Coastal bathymetry estimation using an ensemble of synthetic aperture radar images from Sentinel-1

In this study, coastal bathymetry is estimated with a wave ray-tracing algorithm using wave parameters retrieved from Synthetic Aperture Radar (SAR) images acquired by the Sentinel-1 satellites. The method relies on the long swell wave’s detection by SAR imagery and the wave’s properties adjustment to the underwater topography, which can be mathematically related using the linear dispersion relation. The ray-tracing algorithm tracks the shoaling waves until the wave breaking zone, using the wavelength and wave direction retrieved from the 2D directional spectra applied at consecutive sub-images. Then, by inverting the linear wave dispersion relationship, the depth is calculated based on the mean wavelength obtained for each sub-image and maintaining the wave period retrieved at the first offshore position, which is computed using a mean depth from an independent bathymetric source. The output of the algorithm is a bathymetric model that results from the interpolation of the depth computed at each tracking position to a uniform grid and the results are compared with bathymetric information from the General Bathymetric Chart of the Ocean. The use of a monthly ensemble of SAR images, instead of individual ones, to reproduce the bathymetry near Aveiro, Portugal, resulted in a smoother topography with lower relative errors, suggesting that the final bathymetric model retrieved from SAR should result from a combination of SAR images. The methodology presented here to infer the bathymetry using space-borne SAR imagery can be useful to retrieve the mean bottom topography (especially in remote areas where the traditional hydrographic surveying methods are not performed regularly) and to reproduce new underwater structures, such as banks, reefs or bars, which are important to detect for the safety of navigation.Peer Reviewe

Real-time control of a laboratory heat exchanger using the particle swarm optimisation algorithm

In the past decade, evolutionary based algorithms have been a popular research theme in many disciplinary areas like control systems. Although, due to the computational load required, this type of algorithms usually are applied off-line. In this paper, a stochastic search algorithm known as particle swarm is used as an optimisation tool for on-line control of a custom made laboratory thermodynamic system

Hardware-in-the-loop control using the particle swarm optimisation

In the last two decades, evolutionary based algorithms have proved to be an important tool in solving optimisation problems in many disciplinary areas namely in control system design. However one of its limitations, for some type of applications, is the usually high computational load required, which restricts its use for on-line control. This paper proposes the use of a stochastic search algorithm, known as particle swarm, as an optimisation tool for an on-line predictive control of a custom made thermodynamic system. Preliminary results are presented

Greenhouse air temperature control using the particle swarm optimisation algorithm

The particle swarm optimisation algorithm is proposed as a new method to design a model based predictive controller subject to restrictions. Its performance is compared with the one obtained by using a genetic algorithm for the environmental temperature control of a greenhouse. Controller outputs are computed in order to optimise future behaviour of the greenhouse environment, regarding set-point tracking and minimisation of the control effort over a prediction horizon of one hour with a one-minute sampling period

Greenhouse air temperature modelling

This paper describes two implementation approaches for modelling the air temperature of an automated greenhouse located in the campus of the University of Trás-os- Montes e Alto Douro. Linear models, based in the discretization of the heat transfer physical laws, and non-linear neural networks models are used. These models are describes as functions of the outside climate and control actions performed for heating and cooling. Results are presented to illustrate the performance of each model in the simulation and prediction of the greenhouse air temperature. The data used to compute the simulation models was collected with a PC-based acquisition and control system using a sampling time interval of 1 minute.The authors appreciate the support of the Portuguese Foundation for Science and Technology (FCT) through the project MGS/ 33906/2000

On-line control using the particle swarm optimisation algorithm

In the last two decades, evolutionary based algorithms have proved to be an important tool in solving optimisation problems in many disciplinary areas, namely in control system design. However one of its limitations for some type of applications is the usually high computational load required, which restricts its use for on-line control. This paper proposes the use of a stochastic search algorithm, known as particle swarm, as an optimisation tool for an on-line model predictive control of a custom made laboratory thermodynamic system. Preliminary results are presented

Automation and control of the SORTEGEL wastewater plant

Food Processing Industries produce large amounts of wastewater with high environmental impact. Due to the high content of suspended matter and inadequate pH value of the wastewater, national laws prohibit direct discharges of the influent to the environment. This work describes the design and operation of a wastewater treatment plant installed in the Sortegel food-processing company located in Sortes, Portugal. This industry uses the water collected from groundwater wells to process raw materials and to wash the equipments, being the volume of wastewater produced season dependent (80 to 300m3/day). Results show that the implemented wastewater treatment plant and the automation solutions generate treated effluents that comply with the Portuguese legislation

Scanning Fourier Spectroscopy: A microwave analog study to image transmission paths in quantum dots

We use a microwave cavity to investigate the influence of a movable absorbing center on the wave function of an open quantum dot. Our study shows that the absorber acts as a position-selective probe, which may be used to suppress those wave function states that exhibit an enhancement of their probability density near the region where the impurity is located. For an experimental probe of this wave function selection, we develop a technique that we refer to as scanning Fourier spectroscopy, which allows us to identify, and map out, the structure of the classical trajectories that are important for transmission through the cavity.Comment: 4 pages, 5 figure

Transport spectroscopy in a time-modulated open quantum dot

We have investigated the time-modulated coherent quantum transport phenomena in a ballistic open quantum dot. The conductance $G$ and the electron dwell time in the dots are calculated by a time-dependent mode-matching method. Under high-frequency modulation, the traversing electrons are found to exhibit three types of resonant scatterings. They are intersideband scatterings: into quasibound states in the dots, into true bound states in the dots, and into quasibound states just beneath the subband threshold in the leads. Dip structures or fano structures in $G$ are their signatures. Our results show structures due to 2$\hbar\omega$ intersideband processes. At the above scattering resonances, we have estimated, according to our dwell time calculation, the number of round-trip scatterings that the traversing electrons undertake between the two dot openings.Comment: 8 pages, 5 figure

Waterborne Toxoplasmosis, Brazil, from Field to Gene

Water was the suspected vehicle of Toxoplasma gondii dissemination in a toxoplasmosis outbreak in Brazil. A case-control study and geographic mapping of cases were performed. T. gondii was isolated directly from the implicated water and genotyped as SAG 2 type I