QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

Technological enhancements to optometric clinical tests

A sizeable amount of the testing in eye care, requires either the identification of targets such as letters to assess functional vision, or the subjective evaluation of imagery by an examiner. Computers can render a variety of different targets on their monitors and can be used to store and analyse ophthalmic images. However, existing computing hardware tends to be large, screen resolutions are often too low, and objective assessments of ophthalmic images unreliable. Recent advances in mobile computing hardware and computer-vision systems can be used to enhance clinical testing in optometry. High resolution touch screens embedded in mobile devices, can render targets at a wide variety of distances and can be used to record and respond to patient responses, automating testing methods. This has opened up new opportunities in computerised near vision testing. Equally, new image processing techniques can be used to increase the validity and reliability of objective computer vision systems. Three novel apps for assessing reading speed, contrast sensitivity and amplitude of accommodation were created by the author to demonstrate the potential of mobile computing to enhance clinical measurement. The reading speed app could present sentences effectively, control illumination and automate the testing procedure for reading speed assessment. Meanwhile the contrast sensitivity app made use of a bit stealing technique and swept frequency target, to rapidly assess a patient’s full contrast sensitivity function at both near and far distances. Finally, customised electronic hardware was created and interfaced to an app on a smartphone device to allow free space amplitude of accommodation measurement. A new geometrical model of the tear film and a ray tracing simulation of a Placido disc topographer were produced to provide insights on the effect of tear film breakdown on ophthalmic images. Furthermore, a new computer vision system, that used a novel eye-lash segmentation technique, was created to demonstrate the potential of computer vision systems for the clinical assessment of tear stability. Studies undertaken by the author to assess the validity and repeatability of the novel apps, found that their repeatability was comparable to, or better, than existing clinical methods for reading speed and contrast sensitivity assessment. Furthermore, the apps offered reduced examination times in comparison to their paper based equivalents. The reading speed and amplitude of accommodation apps correlated highly with existing methods of assessment supporting their validity. Their still remains questions over the validity of using a swept frequency sine-wave target to assess patient’s contrast sensitivity functions as no clinical test provides the range of spatial frequencies and contrasts, nor equivalent assessment at distance and near. A validation study of the new computer vision system found that the authors tear metric correlated better with existing subjective measures of tear film stability than those of a competing computer-vision system. However, repeatability was poor in comparison to the subjective measures due to eye lash interference. The new mobile apps, computer vision system, and studies outlined in this thesis provide further insight into the potential of applying mobile and image processing technology to enhance clinical testing by eye care professionals.

Impact of driver behaviour on availability of electric vehicle stored energy for STOR

As take up of low carbon vehicles increase, there is interest in using the energy stored in the vehicles to help maintain system frequency through ancillary services on the electricity grid system. Research into this area is generally classed as vehicle-to-grid research. In theory, the energy available from electric vehicles could be directly correlated to the vehicle's state of charge (SoC) and battery capacity during the time the car is parked and plugged in. However, not all the energy in the vehicle may be used, as some capacity is required by the driver for their next journey. As such, this paper uses data captured as part of a large scale electric vehicle trial to investigate the effect of three different types of driver routine on vehicle-to-grid availability. Each driver's behaviour is analysed to assess the energy that is available for STOR, with follow on journey requirements also considered.

Elasto-plastic impact of fine particles and fragmentation of small agglomerates

Surface deposition of dense aerosol particles is of major concern in the nuclear industry for safety assessment. This study presents theoretical investigations and computer simulations of single gas-born U3O8 particles impacting with the in-reactor surface and the fragmentation of small agglomerates. A theoretical model for elasto-plastic spheres has been developed and used to analyse the force-displacement and force-time relationships. The impulse equations, based on Newton's second law, are applied to govern the tangential bouncing behaviour. The theoretical model is then incorporated into the Distinct Element Method code TRUBAL in order to perform computer simulated tests of particle collisions. A comparison of simulated results with both theoretical predictions and experimental measurements is provided. For oblique impacts, the results in terms of the force-displacement relationship, coefficients of restitution, trajectory of the impacting particle, and distribution of kinetic energy and work done during the process of impact are presented. The effects of Poisson's ratio, friction, plastic deformation and initial particle rotation on the bouncing behaviour are also discussed. In the presence of adhesion an elasto-plastic collision model, which is an extension to the JKR theory, is developed. Based on an energy balance equation the critical sticking velocity is obtained. For oblique collisions computer simulated results are used to establish a set of criteria determining whether or not the particle bounces off the target plate. For impact velocities above the critical sticking value, computer simulated results for the coefficients of restitution and rebound angles of the particle are presented. Computer simulations of fracture/fragmentation resulting from agglomerate-wall impact have also been performed, where two randomly generated agglomerates (one monodisperse, the other polydisperse), each consisting of 50 primary particles are used. The effects of impact angle, local structural arrangements close to the impact point, and plastic deformation at the contacts on agglomerate damage are examined. The simulated results show a significant difference in agglomerate strength between the two assemblies. The computer data also shows that agglomerate damage resulting from an oblique impact is determined by the normal velocity component rather than the impact speed.

