Chaotic Patterns in Aeroelastic Signals

This work presents the analysis of nonlinear aeroelastic time series from wing vibrations due to airflow separation during wind tunnel experiments. Surrogate data method is used to justify the application of nonlinear time series analysis to the aeroelastic system, after rejecting the chance for nonstationarity. The singular value decomposition (SVD) approach is used to reconstruct the state space, reducing noise from the aeroelastic time series. Direct analysis of reconstructed trajectories in the state space and the determination of Poincare sections have been employed to investigate complex dynamics and chaotic patterns. With the reconstructed state spaces, qualitative analyses may be done, and the attractors evolutions with parametric variation are presented. Overall results reveal complex system dynamics associated with highly separated flow effects together with nonlinear coupling between aeroelastic modes. Bifurcations to the nonlinear aeroelastic system are observed for two investigations, that is, considering oscillations-induced aeroelastic evolutions with varying freestream speed, and aeroelastic evolutions at constant freestream speed and varying oscillations. Finally, Lyapunov exponent calculation is proceeded in order to infer on chaotic behavior. Poincare mappings also suggest bifurcations and chaos, reinforced by the attainment of maximum positive Lyapunov exponents. Copyright (C) 2009 F. D. Marques and R. M. G. Vasconcellos.

Evaluation technique for determining wheel performance in the grinding of aerospace materials

Nickel-based super alloys are used in a variety of applications in which high-temperature strength and resistance to creep, corrosion, and oxidation are required, such as in aircraft gas turbines, combustion chambers, and automotive engine valves. The properties that make these materials suitable for these applications also make them difficult to grind. Grinding systems for such materials are often built around vitrified cBN (cubic boron nitride) wheels to realize maximum productivity and minimum cost per part. Conditions that yield the most economical combination of stock removal rate and wheel wear are key to the successful implementation of the grinding system. Identifying the transition point for excessive wheel wear is important. The aim of this study is to compare the performance of different cBN wheels when grinding difficult-to-grind (DTG) materials by determining the 'wheel wear characteristic curve', which correlates the G-ratio to the calculated tangential force per abrasive grain. With the proposed methodology, a threshold force per grit above which the wheel wear rate increases rapidly can be quickly identified. A comparison of performance for two abrasive product formulations in the grinding of three materials is presented. The obtained results can be applied for the development of grinding applications for DTG materials.

Architecture for machining process and production monitoring based in open computer numerical control

This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.

Tool wear aspects when applying high-speed tapping on grey cast iron

Tool wear is a very important subject affecting the economics of machining, especially in tapping, since it is one of the last operations to be performed within most operation sequences. In the present study, some aspects of tapping such as the mechanisms and types of wear were investigated in taps working at conventional and high-speed cutting (HSC). Additionally, different types of coatings and cooling /lubrication conditions were used. The tapping operation (M8 x 1.25) was performed in through holes with two cutting speeds (30 and 60 m/min) in grey cast iron GG25. Lubrication conditions tested were dry and with minimal quantity of lubricant. Tap materials were manufactured by powder metallurgy and coated with (TiAl)N and with TiCN. A go-non-go gauge criterion was used to assess tool life. The wear and surface aspects of the tools and workpiece were evaluated by scanning electron microscopy and energy dissipation spectroscopy. Torque signals were also measured during the tests. The main wear mechanism observed was adhesion, although some abrasion and diffusion may also have occurred, and the main type of wear was flank wear. The adhesion of workpiece material on the tool was the main and decisive factor ending tool life. Tool coatings proved to be an efficient way to minimize adhesion. Torque signals followed the same pattern as the flank wear and no significant change was observed when the cutting speed was increased.

An Extension of the Invariance Principle for a Class of Differential Equations with Finite Delay

An extension of the uniform invariance principle for ordinary differential equations with finite delay is developed. The uniform invariance principle allows the derivative of the auxiliary scalar function V to be positive in some bounded sets of the state space while the classical invariance principle assumes that. V <= 0. As a consequence, the uniform invariance principle can deal with a larger class of problems. The main difficulty to prove an invariance principle for functional differential equations is the fact that flows are defined on an infinite dimensional space and, in such spaces, bounded solutions may not be precompact. This difficulty is overcome by imposing the vector field taking bounded sets into bounded sets.

Diffusive Synchronization of Hyperchaotic Lorenz Systems

The synchronizing properties of two diffusively coupled hyperchaotic Lorenz 4D systems are investigated by calculating the transverse Lyapunov exponents and by observing the phase space trajectories near the synchronization hyperplane. The effect of parameter mismatch is also observed. A simple electrical circuit described by the Lorenz 4D equations is proposed. Some results from laboratory experiments with two coupled circuits are presented. Copyright (C) 2009 Ruy Barboza.

