Master of Science

thesisThe moisture content in civil engineering materials determines many of the structural properties of the material such as strength and durability. In geotechnical engineering, the moisture content of soil deposits determines their susceptibility to landslides and settling. In structural engineering, the moisture content in concrete, typically measured in terms of the water-to-cement (w/cm) weight ratio, determines its compressive strength as well as other hardened properties such as permeability and shrinkage. The moisture contents of sand and concrete composites were measured using a handheld microwave moisture meter developed for the purpose of moisture measurements in concrete. The results in concrete obtained from the meter were compared to the results obtained from the standard method of determining moisture content in concrete. In sand, the meter was able to detect the change in moisture content with a linear fit R 2 of 0.962 and 0.945 for the twotypes of sands tested. As for concrete, the linear fit R 2 was as low as 0.0034.The p-values obtained on concrete testing were less than the specified confidence level of 0.05, rejecting the hypothesis that the meter's average output is equal to the average actual w/cm tested. The output w/cm obtained from the meter was compared to moisture content and calculated w/cm from the AASHTO standard method. The linear fit through the data obtained from the test had an R 2 value of 0.62 or higher and a p-value of 0.91, making this methodthe preferred option when wanting accurate in-situ measurements

Impact of Capital Structure on Bank Financial Performance of Al Ahli Bank in Saudi Arabia

This paper seeks to examine the relationship between capital structure and bank financial performance This research had verified the existence of several negative relationships between capital structure (accumulated capital and annual investments) and strategic financial performance, while finding mixed results for the relationship between capital structure (accumulated capital and annual investments) and profitability

Enhanced Microgrid Control through Genetic Predictive Control: Integrating Genetic Algorithms with Model Predictive Control for Improved Non-Linearity and Non-Convexity Handling

\ua9 2024 by the authors.Microgrid (MG) control is crucial for efficient, reliable, and sustainable energy management in distributed energy systems. Genetic Algorithm-based energy management systems (GA-EMS) can optimally control MGs by solving complex, non-linear, and non-convex problems but may struggle with real-time application due to their computational demands. Model Predictive Control (MPC)-based EMS, which predicts future behaviour to ensure optimal performance, usually depends on linear models. This paper introduces a novel Genetic Predictive Control (GPC) method that combines a GA and MPC to enhance resource allocation, balance multiple objectives, and adapt dynamically to changing conditions. Integrating GAs with MPC improves the handling of non-linearities and non-convexity, resulting in more accurate and effective control. Comparative analysis reveals that GPC significantly reduces excess power production, improves resource allocation, and balances cost, emissions, and power efficiency. For example, in the Mutation–Random Selection scenario, GPC reduced excess power to 76.0 W compared to 87.0 W with GA; in the Crossover-Elitism scenario, GPC achieved a lower daily cost of USD 113.94 versus the GA’s USD 127.80 and reduced carbon emissions to 52.83 kg CO2e compared to the GA’s 69.71 kg CO2e. While MPC optimises a weighted sum of objectives, setting appropriate weights can be difficult and may lead to non-convex problems. GAs offer multi-objective optimisation, providing Pareto-optimal solutions. GPC maintains optimal performance by forecasting future load demands and adjusting control actions dynamically. Although GPC can sometimes result in higher costs, such as USD 113.94 compared to USD 131.90 in the Crossover–Random Selection scenario, it achieves a better balance among various metrics, proving cost-effective in the long term. By reducing excess power and emissions, GPC promotes economic savings and sustainability. These findings highlight GPC’s potential as a versatile, efficient, and environmentally beneficial tool for power generation systems

Investment decisions in a liberalised energy market with generation and hydrogen-based vector coupling storage in Integrated Energy System:A game-theoretic model-based approach

Meeting carbon reduction targets and enhancing energy supply flexibility necessitate the integration of natural gas and electricity networks, coupled with increased adoption of renewable energy. Bidirectional hydrogen-based Vector-Coupling Storage (VCS) offers a promising avenue for efficiently utilising surplus power from renewables, linking hydrogen as an energy carrier and storage with the Integrated Energy System (IES). This paper introduces a game-theoretic planning model for IES, encompassing natural gas, electricity, and independent VCS participants in a liberalised market. A game-theoretic model for capacity investment under an oligopolistic market structure in the liberalised energy market context is developed to capture the strategic behaviour of market participants. An annual investment model and an hourly operation simulation model are used to evaluate the value of hydrogen production, coupling components, and vector coupling storage in long-term investment decisions. The model, applied to the North of Tyne region in the UK, employs a scaled-down Future Energy Scenario dataset, reflecting a regional trajectory towards a net-zero emission target by 2050. Simulation results highlight market liberalisation's crucial role in attracting investments in renewable energy and hydrogen systems. Conversion efficiencies of electrolysers and fuel cells emerge as key profitability determinants, emphasising the significance of achieving at least 50% round trip efficiency for profitable vector coupling storage. The findings quantify the advantages of large-scale VCS investments over Li-ion battery storage.</p

