Review of continuum, finite element and hybrid techniques in the analysis of stress concentrations in structures

When a uniform flow of any nature is interrupted, the readjustment of the flow results in concentrations and rare-factions, so that the peak value of the flow parameter will be higher than that which an elementary computation would suggest. When stress flow in a structure is interrupted, there are stress concentrations. These are generally localized and often large, in relation to the values indicated by simple equilibrium calculations. With the advent of the industrial revolution, dynamic and repeated loading of materials had become commonplace in engine parts and fast moving vehicles of locomotion. This led to serious fatigue failures arising from stress concentrations. Also, many metal forming processes, fabrication techniques and weak-link type safety systems benefit substantially from the intelligent use or avoidance, as appropriate, of stress concentrations. As a result, in the last 80 years, the study and and evaluation of stress concentrations has been a primary objective in the study of solid mechanics. Exact mathematical analysis of stress concentrations in finite bodies presents considerable difficulty for all but a few problems of infinite fields, concentric annuli and the like, treated under the presumption of small deformation, linear elasticity. A whole series of techniques have been developed to deal with different classes of shapes and domains, causes and sources of concentration, material behaviour, phenomenological formulation, etc. These include real and complex functions, conformal mapping, transform techniques, integral equations, finite differences and relaxation, and, more recently, the finite element methods. With the advent of large high speed computers, development of finite element concepts and a good understanding of functional analysis, it is now, in principle, possible to obtain with economy satisfactory solutions to a whole range of concentration problems by intelligently combining theory and computer application. An example is the hybridization of continuum concepts with computer based finite element formulations. This new situation also makes possible a more direct approach to the problem of design which is the primary purpose of most engineering analyses. The trend would appear to be clear: the computer will shape the theory, analysis and design.

Mathematical study of complex networks : brain, internet, and power grid

The dissertation is concerned with the mathematical study of various network problems. First, three real-world networks are considered: (i) the human brain network (ii) communication networks, (iii) electric power networks. Although these networks perform very different tasks, they share similar mathematical foundations. The high-level goal is to analyze and/or synthesis each of these systems from a “control and optimization” point of view. After studying these three real-world networks, two abstract network problems are also explored, which are motivated by power systems. The first one is “flow optimization over a flow network” and the second one is “nonlinear optimization over a generalized weighted graph”. The results derived in this dissertation are summarized below.

Brain Networks: Neuroimaging data reveals the coordinated activity of spatially distinct brain regions, which may be represented mathematically as a network of nodes (brain regions) and links (interdependencies). To obtain the brain connectivity network, the graphs associated with the correlation matrix and the inverse covariance matrix—describing marginal and conditional dependencies between brain regions—have been proposed in the literature. A question arises as to whether any of these graphs provides useful information about the brain connectivity. Due to the electrical properties of the brain, this problem will be investigated in the context of electrical circuits. First, we consider an electric circuit model and show that the inverse covariance matrix of the node voltages reveals the topology of the circuit. Second, we study the problem of finding the topology of the circuit based on only measurement. In this case, by assuming that the circuit is hidden inside a black box and only the nodal signals are available for measurement, the aim is to find the topology of the circuit when a limited number of samples are available. For this purpose, we deploy the graphical lasso technique to estimate a sparse inverse covariance matrix. It is shown that the graphical lasso may find most of the circuit topology if the exact covariance matrix is well-conditioned. However, it may fail to work well when this matrix is ill-conditioned. To deal with ill-conditioned matrices, we propose a small modification to the graphical lasso algorithm and demonstrate its performance. Finally, the technique developed in this work will be applied to the resting-state fMRI data of a number of healthy subjects.

Communication Networks: Congestion control techniques aim to adjust the transmission rates of competing users in the Internet in such a way that the network resources are shared efficiently. Despite the progress in the analysis and synthesis of the Internet congestion control, almost all existing fluid models of congestion control assume that every link in the path of a flow observes the original source rate. To address this issue, a more accurate model is derived in this work for the behavior of the network under an arbitrary congestion controller, which takes into account of the effect of buffering (queueing) on data flows. Using this model, it is proved that the well-known Internet congestion control algorithms may no longer be stable for the common pricing schemes, unless a sufficient condition is satisfied. It is also shown that these algorithms are guaranteed to be stable if a new pricing mechanism is used.

Electrical Power Networks: Optimal power flow (OPF) has been one of the most studied problems for power systems since its introduction by Carpentier in 1962. This problem is concerned with finding an optimal operating point of a power network minimizing the total power generation cost subject to network and physical constraints. It is well known that OPF is computationally hard to solve due to the nonlinear interrelation among the optimization variables. The objective is to identify a large class of networks over which every OPF problem can be solved in polynomial time. To this end, a convex relaxation is proposed, which solves the OPF problem exactly for every radial network and every meshed network with a sufficient number of phase shifters, provided power over-delivery is allowed. The concept of “power over-delivery” is equivalent to relaxing the power balance equations to inequality constraints.

Flow Networks: In this part of the dissertation, the minimum-cost flow problem over an arbitrary flow network is considered. In this problem, each node is associated with some possibly unknown injection, each line has two unknown flows at its ends related to each other via a nonlinear function, and all injections and flows need to satisfy certain box constraints. This problem, named generalized network flow (GNF), is highly non-convex due to its nonlinear equality constraints. Under the assumption of monotonicity and convexity of the flow and cost functions, a convex relaxation is proposed, which always finds the optimal injections. A primary application of this work is in the OPF problem. The results of this work on GNF prove that the relaxation on power balance equations (i.e., load over-delivery) is not needed in practice under a very mild angle assumption.

