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Enhancing agile application in construction projects using BIM
Get PDFThe construction industry's traditional management approach faced some difficulties during the
project lifecycle. This research integrated agile project management principles with Building
Information Modelling functionalities to develop a strategy to overcome some of the challenges
facing construction projects. On the other hand, agile project management had left a positive and
effective print in the software and manufacturing industries. So, this research reflects upon the
implementation of agile as a management approach for the construction industry. Moreover, the
technology revolution in the construction industry started to apply and develop modern methods
of 3D, 4D and nD modelling techniques. BIM (Building Information Modelling) is a technical
programme and a process that adopts changes and provides better results to the management and
construction team during the project lifecycle.
This research approach is deductive research. This study considered several measurements to
validate the study findings. The research epistemology is positivism which depends on science to
evaluate results. The research ontology is objectivism influenced by values, beliefs, culture, rules
and social acting. Moreover, this research strategy considered qualitative and quantitative
approaches to collect data and analyse results based upon professionals in the construction and
software industries. Also, it is designed on both primary and secondary case studies to drive data
from the two sectors (construction and IT sectors). The study relied on multiple research
methods encompassing interviewees, questionnaire surveys and Delphi techniques to collect data
from professionals in these sectors. The evaluation criterion considered validity to confirm
research results.
A summary of the research finding revealed that the agile project management approach's
application increased the construction industry's productivity by eliminating non-adding value
activities and increasing collaboration and communication with stakeholders. Moreover, this
study found that the adoption of BIM will enhance the capabilities of agile methods to achieve
more successful construction projects by reducing human errors, avoiding reworks and
improving quality.
In this research, agile project management is evaluated more practically in adopting changes,
communication, encouraging and empowering individuals. On the other hand, this study carried
out additional assessments on BIM functionalities of simulation, 4D scheduling, 5D cost
estimation, collaboration and coordination. In addition, this study investigated Agile, and BIM implementation challenges to support professionals in the construction industry to overcome
these challenges.
This research has proven that the agile project management approach can improve the
construction industry's productivity. Moreover, BIM technologies supported team members to
understand and visualise the project during the design and construction stages. BIM assists the
project management team ensure better time management, constant improvement, and reduction
of uncertainties, minimising risks and better financial control to make better decisions.
This research developed 2D, 3D and 4D dimensional integrated frameworks between 12 agile
principles and 13 BIM functionalities, RIBA plan of work and procurement methods. These
integrations are validated through case studies, interviews and questionnaire surveys and linked
to a literature review to support this study
An improved approach for quantifying the impact of geological uncertainty and modelling decisions on static and dynamic reservoir models - a case study from a giant fractured carbonate reservoir
Get PDFCarbonate reservoirs hold more than 60% of the world's oil and 40% of the world's gas
reserves. These reservoirs are characterised by geological heterogeneity, petrophysical
complexity, presence of naturally fractures, and mixed wettability, all of which contribute
to significant uncertainty in volumetric estimation and fluid flow behaviour within the
reservoir.
In this thesis, a comprehensive 3D multiple deterministic scenario workflow was applied
to compare and contrast how modelling decisions and geological uncertainties influence
this reservoir's volumetric estimates and flow behaviour. Specifically, the uncertainties
associated with the presence of fractures, the approach to reservoir rock type, and the
modelling of the initial hydrocarbon distribution were examined. This workflow was
applied to one of the giant complex carbonate reservoirs known to be fractured with a
thick transition zone in the Middle East. The most significant findings of this work
demonstrate that even minor changes in modelling decisions and reservoir rock typing
have a substantial effect on the saturation model, resulting in up to a 28% change in
STOIIP estimates, which may potentially mask the effect of other geological
uncertainties. These models were validated using repeated and randomised blind tests.
Such uncertainties must be carried forward in future reservoir management decisions and
when estimating reserves. Additionally, some of these reservoir models led to
significantly improved history match, especially for wells located in the transition zone
of the reservoir. The best history matches were obtained once sparse, fault-controlled
fractures were included in the reservoir model, using effective medium theory. The
presence of fractures specifically improved the history matching quality for wells located
close to the faults; these wells were very difficult to match in the past as fractures were
not considered by the operator.
