Nonlinear Analysis of Shear Dominant Prestressed Concrete Beams using ANSYS

This study reports the details of the finite element analysis of eleven shear critical partially prestressed concrete T-beams having steel fibers over partial or full depth. Prestressed T-beams having a shear span to depth ratio of 2.65 and 1.59 that failed in shear have been analyzed using the ‘ANSYS’ program. The ‘ANSYS’ model accounts for the nonlinearity, such as, bond-slip of longitudinal reinforcement, postcracking tensile stiffness of the concrete, stress transfer across the cracked blocks of the concrete and load sustenance through the bridging action of steel fibers at crack interface. The concrete is modeled using ‘SOLID65’- eight-node brick element, which is capable of simulating the cracking and crushing behavior of brittle materials. The reinforcement such as deformed bars, prestressing wires and steel fibers have been modeled discretely using ‘LINK8’ – 3D spar element. The slip between the reinforcement (rebars, fibers) and the concrete has been modeled using a ‘COMBIN39’- nonlinear spring element connecting the nodes of the ‘LINK8’ element representing the reinforcement and nodes of the ‘SOLID65’ elements representing the concrete. The ‘ANSYS’ model correctly predicted the diagonal tension failure and shear compression failure of prestressed concrete beams observed in the experiment. The capability of the model to capture the critical crack regions, loads and deflections for various types of shear failures in prestressed concrete beam has been illustrated.

New studies on the versatile roles of Polyaniline and its composites in polymer based optoelectronic and energy storage devices

From the early stages of the twentieth century, polyaniline (PANI), a well-known and extensively studied conducting polymer has captured the attention of scientific community owing to its interesting electrical and optical properties. Starting from its structural properties, to the currently pursued optical, electrical and electrochemical properties, extensive investigations on pure PANI and its composites are still much relevant to explore its potentialities to the maximum extent. The synthesis of highly crystalline PANI films with ordered structure and high electrical conductivity has not been pursued in depth yet. Recently, nanostructured PANI and the nanocomposites of PANI have attracted a great deal of research attention owing to the possibilities of applications in optical switching devices, optoelectronics and energy storage devices. The work presented in the thesis is centered around the realization of highly conducting and structurally ordered PANI and its composites for applications mainly in the areas of nonlinear optics and electrochemical energy storage. Out of the vast variety of application fields of PANI, these two areas are specifically selected for the present studies, because of the following observations. The non-linear optical properties and the energy storing properties of PANI depend quite sensitively on the extent of conjugation of the polymer structure, the type and concentration of the dopants added and the type and size of the nano particles selected for making the nanocomposites. The first phase of the work is devoted to the synthesis of highly ordered and conducting films of PANI doped with various dopants and the structural, morphological and electrical characterization followed by the synthesis of metal nanoparticles incorporated PANI samples and the detailed optical characterization in the linear and nonlinear regimes. The second phase of the work comprises the investigations on the prospects of PANI in realizing polymer based rechargeable lithium ion cells with the inherent structural flexibility of polymer systems and environmental safety and stability. Secondary battery systems have become an inevitable part of daily life. They can be found in most of the portable electronic gadgets and recently they have started powering automobiles, although the power generated is low. The efficient storage of electrical energy generated from solar cells is achieved by using suitable secondary battery systems. The development of rechargeable battery systems having excellent charge storage capacity, cyclability, environmental friendliness and flexibility has yet to be realized in practice. Rechargeable Li-ion cells employing cathode active materials like LiCoO2, LiMn2O4, LiFePO4 have got remarkable charge storage capacity with least charge leakage when not in use. However, material toxicity, chance of cell explosion and lack of effective cell recycling mechanism pose significant risk factors which are to be addressed seriously. These cells also lack flexibility in their design due to the structural characteristics of the electrode materials. Global research is directed towards identifying new class of electrode materials with less risk factors and better structural stability and flexibility. Polymer based electrode materials with inherent flexibility, stability and eco-friendliness can be a suitable choice. One of the prime drawbacks of polymer based cathode materials is the low electronic conductivity. Hence the real task with this class of materials is to get better electronic conductivity with good electrical storage capability. Electronic conductivity can be enhanced by using proper dopants. In the designing of rechargeable Li-ion cells with polymer based cathode active materials, the key issue is to identify the optimum lithiation of the polymer cathode which can ensure the highest electronic conductivity and specific charge capacity possible The development of conducting polymer based rechargeable Li-ion cells with high specific capacity and excellent cycling characteristics is a highly competitive area among research and development groups, worldwide. Polymer based rechargeable batteries are specifically attractive due to the environmentally benign nature and the possible constructional flexibility they offer. Among polymers having electrical transport properties suitable for rechargeable battery applications, polyaniline is the most favoured one due to its tunable electrical conducting properties and the availability of cost effective precursor materials for its synthesis. The performance of a battery depends significantly on the characteristics of its integral parts, the cathode, anode and the electrolyte, which in turn depend on the materials used. Many research groups are involved in developing new electrode and electrolyte materials to enhance the overall performance efficiency of the battery. Currently explored electrolytes for Li ion battery applications are in liquid or gel form, which makes well-defined sealing essential. The use of solid electrolytes eliminates the need for containment of liquid electrolytes, which will certainly simplify the cell design and improve the safety and durability. The other advantages of polymer electrolytes include dimensional stability, safety and the ability to prevent lithium dendrite formation. One of the ultimate aims of the present work is to realize all solid state, flexible and environment friendly Li-ion cells with high specific capacity and excellent cycling stability. Part of the present work is hence focused on identifying good polymer based solid electrolytes essential for realizing all solid state polymer based Li ion cells.The present work is an attempt to study the versatile roles of polyaniline in two different fields of technological applications like nonlinear optics and energy storage. Conducting form of doped PANI films with good extent of crystallinity have been realized using a level surface assisted casting method in addition to the generally employed technique of spin coating. Metal nanoparticles embedded PANI offers a rich source for nonlinear optical studies and hence gold and silver nanoparticles have been used for making the nanocomposites in bulk and thin film forms. These PANI nanocomposites are found to exhibit quite dominant third order optical non-linearity. The highlight of these studies is the observation of the interesting phenomenon of the switching between saturable absorption (SA) and reverse saturable absorption (RSA) in the films of Ag/PANI and Au/PANI nanocomposites, which offers prospects of applications in optical switching. The investigations on the energy storage prospects of PANI were carried out on Li enriched PANI which was used as the cathode active material for assembling rechargeable Li-ion cells. For Li enrichment or Li doping of PANI, n-Butyllithium (n-BuLi) in hexanes was used. The Li doping as well as the Li-ion cell assembling were carried out in an argon filled glove box. Coin cells were assembled with Li doped PANI with different doping concentrations, as the cathode, LiPF6 as the electrolyte and Li metal as the anode. These coin cells are found to show reasonably good specific capacity around 22mAh/g and excellent cycling stability and coulombic efficiency around 99%. To improve the specific capacity, composites of Li doped PANI with inorganic cathode active materials like LiFePO4 and LiMn2O4 were synthesized and coin cells were assembled as mentioned earlier to assess the electrochemical capability. The cells assembled using the composite cathodes are found to show significant enhancement in specific capacity to around 40mAh/g. One of the other interesting observations is the complete blocking of the adverse effects of Jahn-Teller distortion, when the composite cathode, PANI-LiMn2O4 is used for assembling the Li-ion cells. This distortion is generally observed, near room temperature, when LiMn2O4 is used as the cathode, which significantly reduces the cycling stability of the cells.