Impact of electric vehicles on GB electricity demand and associated benefits for system control

This paper investigates the impact that electric vehicle uptake will have on the national electricity demand of Great Britain. Data from the National Travel Survey, and the Coventry and Birmingham Low Emissions Demonstration (CABLED) are used to model an electrical demand profile in a future scenario of significant electric vehicle market penetration. These two methods allow comparison of how conventional cars are currently used, and the resulting electrical demand with simple substitution of energy source, with data showing how electric vehicles are actually being used at present. The report finds that electric vehicles are unlikely to significantly impact electricity demand in GB. The paper also aims to determine whether electric vehicles have the potential to provide ancillary services to the grid operator, and if so, the capacity for such services that would be available. Demand side management, frequency response and Short term Operating Reserve (STOR) are the services considered. The report finds that electric cars are unlikely to provide enough moveable demand peak shedding to be worthwhile. However, it is found that controlling vehicle charging would provide sufficient power control to viably act as frequency response for dispatch by the transmission system operator. This paper concludes that electric vehicles have technical potential to aid management of the transmission network without adding a significant demand burden. © 2013 IEEE.

Patient experiences of serious adverse drug reactions and their attitudes to medicines:a qualitative study of survivors of Stevens-Johnson syndrome and toxic epidermal necrolysis in the UK

Background: Adverse drug reactions (ADRs) cause significant morbidity and mortality and account for around 6.5% of hospital admissions. Patient experiences of serious ADRs and their long-term impact on patients' lives, including their influence on current attitudes towards medicines, have not been previously explored. Objective: The aim of the study was to explore the experiences, beliefs, and attitudes of survivors of serious ADRs, using drug-induced Stevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) as a paradigm. Methods: A retrospective, qualitative study was undertaken using detailed semi-structured interviews. Fourteen adult survivors of SJS and TEN, admitted to two teaching hospitals in the UK, one the location of a tertiary burns centre, were interviewed. Interview transcripts were independently analysed by three different researchers and themes emerging from the text identified. Results: All 14 patients were aware that their condition was drug induced, and all but one knew the specific drug(s) implicated. Several expressed surprise at the perceived lack of awareness of the ADR amongst healthcare professionals, and described how the ADR was mistaken for another condition. Survivors believed that causes of the ADR included (i) being given too high a dose of the drug; (ii) medical staff ignoring existing allergies; and (iii) failure to monitor blood tests. Only two believed that the reaction was unavoidable. Those who believed that the condition could have been avoided had less trust in healthcare professionals. The ADR had a persisting impact on their current lives physically and psychologically. Many now avoided medicines altogether and were fearful of becoming ill enough to need them. © 2011 Adis Data Information BV. All rights reserved. Conclusions: Life-threatening ADRs continued to affect patients’ lives long after the event. Patients’ beliefs regarding the cause of the ADR differed, and may have influenced their trust in healthcare professionals and medicines. We propose that clear communication during the acute phase of a serious ADR may therefore be important.