This thesis demonstrates that a multi-deterministic scenario workflow is key to exploring
the appropriate range of geological uncertainties and that, equally importantly, the impact
of different modelling decisions (i.e., interpretation of the top structure, geostatistical
parameters, reservoir rock type approach, saturation approach, and presence of fracture)
must be accounted for when quantifying uncertainty during reservoir modelling. This is
particularly applicable to giant carbonate reservoirs, where relatively minor changes in
the workflow and data interpretation influence reserve estimates and subsequent history
matching and forecasts
Emergent geometry and discrete curvature in random graphs
Get PDFIn this thesis, we explore various themes relating to the emergence of geometry in (ensembles of
random) graphs in connection with the notion of Ollivier curvature, a synthetic generalisation of the
manifold Ricci curvature. In particular we study the problem of computing the Ollivier curvature
in classes of graphs, presenting the most general valid explicit expressions available. These exact
expressions greatly facilitate the analytic and numerical study of a model of random graphs dubbed
combinatorial quantum gravity by its initiator Trugenberger [282], essentially defined by a formal
discretisation of the Einstein-Hilbert action. Restricting to a configuration space of cubic graphs
allows us to show both analytically and numerically that there is a geometric phase consisting of
a discrete cylinder/M¨obius strip. The scaling limit—formally a Gromov-Hausdorff limit—of these
configurations turns out to be the circle, while numerical evidence suggests that the transition
to this geometric phase is continuous. The critical temperature appears to be asymptotically
nonfinite. Higher degree results are less conclusive and the phase transition appears to become
first-order, but there are good analytical and numerical indications that configurations retain a
nearly geometric phase. We also develop a geometric convergence theory for the Ollivier curvature
in discrete graphs that approximate (compact) Riemannian manifolds in the sense of Gromov-Hausdorff and find a convergent discrete Einstein-Hilbert action. Our results thus present some
of the best concrete models of geometrogenesis in discrete structures and show that the Ollivier
curvature can be used as the basis for a regularisation of classical Euclidean spacetime in terms of
networks
Expectation propagation for scalable inverse problems in imaging
Get PDFThe solutions of ill-posed inverse problems in imaging are usually non-unique,
making it important to quantify the uncertainties associated with the estimates.
Bayesian inference provides a powerful theoretical framework to derive various summaries of the posterior distribution of the unknown parameter of interest, such as
the posterior mean and covariance. However, using Bayesian inference to find such
solutions requires to compute integrals over the high-dimensional unknown image
vectors. While Markov chain Monte Carlo sampling based methods are classically
and widely used to draw samples from the posterior distributions, sampling methods
for accurate evaluation of higher-order moments are still computationally expensive
and not yet fully scalable for fast inference.
Expectation Propagation provides a fast alternative to sampling methods and
has recently become popular for approximate Bayesian inference. In this thesis,
a set of new Expectation Propagation algorithms are proposed to achieve scalable
posterior approximation for high-dimensional imaging inverse problems. The main
contribution of this thesis is to construct new Expectation Propagation algorithms
to provide both point estimate and uncertainty quantification for imaging inverse
problems. By designing the factorization over the posterior distribution and tailoring
the covariance matrix structure of the approximating distributions, the resulting Expectation Propagation algorithms are scalable to address high-dimensional imaging
problems. The main novelty considers three aspects: (1) block diagonal covariance
matrix structure is, to the best of this author’s knowledge, proposed for the first
time in applying Expectation Propagation for Bayesian models with patch-based
image prior, (2) factorization over convex and non-convex gradient-based priors is
designed to allow for highly parallel computation in using Expectation Propagation
to solve high-dimensional imaging inverse problems, and (3) the proposed Expectation Propagation algorithms are embedded within larger inference schemes where the
prior regularization parameters are unknown. Without significantly increasing the
computational footprint, the resulting Expectation Propagation based algorithms
allow for greater scalability with unsupervised hyperparameter tuning
Evaluation and prediction of Enhanced Oil Recovery (EOR) by Low Salinity Water Flooding (LSWF) injection
Get PDFLow Salinity WaterFlood (LSWF) injection is an Enhanced Oil Recovery (EOR)
method proven to be effective by extensive experimental studies. Correct implementation
of this method in reservoir-scale simulations requires reliable estimation of relative
permeability data. However, due to the ongoing debate regarding the dominant
mechanism in this process and the inadequate understanding of complicated brine-oil-rock interactions, only a few models have been suggested to estimate relative permeability
associated with LSWF for either carbonate or sandstone rocks. Existing models simulate
the impact of LSWF based on geochemical interactions; however, the fluid-fluid
interaction has been overlooked. Some models depend on the cation-exchange capacity
of clay which is not adequate for clay-free rock. In contrast, others are based on weighting
factors such as the divalent ions desorption, which is case dependent.