Investment decisions in a liberalised energy market with generation and hydrogen-based vector coupling storage in Integrated Energy System: A game-theoretic model-based approach

\ua9 2025 The Author(s). Meeting carbon reduction targets and enhancing energy supply flexibility necessitate the integration of natural gas and electricity networks, coupled with increased adoption of renewable energy. Bidirectional hydrogen-based Vector-Coupling Storage (VCS) offers a promising avenue for efficiently utilising surplus power from renewables, linking hydrogen as an energy carrier and storage with the Integrated Energy System (IES). This paper introduces a game-theoretic planning model for IES, encompassing natural gas, electricity, and independent VCS participants in a liberalised market. A game-theoretic model for capacity investment under an oligopolistic market structure in the liberalised energy market context is developed to capture the strategic behaviour of market participants. An annual investment model and an hourly operation simulation model are used to evaluate the value of hydrogen production, coupling components, and vector coupling storage in long-term investment decisions. The model, applied to the North of Tyne region in the UK, employs a scaled-down Future Energy Scenario dataset, reflecting a regional trajectory towards a net-zero emission target by 2050. Simulation results highlight market liberalisation\u27s crucial role in attracting investments in renewable energy and hydrogen systems. Conversion efficiencies of electrolysers and fuel cells emerge as key profitability determinants, emphasising the significance of achieving at least 50% round trip efficiency for profitable vector coupling storage. The findings quantify the advantages of large-scale VCS investments over Li-ion battery storage

A hybrid method based on logic predictive controller for flexible hybrid microgrid with plug-and-play capabilities

\ua9 2024 The Author(s). Controlling flexible hybrid microgrids (MGs) is difficult due to the system\u27s complexity, which includes multiple energy sources, storage devices, and loads. Although adding new components to the MG system through the plug-and-play (PnP) feature enables operating of the system in different modes, it adds to the system\u27s complexity, hence necessitates careful control system design. The most challenging aspect of designing the control system is ensuring that it can control the MG optimally in its various modes of operation. Previous methods based on logical control allow for synthesizing a controller capable of controlling the MG in its various operational modes. However, the resultant controller does not optimally operate the MG. Classical model predictive control allows optimal control of the MG only in specific operating modes. On the other hand, switched model predictive control (S-MPC) can optimally control the MG in its various modes. However, the design of S-MPC is complex, particularly for MGs with many operating modes or complex switching logic. Multiple factors contribute to the complexity, including model development, mode detection, and switching logic. This paper presents a hybrid method based on ɛ-variables and classical MPC for constructing the S-MPC for flexible hybrid MG with PnP capabilities. Our results show that the proposed controller synthesis approach provides an effective solution for optimally controlling flexible hybrid MGs with PnP capabilities as the proposed method enables: (i) an increase in the amount of energy export to the utility grid by 50.77% and (ii) a significant decrease in the amount of energy import from the grid by 46.7%

Bestimmung des Rotationszentrums des distrahierten Komplexes bei verschiedenen LeFort-Osteotomien Eine Finite-Elemente-Studie

Die Verwendung der Knochenverlängerung bei der Behandlung zahlreicher Gesichtsfehlbildungen in der Mund-, Kiefer- und Kraniogesichtschirurgie gilt mittlerweile als unverzichtbare therapeutische Methode. Die computergestützten Simulationen führen zu einem besseren Verständnis der physikalischen Eigenschaften des Behandlungsprozesses, welches am lebenden Patienten direkt nicht zu erreichen ist. Das Ziel der vorliegenden Arbeit war die Bestimmung des Rotationszentrums im Rahmen der Knochenverlängerung bei drei verschiedenen simulierten Knochensegmenten (LeFort-I, II und III). Ein Master-Modell (849921 Elemente, 221064 Knoten) wurde durch 3D-Modell-entwicklung eines menschlichen Gesichtsschädels hergestellt, indem Primärdaten von einer Computertomographie des Kopfes einer anonymisierten jungen Patientin, übertragen wurden. In dem Modell wurden vier Masken identifiziert: kortikaler Knochen, spongiöser Knochen, Zähne und Weichgewebe. Von dem Master-Modell wurden drei Kopien angefertigt, an denen jeweils eine Osteotomie (LeFort-I, II und III) simuliert wurde. Um den Einfluss des Weichgewebes und der Kallus-Elastizität auf die Lageänderung des Rotationszentrums besser darzustellen, wurden verschiedene Elastizitäts- und Kontaktparameter vom Kallus und Weichgeweben verwendet, damit entstanden 18 Simulationmodelle. Die maxilläre Komponente wurde in jedem Fall in der sagittalen Ebene um 0,5 mm durch Zugkräfte verlagert. Die verlagerte maxilläre Komponente zeigte komplexe dreidimensionale Bewegungen. Das Rotationszentrums der maxillären Komponente wurde nur in der sagittalen Ebene analysiert. Die Lageänderung des Rotationszentrums wurde in allen Simulationen anhand von drei Werten, zwei Winkeln und einem Verhältnis, bestimmt. Im Rahmen dieser Studie konnte der Einfluss der verschiedenen Faktoren (Weichgewebe, Kallus E-Modul und Osteotomielinie) auf die Lage des Rotationszentrums gezeigt werden

