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Seasonal solar energy storage using thermochemical adsorption for space heating
Full text linkAdsorption-based thermochemical heat storage is a long-term thermal energy storage technology that can be used for seasonal solar energy storage and especially for space heating, which has received significant attention. Pure salt as the adsorbent, even though has huge water-adsorption capacity, takes the disadvantage of low thermal conductivity, deliquescence, and swallow problems during cyclic sorption operations, which could finally reduce both the thermal energy storage and the space heating performance. Composite adsorbent, integrating the salt with the porous matrix such as activated carbon and zeolite, could keep the high water-adsorption capacity (energy density) when the porous structure of the matrix providing a more stable form to hold the adsorbed/desorbed adsorbent and to prevent it from agglomeration.
In this project, an efficient adsorption-integrated space heating system has been investigated with the seasonal solar energy storage (SSES) function using the composite adsorbent made by the salt and the zeolite. The water-adsorption space heating system using the composite which could take the advantage like that the water vapour widely spreads in the environment and the zeolite is a popular material for the concrete mixing in the sustainable architecture research.
The composite adsorbent made by salt solutions (MgSO4, LiCl, and LiBr) with different concentrations and various zeolites have been investigated as these salts are easy to obtain and safe for the environment. Moreover, beside the single salt-zeolite composite of MgSO4-zeolite, LiCl and LiBr could form the complex salt(A)-salt(B)-zeolite as LiCl-LiBr-zeolite composite to potentially increase the water-adsorption capacity and thus enhance its space heating and energy storage performance. The manufacturing methodology has been developed according to the practical experimental experience by the author. The prepared composite adsorbent has been experimentally characterized in respect of the surface morphology, thermal-physical properties, porous properties, and adsorption-related characteristics. The involved investigations include Scanning Electron Microscope (SEM) – Energy Dispersive Spectroscope (EDS), Nitrogen Adsorption, X-ray Diffractometer (XRD), and Thermogravimetric Analysis (TGA) - Differential Scanning Calorimetry (DSC). Besides, the adsorption kinetics of the composite adsorbent has been tested by the climate chamber, which could control the adsorption environment of the temperature and the relative humidity. For MgSO4-zeolite, the maximum heat storage density found in the TGA-DSC desorption tests was 481.3 J/g by MgSO4(20%)-4A, while the maximum water adsorption capacity obtained was 0.1803 g/g by MgSO4(20%)-13X. For LiCl/LiBr-zeolite, the maximum heat storage density, 592.8 J/g, is found in 5%LiCl-5%LiBr-zeolite. The most water adsorption capacity observed in the climatic chamber adsorption experiment is 0.22 g/g (5%LiCl-25%LiBr-zeolite).
As LiCl-LiBr-zeolite has proved its superior water-adsorption capacity as well as the energy density, they are selected as the adsorption composite to be used in the further space heating experiments. An adsorption pipeline reactor has been established to experimentally investigate the air heating effect by using the selected candidates. Moreover, a 1:22.5 scaled house model was printed by a 3D-printer to simulate the condition that the house model is heated by the adsorption heat provided by the tube reactor. The effects of air velocity and relative humidity on the adsorption performance has been examined. The outlet air and room temperature profiles are recorded for analysis. It is found that a flow rate of 15 m3/h and a relative humidity of 70% could lead to the maximum adsorption heat, 434.4 J/g, from the water-adsorption reaction by the composite material, and the highest energy discharge efficiency of 74.3%.
Furthermore, the adsorption-integrated space heating system has been established using the software of TRNSYS. The novel space heating model could collect and store the solar energy under sufficient solar radiation and utilize it to heat the house in the cold seasons. Simulated houses are assumed to be one in Newcastle, UK, and one in Urumqi, China. The gross heat supply by the adsorption-integrated space heating system in Urumqi and in Newcastle is 8862.68 kWh and 6466.39 kWh for the whole space heating seasons, respectively. The results demonstrates that the required room temperature is well kept by the designed space heating system using the composite adsorbent. The system could store the solar thermal energy from 0% of its full storage capacity to 100% during the seasons that the space heating is not required. However, at the end of each space heating season, the heat storage remains 42.85% and 57.00% in Urumqi and Newcastle, respectively. Because after the heat storage capacity is less than 95% of the full capacity, the storage module starts to work simultaneously with the space heating module. When the heat consumption is larger than the heat storage, the storage capacity percentage decreases. After a time, when the heat consumption is less than the heat storage, the storage capacity percentage increases until the end of the space heating season. Thus, the heat storage remains rather than running out. The value of the storage capacity percentage is dependent on the heat consumption and storage relationships.The extra solar radiation after full storage may be utilized into other functions. Moreover, the COP of the adsorption-integrated space heating system in Newcastle is 20% higher than that in Urumqi.