Structural Dynamics Model of a Cartesian Robot

Methods are developed for predicting vibration response characteristics of systems which change configuration during operation. A cartesian robot, an example of such a position-dependent system, served as a test case for these methods and was studied in detail. The chosen system model was formulated using the technique of Component Mode Synthesis (CMS). The model assumes that he system is slowly varying, and connects the carriages to each other and to the robot structure at the slowly varying connection points. The modal data required for each component is obtained experimentally in order to get a realistic model. The analysis results in prediction of vibrations that are produced by the inertia forces as well as gravity and friction forces which arise when the robot carriages move with some prescribed motion. Computer simulations and experimental determinations are conducted in order to calculate the vibrations at the robot end-effector. Comparisons are shown to validate the model in two ways: for fixed configuration the mode shapes and natural frequencies are examined, and then for changing configuration the residual vibration at the end of the mode is evaluated. A preliminary study was done on a geometrically nonlinear system which also has position-dependency. The system consisted of a flexible four-bar linkage with elastic input and output shafts. The behavior of the rocker-beam is analyzed for different boundary conditions to show how some limiting cases are obtained. A dimensional analysis leads to an evaluation of the consequences of dynamic similarity on the resulting vibration.

Nonlinear Device Noise Models:Thermodynamic Requirements

This paper proposes three tests to determine whether a given nonlinear device noise model is in agreement with accepted thermodynamic principles. These tests are applied to several models. One conclusion is that every Gaussian noise model for any nonlinear device predicts thermodynamically impossible circuit behavior: these models should be abandoned. But the nonlinear shot-noise model predicts thermodynamically acceptable behavior under a constraint derived here. Further, this constraint specifies the current noise amplitude at each operating point from knowledge of the device v - i curve alone. For the Gaussian and shot-noise models, this paper shows how the thermodynamic requirements can be reduced to concise mathematical tests involving no approximatio

Constraint satisfaction techniques under uncertain conditions for fault diagnosis in nonlinear dynamic systems

The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Virtualization of seed research: perhaps a continuity model.

The research nurseries serve as a initiative designed for the purpose of contribute to the breakdown of seizure paradigms of knowledge, supported by a theoretical model of discernment that exceed the traditional method of learning in the classroom, to transcend critical insights into transforming the environment under an autonomous space to provide tools essentially scientific, but with ethical criterion and social commitment. Such a conception, however, could be perceived as talkative, and even metaphorical, at the contrast of reality purely versatile in which the neophyte not only tries to get enough of the fruit of knowledge, but also requires that appropriate strategies are put forward to achieve seizure. Then arises, from the formative entelechy the use of technological tools based on virtual learning environments, in order to enhance motivation as an alternative against the blurring of perspectives and the emerging business in some types of nurseries, stranded attitude, that sometimes not far from the master model.