Analysis of the Impact of Fintech Firms’ Lending on the Expansion of Service Base Companies in Jordan

The purpose of this research was to analyze the impact of lending by fintech firms on the expansion of service- based companies in Jordan. The studys population included 210 service-based enterprises located in Jordan. The research used a sample size of 136 respondents from registered service-based enterprises in Jordan. The researchers used a structured questionnaire to gather data from the participants. The data acquired in this study were evaluated using a combination of basic percentage calculations and Pearson product moment analysis. The research has reached the conclusion that the lending activities of Fintech firms have a noteworthy impact on the expansion of service-based companies in Jordan. The study suggests that it would be advantageous for the Fintech service provider to engage in advertising efforts aimed at promoting their services, with the goal of increasing the adoption of their mobile money product among a wider range of business professionals. This would lead to an increased number of entrepreneurs using Fintech as a means to augment the expansion of their businesses. The scope of the research was limited to a small number of service-based organizations. However, it is important to include other service-based companies that were not included in this study. To get a comprehensive understanding, a comparison study should be conducted to explore other characteristics that were not addressed in the current research. The field of financial technology (fintech) has seen significant growth in recent years. This growth can be measured by the degree of utilization observed in various fintech applications and services

Uncertainty Analysis of The Impact of Increasing Levels of Gas and Electricity Network Integration and Storage on Techno-Economic-Environmental Performance

This paper presents an evaluation framework for Techno-Economic-Environmental (TEE) impact ofdifferent networks integration levels and storage devices on performance of Integrated Gas and ElectricityNetworks (IGENs). Probabilistic distributions for modelling sources of uncertainty (loads, RenewableEnergy Sources (RESs), economic and environmental analysis) were sampled through Monte CarloSimulation. The framework performs the TEE operational analysis of IGENs for future possible scenariosfor different technology development status and different levels of load and RESs. Then, it calculates theenergy imported from upstream networks, operational costs, and emissions. In this way, the frameworkprovides a basis for making well-informed and risk-based decisions of design choices for meeting 2050carbon targets in the presence of aforementioned sources of uncertainty. Analysis of the results of applicationof the framework to a real-world case study shows that as the electrical renewable generation grows withrespect to the total demand, the value of integrated operation of the networks also grows as shown by thereduction in the TEE parameters. Given that demand reduction and decarbonisation of electricity and gasnetworks is a priority, the coupled configurations are likely to become more attractive between now and2050, in the presence of the considered sources of uncertainty

Primary frequency response from hydrogen-based bidirectional vector coupling storage:modelling and demonstration using power-hardware-in-the-loop simulation

To meet reduction targets for carbon emissions and improve the flexibility and security of the energy supply, future energy networks will require enhanced energy vector coupling in addition to the generation of energy from renewable sources. Increased renewable generation penetration significantly affects the electrical grid’s inertia and consequently the severity and regularity of frequency deviations from nominal values. Bidirectional Hydrogen-based Vector Coupling Storage (VCS) has been explored as a means to provide primary frequency response (PFR) services to the electrical network. This paper demonstrates the use of Power Hardware-In-the-Loop (PHIL) simulation and Digital Twin (DT) technique for such an application. This new suggested structure of VCS is composed of grid-scale electrolysers, fuel cells, and hydrogen storage. Existing works focus on unidirectional VCS, and also use simplifications or neglect the impacts of power converters on the performance of the VCS. In addition, these works do not have any control over the hydrogen storage, therefore there is no guarantee that there will be enough energy available in the storage to meet the PFR service responsibilities. This paper presents the dynamic models of electrolysis, fuel cell stacks, and hydrogen storage as a DT. The key parameters affecting the behaviours of these main components are considered. The power converters’ accurate impact on the VCS’s performance is considered through PHIL simulations. The level of stored hydrogen is also considered in the VCS controller. The DT representing the VCS is integrated with the PHIL setup representing the deployment environment. The impact of VCS is then analysed as it propagates to the deployment environment. Results of the considered case studies demonstrate that the size of the VCS plays a significant role in bringing the frequency to the statutory allowed range. In addition, more VCS capacity was installed, the nadir frequency improved. Furthermore, the VCS is fast enough to offer PFR. The response times of the VCS were 2.857 s (during under-frequency periods), corresponding to the operation of the fuel cells, and 2.252 s during over-frequency periods, corresponding to electrolyser operation.</p