942 resultados para Electrical impedance tomography, Calderon problem, factorization method
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Integration of a piezoelectric high frequency ultrasound (HFUS) array with a microfabricated application specific integrated circuit (ASIC) performing a range of functions has several advantages for ultrasound imaging. The number of signal cables between the array/electronics and the data acquisition / imaging system can be reduced, cutting costs and increasing functionality. Electrical impedance matching is also simplified and the same approach can reduce overall system dimensions for applications such as endoscopic ultrasound. The work reported in this paper demonstrates early ASIC operation with a piezocomposite HFUS array operating at approximately 30 MHz. The array was tested in three different modes. Clear signals were seen in catch-mode, with an external transducer as a source of ultrasound, and in pitch-mode with the external transducer as a receiver. Pitch-catch mode was also tested successfully, using sequential excitation on three array elements, and viable signals were detected. However, these were relatively small and affected by interference from mixed-signal sources in the ASIC. Nevertheless, the functionality and compatibility of the two main components of an integrated HFUS - ASIC device have been demonstrated and the means of further optimization are evident.
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We conjugated 2-(hexylthio)thiophene with bipyridine to construct a new heteroleptic polypyridyl ruthenium sensitizer exhibiting a charge-transfer band at 550 nm with a molar extinction coefficient of 18.7 x 10(3) M-1 cm(-1). In contrast to its analogues Z907 and C101, a mesoporous titania film stained with this new sensitizer featured a short light absorption length, allowing for the use of a thin photoactive layer for efficient light-harvesting and conversion of solar energy to electricity. With a preliminary testing, we have reached 11.4% overall power conversion efficiency measured at the air mass 1.5 global conditions. Transient photoelectrical decays and electrical impedance spectra were analyzed to picture the intrinsic physics of temperature-dependent photovoltage and photocurrent.
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Six organic dyes with different conjugated linkers such as furan, bifuran, thiophene, bithiophene, selenophene, and biselenophene have been prepared in combination with the dihexyloxy-substituted triphenylamine donor and the cyanoacrylic acid acceptor. In conjunction with an acetonitrile-based electrolyte and a solvent-free ionic liquid electrolyte, these dyes exhibit 6.88-7.77% and 6.39-7.00% efficiencies, respectively. We have demonstrated that furan and selenophene can be employed as building blocks of sensitizers in stable solar cells for the first time. We have also studied the influence of heteroatoms on photocurrents and photovoltages with the aid of quantum calculations and transient photoelectrical decay measurements. Temperature-dependent electrical impedance experiments have shown that a relatively low external quantum efficiency of the dye with biselenophene linker is not related to the charge collection yield in the case of an acetonitrile electrolyte.
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Since C.L. Hearn presented the concept of flow unit in 1984, its generation mechanisms and controlling factors have been studied in many aspects using different methods by researchers. There are some basic methods to do the research, and there are several concepts and classification standards about flow unit. Based on previous achievements and using methodologies from sedimentary geology, geophysics, seismic stratigraphy, and reservoir engineering, the author systemically studies the factors controlling flow unit, puts forward a series of methods for recognition, classification and evaluation of flow unit. The results obtained in this paper have important significance not only for understanding the flow unit, but also for revealing the distribution of remaining oil. As a case, this paper deals with the reservoir rocks in Guantao Group of Gudong Oilfield. Zhanhua Sag, Jiyang Depression in Bohaiwan Basin. Based on the study of stratigraphic, depositional and structural characteristics, the author establishes reservoir geological models, reveals the geological characteristics of oil-bearing reservoir of fluvial facies, points out the factors controlling flow unit and geological parameters for classification of flow unit. and summarizes methods and technologies for flow unit study when geological, well-logging and mathematical methods are used. It is the first attempt in literatures to evaluate reservoir by well-logging data constrained by geological conditions, then a well-logging evaluation model can be built. This kind of model is more precise than ever for calculating physical parameters in flow unit. In a well bore, there are six methods to recognize a flow unit. Among them, the activity function and intra-layer difference methods are the most effective. Along a section, the composition type of flow unit can be located according amplitude and impedance on seismic section. Slice method and other methods are used to distinguish flow unit. In order to reveal the distribution laws of flow unit in space, the author create a new method, named combination and composition of flow unit. Based on microscopic pore structure research, the classification methods of flow unit are developed. There are three types of flow unit in the reservoir of fluvial facies. They have their own lithology, petrophysics and pore structure character. Using judgement method, standard functions are built to determine the class of flow unit of fluvial facies. Combining reservoir engineering methods, the distribution laws of remaining oil in different types, or in different part of a flow unit are studied. It is evident that the remaining oil is controlled by the type of flow unit. The author reveals the relationship between flow unit and remaining oil distribution, builds the flowing models, predicts the variation of reservoir parameters in space, put forward different methods developing remaining oil in different flow unit. Especially, based on the results obtained in this paper, some suggestions for the adjustment of the developing flow units have been applied in Districts No.4 and No.7, and good results have been yielded. So, the results of this paper can guide oil field development. They are useful and significant for developing the remaining oil and enhancing the oil recovery efficiency.
