Fibre agglomerate transport in a horizontal flow

An experimental and theoretical study of the transport of mineral wool fibre agglomerates in nuclear power plant containment sumps is being performed. A racetrack channel was devised to provide data for the validation of numerical models, which are intended to model the transport of fibre agglomerates. The racetrack channel provides near uniform and steady conditions that lead to either the sedimentation or suspension of the agglomerates. Various experimental techniques were used to determine the velocity conditions and the distribution of the fibre agglomerates in the channel. The fibre agglomerates are modelled as fluid particles in the Eulerian reference frame. Simulations of pure sedimentation of a known mass and volume of agglomerations show that the transport of the fibre agglomerates can be replicated. The suspension of the fibres is also replicated in the simulations; however, the definition of the fibre agglomerate phase is strongly dependent on the selected density and diameter. Detailed information on the morphology of the fibre agglomerates is lacking for the suspension conditions, as the fibre agglomerates may undergo breakage and erosion. Therefore, ongoing work, which is described here, is being pursued to improve the experimental characterisation of the suspended transport of the fibre agglomerates.

Optical fibre sensors with applications in gas and biological sensing

This thesis describes the study of various grating based optical fibre sensors for applications in refractive index sensing. The sensitivity of these sensors has been studied and in some cases enhanced using novel techniques. The major areas of development are as follows. The sensitivity of long period gratings (LPGs) to surrounding medium refractive index (SRI) for various periods was investigated. The most sensitive period of LPG was found to be around 160 µm and this was due to the core mode coupling to a single cladding mode but phase matching at two wavelength locations, creating two attenuation peaks, close to the waveguide dispersion turning point. Large angle tilted fibre gratings (TFGs) have similar behaviour to LPGs, in that they couple to the co-propagating cladding modes. The tilted structure of the index modulation within the core of the fibre gives rise to a polarisation dependency, differing the large angle TFG from a LPG. Since the large angle TFG couple to the cladding mode they are SRI sensitive, the sensitivity to SRI can be further increased through cladding etching using HF acid. The thinning of the cladding layer caused a reordering of the cladding modes and shifted to more SRI sensitive cladding modes as the investigation discovered. In a SRI range of 1.36 to 1.40 a sensitivity of 506.9 nm/URI was achieved for the etched large angle TFG, which is greater than the dual resonance LPG. UV inscribed LPGs were coated with sol-gel materials with high RIs. The high RI of the coating caused an increase in cladding mode effective index which in turn caused an increase in the LPG sensitivity to SRI. LPGs of various periods of LPG were coated with sol-gel TiO2 and the optimal thickness was found to vary for each period. By coating of the already highly SRI sensitive 160µm period LPG (which is a dual resonance) with a sol-gel TiO2, the SRI sensitivity was further increased with a peak value of 1458 nm/URI, which was an almost 3 fold increase compared to the uncoated LPG. LPGs were also inscribed using a femtosecond laser which produced a highly focused index change which was no uniform throughout the core of the optical fibre. The inscription technique gave rise to a large polarisation sensitivity and the ability to couple to multiple azimuthal cladding mode sets, not seen with uniform UV inscribed gratings. Through coupling of the core mode to multiple sets of cladding modes, attenuation peaks with opposite wavelength shifts for increasing SRI was observed. Through combining this opposite wavelength shifts, a SRI sensitivity was achieved greater than any single observed attenuations peak. The maximum SRI achieved was 1680 nm/URI for a femtosecond inscribed LPG of period 400 µm. Three different types of surface plasmon resonance (SPR) sensors with a multilayer metal top coating were investigated in D shape optical fibre. The sensors could be separated into two types, utilized a pre UV inscribed tilted Bragg grating and the other employed a post UV exposure to generate surface relief grating structure. This surface perturbation aided the out coupling of light from the core but also changed the sensing mechanism from SPR to localised surface plasmon resonance (LSPR). This greatly increased the SRI sensitivity, compared to the SPR sensors; with the gold coated top layer surface relief sensor producing the largest SRI sensitivity of 2111.5nm/URI was achieved. While, the platinum and silver coated top layer surface relief sensors also gave high SRI sensitivities but also the ability to produce resonances in air (not previously seen with the SPR sensors). These properties were employed in two applications. The silver and platinum surface relief devices were used as gas sensors and were shown to be capable of detecting the minute RI change of different gases. The calculated maximum sensitivities produced were 1882.1dB/URI and 1493.5nm/URI for silver and platinum, respectively. Using a DFB laser and power meter a cheap alternative approach was investigated which showed the ability of the sensors to distinguish between different gases and flow rates of those gases. The gold surface relief sensor was coated in a with a bio compound called an aptamer and it was able to detect various concentrations of a biological compound called Thrombin, ranging from 1mM to as low as 10fM. A solution of 2M NaCl was found to give the best stripping results for Thrombin from the aptamer and showed the reusability of the sensor. The association and disassociation constants were calculated to be 1.0638×106Ms-1 and 0.2482s-1, respectively, showing the high affinity of the Aptamer to thrombin. This supports existing working stating that aptamers could be alternative to enzymes for chemical detection and also helps to explain the low detection limit of the gold surface relief sensor.

