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Applying ANN technology to determine acceptable control parameters for the National Library of Scotland’s collections to inform energy efficiency improvements in the UK heritage sector
Get PDFThe National Library of Scotland (NLS) uses purpose-built storage enclosures to protect
their heritage collections. These enclosures can moderate micro-environmental
temperature and humidity fluctuations inside. This study aims to determine an acceptable
macro-environment in storage room to inform energy efficiency improvements based on
a relaxing macro-environmental control. There are four objectives: 1) to assess the
feasibility of using the enclosure’s buffering capacity and to obtain its hygrothermal
properties; 2) to determine an acceptable macro-environment; 3) to achieve real-time
micro-environment predictions; and 4) to assess potential energy savings from the relaxed
control strategy.
Correspondingly, the methodology comprises four parts: 1) using laboratory measures to
quantify the buffering capacity of an enclosure and associated hygrothermal properties;
2) using a heat, air, and moisture (HAM) transfer model to simulate the hygrothermal
interaction between macro- and micro-environments, and using a trial-and-error method
with this model simulation to determine the acceptable macro-environment; 3) training a
long short-term memory neural network; and 4) using a transform function to create the
energy consumption model.
The results show that 1) The enclosure’s buffering capacity is feasible to moderate the
short-term micro-environmental temperature and RH fluctuations. 2) The acceptable
macro-environment was determined to be 33%~65% RH and 15-25 °C control bands with
±16% RH and 5 °C 24 h fluctuations while there is no any detrimental effect on collections.
3) The trained Long Short-term Memory (LSTM) neural network can is robust for real-time prediction of micro-environment. 4) Implementing the relaxed control strategy
presents a promising way to achieve the NLS's targeted annual reduction rate of 7.6%
over the next decade.
In conclusion, this study confirms that relaxed macro-environmental controls, enabled by
the enclosure’s buffering capacity, ensure collection safety while achieving significant
energy savings. Additionally, this control strategy advances the NLS’s building
management toward smarter, energy-efficient control and offers scalable solutions for
other heritage institutions
Identifying the chemical, biological and physical conditions involved in marine (oil) snow formation and microbial biodegradation of entrained oil
No full textThe formation of marine oil snow (MOS) was a major event during the Deepwater
Horizon disaster, with significant consequences to the fate of spilled oil. This process likely has
direct implications on the biological carbon pump, the overall effect of which is still widely
unknown. Many research gaps remain within MOS research, and using ‘model’ oil snow
aggregates produced in the absence of living cells allows the disentangling of chemical,
biological and physical processes involved in aggregate formation and on the oil
biodegradation process.
Using roller-table microcosms containing crude oil and microbially-produced and
commercially available polymers, chemical properties including protein/carbohydrate ratio
and molecular size were assessed for their capability to form snow aggregates. Using cell-free
‘model’ aggregates, oil biodegradation by selected individual bacterial strains, isolated from
the Deepwater Horizon plume, from the point of colonisation, was measured using oxygen
microprobes and gas chromatography. The microbial community associated with colonisation
of oiled particles in the northeast Atlantic was assessed to firstly identify any significant
differences in community composition of the particles compared to that in the surrounding
seawater, and secondly to identify which members of the particle-attached community
contributed to oil degradation. Following these experiments, the physical interactions of
polymer, seawater, crude oil, and chemical dispersant were assessed with a combination of
laboratory observations and computational simulations of ‘model’ aggregates.
Using bespoke, model oiled aggregates formed using commercial polymers of known
molecular weight, structure and composition, carefully controlled experiments were
conducted that revealed molecular size may be an indicator of marine snow and oil snow
formation, and contests widely accepted hypotheses that the protein/carbohydrate ratio as a
proxy for ‘stickiness’ play a role in chemical-mediated aggregation. Model aggregates exposed
to single oil-degrading bacterial species also offered a unique perspective, allowing the oil
biodegradation rates of individual Deepwater Horizon strains to be measured, and confirming
that for some strains, aggregates can act as a ‘hotspot’ for enhanced oil biodegradation rates.