Phytochemical-loaded mesoporous silica nanoparticles for nose-to-brain olfactory drug delivery

Central nervous system (CNS) drug delivery is often hampered due to the insidious nature of the blood-brain barrier (BBB). Nose-to-brain delivery via olfactory pathways have become a target of attention for drug delivery due to bypassing of the BBB. The antioxidant properties of phytochemicals make them promising as CNS active agents but possess poor water solubility and limited BBB penetration. The primary aim of this study was the development of mesoporous silica nanoparticles (MSNs) loaded with the poorly water-soluble phytochemicals curcumin and chrysin which could be utilised for nose-to-brain delivery. We formulated spherical MSNP using a templating approach resulting in ∼220nm particles with a high surface porosity. Curcumin and chrysin were successfully loaded into MSNP and confirmed through Fourier transformation infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and HPLC approaches with a loading of 11-14% for curcumin and chrysin. Release was pH dependant with curcumin demonstrating increased chemical stability at a lower pH (5.5) with a release of 53.2%±2.2% over 24h and 9.4±0.6% for chrysin. MSNP were demonstrated to be non-toxic to olfactory neuroblastoma cells OBGF400, with chrysin (100μM) demonstrating a decrease in cell viability to 58.2±8.5% and curcumin an IC50 of 33±0.18μM. Furthermore confocal microscopy demonstrated nanoparticles of <500nm were able to accumulate within cells with FITC-loaded MSNP showing membrane localised and cytoplasmic accumulation following a 2h incubation. MSNP are useful carriers for poorly soluble phytochemicals and provide a novel vehicle to target and deliver drugs into the CNS and bypass the BBB through olfactory drug delivery.

Experiments to assess the transport of fibrous insulation debris

Loss of coolant accidents (LOCA) in the primary cooling circuit of a nuclear reactor may result in damage to insulation materials that are located near to the leak. The insulation materials released may compromise the operation of the emergency core cooling system (ECCS). Insulation material in the form of mineral wool fibre agglomerates (MWFA) maybe transported to the containment sump strainers mounted at the inlet of the emergency cooling pumps, where the insulation fibres may block or penetrate the strainers. In addition to the impact of MWFA on the pressure drop across the strainers, corrosion products formed over time may also accumulate in the fibre cakes on the strainers, which can lead to a significant increase in the strainer pressure drop and result in cavitation in the ECCS. Thus, knowledge of transport characteristics of the damaged insulation materials in various scenarios is required to help plan for the long-term operability of nuclear reactors, which undergo LOCA. An experimental and theoretical study performed by the Helmholtz-Zentrum Dresden-Rossendorf and the Hochschule Zittau/Görlitz1 is investigating the phenomena that maybe observed in the containment vessel during a LOCA. The study entails the generation of fibre agglomerates, the determination of their transport properties in single and multi-effect experiments and the long-term effect that corrosion of the containment internals by the coolant has on the strainer pressure drop. The focus of this presentation is on the experiments performed that characterize the horizontal transport of MWFA, whereas the corresponding CFD simulations are described in an accompanying contribution (see abstract of Cartland Glover et al.). The experiments were performed a racetrack type channel that provided a near uniform horizontal flow. The channel is 0.1 wide by 1.2 m high with a straight length of 5 m and two bends of 0.5 m. The measurement techniques include particle imaging (both wide-angle and macro lens), concurrent particle image velocimetry, ultravelocimetry, laser detection sensors to sense the presence of absence of MWFA and pertinent measurements of the MWFA concentration and quiescent settling characteristics. The transport of the MWFA was observed at velocities of 0.1 and 0.25 m s-1 to verify numerical model behaviour in and just beyond expected velocities in the containment sump of a nuclear reactor.

Privatisation and sustainable competitive advantage in the emerging economies of Central Europe

Extant research on the impact of privatization in the Central Europe (CE) region has focused on improvements in efficiency and the nature of cost-based advantages. This study argues that the development of a vibrant privatized sector requires attention to the broader resource configurations of domestic enterprises. Empirical research was conducted on a large sample of firms in Poland, Hungary and Slovenia. Foreign investment was found to significantly impact on resource accumulation with implications for the development of strategic capabilities and competitive advantage. Foreign direct investment is an effective vehicle for the transfer of financial resources, reputation and new brands but not organizational capabilities. In terms of practice, this study demonstrates the important role of outside investment in the development of a firm's resource base (Frydman et al. 1999). Companies can gain a competitive advantage in their domestic markets through gaining access to the resources of foreign investors.