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The processes of seismic wave propagation in phase space and one way wave extrapolation in frequency-space domain, if without dissipation, are essentially transformation under the action of one parameter Lie groups. Consequently, the numerical calculation methods of the propagation ought to be Lie group transformation too, which is known as Lie group method. After a fruitful study on the fast methods in matrix inversion, some of the Lie group methods in seismic numerical modeling and depth migration are presented here. Firstly the Lie group description and method of seismic wave propagation in phase space is proposed, which is, in other words, symplectic group description and method for seismic wave propagation, since symplectic group is a Lie subgroup and symplectic method is a special Lie group method. Under the frame of Hamiltonian, the propagation of seismic wave is a symplectic group transformation with one parameter and consequently, the numerical calculation methods of the propagation ought to be symplectic method. After discrete the wave field in time and phase space, many explicit, implicit and leap-frog symplectic schemes are deduced for numerical modeling. Compared to symplectic schemes, Finite difference (FD) method is an approximate of symplectic method. Consequently, explicit, implicit and leap-frog symplectic schemes and FD method are applied in the same conditions to get a wave field in constant velocity model, a synthetic model and Marmousi model. The result illustrates the potential power of the symplectic methods. As an application, symplectic method is employed to give synthetic seismic record of Qinghai foothills model. Another application is the development of Ray+symplectic reverse-time migration method. To make a reasonable balance between the computational efficiency and accuracy, we combine the multi-valued wave field & Green function algorithm with symplectic reverse time migration and thus develop a new ray+wave equation prestack depth migration method. Marmousi model data and Qinghai foothills model data are processed here. The result shows that our method is a better alternative to ray migration for complex structure imaging. Similarly, the extrapolation of one way wave in frequency-space domain is a Lie group transformation with one parameter Z and consequently, the numerical calculation methods of the extrapolation ought to be Lie group methods. After discrete the wave field in depth and space, the Lie group transformation has the form of matrix exponential and each approximation of it gives a Lie group algorithm. Though Pade symmetrical series approximation of matrix exponential gives a extrapolation method which is traditionally regarded as implicit FD migration, it benefits the theoretic and applying study of seismic imaging for it represent the depth extrapolation and migration method in a entirely different way. While, the technique of coordinates of second kind for the approximation of the matrix exponential begins a new way to develop migration operator. The inversion of matrix plays a vital role in the numerical migration method given by Pade symmetrical series approximation. The matrix has a Toepelitz structure with a helical boundary condition and is easy to inverse with LU decomposition. A efficient LU decomposition method is spectral factorization. That is, after the minimum phase correlative function of each array of matrix had be given by a spectral factorization method, all of the functions are arranged in a position according to its former location to get a lower triangular matrix. The major merit of LU decomposition with spectral factorization (SF Decomposition) is its efficiency in dealing with a large number of matrixes. After the setup of a table of the spectral factorization results of each array of matrix, the SF decomposition can give the lower triangular matrix by reading the table. However, the relationship among arrays is ignored in this method, which brings errors in decomposition method. Especially for numerical calculation in complex model, the errors is fatal. Direct elimination method can give the exact LU decomposition But even it is simplified in our case, the large number of decomposition cost unendurable computer time. A hybrid method is proposed here, which combines spectral factorization with direct elimination. Its decomposition errors is 10 times little than that of spectral factorization, and its decomposition speed is quite faster than that of direct elimination, especially in dealing with a large number of matrix. With the hybrid method, the 3D implicit migration can be expected to apply on real seismic data. Finally, the impulse response of 3D implicit migration operator is presented.