In a summary, using the composite adsorbent, the adsorption-integrated space heating system is promising to also achieve a high-efficiency and low-environmental impact seasonal solar thermal energy storage system.
Combined Photovoltaic-Thermal System with Phase Change Material Thermal Storage Tank for Decarbonising Domestic Buildings
No full textUtilizing solar energy to replace fossil fuels for residential energy supply offers a promising strategy for decarbonizing domestic buildings. This study designed a Photovoltaic-Thermal system assisted by a Heat Pump and integrated with a Phase Change Material thermal storage tank (PVT-PCM) for residential heating and hot water supply. To analyze the performance of the solar energy supply and storage system, a thermal consumption model of a conventional house was built and combined with the PVT-PCM system model on the TRNSYS software. When using a 61.75 m2 PVT panel and 1.35m3 PVT float tank, along with a 0.45 m3 DHW tank, the system can cover 96% of the conventional house's thermal load in January and December, and fully meet the house's thermal needs in other months, maintaining an average temperature of 18.8 °C. The integration of a 0.382 m3 PCM tank has a limited impact on the system's thermal supply performance. However, when the PCM can be fully charged and has a release rate of 63.8%, it can lead to an 18.8% increase in thermal supply, a 1.5% improvement in the heat pump's Coefficient of Performance (COP), and an energy density of the PCM tank that's 17.8% higher than that of the water tank
European Gas Markets: Market Integration & Market Efficiency: A Network Perspective
Full text linkIn this thesis, I study the market integration of European Natural Gas markets through two papers, whilst the third paper considers the impact of News Sentiment on the pricing and trading of Clean Energy and Traditional Energy stocks. Specifically, the first paper studies the level of harmonisation of European Natural Gas prices, characterised by 12 European gas hubs. The key finding is that, under normal market conditions, European Natural Gas markets are becoming increasingly integrated, with few physical barriers to increased market integration. Conversely, the detection of non-physical barriers to trade suggests that the liberalisation and development of certain national gas markets is yet to be fully achieved, inferring that improvements in technical arrangements are required.
The second paper provides a framework for forecasting the short term presence of phys- ical barriers to market integration of European Natural Gas markets. The identification of infrastructure congestion is an important prerequisite in enforcing price competition, and the implementation of an internal European gas market. In order to address this challenge, the underlying infrastructure network is learnt as a graph, and a deep learning framework, Graph Convolutional Long Short-Term Memory Neural Network (GC-LSTM), based on the topology of the infrastructure network, is applied to learn the interactions between different pipelines, and forecast gas flows throughout the network. Empirical results show that the GC-LSTM outperforms baseline methods in predicting gas pipeline flows.
The third paper studies the impact of News sentiment on pricing and trading for European Clean Energy companies and Traditional Energy companies. Using daily news extracted from Bloomberg, we estimate Vector Autoregressive (VAR) models and evaluate the dynamic spillover effects between News sentiment, stock returns and trading volumes. We find that European Clean Energy firms and Traditional Energy firms share the same patterns; that News sentiment positively affects both stock returns and trading volumes, and in return, stock returns and trading volumes have a limited impact on News sentiment. Nevertheless, the spillovers are relatively moderate and asymmetric
The Side-Channel Resistance of Error Correcting Codes for Post Quantum Cryptography
Full text linkThis thesis examines: how can we secure error correcting codes against side-channel attacks so that they can be securely used in cryptography?, as well as how can they be used to improve certain lattice-based cryptosystems? The thesis discusses how error correcting codes can be used to reduce the size of ciphertexts produced by LWE based schemes. Examining the use of Gray codes to reduce the number of bit errors when multi-bit encryption techniques are used, the full analysis of how various techniques could be applied to current KEMs (rather than to just a general scheme) with scripts to enable researchers to find improved parameter sets from a given starting point, and to provide specific parameter sets for these KEMs.
We move on to show how various linear algebra algorithms, including LUP Decomposition, can be made to be secure against side-channel attacks. We prove the security of these algorithms in the probing mode as well as giving experimental proofs. We then show how these algorithms can be used to create a secure version of the BCH code decoding algorithm. We also prove the security of these algorithms in the probing mode as well as giving experimental proofs.