New delay-dependent stability criteria for uncertain neutral systems with mixed time-varying delays and nonlinear perturbations

The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range dependent, and distributeddelay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method

QUAGMIRE v1.3: a quasi-geostrophic model for investigating rotating fluids experiments

QUAGMIRE is a quasi-geostrophic numerical model for performing fast, high-resolution simulations of multi-layer rotating annulus laboratory experiments on a desktop personal computer. The model uses a hybrid finite-difference/spectral approach to numerically integrate the coupled nonlinear partial differential equations of motion in cylindrical geometry in each layer. Version 1.3 implements the special case of two fluid layers of equal resting depths. The flow is forced either by a differentially rotating lid, or by relaxation to specified streamfunction or potential vorticity fields, or both. Dissipation is achieved through Ekman layer pumping and suction at the horizontal boundaries, including the internal interface. The effects of weak interfacial tension are included, as well as the linear topographic beta-effect and the quadratic centripetal beta-effect. Stochastic forcing may optionally be activated, to represent approximately the effects of random unresolved features. A leapfrog time stepping scheme is used, with a Robert filter. Flows simulated by the model agree well with those observed in the corresponding laboratory experiments.

A simple theoretical model for the intensification of tropical cyclones and polar lows

A simple theoretical model for the intensification of tropical cyclones and polar lows is developed using a minimal set of physical assumptions. These disturbances are assumed to be balanced systems intensifying through the WISHE (Wind-Induced Surface Heat Exchange) intensification mechanism, driven by surface fluxes of heat and moisture into an atmosphere which is neutral to moist convection. The equation set is linearized about a resting basic state and solved as an initial-value problem. A system is predicted to intensify with an exponential perturbation growth rate scaled by the radial gradient of an efficiency parameter which crudely represents the effects of unsaturated processes. The form of this efficiency parameter is assumed to be defined by initial conditions, dependent on the nature of a pre-existing vortex required to precondition the atmosphere to a state in which the vortex can intensify. Evaluation of the simple model using a primitive-equation, nonlinear numerical model provides support for the prediction of exponential perturbation growth. Good agreement is found between the simple and numerical models for the sensitivities of the measured growth rate to various parameters, including surface roughness, the rate of transfer of heat and moisture from the ocean surface, and the scale for the growing vortex.

Bayesian estimation and selection of nonlinear vector error correction models: The case of the sugar-ethanol-oil nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Inclusion of nonlinear demand-supply relationships within large-scale partial equilibrium linear programming models

This paper presents a new method for the inclusion of nonlinear demand and supply relationships within a linear programming model. An existing method for this purpose is described first and its shortcomings are pointed out before showing how the new approach overcomes those difficulties and how it provides a more accurate and 'smooth' (rather than a kinked) approximation of the nonlinear functions as well as dealing with equilibrium under perfect competition instead of handling just the monopolistic situation. The workings of the proposed method are illustrated by extending a previously available sectoral model for the UK agriculture.

From a discrete to a continuum model of cell dynamics in one dimension

Multiscale modeling is emerging as one of the key challenges in mathematical biology. However, the recent rapid increase in the number of modeling methodologies being used to describe cell populations has raised a number of interesting questions. For example, at the cellular scale, how can the appropriate discrete cell-level model be identified in a given context? Additionally, how can the many phenomenological assumptions used in the derivation of models at the continuum scale be related to individual cell behavior? In order to begin to address such questions, we consider a discrete one-dimensional cell-based model in which cells are assumed to interact via linear springs. From the discrete equations of motion, the continuous Rouse [P. E. Rouse, J. Chem. Phys. 21, 1272 (1953)] model is obtained. This formalism readily allows the definition of a cell number density for which a nonlinear "fast" diffusion equation is derived. Excellent agreement is demonstrated between the continuum and discrete models. Subsequently, via the incorporation of cell division, we demonstrate that the derived nonlinear diffusion model is robust to the inclusion of more realistic biological detail. In the limit of stiff springs, where cells can be considered to be incompressible, we show that cell velocity can be directly related to cell production. This assumption is frequently made in the literature but our derivation places limits on its validity. Finally, the model is compared with a model of a similar form recently derived for a different discrete cell-based model and it is shown how the different diffusion coefficients can be understood in terms of the underlying assumptions about cell behavior in the respective discrete models.

Solving optimal control problems with state constraints using nonlinear programming and simulation tools

This paper illustrates how nonlinear programming and simulation tools, which are available in packages such as MATLAB and SIMULINK, can easily be used to solve optimal control problems with state- and/or input-dependent inequality constraints. The method presented is illustrated with a model of a single-link manipulator. The method is suitable to be taught to advanced undergraduate and Master's level students in control engineering.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.