Trajectory Sensitivity Method and Master-Slave Synchronization to Estimate Parameters of Nonlinear Systems

A combination of trajectory sensitivity method and master-slave synchronization was proposed to parameter estimation of nonlinear systems. It was shown that master-slave coupling increases the robustness of the trajectory sensitivity algorithm with respect to the initial guess of parameters. Since synchronization is not a guarantee that the estimation process converges to the correct parameters, a conditional test that guarantees that the new combined methodology estimates the true values of parameters was proposed. This conditional test was successfully applied to Lorenz's and Chua's systems, and the proposed parameter estimation algorithm has shown to be very robust with respect to parameter initial guesses and measurement noise for these examples. Copyright (C) 2009 Elmer P. T. Cari et al.

Brittle and ductile removal modes observed during diamond turning of carbon nanotube composites

Ultraprecision diamond turning was used to evaluate the surface integrity of a carbon nanotube (CNT) composite as a function of the cutting conditions and the percentage of CNT in the epoxy matrix. The effects of cutting conditions on the chip morphology and surface roughness were analysed. The results showed that an increase in the percentage of CNT may influence the mechanism of material removal and consequently improve the quality of the machined surface. When smaller quantities of CNT (0.02 and 0.07 wt %) are present in the matrix, microcracks form within the cutting grooves (perpendicular to the cutting direction). This indicates that the amount of CNT on the epoxy matrix may have a direct influence on the mechanical properties of these materials. Chips removed from the CNT composite samples were analysed by scanning electron microscopy in order to correlate the material removal mechanism and the surface generation process. The area average surface roughness Sa was influenced by the material removal mechanism (Sa ranging from 0.28 to 1.1 mu m).

Phase transformation and residual stress probed by Raman spectroscopy in diamond-turned single crystal silicon

Single-point diamond turning of monocrystalline semiconductors is an important field of research within brittle materials machining. Monocrystalline silicon samples with a (100) orientation have been diamond turned under different cutting conditions (feed rate and depth of cut). Micro-Raman spectroscopy and atomic force microscopy have been used to assess structural alterations and surface finish of the samples diamond turned under ductile and brittle modes. It was found that silicon undergoes a phase transformation when machined in the ductile mode. This phase transformation is evidenced by the creation of an amorphous surface layer after machining which has been probed by Raman scattering. Compressive residual stresses are estimated for the machined surface and it is observed that they decrease with an increase in the feed rate and depth of cut. This behaviour has been attributed to the formation of subsurface cracks when the feed rate is higher than or equal to 2.5 mu m/rev. The surface roughness was observed to vary with the feed rate and the depth of cut. An increase in the surface roughness was influenced by microcrack formation when the feed rate reached 5.0 mu m/rev. Furthermore, a high-pressure phase transformation induced by the tool/material interaction and responsible for the ductile response of this typical brittle material is discussed based upon the presented Raman spectra. The application of this machining technology finds use for a wide range of high quality components, for example the creation of a micrometre-range channel for microfluidic devices as well as microlenses used in the infrared spectrum range.

Effects of Variations in Nonlinear Damping Coefficients on the Parametric Vibration of a Cantilever Beam with a Lumped Mass

Uncertainties in damping estimates can significantly affect the dynamic response of a given flexible structure. A common practice in linear structural dynamics is to consider a linear viscous damping model as the major energy dissipation mechanism. However, it is well known that different forms of energy dissipation can affect the structure's dynamic response. The major goal of this paper is to address the effects of the turbulent frictional damping force, also known as drag force on the dynamic behavior of a typical flexible structure composed of a slender cantilever beam carrying a lumped-mass on the tip. First, the system's analytical equation is obtained and solved by employing a perturbation technique. The solution process considers variations of the drag force coefficient and its effects on the system's response. Then, experimental results are presented to demonstrate the effects of the nonlinear quadratic damping due to the turbulent frictional force on the system's dynamic response. In particular, the effects of the quadratic damping on the frequency-response and amplitude-response curves are investigated. Numerically simulated as well as experimental results indicate that variations on the drag force coefficient significantly alter the dynamics of the structure under investigation. Copyright (c) 2008 D. G. Silva and P. S. Varoto.

Time-frequency and time-scale analysis of Barkhausen noise signals

Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.

Contribution margin model applied to the marketing planning of a container liner carrier

The implementation of confidential contracts between a container liner carrier and its customers, because of the Ocean Shipping Reform Act (OSRA) 1998, demands a revision in the methodology applied in the carrier's planning of marketing and sales. The marketing and sales planning process should be more scientific and with a better use of operational research tools considering the selection of the customers under contracts, the duration of the contracts, the freight, and the container imbalances of these contracts are basic factors for the carrier's yield. This work aims to develop a decision support system based on a linear programming model to generate the business plan for a container liner carrier, maximizing the contribution margin of its freight.

Multidisciplinary optimization of a catamaran's hydrofoil design with dynamic response surface and distributive processing

This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.

The Effect of Spatial Scale on Predicting Time Series: A Study on Epidemiological System Identification

A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.