities and were evaluated for enzyme production on cellobiose, botryosphaeran, and mycelial biomass from Botryosphaeria rhodina (MAMB-05). Yeast strain 1WA1 produced the highest β-(1 → 3)-glucanase and β-glucosidase activities and was identified by molecular characterization as Aureobasidium pullulans. The physicochemical properties of the crude β-glucanolytic enzyme preparation were characterized, and the preparation was used to hydrolyze several β-d-glucans (laminarin, botryosphaeran, lasiodiplodan, pustulan, and curdlan). The production and physicochemical properties of the β-glucanolytic preparation enable its potential applications in wine enology and production of prebiotics through hydrolysis of β-d-glucans.
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