Generalized Weighted Graphs: Motivated by power optimizations, this part aims to find a global optimization technique for a nonlinear optimization defined over a generalized weighted graph. Every edge of this type of graph is associated with a weight set corresponding to the known parameters of the optimization (e.g., the coefficients). The motivation behind this problem is to investigate how the (hidden) structure of a given real/complex valued optimization makes the problem easy to solve, and indeed the generalized weighted graph is introduced to capture the structure of an optimization. Various sufficient conditions are derived, which relate the polynomial-time solvability of different classes of optimization problems to weak properties of the generalized weighted graph such as its topology and the sign definiteness of its weight sets. As an application, it is proved that a broad class of real and complex optimizations over power networks are polynomial-time solvable due to the passivity of transmission lines and transformers.

A novel trinuclear nickel(II) complex of an unsymmetrical tetradentate ligand involving bridging oxime and acetylacetone functions

A novel trinuclear nickel(II) complex, [Ni-3(L)(2)(H2O)(2)](ClO4)(2), where L is a bridging unsymmetrical tetradentate ligand, involving o-phenylenediamine, diacetyl monoxime and acetylacetone (H2L = 4-[2-(3-hydroxy-1-methyl-but-2-enylideneamino)-phenylimino]-pentan-2- one oxime) has been synthesized and characterized structurally. In the complex, an octahedral Ni( II) centre is held in the middle by two square planar units with the aid of oxime and ketonic bridges. (c) 2007 Elsevier B. V. All rights reserved.

CELLULAR AND DEVELOPMENTAL FUNCTIONS OF THE XENOPUS ARVCF-CATENIN:KAZRIN COMPLEX

Xenopus ARVCF (xARVCF), a member of p120-catenin subfamily, binds cadherin cytoplasmic domains to enhance cadherin metabolic stability, or when dissociated, modulates Rho-family GTPases. We previously found that xARVCF binds directly to Xenopus KazrinA (xKazrinA), a widely expressed, conserved protein that bears little homology to established protein families. xKazrinA is also known to influence keratinocyte proliferation-differentiation and cytoskeletal activity. In my study, I first evaluated the expression pattern of endogenous Kazrin RNA and protein in Xenopus embryogenesis as well as in adult tissues. We then collaboratively predicted the helical structure of Kazrin’s coiled-coil domain, and I obtained evidence of Kazrin’s dimerization/oligomerization. In considering the intracellular localization of the xARVCF-catenin:xKazrin complex, I did not resolve xKazrinA in a larger ternary complex with cadherin, nor did I detect its co-precipitation with core desmosomal components. Instead, screening revealed that xKazrinA binds spectrin. This suggested a potential means by which xKazrinA localizes to cell-cell junctions, and indeed, biochemical assays confirmed a ternary xARVCF:xKazrinA:xβ2-spectrin complex. Functionally, I demonstrated that xKazrin stabilizes cadherins by negatively modulating the RhoA small-GTPase. I further revealed that xKazrinA binds to p190B RhoGAP (an inhibitor of RhoA), and enhances p190B’s association with xARVCF. Supporting their functional interaction in vivo, Xenopus embryos depleted of xKazrin exhibited ectodermal shedding, a phenotype that could be rescued with exogenous xARVCF. Cell shedding appeared to be caused by RhoA activation, which consequently altered actin organization and cadherin function. Indeed, I was capable of rescuing Kazrin depletion with ectopic expression of p190B RhoGAP. In addition, I obtained evidence that xARVCF and xKazrin participate in craniofacial development, with effects observed upon the neural crest. Finally, I found that xKazrinA associates further with delta-catenin and p0071-catenin, but not with p120-catenin, suggesting that Kazrin interacts selectively with additional members of the p120-catenin sub-family. Taken together, my study supports Kazrin’s essential role in development, and reveals KazrinA’s biochemical and functional association with ARVCF-catenin, spectrin and p190B RhoGAP.

A hardware in the loop design methodology for FPGA system and its application to complex functions

In this work, a unified algorithm-architecture-circuit co-design environment for complex FPGA system development is presented. The main objective is to find an efficient methodology for designing a configurable optimized FPGA system by using as few efforts as possible in verification stage, so as to speed up the development period. A proposed high performance FFT/iFFT processor for Multiband Orthogonal Frequency Division Multiplexing Ultra Wideband (MB-OFDM UWB) system design process is given as an example to demonstrate the proposed methodology. This efficient design methodology is tested and considered to be suitable for almost all types of complex FPGA system designs and verifications.

Tables of complex hyperbolic and circular functions,

Bibliography: p. 209-212.

Complex functions with Geogebra

Complex functions, generally feature some interesting peculiarities, seen as extensions real functions, complementing the study of real analysis. However, the visualization of some complex functions properties requires the simultaneous visualization of two-dimensional spaces. The multiple Windows of GeoGebra, combined with its ability of algebraic computation with complex numbers, allow the study of the functions defined from ℂ to ℂ through traditional techniques and by the use of Domain Colouring. Here, we will show how we can use GeoGebra for the study of complex functions, using several representations and creating tools which complement the tools already provided by the software. Our proposals designed for students of the first year of engineering and science courses can and should be used as an educational tool in collaborative learning environments. The main advantage in its use in individual terms is the promotion of the deductive reasoning (conjecture / proof). In performed the literature review few references were found involving this educational topic and by the use of a single software.