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Developing and testing a training program to promote creativity among Saudi female fashion design students : concentrating on a combination of design behaviours, namely visual literacy, creative thinking and use of modelling systems, in the early stages of the design process.
Get PDFThis case study research aimed to develop and test a training program that promotes Saudi
female fashion design students’ creativity in the early stages of the design process. It also
investigated the factors that contributed to its results. The training program targeted a
combination of design behaviours including visual literacy, use of creative thinking
techniques, use of modelling systems and proposed that enhancing these behaviours
together in the early stages of the design process could help improve students’ creativity. A
comprehensive review of the literature in creativity enhancement in design was conducted
to inform the development of the training program. An embedded design of mixed methods
was employed, in which a qualitative method, in the form of a semi structured interview,
was embedded within a quantitative method, in the form of a quasi-experiment with a pre-test-post-test control and experimental group design, to provide a deep and thorough
understanding of the effect of the proposed training program on students’ creativity.
The findings showed a significant enhancement in students’ awareness of creativity and the
creative design process, and significant improvements in all targeted creative abilities in
terms of fluency, originality, and creativity, with fluency being the most increased creative
metric and creativity the least. The findings also revealed the students’ perspective on how
people in their cultures understand and appreciate creativity in fashion and how this
influenced their creativity. The findings also addressed the influence of students’ personal
attitudes on their creative behaviours and abilities in the early stages of the design process
An application of Probabilistic Flood Maps, geodemographics and Agent-Based Modelling to improve the characterisation of flood vulnerability
Get PDFVulnerability is the most important concept within Flood Risk Management. Describing
the propensity to which entities at risk of flooding may be harmed, this concept acts as a
vital framework in which to mitigate and (where possible) eliminate flood risk in the face
of a changing climate. Existing methods to quantify vulnerability and its subcomponents
(exposure, susceptibility, and resilience) are plentiful. However, issues with data
aggregation and deterministic methods mean that the full extent of flood vulnerability is
not captured. Traditional flood maps do not account for hazard uncertainty, coarse social
data make it difficult to accurately define those in the floodplain and human behaviour is
often omitted from risk assessments, therefore ignoring the role of adaptive capacity in
mitigating flood risk.
However, in the era of ‘Big Data’, commercially available geodemographic datasets
present an opportunity to improve the heterogeneity of exposed populations using diverse
social typologies. Increases in computing power combined with advances in sampling
techniques have enabled probabilistic frameworks and Agent-Based Modelling to
flourish. This thesis leverages these technological advances and proposes that
geodemographics, Probabilistic Flood Mapping and Agent-Based Modelling are key
ingredients in developing how flood vulnerability is characterised.
This work reveals new insights for each sub-component of vulnerability by demonstrating
that; spatially aggregated data can mischaracterise susceptibility, failing to acknowledge
hazard uncertainty can under-estimate the number of exposed people and that
heterogenous social typologies could be a useful means of understanding what drives
adaptive capacity and enhancing Agent-Based Models. Not only does this work highlight
how existing techniques can be enhanced by better data, but it presents Agent-Based
Modelling as a holistic platform in which to simulate interaction between physical and
social systems using the three-dimensions of vulnerability as a framework.Engineering and Physical Sciences Research Council fundingHeriot-Watt University fundin
Vital sign sensing using radio frequency technologies
No full textAbstract unavailable. Please refer to PDF. Restricted access until 31.12.2033
Quantum transport on disordered systems of varying dimensions
Get PDFThis thesis is concerned with the ideal conditions for environmental noise-assisted quantum
transport (ENAQT) on various localised systems. By studying the optimal transport properties,
both dynamically and in the steady state, we clarify the relationship between localisation,
system structure, and ENAQT.
Chapters 1-3 provide an introduction and background for the research along with the computational methods used. Chapter 4 contains the first research results: establishing a power law
relationship between the ideal noise rate of disordered 1d chains and their localisation as measured by the inverse participation ratio. Chapter 5 considers Wannier-Stark localisation, the
result of introducing a linear energetic gradient across 1d chains. We show a totally different,
linear relationship between this form of localisation and ENAQT, dependent on the energetic
difference between sites.
