Scalable harmonization of complex networks with local controllers

Computational and communication complexities call for distributed, robust, and adaptive control. This paper proposes a promising way of bottom-up design of distributed control in which simple controllers are responsible for individual nodes. The overall behavior of the network can be achieved by interconnecting such controlled loops in cascade control for example and by enabling the individual nodes to share information about data with their neighbors without aiming at unattainable global solution. The problem is addressed by employing a fully probabilistic design, which can cope with inherent uncertainties, that can be implemented adaptively and which provide a systematic rich way to information sharing. This paper elaborates the overall solution, applies it to linear-Gaussian case, and provides simulation results.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Análise não-linear do campo de temperaturas desenvolvidas durante a soldagem do tipo TIG contínuo em placas delgadas

This study offers an analytical approach in order to provide a determination of the temperature field developed during the DC TIG welding of a thin plate of aluminum. The non-linear characteristics of the phenomenon, such as the dependence of the thermophysical and mechanical properties with temperature were considered in this study. In addition to the conductive heat exchange process, were taken into account the exchange by natural convection and radiation. A transient analysis is performed in order to obtain the temperature field as a function of time. It is also discussed a three-dimensional modeling of the heat source. The results obtained from the analytical model were be compared with the experimental ones and those available in the literature. The analytical results show a good correlation with the experimental ones available in the literature, thus proving the feasibility and efficiency of the analytical method for the simulation of the heat cycle for this welding process.

Seawater carbonate chemistry and Mytilus edulis biological processes during experiments, 2010

CO2 emissions are leading to an acidification of the oceans. Predicting marine community vulnerability towards acidification is difficult, as adaptation processes cannot be accounted for in most experimental studies. Naturally CO2 enriched sites thus can serve as valuable proxies for future changes in community structure. Here we describe a natural analogue site in the Western Baltic Sea. Seawater pCO2 in Kiel Fjord is elevated for large parts of the year due to upwelling of CO2 rich waters. Peak pCO2 values of >230 Pa (>2300 µatm) and pHNBS values of <7.5 are encountered during summer and autumn, average pCO2 values are ~70 Pa (~700 µatm). In contrast to previously described naturally CO2 enriched sites that have suggested a progressive displacement of calcifying auto- and heterotrophic species, the macrobenthic community in Kiel Fjord is dominated by calcifying invertebrates. We show that blue mussels from Kiel Fjord can maintain control rates of somatic and shell growth at a pCO2 of 142 Pa (1400 µatm, pHNBS = 7.7). Juvenile mussel recruitment peaks during the summer months, when high water pCO2 values of ~100 Pa (~1000 µatm) prevail. Our findings indicate that calcifying keystone species may be able to cope with surface ocean pHNBS values projected for the end of this century when food supply is sufficient. However, owing to non-linear synergistic effects of future acidification and upwelling of corrosive water, peak seawater pCO2 in Kiel Fjord and many other productive estuarine habitats could increase to values >400 Pa (>4000 µatm). These changes will most likely affect calcification and recruitment, and increase external shell dissolution.

Optimising power take-off of an oscillating wave surge converter using high fidelity numerical simulations

Oscillating wave surge converters are a promising technology to harvest ocean wave energy in the near shore region. Although research has been going on for many years, the characteristics of the wave action on the structure and especially the phase relation between the driving force and wave quantities like velocity or surface elevation have not been investigated in detail. The main reason for this is the lack of suitable methods. Experimental investigations using tank tests do not give direct access to overall hydrodynamic loads, only damping torque of a power take off system can be measured directly. Non-linear computational fluid dynamics methods have only recently been applied in the research of this type of devices. This paper presents a new metric named wave torque, which is the total hydrodynamic torque minus the still water pitch stiffness at any given angle of rotation. Changes in characteristics of that metric over a wave cycle and for different power take off settings are investigated using computational fluid dynamics methods. Firstly, it is shown that linearised methods cannot predict optimum damping in typical operating states of OWSCs. We then present phase relationships between main kinetic parameters for different damping levels. Although the flap seems to operate close to resonance, as predicted by linear theory, no obvious condition defining optimum damping is found.

Residence Time Distribution (Rtd) Associated with Statistical Weighted Moments to Fit Mathematical Models Using In Industrial Systems Diagnosis

This work presents a computational, called MOMENTS, code developed to be used in process control to determine a characteristic transfer function to industrial units when radiotracer techniques were been applied to study the unit´s performance. The methodology is based on the measuring the residence time distribution function (RTD) and calculate the first and second temporal moments of the tracer data obtained by two scintillators detectors NaI positioned to register a complete tracer movement inside the unit. Non linear regression technique has been used to fit various mathematical models and a statistical test was used to select the best result to the transfer function. Using the code MOMENTS, twelve different models can be used to fit a curve and calculate technical parameters to the unit.

