955 resultados para hybrid dynamical system


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When making predictions with complex simulators it can be important to quantify the various sources of uncertainty. Errors in the structural specification of the simulator, for example due to missing processes or incorrect mathematical specification, can be a major source of uncertainty, but are often ignored. We introduce a methodology for inferring the discrepancy between the simulator and the system in discrete-time dynamical simulators. We assume a structural form for the discrepancy function, and show how to infer the maximum-likelihood parameter estimates using a particle filter embedded within a Monte Carlo expectation maximization (MCEM) algorithm. We illustrate the method on a conceptual rainfall-runoff simulator (logSPM) used to model the Abercrombie catchment in Australia. We assess the simulator and discrepancy model on the basis of their predictive performance using proper scoring rules. This article has supplementary material online. © 2011 International Biometric Society.

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This work is concerned with approximate inference in dynamical systems, from a variational Bayesian perspective. When modelling real world dynamical systems, stochastic differential equations appear as a natural choice, mainly because of their ability to model the noise of the system by adding a variation of some stochastic process to the deterministic dynamics. Hence, inference in such processes has drawn much attention. Here a new extended framework is derived that is based on a local polynomial approximation of a recently proposed variational Bayesian algorithm. The paper begins by showing that the new extension of this variational algorithm can be used for state estimation (smoothing) and converges to the original algorithm. However, the main focus is on estimating the (hyper-) parameters of these systems (i.e. drift parameters and diffusion coefficients). The new approach is validated on a range of different systems which vary in dimensionality and non-linearity. These are the Ornstein–Uhlenbeck process, the exact likelihood of which can be computed analytically, the univariate and highly non-linear, stochastic double well and the multivariate chaotic stochastic Lorenz ’63 (3D model). As a special case the algorithm is also applied to the 40 dimensional stochastic Lorenz ’96 system. In our investigation we compare this new approach with a variety of other well known methods, such as the hybrid Monte Carlo, dual unscented Kalman filter, full weak-constraint 4D-Var algorithm and analyse empirically their asymptotic behaviour as a function of observation density or length of time window increases. In particular we show that we are able to estimate parameters in both the drift (deterministic) and the diffusion (stochastic) part of the model evolution equations using our new methods.

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The impact of hybrid erbium-doped fiber amplifier (EDFA)/Raman amplification on a spectrally efficient coherent-wavelength-division-multiplexed (CoWDM) optical communication system is experimentally studied and modeled. Simulations suggested that 23-dB Raman gain over an unrepeatered span of 124 km single-mode fiber would allow a decrease of the mean input power of ~6 dB for a fixed bit-error rate (BER). Experimentally we demonstrated 1.2-dB Q-factor improvement for a 2-Tb/s seven-band CoWDM with backward Raman amplification. The system delivered an optical signal-to-noise ratio of 35 dB at the output of the receiver preamplifier providing a worst-case BER of 2 × 10 -6 over 49 subcarriers at 42.8 Gbaud, leaving a system margin (in terms of Q -factor) of ~4 dB from the forward-error correction threshold.

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This thesis examined solar thermal collectors for use in alternative hybrid solar-biomass power plant applications in Gujarat, India. Following a preliminary review, the cost-effective selection and design of the solar thermal field were identified as critical factors underlying the success of hybrid plants. Consequently, the existing solar thermal technologies were reviewed and ranked for use in India by means of a multi-criteria decision-making method, the Analytical Hierarchy Process (AHP). Informed by the outcome of the AHP, the thesis went on to pursue the Linear Fresnel Reflector (LFR), the design of which was optimised with the help of ray-tracing. To further enhance collector performance, LFR concepts incorporating novel mirror spacing and drive mechanisms were evaluated. Subsequently, a new variant, termed the Elevation Linear Fresnel Reflector (ELFR) was designed, constructed and tested at Aston University, UK, therefore allowing theoretical models for the performance of a solar thermal field to be verified. Based on the resulting characteristics of the LFR, and data gathered for the other hybrid system components, models of hybrid LFR- and ELFR-biomass power plants were developed and analysed in TRNSYS®. The techno-economic and environmental consequences of varying the size of the solar field in relation to the total plant capacity were modelled for a series of case studies to evaluate different applications: tri-generation (electricity, ice and heat), electricity-only generation, and process heat. The case studies also encompassed varying site locations, capacities, operational conditions and financial situations. In the case of a hybrid tri-generation plant in Gujarat, it was recommended to use an LFR solar thermal field of 14,000 m2 aperture with a 3 tonne biomass boiler, generating 815 MWh per annum of electricity for nearby villages and 12,450 tonnes of ice per annum for local fisheries and food industries. However, at the expense of a 0.3 ¢/kWh increase in levelised energy costs, the ELFR increased saving of biomass (100 t/a) and land (9 ha/a). For solar thermal applications in areas with high land cost, the ELFR reduced levelised energy costs. It was determined that off-grid hybrid plants for tri-generation were the most feasible application in India. Whereas biomass-only plants were found to be more economically viable, it was concluded that hybrid systems will soon become cost competitive and can considerably improve current energy security and biomass supply chain issues in India.

