Optimization and characterization of femtosecond laser inscribed in-fiber microchannels for liquid sensing

In-fiber microchannels were fabricated directly in standard single mode fiber using the femtosecond laser inscribe and etch technique. This method of creating in-fiber microchannels offers great versatility, since it allows complex three-dimensional structures to be inscribed and then preferentially etched with hydrofluoric acid. In addition, inscription does not require a photosensitive fiber; the modification is induced through nonlinear processes triggered by an ultrashort laser pulse. Four in-fiber microchannel designs were experimentally investigated using this technique - microhole, microslot channel along the core, microslot channel perpendicular to the core and helical channel around the core. Each device design was evaluated through monitoring the optical spectral change while inserting a range of index matching oils into each microchannel; an R.I. sensitivity up to 1.55 dB/RIU was achieved in these initial tests. Furthermore, an all femtosecond laser inscribed Fabry-Pérot-based refractometer with an R.I. sensitivity of 2.75 nm/RIU was also demonstrated. The Fabry-Pérot refractometer was formed by positioning a microchannel between two femtosecond laser inscribed point-by-point fiber Bragg gratings.

Inverse four-wave mixing and self-parametric amplification in optical fibre

An important group of nonlinear processes in optical fibre involve the mixing of four waves due to the intensity dependence of the refractive index. It is customary to distinguish between nonlinear effects that require external/pumping waves (cross-phase modulation and parametric processes such as four-wave mixing) and those arising from self-action of the propagating optical field (self-phase modulation and modulation instability). Here, we present a new nonlinear self-action effect—self-parametric amplification—which manifests itself as optical spectrum narrowing in normal dispersion fibre, leading to very stable propagation with a distinctive spectral distribution. The narrowing results from inverse four-wave mixing, resembling an effective parametric amplification of the central part of the spectrum by energy transfer from the spectral tails. Self-parametric amplification and the observed stable nonlinear spectral propagation with a random temporal waveform can find applications in optical communications and high-power fibre lasers with nonlinear intracavity dynamics.

Stochastically forced dislocation density distribution in plastic deformation

The dynamical evolution of dislocations in plastically deformed metals is controlled by both deterministic factors arising out of applied loads and stochastic effects appearing due to fluctuations of internal stress. Such type of stochastic dislocation processes and the associated spatially inhomogeneous modes lead to randomness in the observed deformation structure. Previous studies have analyzed the role of randomness in such textural evolution but none of these models have considered the impact of a finite decay time (all previous models assumed instantaneous relaxation which is "unphysical") of the stochastic perturbations in the overall dynamics of the system. The present article bridges this knowledge gap by introducing a colored noise in the form of an Ornstein-Uhlenbeck noise in the analysis of a class of linear and nonlinear Wiener and Ornstein-Uhlenbeck processes that these structural dislocation dynamics could be mapped on to. Based on an analysis of the relevant Fokker-Planck model, our results show that linear Wiener processes remain unaffected by the second time scale in the problem but all nonlinear processes, both Wiener type and Ornstein-Uhlenbeck type, scale as a function of the noise decay time τ. The results are expected to ramify existing experimental observations and inspire new numerical and laboratory tests to gain further insight into the competition between deterministic and random effects in modeling plastically deformed samples.

Calcareous nannofossils and C37 alkenones at ODP Site 162-982

During the late Pliocene (~3 to 2.5 Ma), oceanic records of opal and C37 alkenone accumulation from around the world show a secular shift towards lower values in the high latitudes and higher values in the low and mid latitudes. These shifts are broadly coincident with the intensification of northern hemisphere glaciation and are suggestive of changes in export productivity, with potential implications for Pliocene atmospheric carbon dioxide concentrations. The interpretation of a global latitudinal shift in productivity, however, requires testing because of the potential uncertainties associated with site to site comparisons of records that can be influenced by highly nonlinear processes associated with production, export, and preservation. Here, we assess the inferred Pliocene latitudinal productivity shift interpretation by presenting new records of C37 alkenone accumulation from Ocean Drilling Program (ODP) Site 982 in the North Atlantic and biotic assemblages (calcareous nannoplankton) from this site and ODP Site 846 in the eastern tropical Pacific. Our results corroborate the interpretation of C37 alkenone accumulation as a proxy for gross export productivity at these sites, indicating that large-scale productivity decreases at high latitudes and increases at tropical sites are recorded robustly. We conclude that the intensification of northern hemisphere glaciation during the late Pliocene was associated with a profound reorganisation of ocean biogeochemistry.

Resilience of small-scale societies’ livelihoods: a framework for studying the transition from food gathering to food production

The origins of agriculture and the shift from hunting and gathering to committed agriculture is regarded as one of the major transitions in human history. Archeologists and anthropologists have invested significant efforts in explaining the origins of agriculture. A period of gathering intensification and experimentation and pursuing a mixed economic strategy seems the most plausible explanation for the transition to agriculture and provides an approach to study a process in which several nonlinear processes may have played a role. However, the mechanisms underlying the transition to full agriculture are not completely clear. This is partly due to the nature of the archeological record, which registers a practice only once it has become clearly established. Thus, points of transitions have limited visibility and the mechanisms involved in the process are difficult to untangle. The complexity of such transitions also implies that shifts can be distinctively different in particular environments and under varying historical and social conditions. In this paper we discuss some of the elements involved in the transition to food production within the framework of resilience theory. We propose a theoretical conceptual model in which the resilience of livelihood strategies lies at the intersection of three spheres: the environmental, economical, and social domains. Transitions occur when the rate of change, in one or more of these domains, is so elevated or its magnitude so large that the livelihood system is unable to bounce back to its original state. In this situation, the system moves to an alternative stable state, from one livelihood strategy to another.

