Interaction of pulses in the nonlinear Schrödinger model

A study was conducted on the interaction of two pulses in the nonlinear Schrodinger (NLS) model. The presence of different scenarios of the behavior depending on the initial parameters of the pulses, such as the pulse areas, the relative phase shift, the spatial and frequency separations were shown. It was observed that a pure real initial condition of the NLS equation can result in additional moving solitons.

Analytical/numerical hybrid solution for one-dimensional ablation problem

Ablation is a thermal protection process with several applications in engineering, mainly in the field of airspace industry. The use of conventional materials must be quite restricted, because they would suffer catastrophic flaws due to thermal degradation of their structures. However, the same materials can be quite suitable once being protected by well-known ablative materials. The process that involves the ablative phenomena is complex, could involve the whole or partial loss of material that is sacrificed for absorption of energy. The analysis of the ablative process in a blunt body with revolution geometry will be made on the stagnation point area that can be simplified as a one-dimensional plane plate problem, hi this work the Generalized Integral Transform Technique (GITT) is employed for the solution of the non-linear system of coupled partial differential equations that model the phenomena. The solution of the problem is obtained by transforming the non-linear partial differential equation system to a system of coupled first order ordinary differential equations and then solving it by using well-established numerical routines. The results of interest such as the temperature field, the depth and the rate of removal of the ablative material are presented and compared with those ones available in the open literature.

The LQ control problem for Markovian jumps linear systems with horizon defined by stopping times

This paper deals with a stochastic optimal control problem involving discrete-time jump Markov linear systems. The jumps or changes between the system operation modes evolve according to an underlying Markov chain. In the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (TN), or the occurrence of a crucial failure event (τΔ), after which the system is brought to a halt for maintenance. In addition, an intermediary mixed case for which T represents the minimum between TN and τΔ is also considered. These stopping times coincide with some of the jump times of the Markov state and the information available allows the reconfiguration of the control action at each jump time, in the form of a linear feedback gain. The solution for the linear quadratic problem with complete Markov state observation is presented. The solution is given in terms of recursions of a set of algebraic Riccati equations (ARE) or a coupled set of algebraic Riccati equation (CARE).

An active/reactive predispatch model incorporating ramp rate constraints solved by dual decomposition/lagrangian relaxation

The Predispatch model (PD) calculates a short-term generation policy for power systems. In this work a PD model is proposed that improves two modeling aspects generally neglected in the literature: voltage/reactive power constraints and ramp rate constraints for generating units. Reactive power constraints turn the PD into a non-linear problem and the ramp rate constraints couple the problem dynamically in time domain. The solution of the PD is turned into a harder task when such constraints are introduced. The dual decomposition/ lagrangian relaxation technique is used in the solution approach for handing dynamic constraints. As a result the PD is decomposed into a series of independent Optimal Power Flow (FPO) sub problems, in which the reactive power is represented in detail. The solution of the independent FPO is coordinated by means of Lagrange multipliers, so that dynamic constraints are iteratively satisfied. Comparisons between dispatch policies calculated with and without the representation of ramp rate constraints are performed, using the IEEE 30 bus test system. The results point-out the importance of representing such constraints in the generation dispatch policy. © 2004 IEEE.

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Thermoeconomic model considering the environment impacts on thermoelectric power plants: Natural gas versus diesel

In this paper a comparative analysis of the environmental impact caused by the use of natural gas and diesel in thermoelectric power plants utilizing combined cycle is performed. The objective is to apply a thermoeconomical analysis in order to compare the two proposed fuels. In this analysis, a new methodology that incorporates the economical engineering concept to the ecological efficiency once Cardu and Baica [1, 2], which evaluates, in general terms, the environmental impacts caused by CO2, SO2, NOx and Particulate Matter (PM), adopting as reference the air quality standards in vigour is employed. The thermoeconomic model herein proposed utilizes functional diagrams that allow the minimization the Exergetic Manufacturing Cost, which represents the cost of production of electricity incorporating the environmental impact effects to study the performance of the thermoelectric power plant [3,4], It follows that it is possible to determine the environmental impact caused by thermoelectric power plants and, under the ecological standpoint, the use of natural gas as a fuel is the best option compared to the use of the diesel, presenting ecological efficiency values of 0.944 and 0.914 respectively. From the Exergoeconomic point of view of, it was found out that the EMC (Exergetic Manufacturing Cost) is better when natural gas is used as fuel compared to the diesel fuel. Copyright © 2006 by ASME.