Having shown how to secure the BCH code decoding algorithm, we finally show how to secure the decoding algorithm for Polar codes. As with the BCH code decoding algorithm, we also prove the security of these algorithms in the probing mode as well as giving experimental proofs
Management strategies and contributory factors for resistance exercise-induced muscle damage: an exploration of dietary protein, exercise load, and sex
Full text linkThe World Health Organisation recommends that resistance exercise be performed at least twice per week to benefit general health and wellbeing. However, resistance exercise is associated with acute muscle damage that potentially can dampen muscle adaptations promoted by chronic resistance training. The extent to which muscle is damaged by exercise is influenced by various factors, including age, training status, exercise type, and – notable to this thesis – sex. To this end, establishing sex-specific management strategies for exercise-induced muscle damage (EIMD) is important to optimise the benefits of exercise. Two EIMD management strategies were focussed on in this thesis: dietary protein supplementation and exercise load manipulation.
It was identified in this thesis that research into the impact both of protein supplementation and exercise load on EIMD heavily underrepresent female populations (chapters 3 and 5), despite well-documented sex differences in EIMD responses. Therefore, future research priority should be placed on bridging the sex data gap by conducting high-quality studies centralising around female-focussed and sex-comparative methodological designs.
Both peri-exercise protein supplementation and exercise load manipulation in favour of lighter loads were revealed to be effective management strategies for resistance EIMD in males through systematic and scoping review of the current literature (chapters 3 and 5, respectively). Due to a lack of data from females, it is only appropriate for these strategies to be recommended for males at present. To decipher whether protein supplementation and lower exercise loads are beneficial for managing EIMD in females, a randomised controlled trial (RCT) (chapter 4) and a protocol for an RCT (chapter 6) involving male and female participants are presented in this thesis.
The incorporation of ecologically-valid resistance exercise in the RCT in chapter 4 highlighted that even mild muscle damage is attenuated in females, reflected in diminished increases in post-exercise creatine kinase concentration and muscle soreness compared with males; however, the reason for this difference requires further investigation. This study, while supporting sex differences, contrasted previous studies, as neither males nor females experienced an attenuation of EIMD during milk protein supplementation. This difference likely owed to the lower severity of muscle damage induced in the current study relative to previous studies, and accordingly, future research should seek to discover alternative management strategies for mild EIMD. A protocol for an RCT examining the impact of exercise load on EIMD in untrained males and females is described in Chapter 6 of this thesis and may be used as guidance for researchers developing similar, sex-comparative studies. It was hypothesised that females will experience attenuated muscle damage relative to males and low-load exercise will induce less muscle damage than high-load exercise in both sexes.
A lack of methodological consistency among EIMD studies was a recurring finding throughout this thesis, which posed an issue when attempting to compare between-study outcomes and reach a consensus. Achieving greater uniformity in study designs by adopting comparable methods relating to EIMD markers and time-points of assessment would help improve understanding of the factors influencing the magnitude of EIMD and effective management strategies. While there are limitations with several EIMD markers – for example the variability of biomarkers and subjectivity of perceptual assessments – once the optimal markers are determined, these should be consistently used moving forward.
Overall, this thesis has contributed to the current body of knowledge by demonstrating that milk protein ingestion is not an effective management strategy for muscle damage following ecologically-valid resistance exercise; therefore, alternative strategies to mitigate mild muscle damage should be investigated. Further, this work supported previous reports of sex differences in EIMD and indicated that the attenuation of EIMD in females relative to males was not attributed to sex differences in body composition; thus, the aetiology of such differences necessitates further exploration by means of high-quality sex comparative research. Finally, this thesis reached the consensus recommendation that lower exercise loads can be utilised to reduce muscle damage in males; nonetheless, supporting evidence for the application of this recommendation to females is required
On Monte Carlo methods for the Dirichlet process mixture model, and the selection of its precision parameter prior
Full text linkTwo issues commonly faced by users of Dirichlet process mixture models are: 1) how to appropriately select a hyperprior for its precision parameter alpha, and 2) the typically slow mixing of the MCMC chain produced by conditional Gibbs samplers based on its stick-breaking representation, as opposed to marginal collapsed Gibbs samplers based on the Polya urn, which have smaller integrated autocorrelation times.
In this thesis, we analyse the most common approaches to hyperprior selection for alpha, we identify their limitations, and we propose a new methodology to overcome them.