Chapter 6 concerns various regular 2d systems, and shows that the effects described for disordered 1d chains still apply. For some 2d systems we also note new behaviour where small
quantities of disorder improve the transport efficiency. Chapter 7 concludes by studying naturally inspired networks of randomly arranged chromophores. We show that counter to existing
assumptions, some of these random 3d systems can have multiple noise rates where their transport efficiency is maximised
Development of novel techniques of model preconditioning, simulator enhancements and well placement automation to accelerate the timeline of integrated reservoir studies
Get PDFThis research developed a novel approach to pre-condition historical datum pressure and
internal reservoir architecture into geological models. A pattern recognition algorithm was
developed to conduct pressure cluster differentiation for deriving the reservoir’s heterogeneity
map which was subsequently used to condition the spatial property field distribution. The
internal architecture was derived from Routine Core Analysis (RCA) permeability data using
a fixed interval average algorithm, and used to condition the vertical property distribution. The
result was a pre-conditioned reservoir model, which honours both the pressure-derived
heterogeneity map and the RCA-derived internal reservoir architecture. The resulting pre-conditioned model required limited history-matching as it already matched the historical
pressure data within an acceptable misfit tolerance, thereby saving considerable time by
eliminating the need for time consuming history-matching.
A novel methodology was also developed to derive Saturation Height Function (SHF) and
Petrophysical Rock-Type (PRT) from RCA and log data in the absence of Mercury Injection
Capillary Pressure (MICP) data, using k-means clustering. The results were similar to SHF and
PRT from MICP-based Winland’s approach. When dealing with a secondary reservoir having
little or no MICP data, the developed methodology enables a reservoir study to advance rather
than wait on the acquisition of expensive MICP experimental results.
A novel well placement automation process and algorithm were developed, for rapid placement
of infill and sidetrack wells in simulation runtime, thereby eliminating the longer time required
by traditional manual processes.
More representative numerical modelling of equivalent dual-media pressure, wellbore pressure
of shut-in wells, productivity index and frontal advance of water-oil immiscible displacement
were developed. Seven USPTO patents were filed on the novel methodologies developed in
this research, of which four have been granted.
For the purpose of confidentiality, the developed algorithms are not disclosed in this document,
but a process workflow of the algorithms are clearly presented
Embedding optical sensors within additive manufactured high melting point metals for condition measurement within harsh environments
Get PDFThe use of optical fibre sensors, such as fibre Bragg gratings (FBG), provides opportunity for condition
health monitoring of a structure or process. FBGs allow for in-situ measurement of temperature and strain.
The measurement of these parameters is important for advanced and complex structures where these
sensors can provide real-time information to support lifetime condition monitoring.
In general, sensor reliability drops as the temperature, moisture content and environmental corrosiveness
increases. These limitations can be overcome by embedding sensors in high melting point metals to extend
their operation for use at elevated temperatures and within harsh environments.
A fibre embedding process chain has been devised to facilitate embedding of optical fibres within additive
layer manufactured (ALM) stainless steel (SS) components. The ALM process provides access to any
point of the component during manufacture, which is beneficial for the embedding of sensors inside a
functional component. Furthermore, parts with complex geometries and internal features, unattainable with
other forms of manufacture, become feasible using ALM technologies, but pose additional challenges for
accurate modelling and external monitoring. Embedding sensors directly into such structures is a possible
solution to this challenge.
Selective laser melting is a powder bed fusion ALM technique where a laser selectively melts metallic
powder in accordance with the geometrical data of the build layer, defined by a 3D model. The small spot
sizes achievable by selective laser melting (SLM) systems are well suited for fibre embedding as the
localised melt pools limits interaction through conduction with the surrounding material. A system has
been set up for use with SS-316 powder, that is capable of embedding fibres in test structures. The high
nickel content within SS-316 allows for intermixing of the host material with the fibre protective nickel
jacket thereby bonding the fibre to the surrounding material.