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Neoplastic tissue is typically highly vascularized, contains abnormal concentrations of extracellular proteins (e.g. collagen, proteoglycans) and has a high interstitial fluid pres- sure compared to most normal tissues. These changes result in an overall stiffening typical of most solid tumors. Elasticity Imaging (EI) is a technique which uses imaging systems to measure relative tissue deformation and thus noninvasively infer its mechanical stiffness. Stiffness is recovered from measured deformation by using an appropriate mathematical model and solving an inverse problem. The integration of EI with existing imaging modal- ities can improve their diagnostic and research capabilities. The aim of this work is to develop and evaluate techniques to image and quantify the mechanical properties of soft tissues in three dimensions (3D). To that end, this thesis presents and validates a method by which three dimensional ultrasound images can be used to image and quantify the shear modulus distribution of tissue mimicking phantoms. This work is presented to motivate and justify the use of this elasticity imaging technique in a clinical breast cancer screening study. The imaging methodologies discussed are intended to improve the specificity of mammography practices in general. During the development of these techniques, several issues concerning the accuracy and uniqueness of the result were elucidated. Two new algorithms for 3D EI are designed and characterized in this thesis. The first provides three dimensional motion estimates from ultrasound images of the deforming ma- terial. The novel features include finite element interpolation of the displacement field, inclusion of prior information and the ability to enforce physical constraints. The roles of regularization, mesh resolution and an incompressibility constraint on the accuracy of the measured deformation is quantified. The estimated signal to noise ratio of the measured displacement fields are approximately 1800, 21 and 41 for the axial, lateral and eleva- tional components, respectively. The second algorithm recovers the shear elastic modulus distribution of the deforming material by efficiently solving the three dimensional inverse problem as an optimization problem. This method utilizes finite element interpolations, the adjoint method to evaluate the gradient and a quasi-Newton BFGS method for optimiza- tion. Its novel features include the use of the adjoint method and TVD regularization with piece-wise constant interpolation. A source of non-uniqueness in this inverse problem is identified theoretically, demonstrated computationally, explained physically and overcome practically. Both algorithms were test on ultrasound data of independently characterized tissue mimicking phantoms. The recovered elastic modulus was in all cases within 35% of the reference elastic contrast. Finally, the preliminary application of these techniques to tomosynthesis images showed the feasiblity of imaging an elastic inclusion.
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A method for reconstructing 3D rational B-spline surfaces from multiple views is proposed. The method takes advantage of the projective invariance properties of rational B-splines. Given feature correspondences in multiple views, the 3D surface is reconstructed via a four step framework. First, corresponding features in each view are given an initial surface parameter value (s; t), and a 2D B-spline is fitted in each view. After this initialization, an iterative minimization procedure alternates between updating the 2D B-spline control points and re-estimating each feature's (s; t). Next, a non-linear minimization method is used to upgrade the 2D B-splines to 2D rational B-splines, and obtain a better fit. Finally, a factorization method is used to reconstruct the 3D B-spline surface given 2D B-splines in each view. This surface recovery method can be applied in both the perspective and orthographic case. The orthographic case allows the use of additional constraints in the recovery. Experiments with real and synthetic imagery demonstrate the efficacy of the approach for the orthographic case.
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This paper presents the results of field geophysical testing and laboratory testing of peat from Carn Park and Roosky raised bogs in the Irish Midlands. The motivation for the work was highlight the importance of these areas and to begin to attempt to understand the reasons for the failure of the bogs despite them having surface slopes of some 1°. It was found that the peat is typical of that of Irish raised bogs being up to 8m thick towards the “high” dome of the bogs. The peat is characterised by low density, high water content, high organic content, low undrained shear strength and high compressibility. The peat is also relatively permeable at in situ stress. Geophysical electrical resistivity tomography and ground penetrating radar data shows a clear thinning of the peat in the area of the failures corresponding to a reduction in volume from dewatering by edge drains/peat harvesting. This finding is supported by detailed water content measurements. It was also shown that the peat base topography is relatively flat and indicates that the observed surface movement has come from within the peat rather than from the material below the peat. Potential causes of the failures include conventional slope instability, the effect of seepage forces or the release of built-up gas in the peat mass. Further measurements are required in order to study these in more detail.
