38 resultados para non-thermal technologies

em Aston University Research Archive


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This paper draws attention for the fact that traditional Data Envelopment Analysis (DEA) models do not provide the closest possible targets (or peers) to inefficient units, and presents a procedure to obtain such targets. It focuses on non-oriented efficiency measures (which assume that production units are able to control, and thus change, inputs and outputs simultaneously) both measured in relation to a Free Disposal Hull (FDH) technology and in relation to a convex technology. The approaches developed for finding close targets are applied to a sample of Portuguese bank branches.

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This work introduces a model in which agents of a network act upon one another according to three different kinds of moral decisions. These decisions are based on an increasing level of sophistication in the empathy capacity of the agent, a hierarchy which we name Piaget's ladder. The decision strategy of the agents is non-rational, in the sense they are arbitrarily fixed, and the model presents quenched disorder given by the distribution of its defining parameters. An analytical solution for this model is obtained in the large system limit as well as a leading order correction for finite-size systems which shows that typical realisations of the model develop a phase structure with both continuous and discontinuous non-thermal transitions.

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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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In the quest to secure the much vaunted benefits of North Sea oil, highly non-incremental technologies have been adopted. Nowhere is this more the case than with the early fields of the central and northern North Sea. By focusing on the inflexible nature of North Sea hardware, in such fields, this thesis examines the problems that this sort of technology might pose for policy making. More particularly, the following issues are raised. First, the implications of non-incremental technical change for the successful conduct of oil policy is raised. Here, the focus is on the micro-economic performance of the first generation of North Sea oil fields and the manner in which this relates to government policy. Secondly, the question is posed as to whether there were more flexible, perhaps more incremental policy alternatives open to the decision makers. Conclusions drawn relate to the degree to which non-incremental shifts in policy permit decision makers to achieve their objectives at relatively low cost. To discover cases where non-incremental policy making has led to success in this way, would be to falsify the thesis that decision makers are best served by employing incremental politics as an approach to complex problem solving.

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As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. While it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This article reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range of 0 °C–50 °C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.

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The use of Diagnosis Related Groups (DRG) as a mechanism for hospital financing is a currently debated topic in Portugal. The DRG system was scheduled to be initiated by the Health Ministry of Portugal on January 1, 1990 as an instrument for the allocation of public hospital budgets funded by the National Health Service (NHS), and as a method of payment for other third party payers (e.g., Public Employees (ADSE), private insurers, etc.). Based on experience from other countries such as the United States, it was expected that implementation of this system would result in more efficient hospital resource utilisation and a more equitable distribution of hospital budgets. However, in order to minimise the potentially adverse financial impact on hospitals, the Portuguese Health Ministry decided to gradually phase in the use of the DRG system for budget allocation by using blended hospitalspecific and national DRG casemix rates. Since implementation in 1990, the percentage of each hospitals budget based on hospital specific costs was to decrease, while the percentage based on DRG casemix was to increase. This was scheduled to continue until 1995 when the plan called for allocating yearly budgets on a 50% national and 50% hospitalspecific cost basis. While all other nonNHS third party payers are currently paying based on DRGs, the adoption of DRG casemix as a National Health Service budget setting tool has been slower than anticipated. There is now some argument in both the political and academic communities as to the appropriateness of DRGs as a budget setting criterion as well as to their impact on hospital efficiency in Portugal. This paper uses a twostage procedure to assess the impact of actual DRG payment on the productivity (through its components, i.e., technological change and technical efficiency change) of diagnostic technology in Portuguese hospitals during the years 1992–1994, using both parametric and nonparametric frontier models. We find evidence that the DRG payment system does appear to have had a positive impact on productivity and technical efficiency of some commonly employed diagnostic technologies in Portugal during this time span.