Upon further investigation with model aggregates exposed to northeast Atlantic bacterial
communities, specific taxa, such as members of the genus Pseudoalteromonas, were identified
as key players in aggregate-associated oil attenuation. Computational models identified interfacial interactions between oil and polymers to be key in MOS formation, and showed the
efficacy of chemical dispersant in the process of oil droplet entrainment into MOS aggregates.
The research within this thesis provides biological, chemical and physical perspectives to
knowledge gaps surrounding marine snow and MOS formation, and biodegradation of MOS-associated oil, paramount to furthering oil spill mitigation plans
Understanding CO2 flow measurement for carbon capture and storage (CCS) transport applications
Get PDFCarbon Capture and Storage (CCS) is a decarbonization solution, particularly suited to
industries with hard-to-abate emissions such as cement, iron & steel, and fertilizer production.
However, as a prerequisite for commercialisation of CCS, accurate measurement is required
for quantifying CO2 streams across the CCS value chain and to comply with a range of
environmental legislation and regulations.
Unlike other industrial process fluids such as water, oil, and natural gas, it is still unclear
whether current commercially available metering technologies can meet the requisite accuracy
levels, specifically the ±2.5% accuracy recommended within the EU/UK European Trading
Scheme for CO2 mass transfer.
Therefore, this research is aimed towards gaining a comprehensive understanding of flow
measurement of CO2 under relevant CCS transport conditions. This understanding is crucial
for examining the capabilities of both Coriolis and orifice meters under more realistic CCS
transport conditions, specifically assessing whether these CCS metering technologies meet the
MRR Tier 4 MPE requirement. The experimental study predominantly focuses on evaluating
the performance of two distinct designs of Coriolis meters and an orifice meter, across gas,
liquid, and supercritical conditions, using both pure CO2 and CO2-rich mixture samples.
In order to understand the influence of non-condensable gas impurities in CCS flow operations,
a review of relevant thermodynamic modelling equations was conducted. These models play a
relevant role in predicting the optimal transport conditions for the CO2-rich mixtures.
Moreover, a dedicated laboratory-scale gravimetric flow facility was designed for conducting
CO2 flow measurement tests. Using this facility, flow measurement tests were conducted to
evaluate the performance of the selected meters under gas, liquid, and supercritical flow
conditions. Additional tests were conducted to assess the performance of one of the Coriolis
meters with light energy carrier gases (hydrogen-methane blend).
The findings from these flow experiments indicate that the non-condensable impurities, such
as N2, H2, O2, Ar, and CH4 have a relatively minor impact on Coriolis meters, with maximum
mean absolute errors of 0.51%, 0.26%, and 0.56% observed in gas, liquid, and supercritical
CO2 flow conditions, respectively. However, the impact of these impurities, which is often
associated with an increase in the compressibility of the fluid and reduction in density or
homogeneity of the fluid, tends to become apparent with different Coriolis designs or quality
of flow operation (flow rates and regions).
In the case of the test orifice meters, impurities also have a less noticeable impact during
gaseous flow conditions, with the highest recorded mean absolute error reaching approximately
1%. However, the impact of these impurities becomes more noticeable in liquid and
supercritical flow conditions, resulting in maximum mean absolute errors of 2.84% and
11.14%, respectively. It is worth noting that although impurities seem to have a more
pronounced effect in these dense phases (high density liquid and supercritical phases), a
substantial component of these errors can be attributed to uncertainty in the density
measurements.
These results conclude that Coriolis metering technology as a robust choice for CCS metering,
underscoring its suitability for accurate measurements in single phase CO2 transport conditions,
as well as in handling other relevant low-carbon fluids. Meanwhile, the performance of orifice
meters in gaseous flow conditions emphasizes their effectiveness and potential applicability in
repurposed gas pipeline infrastructures for CCS transport applications.