Atténuation d'effets non linéaires dans les lasers fibrés de haute puissance opérés en régime continu

Les lasers à fibre de haute puissance sont maintenant la solution privilégiée pour les applications de découpe industrielle. Le développement de lasers pour ces applications n’est pas simple en raison des contraintes qu’imposent les normes industrielles. La fabrication de lasers fibrés de plus en plus puissants est limitée par l’utilisation d’une fibre de gain avec une petite surface de mode propice aux effets non linéaires, d’où l’intérêt de développer de nouvelles techniques permettant l’atténuation de ceux-ci. Les expériences et simulations effectuées dans ce mémoire montrent que les modèles décrivant le lien entre la puissance laser et les effets non linéaires dans le cadre de l’analyse de fibres passives ne peuvent pas être utilisés pour l’analyse des effets non linéaires dans les lasers de haute puissance, des modèles plus généraux doivent donc développés. Il est montré que le choix de l’architecture laser influence les effets non linéaires. En utilisant l’équation de Schrödinger non linéaire généralisée, il a aussi été possible de montrer que pour une architecture en co-propagation, la diffusion Raman influence l’élargissement spectral. Finalement, les expériences et les simulations effectuées montrent qu’augmenter la réflectivité nominale et largeur de bande du réseau légèrement réfléchissant de la cavité permet d’atténuer la diffusion Raman, notamment en réduisant le gain Raman effectif.

A Study on the liquefaction risk in seismic design of foundations

A fully coupled non-linear effective stress response finite difference (FD) model is built to survey the counter-intuitive recent findings on the reliance of pore water pressure ratio on foundation contact pressure. Two alternative design scenarios for a benchmark problem are explored and contrasted in the light of construction emission rates using the EFFC-DFI methodology. A strain-hardening effective stress plasticity model is adopted to simulate the dynamic loading. A combination of input motions, contact pressure, initial vertical total pressure and distance to foundation centreline are employed, as model variables, to further investigate the control of permanent and variable actions on the residual pore pressure ratio. The model is verified against the Ghosh and Madabhushi high acceleration field test database. The outputs of this work is aimed to improve the current computer-aided seismic foundation design that relies on ground’s packing state and consistency. The results confirm that on seismic excitation of shallow foundations, the likelihood of effective stress loss is greater in deeper depths and across free field. For the benchmark problem, adopting a shallow foundation system instead of piled foundation benefitted in a 75% less emission rate, a marked proportion of which is owed to reduced materials and haulage carbon cost.

Physical and chemical kinetics of structural build-up of cement suspensions

Abstract : The structural build-up of fresh cement-based materials has a great impact on their structural performance after casting. Accordingly, the mixture design should be tailored to adapt the kinetics of build-up given the application on hand. The rate of structural build-up of cement-based suspensions at rest is a complex phenomenon affected by both physical and chemical structuration processes. The structuration kinetics are strongly dependent on the mixture’s composition, testing parameters, as well as the shear history. Accurate measurements of build-up rely on the efficiency of the applied pre-shear regime to achieve an initial well-dispersed state as well as the applied stress during the liquid-solid transition. Studying the physical and chemical mechanisms of build-up of cement suspensions at rest can enhance the fundamental understanding of this phenomenon. This can, therefore, allow a better control of the rheological and time-dependent properties of cement-based materials. The research focused on the use of dynamic rheology in investigating the kinetics of structural build-up of fresh cement pastes. The research program was conducted in three different phases. The first phase was devoted to evaluating the dispersing efficiency of various disruptive shear techniques. The investigated shearing profiles included rotational, oscillatory, and combination of both. The initial and final states of suspension’s structure, before and after disruption, were determined by applying a small-amplitude oscillatory shear (SAOS). The difference between the viscoelastic values before and after disruption was used to express the degree of dispersion. An efficient technique to disperse concentrated cement suspensions was developed. The second phase aimed to establish a rheometric approach to dissociate and monitor the individual physical and chemical mechanisms of build-up of cement paste. In this regard, the non-destructive dynamic rheometry was used to investigate the evolutions of both storage modulus and phase angle of inert calcium carbonate and cement suspensions. Two independent build-up indices were proposed. The structural build-up of various cement suspensions made with different cement contents, silica fume replacement percentages, and high-range water reducer dosages was evaluated using the proposed indices. These indices were then compared to the well-known thixotropic index (Athix.). Furthermore, the proposed indices were correlated to the decay in lateral pressure determined for various cement pastes cast in a pressure column. The proposed pre-shearing protocol and build-up indices (phases 1 and 2) were then used to investigate the effect of mixture’s parameters on the kinetics of structural build-up in phase 3. The investigated mixture’s parameters included cement content and fineness, alkali sulfate content, and temperature of cement suspension. Zeta potential, calorimetric, spectrometric measurements were performed to explore the corresponding microstructural changes in cement suspensions, such as inter-particle cohesion, rate of Brownian flocculation, and nucleation rate. A model linking the build-up indices and the microstructural characteristics was developed to predict the build-up behaviour of cement-based suspensions The obtained results showed that oscillatory shear may have a greater effect on dispersing concentrated cement suspension than the rotational shear. Furthermore, the increase in induced shear strain was found to enhance the breakdown of suspension’s structure until a critical point, after which thickening effects dominate. An effective dispersing method is then proposed. This consists of applying a rotational shear around the transitional value between the linear and non-linear variations of the apparent viscosity with shear rate, followed by an oscillatory shear at the crossover shear strain and high angular frequency of 100 rad/s. Investigating the evolutions of viscoelastic properties of inert calcite-based and cement suspensions and allowed establishing two independent build-up indices. The first one (the percolation time) can represent the rest time needed to form the elastic network. On the other hand, the second one (rigidification rate) can describe the increase in stress-bearing capacity of formed network due to cement hydration. In addition, results showed that combining the percolation time and the rigidification rate can provide deeper insight into the structuration process of cement suspensions. Furthermore, these indices were found to be well-correlated to the decay in the lateral pressure of cement suspensions. The variations of proposed build-up indices with mixture’s parameters showed that the percolation time is most likely controlled by the frequency of Brownian collisions, distance between dispersed particles, and intensity of cohesion between cement particles. On the other hand, a higher rigidification rate can be secured by increasing the number of contact points per unit volume of paste, nucleation rate of cement hydrates, and intensity of inter-particle cohesion.