This study presents a novel semi-empirical model of LSWF relative permeability, after
high salinity water flooding, based on incremental oil recovery measured during low
salinity injection. Therefore, it can be applied to all rock types, fluid systems, and
wettability conditions regardless of the active mechanism. The relative permeability at
the high salinity water flooding, krHS and incremental oil recovery during low salinity
injection were inputs to the model for predicting the low salinity kr curve, krLS and,
consequently, this model can be used to assess the performance of LSWF. Well-known
mechanisms in literature on the incremental oil recovery during LSWF are reviewed
including micro-dispersion. In this work, correlation between the incremental oil recovery
and the amount of micro-dispersion has been employed for sensitivity analysis, and
evaluation of the new model's response among various levels of incremental oil recovery.
This new model has been validated utilising 12 coreflood datasets obtained from core
flooding experiments under both unsteady-state and steady-state flooding conditions or
protocols. A new steady-state experiment has been performed in this study to produce the
first reliable relative permeability data that is needed for validation. This dataset, along
with the unsteady-state dataset obtained under tertiary and secondary mode by other
researchers in our group at Heriot-Watt University, has been used to validate the new
model and to quantify the effect of LSWF injection on the relative permeability. Five
experiments have already been published in literature by other researchers from our
group, while the other four experiments have not yet been published. Additional two more
experimental data from other group researchers available in the literature were deployed
for further verification. Due to its mechanism independence, the new model suggested in this thesis can be applied for efficient performance screening of all LSWF injection
scenarios, which is invaluable for the oil and gas industry’s decision-making process.
The results confirm the difference in relative permeability curves between high-salinity and low-salinity injections caused a decrease in water relative permeability and
an increase in the oil relative permeability. They also prove that low-salinity brine can
shift the rock wettability from oil-wet or mixed-wet towards a more water-wet condition.
The obtained relative permeability curves extend across a substantial saturation range,
making this valuable information necessary for numerical simulations. To the best of our
knowledge, the data from the steady-state experiment is a first in assessing the impact of
low-salinity waterflooding at a steady-state condition using a reservoir live crude oil and
long reservoir core sample at reservoir condition. The results of this study are of utmost
importance for the oil and gas industry
Management attention in performance measurement and management
Get PDFPerformance measurement and management (PMM) refers to performance measurement
systems and performance management practices. Management attention (MA) is a limited
cognitive resource that fuels managers’ minds. It can also be understood as the cognitive
process that chooses what information is passed on to higher-level processes such as
judgment and learning. This research postulates the thesis that certain characteristics of
PMM attract greater MA than others. Our knowledge about this phenomenon is still
embryonic. Therefore, this thesis aims to explain how PMM affects MA.