The overall outcome of this study helps contribute towards understanding flow measurement
capabilities of specific commercially available CCS metering technologies. The assessment of
these meters offers crucial insights and measurement data to understand how well some
existing flow metering technologies, currently employed in the oil and gas industry, can be
adapted for CCS transport metering applications. The study also helps understand the impacts
of non-condensable gas impurities in CCS flow operations, showing how well these impacts
can be handled to improve flow activities
Laser manufacturing techniques for non-conformal circuitry, photovoltaics integration and perovskite synthesis
Get PDFThis thesis examines the use of laser manufacturing techniques to fabricate copper
electrode and perovskite materials. Laser beam technology known for its precision and
flexibility, proves advantageous in fabricating complex and accurate structures, including
3D circuitry. This thesis focuses on four key areas of investigation.
Firstly, the study investigates the use of laser for printing copper electrodes on a
polycaprolactone (PCL) substrate, which is a biodegradable material of choice for green
devices. A combination of chemical processes performed before and post laser treatment,
results in cost-effective fabrication of conductive copper tracks on biodegradable surfaces
without the need for expensive equipment or materials. This technology could find
application in biodegradable sensors powered by non-toxic solar cells.
Secondly, a low-power laser is employed to produce 3D printed circuits on non-planar
surfaces by using laser diode integrated into a 5-axis machine. For this, a new technology
has been developed to deposit the contacts on any material substrate. This enables the
precise patterning on curved surfaces of a robot part, which allows the integration of
perovskite solar cells into the robot surface. The performances of these circuits, along
with the integrated solar cells, are conducted under solar simulator, revealing outstanding
performance.
The third area of investigation focuses on the solar cell manufacturing of cobalt-based
hybrid organic inorganic perovskite (HOIP). A laser is utilized for patterning a fluorine
tin oxide (FTO) substrate, then the substrate is used to deposit a Co-based lead-free
perovskite solar cell. This study includes a comparative analysis of device performance
and efficiency, by contrasting the configuration that includes the laser-Patterning
substrate with another Co-based solar cell that follows the conventional architecture.
Lastly, laser direct writing is employed to synthesize inorganic perovskite materials, such
as CsPbBr3 nanoparticles. This study proposes a novel approach of in-situ synthesise
perovskite nanocrystals through direct laser writing within polymer thin films. The
process involves spin coating layers of different precursors (CsBr + PMMA), (PbBr2 +
PMMA) ), followed by laser patterning. CsPbBr3 nanomaterials of varying sizes are
obtained. The technique offers controlled fabrication of nanocrystals within a polymer
matrix
Behaviour-based security with machine learning on IoT networks
Get PDFThe proliferation of Internet of Things (IoT) devices has transformed various aspects
of human life, yet has brought forth significant security challenges due to device heterogeneity and limited resources. Addressing this, the thesis focuses on reliable and
reproducible IoT security measures, specifically device identification (DI) and attack detection (AD). With over 10 billion devices currently connected and a projected 80 billion
by 2026, securing IoT devices is critical. Traditional security approaches face hurdles
due to device diversity, while IoT devices are prone to rapid attacks. Behaviour-based
methods, particularly utilising machine learning, offer potential solutions for both DI
and AD. However, existing studies suffer from limitations in addressing IoT heterogene ity, analysing information leakage features, understanding machine learning insights, and
ensuring reproducibility.
This research aims to bridge these gaps by developing robust, transparent, and generalizable solutions for IoT DI and AD. For DI, a novel aggregation algorithm addresses IP
and non-IP device challenges, significantly improving accuracy. Comprehensive feature
selection results in an optimal feature set, validated across diverse datasets. In AD, a
packet-level expanding and rolling windows method detects attacks earlier, outperforming conventional flow methods. The models are evaluated on isolated first-time-seen
attack datasets, showcasing their adaptability to novel attacks. Furthermore, machine
learning models and features are analysed for deeper attack insights.