Application of ARX neural networks to model the rate of penetration of petroleum wells drilling

Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

Charmed-meson scattering on nucleons in a QCD Coulomb gauge quark model

The scattering of charmed mesons on nucleons is investigated within a chiral quark model inspired on the QCD Hamiltonian in Coulomb gauge. The microscopic model incorporates a longitudinal Coulomb confining interaction derived from a self-consistent quasi-particle approximation to the QCD vacuum, and a traverse hyperfine interaction motivated from lattice simulations of QCD in Coulomb gauge. From the microscopic interactions at the quark level, effective meson-baryon interactions are derived using a mapping formalism that leads to quark-Born diagrams. As an application, the total cross-section of heavy-light D-mesons scattering on nucleons is estimated.

Consequences of quadratic frictional force on the one dimensional bouncing ball model

Some dynamical properties of the one dimensional Fermi accelerator model, under the presence of frictional force are studied. The frictional force is assumed as being proportional to the square particle's velocity. The problem is described by use of a two dimensional non linear mapping, therefore obtained via the solution of differential equations. We confirm that the model experiences contraction of the phase space area and in special, we characterized the behavior of the particle approaching an attracting fixed point. © 2007 American Institute of Physics.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

Optimal Boussinesq model for shallow-water waves interacting with a microstructure

In this paper, we consider the propagation of water waves in a long-wave asymptotic regime, when the bottom topography is periodic on a short length scale. We perform a multiscale asymptotic analysis of the full potential theory model and of a family of reduced Boussinesq systems parametrized by a free parameter that is the depth at which the velocity is evaluated. We obtain explicit expressions for the coefficients of the resulting effective Korteweg-de Vries (KdV) equations. We show that it is possible to choose the free parameter of the reduced model so as to match the KdV limits of the full and reduced models. Hence the reduced model is optimal regarding the embedded linear weakly dispersive and weakly nonlinear characteristics of the underlying physical problem, which has a microstructure. We also discuss the impact of the rough bottom on the effective wave propagation. In particular, nonlinearity is enhanced and we can distinguish two regimes depending on the period of the bottom where the dispersion is either enhanced or reduced compared to the flat bottom case. © 2007 The American Physical Society.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Branch and bound algorithm for transmission network expansion planning using DC model

This paper presents an algorithm to solve the network transmission system expansion planning problem using the DC model which is a mixed non-linear integer programming problem. The major feature of this work is the use of a Branch-and-Bound (B&B) algorithm to directly solve mixed non-linear integer problems. An efficient interior point method is used to solve the non-linear programming problem at each node of the B&B tree. Tests with several known systems are presented to illustrate the performance of the proposed method. ©2007 IEEE.

A structure excited by a DC motor of limited power supply and controlled by a pendulum like device

In this paper, a mathematical model is derived via Lagrange's Equation for a shear building structure that acts as a foundation of a non-ideal direct current electric motor, controlled by a mass loose inside a circular carving. Non-ideal sources of vibrations of structures are those whose characteristics are coupled to the motion of the structure, not being a function of time only as in the ideal case. Thus, in this case, an additional equation of motion is written, related to the motor rotation, coupled to the equation describing the horizontal motion of the shear building. This kind of problem can lead to the so-called Sommerfeld effect: steady state frequencies of the motor will usually increase as more power (voltage) is given to it in a step-by-step fashion. When a resonance condition with the structure is reached, the better part of this energy is consumed to generate large amplitude vibrations of the foundation without sensible change of the motor frequency as before. If additional increase steps in voltage are made, one may reach a situation where the rotor will jump to higher rotation regimes, no steady states being stable in between. As a device of passive control of both large amplitude vibrations and the Sommerfeld effect, a scheme is proposed using a point mass free to bounce back and forth inside a circular carving in the suspended mass of the structure. Numerical simulations of the model are also presented Copyright © 2007 by ASME.

Public-private partnerships for innovation and export development: the Irish model of development

Includes Bibliography