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Contaminants discharging from on-site wastewater treatment systems (OSWTSs) can impact groundwater quality, threatening human health and surface water ecosystems. Risk of negative impacts becomes elevated in areas of extreme vulnerability with high water tables, where thin unsaturated intervals limit vadose zone attenuation. A combined geophysical/hydrogeological investigation into the effects of an OSWTS, located over a poorly productive aquifer (PPA) with thin subsoil cover, aimed to characterise effluent impacts on groundwater. Groundwater, sampled from piezometers down-gradient of the OSWTS percolation area displayed spatially erratic, yet temporally consistent, contaminant distributions. Electrical resistivity tomography identified an area of gross groundwater contamination close to the percolation area and, when combined with seismic refraction and water quality data, indicated that infiltrating effluent reaching the water table discharged to a deeper more permeable zone of weathered shale resting on more competent bedrock. Subsurface structure, defined by geophysics, indicated that elevated chemical and microbiological contaminant levels encountered in groundwater samples collected from piezometers, down-gradient of sampling points with lower contaminant levels, corresponded to those locations where piezometers were screened close to the weathered shale/competent rock interface; those immediately up-gradient were too shallow to intercept this interval, and thus the more impacted zone of the contaminant plume. Intermittent occurrence of faecal indicator bacteria more than 100 m down gradient of the percolation area suggested relatively short travel times. Study findings highlight the utility of geophysics as part of multidisciplinary investigations for OSWTS contaminant plume characterisation, while also demonstrating the capacity of effluent discharging to PPAs to impact groundwater quality at distance. Comparable geophysical responses observed in similar settings across Ireland suggest the phenomena observed in this study are more widespread than previously suspected.
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Accurate conceptual models of groundwater systems are essential for correct interpretation of monitoring data in catchment studies. In surface-water dominated hard rock regions, modern ground and surface water monitoring programmes often have very high resolution chemical, meteorological and hydrological observations but lack an equivalent emphasis on the subsurface environment, the properties of which exert a strong control on flow pathways and interactions with surface waters. The reasons for this disparity are the complexity of the system and the difficulty in accurately characterising the subsurface, except locally at outcrops or in boreholes. This is particularly the case in maritime north-western Europe, where a legacy of glacial activity, combined with large areas underlain by heterogeneous igneous and metamorphic bedrock, make the structure and weathering of bedrock difficult to map or model. Traditional approaches which seek to extrapolate information from borehole to field-scale are of limited application in these environments due to the high degree of spatial heterogeneity. Here we apply an integrative and multi-scale approach, optimising and combining standard geophysical techniques to generate a three-dimensional geological conceptual model of the subsurface in a catchment in NE Ireland. Available airborne LiDAR, electromagnetic and magnetic data sets were analysed for the region. At field-scale surface geophysical methods, including electrical resistivity tomography, seismic refraction, ground penetrating radar and magnetic surveys, were used and combined with field mapping of outcrops and borehole testing. The study demonstrates how combined interpretation of multiple methods at a range of scales produces robust three-dimensional conceptual models and a stronger basis for interpreting groundwater and surface water monitoring data.
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This paper presents a new technique for the detectionof islanding conditions in electrical power systems. This problem isespecially prevalent in systems with significant penetrations of distributedrenewable generation. The proposed technique is based onthe application of principal component analysis (PCA) to data setsof wide-area frequency measurements, recorded by phasor measurementunits. The PCA approach was able to detect islandingaccurately and quickly when compared with conventional RoCoFtechniques, as well as with the frequency difference and change-ofangledifference methods recently proposed in the literature. Thereliability and accuracy of the proposed PCA approach is demonstratedby using a number of test cases, which consider islandingand nonislanding events. The test cases are based on real data,recorded from several phasor measurement units located in theU.K. power system.
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In Boolean games, agents try to reach a goal formulated as a Boolean formula. These games are attractive because of their compact representations. However, few methods are available to compute the solutions and they are either limited or do not take privacy or communication concerns into account. In this paper we propose the use of an algorithm related to reinforcement learning to address this problem. Our method is decentralized in the sense that agents try to achieve their goals without knowledge of the other agents’ goals. We prove that this is a sound method to compute a Pareto optimal pure Nash equilibrium for an interesting class of Boolean games. Experimental results are used to investigate the performance of the algorithm.
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Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Geofísica), Universidade de Lisboa, Faculdade de Ciências, 2014
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Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.
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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística, na Especialização de Artes Plásticas na Educação