To address slow mixing, we revisit three label-switching Metropolis moves from the literature (Hastie et al., 2015; Papaspiliopoulos and Roberts, 2008), improve them, and introduce a fourth move. Secondly, we revisit two i.i.d. sequential importance samplers which operate in the collapsed space (Liu, 1996; S. N. MacEachern et al., 1999), and we develop a new sequential importance sampler for the stick-breaking parameters of Dirichlet process mixtures, which operates in the stick-breaking space and which has minimal integrated autocorrelation time. Thirdly, we introduce the i.i.d. transcoding algorithm which, conditional to a partition of the data, can infer back which specific stick in the stick-breaking construction each observation originated from. We use it as a building block to develop the transcoding sampler, which removes the need for label-switching Metropolis moves in the conditional stick-breaking sampler, as it uses the better performing marginal sampler (or any other sampler) to drive the MCMC chain, and augments its exchangeable partition posterior with conditional i.i.d. stick-breaking parameter inferences after the fact, thereby inheriting its shorter autocorrelation times
Geoarchaeological Approaches to Pictish Settlement Sites: Assessing Heritage at Risk
Full text linkDue to the poor preservation of Pictish period buildings and the occupation deposits within them, very little is known of daily life in early medieval Scotland. In lowland and coastal areas, Pictish buildings are generally truncated by deep ploughing, coastal erosion, or urban development, while those uncovered in upland areas seem to have no preserved floor deposits for reasons that remain poorly understood. Geoarchaeological techniques are particularly effective in clarifying site formation processes and understanding post-depositional transformations. They are also a powerful research tool for identifying floor deposits, distinguishing their composition, and linking this to daily activities. However, archaeologists are often reluctant to apply geoarchaeological methods if they suspect preservation is poor or stratigraphy is not visible in the field.
This study therefore employs an innovative suite of geoarchaeological techniques to evaluate the preservation of Pictish period buildings and the potential that fragmentary buildings have to reconstruct daily life in early medieval Scotland. Alongside literature analysis and a desk-based comparison with national soil datasets, over 400 sediment samples from three key settlement sites were subjected to integrated soil micromorphology, x-ray fluorescence, magnetic susceptibility, loss-on-ignition, pH, electrical conductivity and microrefuse analysis. The combined data were successful in generating new information about the depositional and post-depositional history of the sites, preservation conditions of the occupation deposits, and activity areas within domestic dwellings. Most significantly, the integrated approach demonstrated that ephemeral and fragmented occupation surfaces retain surviving characteristics of the use of space, even if floors are not preserved well enough to be clearly defined in the field or in thin-section. A partnership with Historic Environment Scotland has channelled this work into research-led guidelines aimed at communicating geoarchaeological methods and principles to a wider audience
Nano-scale structure of polymers and small molecules in organic electronic applications
Full text linkThe thesis explores novel electron microscopy techniques for probing the molecular ordering in organic thin-films at high spatial resolution. The research is relevant to the wider field of optoelectronics as organic electronic devices, such as organic photovoltaics (OPV) and organic light emitting diodes (OLED), have become desirable as a potentially low-cost, flexible, and lightweight alternative to conventional inorganic technologies. The crystallinity in organic materials determines important properties, such as charge carrier mobility, but is extremely complex and difficult to characterise. Unlike standard inorganic crystals that have long-range order (LRO), organic materials tend to be disordered, with some regions of the material amorphous, and other regions semi-crystalline or crystalline. The study uses several electron microscopy methods to examine the nanoscale ordering in organic thin-films, including a variation of the fluctuation electron microscopy (FEM) technique performed in a scanning transmission electron microscope (STEM) to probe the medium-range order (MRO), as well as electron energy loss spectroscopy (EELS) to determine the orientation of π-stacking from the carbon K-edge fine structure. Multislice simulation (Chapter 3) is also used to examine the role of a range of parameters such as particle crystalline size, depth in the sample, atomic number, and para-crystallinity on the expected contrast in dark-field STEM imaging. The effect of these parameters is difficult to isolate by experiment, and therefore simulations are required to make estimates. The sensitivity to parameters such as the particle size was found to be similar to that estimated from experiment.
Chapter 4 presents the FEM results. STEM annular dark field (DF) imaging is used to measure the diffracted intensity of crystalline domains. By varying the inner angle of the annular detector used for DF imaging, it is possible to control the ‘coherence volume’, i.e. the volume over which diffraction takes place. This provides information on the degree of crystallinity as well as domain size. The measurements were first performed on a polycrystalline NiO thin-film test sample. It was found that the STEM technique overall showed the expected behaviour for NiO. After testing NiO, we examined samples of drop cast and spin coated TIPS pentacene by a conventional TEM at 200 kV, and found limitations in the information that could be extracted due to specimen damage under the electron beam. However, we found that useful information could be obtained on a 200 kV Talos TEM with direct electron detector and 4D STEM measurements. The drop cast TIPS pentacene diffraction pattern resembles previous reports in the literature. In particular, diffuse streaking due to pentacene molecular movement is seen. The molecular disorder was not uniformly distributed across the sample, as seen by virtual dark-field images taken from several points along the streak. A virtual dark-field image of the spin coated TIPS pentacene sample showed grains with an average size of 58.7 nm, and the diffraction pattern also showed Bragg reflections. The spin coated sample appears to have more paracrystallinity inside the grains than the drop cast sample, according to variance plots obtained from the same 4D STEM datasets.