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The thesis is divided into four chapters. They are: introduction, experimental, results and discussion about the free ligands and results and discussion about the complexes. The First Chapter, the introductory chapter, is a general introduction to the study of solid state reactions. The Second Chapter is devoted to the materials and experimental methods that have been used for carrying out tile experiments. TIle Third Chapter is concerned with the characterisations of free ligands (Picolinic acid, nicotinic acid, and isonicotinic acid) by using elemental analysis, IR spectra, X-ray diffraction, and mass spectra. Additionally, the thermal behaviour of free ligands in air has been studied by means of thermogravimetry (TG), derivative thermogravimetry (DTG), and differential scanning calorimetry (DSC) measurements. The behaviour of thermal decomposition of the three free ligands was not identical Finally, a computer program has been used for kinetic evaluation of non-isothermal differential scanning calorimetry data according to a composite and single heating rate methods in comparison with the methods due to Ozawa and Kissinger methods. The most probable reaction mechanism for the free ligands was the Avrami-Erofeev equation (A) that described the solid-state nucleation-growth mechanism. The activation parameters of the decomposition reaction for free ligands were calculated and the results of different methods of data analysis were compared and discussed. The Fourth Chapter, the final chapter, deals with the preparation of cobalt, nickel, and copper with mono-pyridine carboxylic acids in aqueous solution. The prepared complexes have been characterised by analyses, IR spectra, X-ray diffraction, magnetic moments, and electronic spectra. The stoichiometry of these compounds was ML2x(H20), (where M = metal ion, L = organic ligand and x = water molecule). The environments of cobalt, nickel, and copper nicotinates and the environments of cobalt and nickel picolinates were octahedral, whereas the environment of copper picolinate [Cu(PA)2] was tetragonal. However, the environments of cobalt, nickel, and copper isonicotinates were polymeric octahedral structures. The morphological changes that occurred throughout the decomposition were followed by SEM observation. TG, DTG, and DSC measurements have studied the thermal behaviour of the prepared complexes in air. During the degradation processes of the hydrated complexes, the crystallisation water molecules were lost in one or two steps. This was also followed by loss of organic ligands and the metal oxides remained. Comparison between the DTG temperatures of the first and second steps of the dehydration suggested that the water of crystallisation was more strongly bonded with anion in Ni(II) complexes than in the complexes of Co(II) and Cu(II). The intermediate products of decomposition were not identified. The most probable reaction mechanism for the prepared complexes was also Avrami-Erofeev equation (A) characteristic of solid-state nucleation-growth mechanism. The tempemture dependence of conductivity using direct current was determined for cobalt, nickel, Cl.nd copper isonicotinates. An activation energy (ΔΕ), the activation energy (ΔΕ ) were calculated.The ternperature and frequency dependence of conductivity, the frequency dependence of dielectric constant, and the dielectric loss for nickel isonicotinate were determined by using altemating current. The value of s paralneter and the value of'density of state [N(Ef)] were calculated. Keyword Thermal decomposition, kinetic, electrical conduclion, pyridine rnono~ carboxylic acid, cOlnplex, transition metal compJex.

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The development of reliable, high powered plasma generators has resulted in many plasma processes being proposed as alternatives to existing pyrometallurgical technologies. This work evaluates the advantages and disadvantages of plasma systems by reviewing plasma generators, their integration with reactors and the process economics. Many plasma systems were shown to be technically and economically superior to existing technologies, but some of the plasma system advantages quoted in the literature were found to be impractical because of other system constraints. Process applications were limited by the power inputs available from plasma generators compared to AC electric furnaces. A series of trials were conducted where chromite and steelplant baghouse dusts were smelted in the Tetronics' 2.0 MW transferred arc/open bath reactor to confirm the operating characteristics of the plasma system and its economics. Chromite smelting was technical superior to submerged arc furnace technology, but the economics were unfavourable because of the limited power available from the water-cooled plasma torch and the high electrical energy consumption. A DC graphite electrode plasma furnace using preheated and prereduced chromite concentrates will compete economically with the submerged arc furnace. Ni, Cr and Mo were economically recovered from high alloy content steelplant dusts for recycling. Five Electric Arc Furnace dusts were smelted to produce a non-toxic residue and recover the contained zinc to an enriched zinc oxide product for recycling. It should be possible to condense the zinc vapour directly in a zinc splash condenser to increase the value of the product. Because of the limited power available from plasma generators, plasma processes will be most suitable for treating high and medium value materials such as Au, Pt, Mo, Ni, Ti, V, Cr etc at small production rates, heating metals in tundishes and ladles and remelting superalloy scrap. The treatment of environmentally hazardous waste materials is a particularly interesting application because of the additional financial incentives. Non-transferred arc plasma generators will be used for air and gas preheating in blast furnaces to reduce metallurgical coke consumptions.

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The aim of this research was to investigate the molecular interactions occurring in the formulation of non-ionic surfactant based vesicles composed monopalmitoyl glycerol (MPG), cholesterol (Chol) and dicetyl phosphate (DCP). In the formulation of these vesicles, the thermodynamic attributes and surfactant interactions based on molecular dynamics, Langmuir monolayer studies, differential scanning calorimetry (DSC), hot stage microscopy and thermogravimetric analysis (TGA) were investigated. Initially the melting points of the components individually, and combined at a 5:4:1 MPG:Chol:DCP weight ratio, were investigated; the results show that lower (90 C) than previously reported (120-140 C) temperatures could be adopted to produce molten surfactants for the production of niosomes. This was advantageous for surfactant stability; whilst TGA studies show that the individual components were stable to above 200 C, the 5:4:1 MPG:Chol:DCP mixture show ∼2% surfactant degradation at 140 C, compared to 0.01% was measured at 90 C. Niosomes formed at this lower temperature offered comparable characteristics to vesicles prepared using higher temperatures commonly reported in literature. In the formation of niosome vesicles, cholesterol also played a key role. Langmuir monolayer studies demonstrated that intercalation of cholesterol in the monolayer did not occur in the MPG:Chol:DCP (5:4:1 weight ratio) mixture. This suggests cholesterol may support bilayer assembly, with molecular simulation studies also demonstrating that vesicles cannot be built without the addition of cholesterol, with higher concentrations of cholesterol (5:4:1 vs 5:2:1, MPG:Chol:DCP) decreasing the time required for niosome assembly. © 2013 Elsevier B.V.