Nonparametric Evaluation of Quantitative Traits in Population-Based Association Studies when the Genetic Model is Unknown

Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible multiplicity-adjusted p-values associated with the proposed maximum test.

A matlab-based toolbox for the simulation and design of L1 adaptive controllers

This thesis introduces the L1 Adaptive Control Toolbox, a set of tools implemented in Matlab that aid in the design process of an L1 adaptive controller and enable the user to construct simulations of the closed-loop system to verify its performance. Following a brief review of the existing theory on L1 adaptive controllers, the interface of the toolbox is presented, including a description of the functions accessible to the user. Two novel algorithms for determining the required sampling period of a piecewise constant adaptive law are presented and their implementation in the toolbox is discussed. The detailed description of the structure of the toolbox is provided as well as a discussion of the implementation of the creation of simulations. Finally, the graphical user interface is presented and described in detail, including the graphical design tools provided for the development of the filter C(s). The thesis closes with suggestions for further improvement of the toolbox.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

Controladores repetitivos aplicados a filtros ativos de potência sob variações de carga e de frequência da rede

This work presents the development and modification of techniques to reduce the effects of load variation and mains frequency deviation in repetitive controllers applied to active power filters. To minimize the effects of aperiodic signals resulting from the connection or disconnection of non-linear loads is developed a technique which recognizes linear and nonlinear loads, and operates to reset the controller only when the error due to the transition of considerable value, and the transition is from non-linear to linear load. An algorithm to adapt the gain of the repetitive controller, based on a sigmoid function adaptation, in order to minimize the effects caused by random noise in the measurement system is also used. This work also analyzes the effects of frequency variation and presents the main methods to cope with this situation. Some solutions are the change in the number of samples per period and the variation of the sampling rate. The first has the advantage of using linear design techniques and results in a time invariant system. The second method changes the sampling frequency and leads to a time variant system that demands a difficult analysis of stability. The proposed algorithms were tested using the methods of truncation of the number of samples and the method of changing the sampling rate of the system to compensate possible frequency variations of the grid. Experimental results are presented to validate the proposal.

Comparison of firmness meters for measuring ‘Hass’ avocado fruit firmness

The temporal passage of fruit through the supply chain and the selection of consumable fruit by shoppers depend primarily upon fruit firmness. Traditionally, fruit firmness measuring methods, like Effegi and conical probes, are relatively inefficient and destructive. Simple, accurate and non-damaging methods of measuring fruit firmness are ideally required to help assure eating quality to the consumer without fruit wastage. The firmness of 'Hass' avocado fruit at a range of ripening stages was measured with the various different firmness measuring techniques of the Sinclair iQ Firmness Tester (SIQFT), the Electronic Firmometer (EF), the Analogue Firmness Meter (AFM) and hand squeezing. Measurements were made by each method at different points on the same fruit. Destructive bruise assessment was performed 48 h later, thereby allowing sufficient time for fruit to express any bruising resulting from the act of firmness measurements. Non-linear relationships were determined between fruit firmness values measured with the different techniques. The adjusted R2 for the relationship between the SIQFT and the EF was 91.6%. For the SIQFT and the AFM, the adjusted R2 was 73.7%. It was 77.7% for the SIQFT and hand squeezing. A significantly (P<0.05) high incidence of bruising was associated with firmness assessment by the EF as compared with either the SIQFT or the AFM. Among the methods compared, the SIQFT was non-damaging compared with the EF and relatively efficient for measuring the firmness. This instrument merits consideration as a quality control tool of choice in 'Hass' avocado supply chains.