An approach to verifying and debugging simulation models governed by ordinary differential equations: Part 1. Methodology for residual generation

For dynamic simulations to be credible, verification of the computer code must be an integral part of the modelling process. This two-part paper describes a novel approach to verification through program testing and debugging. In Part 1, a methodology is presented for detecting and isolating coding errors using back-to-back testing. Residuals are generated by comparing the output of two independent implementations, in response to identical inputs. The key feature of the methodology is that a specially modified observer is created using one of the implementations, so as to impose an error-dependent structure on these residuals. Each error can be associated with a fixed and known subspace, permitting errors to be isolated to specific equations in the code. It is shown that the geometric properties extend to multiple errors in either one of the two implementations. Copyright (C) 2003 John Wiley Sons, Ltd.

Ambulatory blood pressure and Doppler echocardiographic indexes of borderline hypertensive men presenting an exaggerated blood pressure response during dynamic exercise

Borderline hypertension (BH) has been associated with an exaggerated blood pressure (BP) response during laboratory stressors. However, the incidence of target organ damage in this condition and its relation to BP hyperreactivity is an unsettled issue. Thus, we assessed the Doppler echocardiographic profile of a group of BH men (N = 36) according to office BP measurements with exaggerated BP in the cycloergometric test. A group of normotensive men (NT, N = 36) with a normal BP response during the cycloergometric test was used as control. To assess vascular function and reactivity, all subjects were submitted to the cold pressor test. Before Doppler echocardiography, the BP profile of all subjects was evaluated by 24-h ambulatory BP monitoring. All subjects from the NT group presented normal monitored levels of BP. In contrast, 19 subjects from the original BH group presented normal monitored BP levels and 17 presented elevated monitored BP levels. In the NT group all Doppler echocardiographic indexes were normal. All subjects from the original BH group presented normal left ventricular mass and geometrical pattern. However, in the subjects with elevated monitored BP levels, fractional shortening was greater, isovolumetric relaxation time longer, and early to late flow velocity ratio was reduced in relation to subjects from the original BH group with normal monitored BP levels (P<0.05). These subjects also presented an exaggerated BP response during the cold pressor test. These results support the notion of an integrated pattern of cardiac and vascular adaptation during the development of hypertension.

Modelagem da dispersão de odores em ambientes urbanos

O presente trabalho investigou o problema da modelagem da dispersão de compostos odorantes em presença de obstáculos (cúbicos e com forma complexa) sob condição de estabilidade atmosférica neutra. Foi empregada modelagem numérica baseada nas equações de transporte (CFD1) bem como em modelos algébricos baseados na pluma Gausseana (AERMOD2, CALPUFF3 e FPM4). Para a validação dos resultados dos modelos e a avaliação do seu desempenho foram empregados dados de experimentos em túnel de vento e em campo. A fim de incluir os efeitos da turbulência atmosférica na dispersão, dois diferentes modelos de sub-malha associados à Simulação das Grandes Escalas (LES5) foram investigados (Smagorinsky dinâmico e WALE6) e, para a inclusão dos efeitos de obstáculos na dispersão nos modelos Gausseanos, foi empregado o modelo PRIME7. O uso do PRIME também foi proposto para o FPM como uma inovação. De forma geral, os resultados indicam que o uso de CFD/LES é uma ferramenta útil para a investigação da dispersão e o impacto de compostos odorantes em presença de obstáculos e também para desenvolvimento dos modelos Gausseanos. Os resultados também indicam que o modelo FPM proposto, com a inclusão dos efeitos do obstáculo baseado no PRIME também é uma ferramenta muito útil em modelagem da dispersão de odores devido à sua simplicidade e fácil configuração quando comparado a modelos mais complexos como CFD e mesmo os modelos regulatórios AERMOD e CALPUFF. A grande vantagem do FPM é a possibilidade de estimar-se o fator de intermitência e a relação pico-média (P/M), parâmetros úteis para a avaliação do impacto de odores. Os resultados obtidos no presente trabalho indicam que a determinação dos parâmetros de dispersão para os segmentos de pluma, bem como os parâmetros de tempo longo nas proximidades da fonte e do obstáculo no modelo FPM pode ser melhorada e simulações CFD podem ser usadas como uma ferramenta de desenvolvimento para este propósito. Palavras chave: controle de odor, dispersão, fluidodinâmica computacional, modelagem matemática, modelagem gaussiana de pluma flutuante, simulação de grandes vórtices (LES).