This thesis explores six micro-level case studies about the impact of PMM concepts and
characteristics on management attention. Control theory, levers of control (LoC), effort
theory, and dual process theory jointly informed the conceptual structure for data
collection. Evidence suggests that PMM concepts and characteristics affect management
attention through MA characteristics of five novel MA concepts: Ideological compass,
social intelligence, reflexivity, routinised behaviours, and engagement. This thesis
develops 86 theoretical propositions that explain the significant impact of PMM
characteristics on MA characteristics which further affects the cognitive judgment
mechanism that governs managers’ attentional allocation policy (i.e., intuitive analytical
judgment). Findings contribute to control theory and LoC in particular
Extension of the Advanced REACH Tool (ART) to include welding fume exposure
Get PDFIntroduction: Welding is basic process commonly carried out in the workplace. Robot
or automated welding are typically used in welding processes where the weld required
is repetitive and quality and speed are crucial. Not every welding operation is suitable
for automated welding. If the project is limited to a single non-repetitive process,
manual welding may be more suitable. The welding process is applied in various
production fields and the demand for welders worldwide is increasing. Welders are
exposed to health hazard from inhalation of metal fumes produced as a by-product of
the process. The concentrations of welding fumes inhaled by workers can be measured,
but it would be advantageous if there were also predictive exposure models to estimate
exposure. However, presently, there are few reliable estimation models for welding
fume exposure.
Objectives: To develop estimation model for welding fume exposure.
Methods: This study consisted of five main stages. The first stage comprised a
literature review, including an evaluation of relevant generic exposure models,
particularly the Advanced REACH Tool (ART), principles of exposure modelling, and
various research studies related to welding fumes. The second stage describes an
investigation to measure welding fume exposure at a production site. The third stage
comprised welding fume exposure model development by adapting the ART model (to
be the weldART model), including the identification of key modifying factors (MF)
and a suitable computational form to undertake the model calculations. The fourth stage
was modelling calibration, which used data obtained from the sampling in stage 2. The
last stage was model verification, which applied welding fume measurement data from
reports and published papers to test the reliability and uncertainty of the weldART
model.
Results: The model was developed within a well-mixed mass-balance computational
framework. An important MF to be used in model development was fume formation
rate (FFR), i.e., the mass emission rate of total metal fume from the welding process.
The identified variables that affect fume formation rate were type of welding process,
electrical current and input power, shielding gas, and welding consumables. In addition,
the model also incorporates other important factors, such as convective dissipation of
the welding fume away from the welding area and the welder’s interaction with the
fume plume. The review indicated that welding process types with the highest to lowest
welding fume particulate emission rates were flux-cored arc welding (FCAW), shielded
metal arc welding (SMAW) and gas tungsten arc welding (GTAW). In order to develop
effective and probabilistic weldART model, variables, namely welder's head (WH) and
localized control (LC) were also taken into consideration. A deterministic four-compartment mass-balance mathematical model, the weldART model, was developed.
In the measurement study two types of sample were collected: a Swinnex sampler to
collect fume for gravimetric analysis and a MicroPEM direct-reading aerosol monitor.
The comparison of fume concentrations between these two samplers showed that the
MicroPEM monitors significantly underestimated exposure concentrations and had low
correlation with the corresponding data from the Swinnex samplers. It was concluded
that it was possible that particles were lost in the sampling tube of the MicroPEM due
to the electrostatic deposition before the entering the aerosol sensor, and these data were
only used to indicate the duration of welding activity. Meanwhile, estimation of the
calibrated four-compartment mass-balance weldART model gave a strong correlation
with the welding fume exposure measurements made during this research. To
accommodate the uncertainties involved in verifying the model using published
exposure data, the weldART was extended to incorporate a probabilistic aspect. This
may be due to a positive systematic bias across the whole applicability domain, which
becomes dominant at low measured values.