The impact of architecture on the performance of artificial neural networks

A number of researchers have investigated the impact of network architecture on the performance of artificial neural networks. Particular attention has been paid to the impact on the performance of the multi-layer perceptron of architectural issues, and the use of various strategies to attain an optimal network structure. However, there are still perceived limitations with the multi-layer perceptron and networks that employ a different architecture to the multi-layer perceptron have gained in popularity in recent years, particularly, networks that implement a more localised solution, where the solution in one area of the problem space does not impact, or has a minimal impact, on other areas of the space. In this study, we discuss the major architectural issues affecting the performance of a multi-layer perceptron, before moving on to examine in detail the performance of a new localised network, namely the bumptree. The work presented here examines the impact on the performance of artificial neural networks of employing alternative networks to the long established multi-layer perceptron. In particular, networks that impose a solution where the impact of each parameter in the final network architecture has a localised impact on the problem space being modelled are examined. The alternatives examined are the radial basis function and bumptree neural networks, and the impact of architectural issues on the performance of these networks is examined. Particular attention is paid to the bumptree, with new techniques for both developing the bumptree structure and employing this structure to classify patterns being examined.

The use of anticholinergic agents to treat excessive oropharyngeal and tracheal secretions in palliative care

Palliative care involves a multi-professional team approach to the provision of active, holistic care for patients and their families when the patient's disease is no longer responsive to curative treatment. Patient care encompasses medical and pharmacological intervention for symptom control, together with psychological, spiritual and social support for patients and families. Care is provided by teams in hospice, hospital or community environments. Although traditionally associated with providing care for cancer patients, palliative care services are increasingly providing for patients with non-malignant disease. Symptoms commonly associated with terminal phase of disease include pain, nausea, agitation, respiratory symptoms and general fatigue. During the last few days of life, patients may become weak, resulting in difficulty taking oral medication and have periods of unconsciousness. Some patients may require drug administration via subcutaneous infusion. A proportion of patients may develop difficulty clearing respiratory secretions causing a characteristic ‘death rattle’, which although not generally considered to be distressing for the patient, is often treated with a variety of anticholinergic drugs in an attempt to reduce the ‘noisy breathing’ for the benefit of relatives and others who may be closely associated with the patient.This study examined treatment of death rattle in two Hospices focusing on objective and subjective outcome measures in order to determine the efficacy of anticholinergic regimens in current use. Qualitative methods were employed to elicit attitudes of professionals and carers working closely with the patient. The number of patients recruited and monitored were small, many confounding factors were identified which questioned firstly the clinical rationale for administering anticholinergic drugs routinely to treat death rattle and secondly, the ethics of administering drug regimens to patients to treat death rattle with the primary aim of relieving distress for others. Ethnical issues, including those of consent are discussed in relation to their impact on the methodology of end of life studies in medicines management in palliative care.

Composite materials impact damage detection using neural networks

This thesis considers two basic aspects of impact damage in composite materials, namely damage severity discrimination and impact damage location by using Acoustic Emissions (AE) and Artificial Neural Networks (ANNs). The experimental work embodies a study of such factors as the application of AE as Non-destructive Damage Testing (NDT), and the evaluation of ANNs modelling. ANNs, however, played an important role in modelling implementation. In the first aspect of the study, different impact energies were used to produce different level of damage in two composite materials (T300/914 and T800/5245). The impacts were detected by their acoustic emissions (AE). The AE waveform signals were analysed and modelled using a Back Propagation (BP) neural network model. The Mean Square Error (MSE) from the output was then used as a damage indicator in the damage severity discrimination study. To evaluate the ANN model, a comparison was made of the correlation coefficients of different parameters, such as MSE, AE energy, AE counts, etc. MSE produced an outstanding result based on the best performance of correlation. In the second aspect, a new artificial neural network model was developed to provide impact damage location on a quasi-isotropic composite panel. It was successfully trained to locate impact sites by correlating the relationship between arriving time differences of AE signals at transducers located on the panel and the impact site coordinates. The performance of the ANN model, which was evaluated by calculating the distance deviation between model output and real location coordinates, supports the application of ANN as an impact damage location identifier. In the study, the accuracy of location prediction decreased when approaching the central area of the panel. Further investigation indicated that this is due to the small arrival time differences, which defect the performance of ANN prediction. This research suggested increasing the number of processing neurons in the ANNs as a practical solution.