The thesis underscores the interdependence of device identification and attack detection within IoT security, emphasising their mutual reinforcement for network safety. By
offering reproducible methodologies, transparent analyses, and adaptable models, this
work contributes to enhancing the security of IoT devices and networks. Ultimately, this
research paves the way for a more secure IoT ecosystem by addressing the unique challenges posed by IoT heterogeneity, resource limitations, and dynamic attack patterns
Towards a set-theoretic foundation of mathematics closer to mathematical practice
Get PDFSet theories like Zermelo-Fraenkel (ZF) are widely used foundations of mathematics. The axioms of ZF and other related systems (e.g., ZFC, TG) allow founding nearly all branches of mathematics within a unified setting. For this reason, set
theories are deeply interesting to mathematicians, logicians, computer scientists
and philosophers.
Foundations are a key component of a kind of computer software called proof
assistants which allow writing and checking mathematical definitions and proofs
with machine assistance. In ZF and similar set theories, nearly all mathematical
objects are of the same type, namely the type “set”. Whilst set theory has been a
popular foundation in mathematical culture, many widely used proof assistants
rely crucially on type theories in which mathematical objects are organized into
a vast number of types. Therefore, formalizations of mathematics in such proof
assistants are drastically different from formalizations in set theory, and therefore
different from the practice of many working mathematicians.
In this thesis, we explore the development of a foundation of mathematics that
maintains some of the advantages of set theory, whilst also gaining some of the
benefits of type theories. Namely, we further develop Aczel and Lunnon’s concept
of a generalized set theory (GST), which is similar to a standard set theory, but allows
having mathematical objects like pairs, functions, ordinals, and so on, as objects
that are not sets.
We present GSTs via axiomatization in higher-order logic (HOL), making use
of soft types in our presentation of GSTs to manage bookkeeping of many properties in a fashion similar to that of a type theory. We generate axioms of GSTs by
assembling together features that specify different kinds of mathematical objects,
including an exception feature which aims to ease treatment of partial functions
and undefinedness. When assembling a GST, extra axioms are generated following a user-modifiable policy to fill specification gaps. We also provide a methodology for building models of GSTs as von-Neumann-style cumulative hierarchies
defined via ordinal recursion.
We have developed a formalization in Isabelle/HOL (one of the most widely
used proof assistants) that provides tools for specifying GSTs and justifies belief
in the soundness of our approach. In particular, we define a specification of and
build a model for ZF+
, a GST with features for sets, ordered pairs, functions, ordinals (with transfinite recursion), and the exception feature. We achieve this
without adding any axioms to Isabelle/HOL other than those given by ZFC in
HOL, which is an extension of Isabelle/HOL written by Paulson (the originator
of Isabelle).Engineering and Physical Sciences Research Council (EPSRC) Project reference EP/R513040/1 227371
New developments of the sequential probability ratio test control chart
Get PDFThis thesis aims to enrich the literature on the SPRT control chart following two
major contributions made in the late 1990s and early 2010s. The SPRT chart has
been chosen as the central premise of this thesis due to its strong detection
performance as well as high sampling efficiency. Two major research gaps have been
identified. The first gap is the lack of documentation on the SPRT chart with
estimated process parameters and its statistical design. The second gap is the lack
of a well-motivated SPRT chart for joint monitoring of the mean and dispersion of
a process. To fill the literature gaps, we formulate the theoretical framework for
the SPRT chart with estimated process parameters, as well as develop a new SPRT
chart for joint monitoring of the mean and dispersion. Optimisation designs based
on various industrial objectives have been developed in this thesis. Real industrial
examples involving a variety of destructive and non-destructive tests are also
presented in this thesis to illustrate the implementation of the proposed SPRT
charts. The thesis should serve as a reference to researchers working in the field of
statistical quality control, as well as practitioners seeking to improve the
performance of their processes
Ultrafast excited-state dynamics of small aromatic molecules in the solution phase
Get PDFPhotochemistry is the study of chemical processes that occur from the interaction of light
with matter. As photochemical processes have a wide range of applications in everyday life
as well as in nature, a deep understanding of the mechanisms through which different
molecules react to absorption of light is highly beneficial. This thesis will explore the time-resolved photodynamics of various small aromatic organic molecules, which can serve as
basic building blocks for different natural products, advanced materials, and pharmaceuticals.