Conclusions: The weldART model can produce reliable and accurate estimates of
welding fume exposure. Especially, if factors related to distance of welder’s head and
localized control were taken into account, along with the presence of additional
workplace exposure sources. The weldART could offer an alternative approach to
evaluate fume concentration for occupational hygienists. At present the model is
available as standalone R-code that is freely available, but it lacks a suitable user-friendly user interface. The weldART is calibrated and has had a limited verification
exercise completed, but further development and evaluation is necessary
Unlocking the inner cell : linking cell biochemistry to the physiology and ecology of coccolithophores
Get PDFCoccolithophores — marine calcifying unicellular algae — make a key contribution to
phytoplankton community diversity and productivity and have important roles in
regulating ocean biogeochemistry. Despite their ecological success, the current
understanding of the clade relies on the knowledge of the model species, Emiliana
huxleyi, whereas very little is known of their diverse physiological ecology. This thesis
presents a detailed analysis of the physiology of a diverse range of coccolithophores,
including a meta-analysis of their cell size as well as biochemical data of cellular
elemental (i.e., carbon, C; nitrogen, N; phosphorus, P) and macromolecular (i.e., protein,
lipid, and carbohydrate) content in nutrient-replete cultures.
Coccolithophore differ from other key phytoplankton in that their cell size spectrum is
restricted with most extant species smaller than 10 μm in diameter, likely giving them
advantages in low nutrient and light environments when competing with other
phytoplankton. In addition, coccolithophores are less C-rich than other phytoplankton,
providing a coccolithophore-specific relationship between cell organic C content and
biovolume.
The examination of coccolithophore elemental composition shows that organic C to N
ratios are similar to other phytoplankton, implying little additional N cost for calcification
and efficient retention and recycling of cell N. On the other hand, C to P ratios imply a
greater P demand in coccolithophores, which hints at efficient metabolic strategies for the
use of this nutrient by the cells. The macromolecular composition of coccolithophores of
this study shows higher lipid and lower protein content than reported previously for
haptophytes. Coccolithophore C to N ratios and high lipid relative to proteins have
implications for N cycling, as well as C fixation, and export relative to blooms of non-biomineralized phytoplankton.
Finally, outputs of a distinct DNA-barcoding field-study of small eukaryote plankton
communities (< 200 !m) revealed differences in the species composition between the
contrasting depth layers of the water column in the sub-tropical oligotrophic gyre.
Nutrient enrichment studies demonstrated the role of P, largely understudied in
comparison with N, in constraining eukaryotic marine biodiversity, which has
implications for ocean productivity
From connected pathway flow to ganglion dynamics : understanding the effect of pore-scale properties on dynamic fluid connectivity and average flow functions
Get PDFSince the turn of the industrial revolution in the early 1900s, the global economy has relied on fossil
fuels for energy, transport, and other day to day industrial, commercial, and domestic activities.
The combustion of fossil fuels (coal, petroleum (oil) and natural gas) is the primary cause of
atmospheric carbon dioxide (CO2) emissions which result in climate change and global warming.
Until we fully transition to cleaner alternative energy sources, the global economy will continue to
rely on fossil fuels. The injection and storage of CO2 in subsurface geological formations such as
saline aquifers and depleted oil and gas reservoirs, has been identified as a promising solution for
mitigating climate change and global warming.
Changes in reservoir rock and/or fluid properties at the pore-scale (scale of several microns) have
been known to have an impact on flow and transport properties at the Darcy-scale (scale of several
centimetres to metres). As such, successful implementation of CO2 storage technology at the large
scale, relies heavily on our ability to understand and predict changes that occur in the subsurface
at the pore scale and their subsequent effect on average flow functions. One of the major,
unresolved challenges in upscaling multiphase flow from the pore scale to the Darcy scale lies in
addressing the effects of connected and disconnected fluid fractions.
Direct numerical simulations (DNS) were coupled with flow through experiments in miniature
replicas of porous rocks fabricated on glass substrates (micromodels) to investigate the effects of
pore-scale flow and transport properties on dynamic fluid connectivity and average flow functions
such as displacement efficiency and the saturation function. Flow and transport properties
investigated include surface roughness, wettability, as well as fluid velocity.