Optic flow in human vision: MEG reveals a foveo-fugal bias in V1, specialization for spiral space in hMSTs, and global motion sensitivity in the IPS

Abstract We recorded MEG responses from 17 participants viewing random-dot patterns simulating global optic flow components (expansion, contraction, rotation, deformation, and translation) and a random motion control condition. Theta-band (3–7 Hz), MEG signal power was greater for expansion than the other optic flow components in a region concentrated along the calcarine sulcus, indicating an ecologically valid, foveo-fugal bias for unidirectional motion sensors in V1. When the responses to the optic flow components were combined, a decrease in MEG beta-band (17–23 Hz) power was found in regions extending beyond the calcarine sulcus to the posterior parietal lobe (inferior to IPS), indicating the importance of structured motion in this region. However, only one cortical area, within or near the V5/hMT+ complex, responded to all three spiral-space components (expansion, contraction, and rotation) and showed no selectivity for global translation or deformation: we term this area hMSTs. This is the first demonstration of an exclusive region for spiral space in the human brain and suggests a functional role better suited to preliminary analysis of ego-motion than surface pose, which would involve deformation. We also observed that the rotation condition activated the cerebellum, suggesting its involvement in visually mediated control of postural adjustment.

A micro gas turbines for UK domestic combined heat and power

Various micro-radial compressor configurations were investigated using one-dimensional meanline and computational fluid dynamics (CFD) techniques for use in a micro gas turbine (MGT) domestic combined heat and power (DCHP) application. Blade backsweep, shaft speed, and blade height were varied at a constant pressure ratio. Shaft speeds were limited to 220 000 r/min, to enable the use of a turbocharger bearing platform. Off-design compressor performance was established and used to determine the MGT performance envelope; this in turn was used to assess potential cost and environmental savings in a heat-led DCHP operating scenario within the target market of a detached family home. A low target-stage pressure ratio provided an opportunity to reduce diffusion within the impeller. Critically for DCHP, this produced very regular flow, which improved impeller performance for a wider operating envelope. The best performing impeller was a low-speed, 170 000 r/min, low-backsweep, 15° configuration producing 71.76 per cent stage efficiency at a pressure ratio of 2.20. This produced an MGT design point system efficiency of 14.85 per cent at 993 W, matching prime movers in the latest commercial DCHP units. Cost and CO2 savings were 10.7 per cent and 6.3 per cent, respectively, for annual power demands of 17.4 MWht and 6.1 MWhe compared to a standard condensing boiler (with grid) installation. The maximum cost saving (on design point) was 14.2 per cent for annual power demands of 22.62 MWht and 6.1 MWhe corresponding to an 8.1 per cent CO2 saving. When sizing, maximum savings were found with larger heat demands. When sized, maximum savings could be made by encouraging more electricity export either by reducing household electricity consumption or by increasing machine efficiency.

A probabilistic model for trust and reputation

This paper concerns the problem of agent trust in an electronic market place. We maintain that agent trust involves making decisions under uncertainty and therefore the phenomenon should be modelled probabilistically. We therefore propose a probabilistic framework that models agent interactions as a Hidden Markov Model (HMM). The observations of the HMM are the interaction outcomes and the hidden state is the underlying probability of a good outcome. The task of deciding whether to interact with another agent reduces to probabilistic inference of the current state of that agent given all previous interaction outcomes. The model is extended to include a probabilistic reputation system which involves agents gathering opinions about other agents and fusing them with their own beliefs. Our system is fully probabilistic and hence delivers the following improvements with respect to previous work: (a) the model assumptions are faithfully translated into algorithms; our system is optimal under those assumptions, (b) It can account for agents whose behaviour is not static with time (c) it can estimate the rate with which an agent's behaviour changes. The system is shown to significantly outperform previous state-of-the-art methods in several numerical experiments. Copyright © 2010, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

Optimal designs of collaborative relay-assisted multiuser beamforming for cellular systems

