Effect of the acoustic impedance in ultrasonic emitter transducers using digital modulations

In an underwater environment it is difficult to implement solutions for wireless communications. The existing technologies using electromagnetic waves or lasers are not very efficient due to the large attenuation in the aquatic environment. Ultrasound reveals a lower attenuation, and thus has been used in underwater long-distance communications. The much slower speed of acoustic propagation in water (about 1500 m/s) compared with that of electromagnetic and optical waves, is another limiting factor for efficient communication and networking. For high data-rates and real-time applications it is necessary to use frequencies in the MHz range, allowing communication distances of hundreds of meters with a delay of milliseconds. To achieve this goal, it is necessary to develop ultrasound transducers able to work at high frequencies and wideband, with suitable responses to digital modulations. This work shows how the acoustic impedance influences the performance of an ultrasonic emitter transducer when digital modulations are used and operating at frequencies between 100 kHz and 1 MHz. The study includes a Finite Element Method (FEM) and a MATLAB/Simulink simulation with an experimental validation to evaluate two types of piezoelectric materials: one based on ceramics (high acoustic impedance) with a resonance design and the other based in polymer (low acoustic impedance) designed to optimize the performance when digital modulations are used. The transducers performance for Binary Amplitude Shift Keying (BASK), On-Off Keying (OOK), Binary Phase Shift Keying (BPSK) and Binary Frequency Shift Keying (BFSK) modulations with a 1 MHz carrier at 125 kbps baud rate are compared.

Effect of NaCl additive on solute-solvent interactions in aqueous polyethylene glycol-sodium sulfate two-phase systems

Abstract Partition behavior of eight small organic compounds and six proteins was examined in poly(ethylene glycol)-8000-sodium sulfate aqueous two-phase systems containing 0.215 M NaCl and 0.5 M osmolyte (sorbitol, sucrose, TMAO) and poly(ethylene glycol)-10000-sodium sulfate-0.215 M NaCl system, all in 0.01 M sodium phosphate buffer, pH 6.8. The differences between the solvent properties of the coexisting phases (solvent dipolarity/polarizability, hydrogen bond donor acidity, and hydrogen bond acceptor basicity) were characterized with solvatochromic dyes using the solvatochromic comparison method. Differences between the electrostatic properties of the phases were determined by analysis of partitioning of sodium salts of dinitrophenylated (DNP-) amino acids with aliphatic alkyl side-chain. The partition coefficients of all compounds examined (including proteins) were described in terms of solute-solvent interactions. The results obtained in the study show that solute-solvent interactions of nonionic organic compounds and proteins in polyethylene glycol-sodium sulfate aqueous two-phase system change in the presence of NaCl additive.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Simulation of OWES with five-Level converter linked to the grid: Harmonic assessment

This paper deals with a computing simulation for an offshore wind energy system taking into account the influence of the marine waves action throughout the floating platform. The wind energy system has a variable-speed turbine equipped with a permanent magnet synchronous generator and a full-power five level converter, injecting energy into the electric grid through a high voltage alternate current link. A reduction on the unbalance of the voltage in the DC-link capacitors of the five-level converter is proposed by a strategic selection of the output voltage vectors. The model for the drive train of the wind energy system is a two mass model, including the dynamics of the floating platform. A case study is presented and the assessment of the quality of the energy injected into the electric grid is discussed.

Simulation of a rectifier malfunction on a offshore wind system with HVDC transmission

A new integrated mathematical model for the simulation of an offshore wind system having a rectifier input voltage malfunction at one phase is presented in this paper. The mathematical model considers an offshore variable-speed wind turbine on a floating platform, equipped with a permanent magnet synchronous generator using full-power three-level converter to inject energy into the electric network, through a high voltage direct current transmission submarine cable. The model for the drive train is a discrete three mass, incorporating the dynamic of the moving surface. A case study is presented to access conclusion about the malfunction.

Numerical simulation of the reflow soldering process

Dissertação de mestrado integrado em Mechanical Engineering

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

An interactive web-based tool for breast reduction surgery simulation

In this work, we present a 3D web-based interactive tool for numerical modeling and simulation approach to breast reduction surgery simulation, to assist surgeons in planning all aspects related to breast reduction surgery before the actual procedure takes place, thereby avoiding unnecessary risks. In particular, it allows the modeling of the initial breast geometry, the definition of all aspects related to the surgery and the visualization of the post-surgery breast shape in a realistic environment.

Singularities of the dynamical structure factors of the spin-1/2 XXX chain at finite magnetic field

We study the longitudinal and transverse spin dynamical structure factors of the spin-1/2 XXX chain at finite magnetic field h, focusing in particular on the singularities at excitation energies in the vicinity of the lower thresholds. While the static properties of the model can be studied within a Fermi-liquid like description in terms of pseudoparticles, our derivation of the dynamical properties relies on the introduction of a form of the ‘pseudofermion dynamical theory’ (PDT) of the 1D Hubbard model suitably modified for the spin-only XXX chain and other models with two pseudoparticle Fermi points. Specifically, we derive the exact momentum and spin-density dependences of the exponents ζτ(k) controlling the singularities for both the longitudinal  and transverse (τ = t) dynamical structure factors for the whole momentum range  , in the thermodynamic limit. This requires the numerical solution of the integral equations that define the phase shifts in these exponents expressions. We discuss the relation to neutron scattering and suggest new experiments on spin-chain compounds using a carefully oriented crystal to test our predictions.

Projeto de produção de tubo elíptico em aço avançado de elevada resistência para uma serra de arco

Dissertação de mestrado integrado em Engenharia Mecânica

Simulação numérica do comportamento ao impacto de componentes metálicos para aplicações de crashworthiness utilizando iniciadores de deformação configuráveis

Dissertação de mestrado integrado em Engenharia Mecânica

Evaluation of temperature influence on embedded kinematic system

Dissertação de mestrado integrado em Engenharia Mecânica

Finite integration methods for isospectral flows

In this paper we consider the approximate computation of isospectral flows based on finite integration methods( FIM) with radial basis functions( RBF) interpolation,a new algorithm is developed. Our method ensures the symmetry of the solutions. Numerical experiments demonstrate that the solutions have higher accuracy by our algorithm than by the second order Runge- Kutta( RK2) method.

Development of procedures for the design, optimization and manufacturing of customized orthopaedic and trauma implants: Geometrical/anatomical modelling from 3D medical imaging

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.