Versão brasileira do Dynamic Gait Index

O Dynamic Gait Index (DGI) é um teste que avalia o equilíbrio e marcha do corpo humano. OBJETIVOS: Os objetivos deste estudo foram adaptar culturalmente o DGI para o português e avaliar a sua confiabilidade. MATERIAL E MÉTODO: Seguiu-se o método de Guillemin et al. (1993) para a adaptação cultural do instrumento. Trata-se de estudo prospectivo em que 46 pacientes foram avaliados na fase de adaptação cultural e os itens que apresentaram 20% ou mais de incompreensão foram reformulados e reaplicados. A versão final do DGI em português foi aplicada em 35 idosos para examinar a confiabilidade intra e inter-observadores. O coeficiente de Spearman foi utilizado para correlacionar os escores inter e intra-observador e o teste de Wilcoxon para comparar as pontuações. A consistência interna foi analisada pelo coeficiente alfa de Cronbach. RESULTADOS: Houve correlações estatisticamente significantes entre os escores obtidos às avaliações inter e intra-observadores para todos os itens (p<0,001), classificadas como boa a muito forte (com de variação de r=0,655 a r=0,951). O DGI mostrou alta consistência interna entre seus itens nas avaliações inter e intra-observadores (variação de µ ou = 0,820 a a=0,894). CONCLUSÃO: O DGI foi adaptado culturalmente para o português brasileiro, mostrando-se um instrumento confiável.

Modelling the Mechanical Behavior of Polymer-Based Nanocomposites

Molecular dynamics simulations were employed to analyze the mechanical properties of polymer-based nanocomposites with varying nanofiber network parameters. The study was focused on nanofiber aspect ratio, concentration and initial orientation. The reinforcing phase affects the behavior of the polymeric nanocomposite. Simulations have shown that the fiber concentration has a significant effect on the properties, with higher loadings resulting in higher stress levels and higher stiffness, matching the general behavior from experimental knowledge in this field. The results also indicate that, within the studied range, the observed effect of the aspect ratio and initial orientation is smaller than that of the concentration, and that these two parameters are interrelated.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

Supercritical CO2 extraction of secondary metabolites from Agaricus blazei: experiments and modelling

The mycelium and young fruiting bodies of Agaricus blazei were submitted to supercritical CO2 extraction, in a modified commercial flow apparatus, at temperatures from 40 to 80 ºC, pressures up to 600 bar and CO2 flow-rates from 2.0 to 9.0 g.min-1. The best extraction conditions of secondary metabolites, whereby the degree of solubilization (g extract/100 g of fungi) is the highest, was obtained with pure CO2 at 400 bar, 70 ºC and a CO2 flow rate of 5.7g.min-1. The extract in that conditions were analysed by GC-Ms. In order to increase the extraction yield of secondary metabolites, which are mostly present in glycolipid fractions, a polar compound (ethanol) was used as co-solvent in the proportions of 5 and 10 % (mol/mol). The presence of ethanol increased the yield when compared with the extraction with pure CO2. Moreover, a simple model was applied to the supercritical CO2 extraction of secondary metabolites from Agaricus blazei.

Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

Tsunami vulnerability assessment of Casablanca-Morocco using numerical modelling and GIS tools

Earthquakes and tsunamis along Morocco's coasts have been reported since historical times. The threat posed by tsunamis must be included in coastal risk studies. This study focuses on the tsunami impact and vulnerability assessment of the Casablanca harbour and surrounding area using a combination of tsunami inundation numerical modelling, field survey data and geographic information system. The tsunami scenario used here is compatible with the 1755 Lisbon event that we considered to be the worst case tsunami scenario. Hydrodynamic modelling was performed with an adapted version of the Cornell Multigrid Coupled Tsunami Model from Cornell University. The simulation covers the eastern domain of the Azores-Gibraltar fracture zone corresponding to the largest tsunamigenic area in the North Atlantic. The proposed vulnerability model attempts to provide an insight into the tsunami vulnerability of building stock. Results in the form of a vulnerability map will be useful for decision makers and local authorities in preventing the community resiliency for tsunami hazards.

Mathematical modelling of supercritical CO2 extraction of volatile oils from aromatic plants

The modelling of the experimental data of the extraction of the volatile oil from six aromatic plants (coriander, fennel, savoury, winter savoury, cotton lavender and thyme) was performed using five mathematical models, based on differential mass balances. In all cases the extraction was internal diffusion controlled and the internal mass transfer coefficienty (k(s)) have been found to change with pressure, temperature and particle size. For fennel, savoury and cotton lavender, the external mass transfer and the equilibrium phase also influenced the second extraction period, since k(s) changed with the tested flow rates. In general, the axial dispersion coefficient could be neglected for the conditions studied, since Peclet numbers were high. On the other hand, the solute-matrix interaction had to be considered in order to ensure a satisfactory description of the experimental data.

Periodic dynamic systems for infected hosts and mosquitoes

A mathematical model for the purpose of analysing the dynamic of the populations of infected hosts anf infected mosquitoes when the populations of mosquitoes are periodic in time is here presented. By the computation of a parameter lambda (the spectral radius of a certain monodromy matrix) one can state that either the infection peters out naturally) (lambda <= 1) or if lambda > 1 the infection becomes endemic. The model generalizes previous models for malaria by considering the case of periodic coefficients; it is also a variation of that for gonorrhea. The main motivation for the consideration of this present model was the recent studies on mosquitoes at an experimental rice irrigation system, in the South-Eastern region of Brazil.

Dynamic equilibrium through reinforcement learning

Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.