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An important field of application of lasers is biomedical optics. Here, they offer great utility for diagnosis, therapy and surgery. For the development of novel methods of laser-based biomedical diagnostics careful study of light propagation in biological tissues is necessary to enhance our understanding of the optical measurements undertaken, increase research and development capacity and the diagnostic reliability of optical technologies. Ultimately, fulfilling these requirements will increase uptake in clinical applications of laser based diagnostics and therapeutics. To address these challenges informative biomarkers relevant to the biological and physiological function or disease state of the organism must be selected. These indicators are the results of the analysis of tissues and cells, such as blood. For non-invasive diagnostics peripheral blood, cells and tissue can potentially provide comprehensive information on the condition of the human organism. A detailed study of the light scattering and absorption characteristics can quickly detect physiological and morphological changes in the cells due to thermal, chemical, antibiotic treatments, etc [1-5]. The selection of a laser source to study the structure of biological particles also benefits from the fact that gross pathological changes are not induced and diagnostics make effective use of the monochromatic directional coherence properties of laser radiation.

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The research presented in this thesis was developed as part of DIBANET, an EC funded project aiming to develop an energetically self-sustainable process for the production of diesel miscible biofuels (i.e. ethyl levulinate) via acid hydrolysis of selected biomass feedstocks. Three thermal conversion technologies, pyrolysis, gasification and combustion, were evaluated in the present work with the aim of recovering the energy stored in the acid hydrolysis solid residue (AHR). Mainly consisting of lignin and humins, the AHR can contain up to 80% of the energy in the original feedstock. Pyrolysis of AHR proved unsatisfactory, so attention focussed on gasification and combustion with the aim of producing heat and/or power to supply the energy demanded by the ethyl levulinate production process. A thermal processing rig consisting on a Laminar Entrained Flow Reactor (LEFR) equipped with solid and liquid collection and online gas analysis systems was designed and built to explore pyrolysis, gasification and air-blown combustion of AHR. Maximum liquid yield for pyrolysis of AHR was 30wt% with volatile conversion of 80%. Gas yield for AHR gasification was 78wt%, with 8wt% tar yields and conversion of volatiles close to 100%. 90wt% of the AHR was transformed into gas by combustion, with volatile conversions above 90%. 5volO2%-95vol%N2 gasification resulted in a nitrogen diluted, low heating value gas (2MJ/m3). Steam and oxygen-blown gasification of AHR were additionally investigated in a batch gasifier at KTH in Sweden. Steam promoted the formation of hydrogen (25vol%) and methane (14vol%) improving the gas heating value to 10MJ/m3, below the typical for steam gasification due to equipment limitations. Arrhenius kinetic parameters were calculated using data collected with the LEFR to provide reaction rate information for process design and optimisation. Activation energy (EA) and pre-exponential factor (ko in s-1) for pyrolysis (EA=80kJ/mol, lnko=14), gasification (EA=69kJ/mol, lnko=13) and combustion (EA=42kJ/mol, lnko=8) were calculated after linearly fitting the data using the random pore model. Kinetic parameters for pyrolysis and combustion were also determined by dynamic thermogravimetric analysis (TGA), including studies of the original biomass feedstocks for comparison. Results obtained by differential and integral isoconversional methods for activation energy determination were compared. Activation energy calculated by the Vyazovkin method was 103-204kJ/mol for pyrolysis of untreated feedstocks and 185-387kJ/mol for AHRs. Combustion activation energy was 138-163kJ/mol for biomass and 119-158 for AHRs. The non-linear least squares method was used to determine reaction model and pre-exponential factor. Pyrolysis and combustion of biomass were best modelled by a combination of third order reaction and 3 dimensional diffusion models, while AHR decomposed following the third order reaction for pyrolysis and the 3 dimensional diffusion for combustion.