Three pore-scale flow regimes were identified from the investigations conducted: two disconnected
pore scale flow regimes namely, the ganglion dynamics (GD) regime and the droplet traffic flow
(DTF) regime and a regime in which fluid displacement occurred by connected flow paths (the
connected pathway flow (CPF) regime). It was established that there is a relationship between the
dominant pore-scale mechanism and the kinetics of fluid displacement processes. Disconnected
flow regimes were found to accelerate the fluid displacement process. The impact of disconnected
and connected flow regimes was studied and it was determined that the GD regime can have a
negative impact on the efficiency of subsurface fluid displacement processes and would adversely
impact CO2 storage operations. In contrast, the DTF regime was found to enhance fluid
displacement efficiency. Transitions between connected and disconnected flow regimes were also
investigated and it was found that the shape of the saturation function is strongly influenced by
transitions between pore-scale flow regimes. This work shows that the impact of pore-scale
dynamic fluid connectivity on flow transport kinetics and the saturation function is highly significant
and should not be ignored. Pore-scale property induced changes in the rate of change of saturation
and the shape of the saturation function and could potentially have a knock-on effect on saturation dependent Darcy-scale functions such as relative permeability-saturation curves. Further work
should be done to ascertain the relationship between dynamic fluid connectivity and relative
permeability-saturation curves
Activating the role of public participation as a new vision towards urban planning system reform : what can Syria learn from the British experience?
Get PDFAs a cross-national comparative study, this research examines the urban development
decision-making process as a form of urban governance, emphasising the progress
achieved in public participation within the British and Syrian urban contexts. According
to the United Nations Development Programme (UNDP), public participation is one of
the key attributes of good governance. Therefore this study addresses public participation
as an indicator of good governance; a means to ensure better development, and an end to
enhancing the capacity building of the society.
There is an abundance of theoretical and practical research addressing the topic of public
participation in the urban development decision-making process in the UK, which might
provide valuable references and lessons for developing countries to benefit from. Since
2011, Syria has been in turmoil and instability due to the ongoing war in the country,
resulting in drastic social, economic, and political changes. Before the war and during the
first decade of the 21st century, Syria sought to make some social and economic changes
under the influence and help of the UNDP. Those change attempts were noted within the
10th Five Year Plan (FYP), where the concepts of ‘civil society’, ‘participation’, and
‘governance’ were introduced. Those changes have affected the urban planning context
within the country, where a new approach to decision-making within the land-use
planning system was introduced. However, the efficiency of the new approach to
achieving better outcomes for development plans was still questionable.
This research aims to critically review, evaluate and compare the progress achieved in the
field of public participation in the urban development decision-making process
(evolution, achievements, and problems) in the British and Syrian contexts by following
a cross-national approach. It reviews the evolution of urban planning theories and public
participation approaches and their practices. Based on the findings, an analytical
framework is adopted to examine and evaluate the level of public participation within the
decision-making process, both theoretically and in practice. The research is based on a
case study approach. A mixed-method of data collection and analysis is applied in both
countries through literature, policy and regulations reviews, and fieldwork in the selected
study cases: Edinburgh, Scotland, UK, and Latakia, Syria. By studying and analysing the
possibilities for broader public participation and more effective engagement of members
of civil society in the urban development decision-making process, this research attempts to promote potential sustainable outcomes of public participation within their related
political, economic, and social contexts.
This research found some theoretical similarities between the UK-Scotland and Syria
when addressing classic democracy (structure of the state, administrative and
geographical division, the structure of state institutions, and the laws and regulations
governing). However, the empirical research found that the fundamental differences lie
in the practical implementation of the concept of democracy on the ground. Empirical
research shows that public participation in the Syrian urban development decision making process is primitive and limited to informing only. Even the methods used to
inform the public are ineffective enough and do not achieve the required propagation.
Whereas in the case of UK-Scotland, public participation is more developed, and the
public is engaged and consulted during the formulation of the decisions.
Despite the difference in the level of democracy, the research indicates that Syria could
benefit from the British experience. However, achieving this is a political matter that
needs a political and societal will that involves restructuring the main forces of society
(the state, the market, and the society). Based on the research findings, a series of
recommendations have been developed to improve the practice of public participation in
the urban development decision-making process and achieve reformatory changes to
urban governance in Syria
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