With careful calculation of signal forwarding weights, relay nodes can be used to work collaboratively to enhance downlink transmission performance by forming a virtual multiple-input multiple-output beamforming system. Although collaborative relay beamforming schemes for single user have been widely investigated for cellular systems in previous literatures, there are few studies on the relay beamforming for multiusers. In this paper, we study the collaborative downlink signal transmission with multiple amplify-and-forward relay nodes for multiusers in cellular systems. We propose two new algorithms to determine the beamforming weights with the same objective of minimizing power consumption of the relay nodes. In the first algorithm, we aim to guarantee the received signal-to-noise ratio at multiusers for the relay beamforming with orthogonal channels. We prove that the solution obtained by a semidefinite relaxation technology is optimal. In the second algorithm, we propose an iterative algorithm that jointly selects the base station antennas and optimizes the relay beamforming weights to reach the target signal-to-interference-and-noise ratio at multiusers with nonorthogonal channels. Numerical results validate our theoretical analysis and demonstrate that the proposed optimal schemes can effectively reduce the relay power consumption compared with several other beamforming approaches. © 2012 John Wiley & Sons, Ltd.

A variational conjugate gradient method for determining the fluid velocity of a slow viscous flow

The problem considered is that of determining the fluid velocity for linear hydrostatics Stokes flow of slow viscous fluids from measured velocity and fluid stress force on a part of the boundary of a bounded domain. A variational conjugate gradient iterative procedure is proposed based on solving a series of mixed well-posed boundary value problems for the Stokes operator and its adjoint. In order to stabilize the Cauchy problem, the iterations are ceased according to an optimal order discrepancy principle stopping criterion. Numerical results obtained using the boundary element method confirm that the procedure produces a convergent and stable numerical solution.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Probabilistic control for uncertain systems

In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the probabilistic models of both the forward and inverse dynamics are estimated such that they are dependent on the state and the control input. The optimal control strategy is then derived which minimizes uncertainty of the closed loop system. In the absence of reliable plant models, the proposed control algorithm incorporates uncertainties in model parameters, observations, and latent processes. The local stability of the closed loop system has been established. The efficacy of the control algorithm is demonstrated on two nonlinear stochastic control examples with additive and multiplicative noise.

A probabilistic indirect adaptive control for systems with input-dependent noise

A probabilistic indirect adaptive controller is proposed for the general nonlinear multivariate class of discrete time system. The proposed probabilistic framework incorporates input–dependent noise prediction parameters in the derivation of the optimal control law. Moreover, because noise can be nonstationary in practice, the proposed adaptive control algorithm provides an elegant method for estimating and tracking the noise. For illustration purposes, the developed method is applied to the affine class of nonlinear multivariate discrete time systems and the desired result is obtained: the optimal control law is determined by solving a cubic equation and the distribution of the tracking error is shown to be Gaussian with zero mean. The efficiency of the proposed scheme is demonstrated numerically through the simulation of an affine nonlinear system.

Fully probabilistic control design in an adaptive critic framework

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem. In particular very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic contro algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this short paper.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Data Flow Analysis and the Linear Programming Model

* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.be

A comparison of in situ constant and falling head permeameter tests to assess the distribution of clogging within horizontal subsurface flow constructed wetlands

Clogging is the main operational problem associated with horizontal subsurface flow constructed wetlands (HSSF CWs). The measurement of saturated hydraulic conductivity has proven to be a suitable technique to assess clogging within HSSF CWs. The vertical and horizontal distribution of hydraulic conductivity was assessed in two full-scale HSSF CWs by using two different in situ permeameter methods (falling head (FH) and constant head (CH) methods). Horizontal hydraulic conductivity profiles showed that both methods are correlated by a power function (FH= CH 0.7821, r 2=0.76) within the recorded range of hydraulic conductivities (0-70 m/day). However, the FH method provided lower values of hydraulic conductivity than the CH method (one to three times lower). Despite discrepancies between the magnitudes of reported readings, the relative distribution of clogging obtained via both methods was similar. Therefore, both methods are useful when exploring the general distribution of clogging and, specially, the assessment of clogged areas originated from preferential flow paths within full-scale HSSF CWs. Discrepancy between methods (either in magnitude and pattern) aroused from the vertical hydraulic conductivity profiles under highly clogged conditions. It is believed this can be attributed to procedural differences between the methods, such as the method of permeameter insertion (twisting versus hammering). Results from both methods suggest that clogging develops along the shortest distance between water input and output. Results also evidence that the design and maintenance of inlet distributors and outlet collectors appear to have a great influence on the pattern of clogging, and hence the asset lifetime of HSSF CWs. © Springer Science+Business Media B.V. 2011.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.