Theory and application of nonlinear wave propagation phenomena in combined reaction/separation processes

Reaction separation processes, reactive distillation, chromatographic reactor, equilibrium theory, nonlinear waves, process control, observer design, asymptoticaly exact input/output-linearization

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Synchronization processes in nonlinear systems and their relation to cortical oscillatory dynamics

This thesis was focused on theoretical models of synchronization to cortical dynamics as measured by magnetoencephalography (MEG). Dynamical systems theory was used in both identifying relevant variables for brain coordination and also in devising methods for their quantification. We presented a method for studying interactions of linear and chaotic neuronal sources using MEG beamforming techniques. We showed that such sources can be accurately reconstructed in terms of their location, temporal dynamics and possible interactions. Synchronization in low-dimensional nonlinear systems was studied to explore specific correlates of functional integration and segregation. In the case of interacting dissimilar systems, relevant coordination phenomena involved generalized and phase synchronization, which were often intermittent. Spatially-extended systems were then studied. For locally-coupled dissimilar systems, as in the case of cortical columns, clustering behaviour occurred. Synchronized clusters emerged at different frequencies and their boundaries were marked through oscillation death. The macroscopic mean field revealed sharp spectral peaks at the frequencies of the clusters and broader spectral drops at their boundaries. These results question existing models of Event Related Synchronization and Desynchronization. We re-examined the concept of the steady-state evoked response following an AM stimulus. We showed that very little variability in the AM following response could be accounted by system noise. We presented a methodology for detecting local and global nonlinear interactions from MEG data in order to account for residual variability. We found crosshemispheric nonlinear interactions of ongoing cortical rhythms concurrent with the stimulus and interactions of these rhythms with the following AM responses. Finally, we hypothesized that holistic spatial stimuli would be accompanied by the emergence of clusters in primary visual cortex resulting in frequency-specific MEG oscillations. Indeed, we found different frequency distributions in induced gamma oscillations for different spatial stimuli, which was suggestive of temporal coding of these spatial stimuli. Further, we addressed the bursting character of these oscillations, which was suggestive of intermittent nonlinear dynamics. However, we did not observe the characteristic-3/2 power-law scaling in the distribution of interburst intervals. Further, this distribution was only seldom significantly different to the one obtained in surrogate data, where nonlinear structure was destroyed. In conclusion, the work presented in this thesis suggests that advances in dynamical systems theory in conjunction with developments in magnetoencephalography may facilitate a mapping between levels of description int he brain. this may potentially represent a major advancement in neuroscience.

Combining Legendre's Polynomials and Genetic Algorithm in the Solution of Nonlinear Initial-Value Problems

This work develops a method for solving ordinary differential equations, that is, initial-value problems, with solutions approximated by using Legendre's polynomials. An iterative procedure for the adjustment of the polynomial coefficients is developed, based on the genetic algorithm. This procedure is applied to several examples providing comparisons between its results and the best polynomial fitting when numerical solutions by the traditional Runge-Kutta or Adams methods are available. The resulting algorithm provides reliable solutions even if the numerical solutions are not available, that is, when the mass matrix is singular or the equation produces unstable running processes.

Nonlinear spectra of ZnO: reverse saturable, two- and three-photon absorption

We present a broadband (460-980 nm) analysis of the nonlinear absorption processes in bulk ZnO, a large-bandgap material with potential blue-to-UV photonic device applications. Using an optical parametric amplifier we generated tunable 1-kHz repetition rate laser pulses and employed the Z-scan technique to investigate the nonlinear absorption spectrum of ZnO. For excitation wavelengths below 500 nm, we observed reverse saturable absorption due to one-photon excitation of the sample, agreeing with rate-equation modeling. Two-and three-photon absorption were observed from 540 to 980 nm. We also determined the spectral regions exhibiting mixture of nonlinear absorption mechanisms, which were confirmed by photoluminescence measurements. (C) 2010 Optical Society of America

Folding processes and solitary waves in structural geology

Evolution of localized folding patterns in layered elastic and visco-elastic materials is reviewed in the context of compressed geological systems. The thin strut or plate embedded in a visco-elastic medium is used as an archetypal example to describe localized buckles which, in contrast to those from earlier formulations, appear in the absence of triggering imperfections. Structural and material effects are surveyed and important nonlinear characteristics are identified. A brief review of possible methods of analysis is conducted.

A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

A web-based tool to evaluate the iterative processes of direct search methods

Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

Development of fractional order capacitors based on electrolyte processes

In recent years, significant research in the field of electrochemistry was developed. The performance of electrical devices, depending on the processes of the electrolytes, was described and the physical origin of each parameter was established. However, the influence of the irregularity of the electrodes was not a subject of study and only recently this problem became relevant in the viewpoint of fractional calculus. This paper describes an electrolytic process in the perspective of fractional order capacitors. In this line of thought, are developed several experiments for measuring the electrical impedance of the devices. The results are analyzed through the frequency response, revealing capacitances of fractional order that can constitute an alternative to the classical integer order elements. Fractional order electric circuits are used to model and study the performance of the electrolyte processes.