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We examine the impact of the fiber type and dispersion management on the performance of a 16 × 40 Gb/s dense wavelength-division-multiplexing nonreturn-to-zero transmission system. The transmission line is composed of G.652 or G.655 fiber with periodic dispersion compensation and hybrid Raman erbium-doped fiber amplifier amplification.

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Direct-drive linear reciprocating compressors offer numerous advantages over conventional counterparts which are usually driven by a rotary induction motor via crank shaft However, to ensure efficient and reliable operation under all conditions, it is essential that the motor current of the linear compressor follows a sinusoidal command profile with a frequency which matches the system resonant frequency. This paper describes a hybrid current controller for the linear compressors. It comprises a conventional proportional-integral (PI) controller, and a B-spline neural network compensator which is trained on-line and in real-time in order to minimize the current tracking error under all conditions with uncertain disturbances. It has been shown that the hybrid current controller has a superior steady-state and transient performance over the conventional carrier based PI controller. The performance of the proposed hybrid controller has been demonstrated by extensive simulations and experiments. It has also been shown that the linear compressor operates stably under the current feedback control and the piston stroke can be adjusted by varying the amplitude of the current command. © 2007 IEEE.

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Fe3O4 GaAs hybrid structures have been studied using reflection high-energy electron diffraction (RHEED), x-ray photoelectron spectroscopy (XPS), x-ray magnetic circular dichroism (XMCD), and low-temperature vibrating-sample magnetometry (VSM). The samples were prepared by oxidizing epitaxial Fe thin films in a partial pressure of 5× 10-5 mbar of oxygen at 500 K for 180 s. Clear RHEED patterns were observed, suggesting the epitaxial growth of Fe oxides with a cubic structure. The XPS spectra show that the oxides were Fe3O4 rather than γ- Fe2O3, as there were no shake-up satellites between the two Fe 2p peaks. This was further confirmed by the XMCD measurements, which show ferromagnetic coupling between the Fe cations, with no evidence of intermixing at the interface. The VSM measurements show that the films have a magnetic uniaxial anisotropy and a "quick" saturation property, with the easy axes along the [011] direction. This detailed study offers further insight into the structure, interface, and magnetic properties of this hybrid Fe3O4 GaAs (100) structure as a promising system for spintronic application. © 2005 American Institute of Physics.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT One of the current research trends in Enterprise Resource Planning (ERP) involves examining the critical factors for its successful implementation. However, such research is limited to system implementation, not focusing on the flexibility of ERP to respond to changes in business. Therefore, this study explores a combination system, made up of an ERP and informality, intended to provide organisations with efficient and flexible performance simultaneously. In addition, this research analyses the benefits and challenges of using the system. The research was based on socio-technical system (STS) theory which contains two dimensions: 1) a technical dimension which evaluates the performance of the system; and 2) a social dimension which examines the impact of the system on an organisation. A mixed method approach has been followed in this research. The qualitative part aims to understand the constraints of using a single ERP system, and to define a new system corresponding to these problems. To achieve this goal, four Chinese companies operating in different industries were studied, all of which faced challenges in using an ERP system due to complexity and uncertainty in their business environments. The quantitative part contains a discrete-event simulation study that is intended to examine the impact of operational performance when a company implements the hybrid system in a real-life situation. Moreover, this research conducts a further qualitative case study, the better to understand the influence of the system in an organisation. The empirical aspect of the study reveals that an ERP with pre-determined business activities cannot react promptly to unanticipated changes in a business. Incorporating informality into an ERP can react to different situations by using different procedures that are based on the practical knowledge of frontline employees. Furthermore, the simulation study shows that the combination system can achieve a balance between efficiency and flexibility. Unlike existing research, which emphasises a continuous improvement in the IT functions of an enterprise system, this research contributes to providing a definition of a new system in theory, which has mixed performance and contains both the formal practices embedded in an ERP and informal activities based on human knowledge. It supports both cost-efficiency in executing business transactions and flexibility in coping with business uncertainty.This research also indicates risks of using the system, such as using an ERP with limited functions; a high cost for performing informally; and a low system acceptance, owing to a shift in organisational culture. With respect to practical contribution, this research suggests that companies can choose the most suitable enterprise system approach in accordance with their operational strategies. The combination system can be implemented in a company that needs to operate a medium amount of volume and variety. By contrast, the traditional ERP system is better suited in a company that operates a high-level volume market, while an informal system is more suitable for a firm with a requirement for a high level of variety.

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We examine impact of the fiber type and nonlinear management over the performance of a 16x40Gb/s DWDM NRZ transmission system. The line is constituted of 3x100km of G.652 or G.655 fiber with hybrid Raman-EDFA amplification.

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This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.