The work of this thesis defines process parameters suitable for repeatable and reliable embedding of FBG
sensors inside SS-316 coupons. 5µm thick Cr layers are deposited onto lengths of stripped optical fibres
containing FBGs using the RF sputter deposition system (RF power 100W, deposition time 30mins,
processing pressure 410
−4mBar). This is followed by a ≥300 µm Ni coating using the developed Ni
plating system (current density 2-7 A/dm2
, voltage 30V max, plating time ≥16hrs). The SLM build
parameters for building SS-316 coupons (100W Laser power, 300mm/s scanning velocity, 60μm hatch
spacing, 200μs pulse duration, 1kHz modulation frequency and scan orientation rotated by 90° between
layers) and the modified build parameters for the embedding process (90W laser power, 300mm/s scan
velocity, 100μm hatch spacing, 200μs pulse duration, 1kHz modulation frequency and a scan orientation
parallel to fibre profile) are defined with respect to optimisation of the available equipment for fibre
embedding procedures
Drivers and success factors of digital transformation in manufacturing in Poland and Romania : evidence from two Tier 1 companies
Get PDFDigital transformation is becoming increasingly influential, both in business and in research. For companies with a complex global footprint and production sites in different
countries, as is the case for Tier 1 suppliers that directly supply automotive manufacturers, it is critical to understand the factors for a successful implementation of digital initiatives in different locations in order to carry out an effective digital transformation. Romania and Poland are popular production locations, which increases the importance of
understanding the particular needs of the locations. Current studies on drivers and success
factors mainly refer to manufacturing and few to automotive. Differences between Poland
and Romania have not been considered so far.
This thesis, through a critical realism approach, provides improved understanding of managers’ different perceptions of digital transformation in Poland and Romania in the drivers
and success factors of digitalisation for Tier 1 suppliers.
For this purpose, a case study has been performed consisting of two Tier 1 suppliers,
which were selected using convenience sampling, have manufacturing sites in both countries and are in similar states of digitalisation as assessed by the IT and plant managers
using the Schuh et al. (2020) model. Twenty semi-structured interviews, each of which
included a questionnaire for triangulation, were conducted with five purposively sampled
managers from each production plant in Romania and Poland between November 2021
and March 2022 to inquire about objectives, drivers and success factors of digital transformation in general and based on their experiences from previous initiatives. The indicative study was analysed using thematic analysis.
The results of the study suggest that managers’ perceptions of the drivers and success
factors of digitalisation are similar but differ from the available literature in their focus
on operational excellence. According to the study results, the main difference between
the two production locations include how emotions are addressed and recommends to
implement a change management process. In addition to managers, production plants’
key stakeholders in digital transformation are the continuous improvement department,
IT-related departments, and departments that work closely with production. The departments should initiate projects, and decisions should be made top-down. The main success
factors the interviewees noted are business benefits and the communication of such.
Covid-19 is a driver for digital transformation, particularly for administration
Exploring the coaching relationship in health coaching and employment service with long-term unemployed using Repertory Grid Technique
Get PDFCoaching in general and health coaching are increasingly used to change (health-related)
behaviour. However, little research exists on the specific impact factors of coaching and
especially on what constitutes effective (health) coaching relationships.
This research explores in a jobcenter in Germany what contributes to effective (health)
coaching relationships in health coaching and employment service coaching. It assesses
both the perspectives of the (health) coaches and the (health) coaching clients, who are
long-term unemployed people with health restrictions. Specifically, this research
investigates how the participants construe effective (health) coaching relationships.
Furthermore, it addresses the commonalities and differences in the construction of
effective (health) coaching relationships within/between coaches and clients and
within/between coaching domains. In addition, it is explored how consistently
participants in the different groups evaluate effective (health) coaching relationships.