EELS spectroscopy (Chapter 5) of the carbon K-edge fine structure is used to map the local orientation of organic thin-films like TIPS pentacene. A natural graphite sample was used to calibrate the π∗/σ∗ ratio as a function of specimen orientation for both TEM and STEM modes. Application of EELS spectrum imaging to a TIPS pentacene thin-film however showed that the minimum dose required for an accurate π∗/σ∗ ratio was several orders of magnitude above the critical electron beam dose for damage under the electron beam. Therefore, successful application of EELS to study molecular disorder requires strategies to overcome the beam damage in organic thin-films. These include increasing the energy of the incident electron beam (higher kV), using a cryo-microscope to cool the specimen, and direct electron detectors with higher detector quantum efficiency, as well as dose fractionation
Optimal Thresholds for Classification Trees using Nonparametric Predictive Inference
Full text linkIn data mining, classification is used to assign a new observation to one of a set of predefined classes based on the attributes of the observation. Classification trees are one of the most commonly used methods in the area of classification because their rules are easy to understand and interpret. Classification trees are constructed recursively by a top-down scheme using repeated splits of the training data set, which is a subset of the data. When the data set involves a continuous-valued attribute, there is a need to select an appropriate threshold value to determine the classes and split the data. In recent years, Nonparametric Predictive Inference (NPI) has been introduced for selecting optimal thresholds for two- and three-class classification problems, where the inferences are explicitly in terms of a given number of future observations and target proportions. These target proportions enable one to choose weights that reflect the relative importance of one class over another. The NPI-based threshold selection method has previously been implemented in the context of Receiver Operating Characteristic (ROC) analysis, but not for building classification trees. Due to the predictive nature of the NPI-based threshold selection method, it is well suited for the classification tree method, as the end goal of building classification trees is to use them for prediction as well. In this thesis, we present new classification algorithms for building classification trees using the NPI approach for selecting the optimal thresholds. We first present a new classification algorithm, which we call the NPI2-Tree algorithm, for building binary classification trees; we then extend it to build classification trees with three ordered classes, which we call the NPI3-Tree algorithm. In order to build classification trees using our algorithms, we introduce a new procedure for selecting the optimal values of target proportions by optimising classification performance on test data. We use different measures to evaluate and compare the performance of the NPI2-Tree and the NPI3-Tree classification algorithms with other classification algorithms from the literature. The experimental results show that our classification algorithms perform well compared to other algorithms. Finally, we present applications of the NPI2-Tree and NPI3-Tree classification algorithms on noisy data sets. Noise refers to situations that occur when the data sets used for classification tasks have incorrect values in the attribute variables or the class variable. The performances of the NPI2-Tree and NPI3-Tree classification algorithms in the case of noisy data are evaluated using different levels of noise added to the class variable. The results show that our classification algorithms perform well in case of noisy data and tend to be quite robust for most noise levels, compared to other classification algorithms
Fast-ion deuterium-alpha measurements on MAST and MAST-U
Full text linkAnalysis and modelling of fast-ion deuterium-α (FIDA) spectroscopy data from both MAST and MAST-U was performed and is described, along with description of the setup of the diagnostic for the first experimental campaign on MAST-U. Analysis of archival MAST data featuring sawtooth crashes show that, while insufficient to distinguish between 3 different ways of modelling the effect of sawtooth crashes on the fast ions, can observe significant redistribution of the fast ions due to the crashes. FIDA data was used to add to a bank of evidence showing problems with the configuration of the neutral beam injection system, which was later confirmed. Analysis of the effect of a large fishbone instability on plasma rotation shows that the large deceleration of the plasma is unlikely to be due to forces induced by a radial inflow of bulk ions, itself induced by a radial outflow of fast ions. An attempt is made to utilise anomalous diffusion in order to examine the effect of Toroidal Alfven Eigenmode (TAE)s and fishbones on the fast ions. Investigation into the effect of locked modes and long-lived mode (LLM)s show severe redistribution due to the locked mode, with correlations made between the dynamics of the locked mode and the FIDA emission. Investigation of the LLM show significant reduction of FIDA emission in core channels, suggesting localised redistribution. Future integration of multiple fast-ion diagnostics including the Solid State Neutral Particle Analyser will allow for a deeper understanding of fast ion/instability interaction
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