To achieve this, a new in-house ultrafast transient absorption spectroscopy experiment was
commissioned, permitting sub-picosecond tracking of the energy redistribution mechanisms
operating in these molecules upon photoexcitation by ultraviolet light (specifically 267 nm).
The first novel experiment undertaken with this setup was an investigation of the
photodynamics of nitrobenzene, the simplest nitroaromatic molecule, in hexane and
isopropanol solutions. This work successfully resolved discrepancies between several other
studies in the literature and identified, for the first time, the role of the T2 excited state.
Overall, the findings provide an important example of how different spectroscopic techniques
can exhibit varying sensitivity to specific steps along the overall photochemical reaction
coordinate.
After this, a series of six bicyclic azanaphthalene molecules (quinoline, isoquinoline,
quinoxaline, quinazoline, 1,6-naphthyridine and 1,8-naphthyridine) were systematically
investigated under hexane solvation. The aim of this work was to investigate the influence
that the relative positioning of nitrogen centres within aromatic systems exerts on the
quantum yield of intersystem crossing (ISC) from the singlet to triplet manifold. Significant
variation in ISC propensity was observed across the series of molecules studied and this is
rationalised in terms of the various excited state couplings and energy barriers.
Finally, the thesis concludes with an outlook on future (and currently ongoing experiments),
including the photodynamics of indole and the conversion of the setup to investigate a
number of solid-state paint pigments
Mid-infrared photonic imaging strategies
Get PDFImaging at mid-infrared (MIR) wavelengths between from 3–12 µm can provide unique
insights and contrast mechanisms because of the low scattering of MIR light and the chemical
specificity of MIR absorption. Consequently, new light sources and spectroscopic methods
applied in the MIR offer previously unavailable capabilities for MIR hyperspectral (HS) or
depth-resolved imaging. In this thesis, I report the development of three new MIR imaging
techniques, configured in particular for applications in heritage science.
Current MIR HS imaging technologies are expensive, as they employ complex cooled
MIR detectors, or slow, in terms of acquisition rates. These factors limit widespread use
in certain applications such as pigment mapping of paintings for cultural heritage. Here, I
demonstrate two relatively inexpensive and fast HS imaging systems which utilise novel
compressive sensing strategies.
The first system is an imaging Fourier-transform spectromter (IFTS) based on recording
a set of microbolometer camera frames of a sample’s response to illumination by uniquely
spectrally structured blackbody radiation from a Michelson interferometer. The developed
non-uniform sampling strategy was, to my knowledge, the first practical implementation of
compressive sensing in Fourier-transform spectroscopy and enabled a sampling rate as low as
15% Nyquist-limited sampling with a generic prior. The instrument was used in a campaign
at the Hunterian Museum on the artwork “Uplands in Lorne” by David Young Cameron.
A second system utilised a fast digital micromirror device (DMD) to arbitrarily shape
MIR spectra, providing sample illumination by optimised spectral structures for material
identification.
OCT has seen extensive work in the visible and near-infrared (NIR) but not as much
in the MIR. This is, in part, due to the limitation of suitable MIR ultrafast sources. MIR
OCT has the advantage of greater sample penetration depth which could find applications
in the security sector. Results are presented from an MIR time-domain OCT system with
an ultrafast orientation-patterned gallium phosphide (OP-GaP) optical parametric oscillator
(OPO)
Development of compact optical devices using ultrafast laser inscription
No full textAbstract unavailable. Restricted access 01.03.2025. Please refer to PDF
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