Based on a phenomenological constructivist epistemology, the Repertory Grid Technique
is used within a Personal Construct Psychology framework for data collection to elicit
latent constructs signifying effective coaching relationships from coaches and coaching
clients, as this technique is especially useful for exploring individual and interpersonal
aspects of human relationships.
Results indicate the effectiveness of Personal Construct Psychology and Repertory Grid
Technique for Coaching Psychology research on the coaching relationship. The content
analysis identified 27 themes of which 12 were relevant to the development of effective
(health) relationships for the total sample. Differential analysis identified themes of
particular importance for the different subgroups. Conclusions after structural analysis
suggest that these categories represent a ‘pool’ of important factors for effective (health)
coaching relationships, from which quite individual constellations of these factors make
the (health) coaching relationship effective. The findings theoretically and
methodologically contribute to Coaching Psychology. Furthermore, the findings are of
utility for coaching practise and can help to create ethical, more effective (health)
coaching relationships. The limitations of this study, its implications for further research,
and coaching practise are discussed
Predicting water content in hydrocarbon production systems
Get PDFThe formation of hydrates in hydrocarbon mixtures presents challenges in industrial sectors,
necessitating the determination of water content, in addition to identifying pressure and temperature
conditions that ensure a hydrate-free zone during production, processing, and transportation. Different
models have been suggested to predict the minimum water content, required to avoid hydrate to form.
However, the capabilities of these models for accurate representation of these variables need to be
evaluated.
In this study, water content measurements of liquid propane in equilibrium with liquid water or
hydrates were determined across a range of pressures (up to 8.274 MPa) and temperatures (276.15 to
313.15 K) using three different measurement methods: a quartz crystal microbalance (QCM), a silicon
oxide-based hygrometer and a novel method developed by Burgass et al. (2021). The new method and
QCM measurements exhibited good agreement. The fluid phase behaviour of the propane-water
system was modelled using the simplified Cubic-Plus-Association (sCPA-SRK) equation of state,
which provided accurate predictions. Deviations of 4.5% were observed between the experimental
measurements and the sCPA-SRK model within the temperature range of 276.15 to 313.15 K. Hydrate-forming conditions were modelled using the van der Waals and Platteeuw's solid solution theory,
showing good agreement with the literature data.
For ethane, a model based on the sCPA-SRK equation of state coupled with the van der Waals' classical
mixing rules and van der Waals’ and Platteeuw's solid solution theory was employed to determine the
minimum water content required for hydrate formation. The model achieved an average absolute
deviation of 9.25% when compared to experimental measurements obtained from this study and
existing literature. Additionally, the model accurately predicted ethane solubility in the aqueous phase
and hydrate dissociation points. The study also investigated methane, the primary component of natural
gas supply, and provided water content measurements for 9 hydrocarbon mixtures. The sCPA-SRK
equation of state was used in conjunction with the van der Waals' classical mixing rules and the van
der Waals’ and Platteeuw's solid solution theory to determine the minimum water content required for
hydrate formation. The model achieved an overall average absolute deviation of 5.2%
Properties of gauge fields and quantum matter
No full textGauge fields are found in the modern description of gravity and the most fundamental
interactions known in our Universe, but they also appear when describing why a cat always
lands on its feet. Gauge fields are both physical entities and useful resources that help us
sharpen our understanding of the world.
In this thesis, we explore the ability of certain gauge fields to deeply alter the properties
of quantum matter and even its mere identity. These dramatic effects become palpable when
said fields back-act on matter. Things get even more exotic when robust structures known as
topological solitons are present in the systems under study.
This work is a journey across dimensions, curved spacetimes, and unconventional phases of
matter. We introduce a composite particle duality, engineer synthetic flux attachment, elaborate
on chiral axion electrodynamics, and delve deep into statistical transmutation. Out of this study,
we are able to predict new topological phases of matter, find anomalous features in the dynamics
of fields, gain a universal understanding on how bosons and fermions can be transmuted into
one another, and speculate on the reason why things gravitate
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