Micromechanics of agglomerate damage processes

This thesis reports a detailed investigation of the micromechanics of agglomerate behaviour under free-fall impact, double (punch) impact and diametrical compression tests using the simulation software TRUBAL. The software is based on the discrete element method (DEM) which incorporates the Newtonian equations of motion and contact mechanics theory to model the interparticle interactions. Four agglomerates have been used: three dense (differing in interface energy and contact density) and one loose. Although the simulated agglomerates are relatively coarse-grained, the results obtained are in good agreement with laboratory test results reported in the literature. The computer simulation results show that, in all three types of test, the loose agglomerate cannot fracture as it is unable to store sufficient elastic energy. Instead, it becomes flattened for low loading-rates and shattered or crushed at higher loading-rates. In impact tests, the dense agglomerates experience only local damage at low impact velocities. Semi-brittle fracture and fragmentation are produced over a range of higher impact velocities and at very high impact velocities shattering occurs. The dense agglomerates fracture in two or three large fragments in the diametrical compression tests. Local damage at the agglomerate-platen interface always occurs prior to fracture and consists of local bond breakage (microcrack formation) and local dislocations (compaction). The fracture process is dynamic and much more complex than that suggested by continuum fracture mechanics theory. Cracks are always initiated from the contact zones and propagate towards the agglomerate centre. Fracture occurs a short time after the start of unloading when a fracture crack "selection" process takes place. The detailed investigation of the agglomerate damage processes includes an examination of the evolution of the fracture surface. Detailed comparisons of the behaviour of the same agglomerate in all three types of test are presented. The particle size distribution curves of the debris are also examined, for both free-fall and double impact tests.

Numerical modelling of agglomerate degradation

In the processing industries particulate materials are often in the form of powders which themselves are agglomerations of much smaller sized particles. During powder processing operations agglomerate degradation occurs primarily as a result of collisions between agglomerates and between agglomerates and the process equipment. Due to the small size of the agglomerates and the very short duration of the collisions it is currently not possible to obtain sufficiently detailed quantitative information from real experiments to provide a sound theoretically based strategy for designing particles to prevent or guarantee breakage. However, with the aid of computer simulated experiments, the micro-examination of these short duration dynamic events is made possible. This thesis presents the results of computer simulated experiments on a 2D monodisperse agglomerate in which the algorithms used to model the particle-particle interactions have been derived from contact mechanics theories and, necessarily, incorporate contact adhesion. A detailed description of the theoretical background is included in the thesis. The results of the agglomerate impact simulations show three types of behaviour depending on whether the initial impact velocity is high, moderate or low. It is demonstrated that high velocity impacts produce extensive plastic deformation which leads to subsequent shattering of the agglomerate. At moderate impact velocities semi-brittle fracture is observed and there is a threshold velocity below which the agglomerate bounces off the wall with little or no visible damage. The micromechanical processes controlling these different types of behaviour are discussed and illustrated by computer graphics. Further work is reported to demonstrate the effect of impact velocity and bond strength on the damage produced. Empirical relationships between impact velocity, bond strength and damage are presented and their relevance to attrition and comminution is discussed. The particle size distribution curves resulting from the agglomerate impacts are also provided. Computer simulated diametrical compression tests on the same agglomerate have also been carried out. Simulations were performed for different platen velocities and different bond strengths. The results show that high platen velocities produce extensive plastic deformation and crushing. Low platen velocities produce semi-brittle failure in which cracks propagate from the platens inwards towards the centre of the agglomerate. The results are compared with the results of the agglomerate impact tests in terms of work input, applied velocity and damage produced.

The autonomous navigation of an electric vehicle

A navigation and positioning system for an electric automatic guided vehicle has been designed and implemented on an industrial pallet truck. The system includes an optical sensor mounted on the vehicle, capable of recognizing special markers at a distance of 0.3m. Software implemented in a z-80 microprocessor controls the sensor, performs all data processing and contains the decision making processes necessary for the vehicle to navigate its way to its task location. A second microprocessor is used to control the vehicle's drive motors under instruction from the navigation unit, to accurately position the vehicle at its destination. The sensor reliably recognises markers at vehicle speeds up to 1ms- 1, and the system has been integrated into a multiprocessor controlled wire-guidance system and applied to a prototype vehicle.