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Thermal effects in uncontrolled factory environments are often the largest source of uncertainty in large volume dimensional metrology. As the standard temperature for metrology of 20°C cannot be achieved practically or economically in many manufacturing facilities, the characterisation and modelling of temperature offers a solution for improving the uncertainty of dimensional measurement and quantifying thermal variability in large assemblies. Technologies that currently exist for temperature measurement in the range of 0-50°C have been presented alongside discussion of these temperature measurement technologies' usefulness for monitoring temperatures in a manufacturing context. Particular aspects of production where the technology could play a role are highlighted as well as practical considerations for deployment. Contact sensors such as platinum resistance thermometers can produce accuracy closest to the desired accuracy given the most challenging measurement conditions calculated to be ∼0.02°C. Non-contact solutions would be most practical in the light controlled factory (LCF) and semi-invasive appear least useful but all technologies can play some role during the initial development of thermal variability models.

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The purpose of this paper is twofold: first, we compute quality-adjusted measures of productivity change for the three most important diagnostic technologies (i.e., the Computerised Tomography Scan, Electrocardiogram and Echocardiogram) in the major Portuguese hospitals. We use the Malmquist–Luenberger index, which allows to measure productivity growth while controlling for the quality of the production. Second, using non-parametric tests, we analyse whether the implementation of the Prospective Payment System may have had a positive impact on the movements of productivity over time. The results show that the PPS has helped hospitals to use these tools more efficiently and to improve their effectiveness.

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Single- and multi-core passive and active germanate and tellurite glass fibers represent a new class of fiber host for in-fiber photonics devices and applications in mid-IR wavelength range, which are in increasing demand. Fiber Bragg grating (FBG) structures have been proven as one of the most functional in-fiber devices and have been mass-produced in silicate fibers by UV-inscription for almost countless laser and sensor applications. However, because of the strong UV absorption in germanate and tellurite fibers, FBG structures cannot be produced by UVinscription. In recent years femtosecond (fs) lasers have been developed for laser machining and microstructuring in a variety of glass fibers and planar substrates. A number of papers have been reported on fabrication of FBGs and long-period gratings in optical fibers and also on the photosensitivity mechanism using 800nm fs lasers. In this paper, we demonstrate for the first time the fabrication of FBG structures created in passive and active single- and three-core germanate and tellurite glass fibers by using 800nm fs-inscription and phase mask technique. With a fs peak power intensity in the order of 1011W/cm2, the FBG spectra with 2nd and 3rd order resonances at 1540nm and 1033nm in a single-core germanate glass fiber and 2nd order resonances between ~1694nm and ~1677nm with strengths up to 14dB in all three cores of three-core passive and active tellurite fibers were observed. Thermal and strain properties of the FBGs made in these mid-IR glass fibers were characterized, showing an average temperature responsivity of ~20pm/°C and a strain sensitivity of 1.219±0.003pm/µe.

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This thesis applies a hierarchical latent trait model system to a large quantity of data. The motivation for it was lack of viable approaches to analyse High Throughput Screening datasets which maybe include thousands of data points with high dimensions. High Throughput Screening (HTS) is an important tool in the pharmaceutical industry for discovering leads which can be optimised and further developed into candidate drugs. Since the development of new robotic technologies, the ability to test the activities of compounds has considerably increased in recent years. Traditional methods, looking at tables and graphical plots for analysing relationships between measured activities and the structure of compounds, have not been feasible when facing a large HTS dataset. Instead, data visualisation provides a method for analysing such large datasets, especially with high dimensions. So far, a few visualisation techniques for drug design have been developed, but most of them just cope with several properties of compounds at one time. We believe that a latent variable model (LTM) with a non-linear mapping from the latent space to the data space is a preferred choice for visualising a complex high-dimensional data set. As a type of latent variable model, the latent trait model can deal with either continuous data or discrete data, which makes it particularly useful in this domain. In addition, with the aid of differential geometry, we can imagine the distribution of data from magnification factor and curvature plots. Rather than obtaining the useful information just from a single plot, a hierarchical LTM arranges a set of LTMs and their corresponding plots in a tree structure. We model the whole data set with a LTM at the top level, which is broken down into clusters at deeper levels of t.he hierarchy. In this manner, the refined visualisation plots can be displayed in deeper levels and sub-clusters may be found. Hierarchy of LTMs is trained using expectation-maximisation (EM) algorithm to maximise its likelihood with respect to the data sample. Training proceeds interactively in a recursive fashion (top-down). The user subjectively identifies interesting regions on the visualisation plot that they would like to model in a greater detail. At each stage of hierarchical LTM construction, the EM algorithm alternates between the E- and M-step. Another problem that can occur when visualising a large data set is that there may be significant overlaps of data clusters. It is very difficult for the user to judge where centres of regions of interest should be put. We address this problem by employing the minimum message length technique, which can help the user to decide the optimal structure of the model. In this thesis we also demonstrate the applicability of the hierarchy of latent trait models in the field of document data mining.