SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted Sustainability in Mega-Infrastructure Projects: Pathways to Achieving Net Zero Emissions in London.(Saudi Digital Library, 2025) Alharbi, Fahad Saleh; Albarazi, RanaSustainability has become a critical priority in mega-infrastructure projects as the United Kingdom aims to achieve net-zero carbon emissions by 2050. This research investigates the role of engineering management practices in enhancing sustainability and supporting net-zero emission objectives within UK mega-infrastructure projects. A quantitative research approach was adopted based on positivist philosophy, using structured survey questionnaires distributed to infrastructure professionals. A total of 42 responses were collected, with 20 valid responses used for statistical analysis. The findings indicate that engineering management practices such as energy efficiency measures, lifecycle assessment, stakeholder engagement, and collaboration with environmental agencies contribute positively to sustainability outcomes. However, advanced technical solutions such as carbon capture, renewable energy integration, and low-carbon materials are not yet widely implemented. The study also identifies key implementation barriers, including regulatory coordination challenges, resource allocation conflicts, stakeholder management issues, and technical limitations. This research contributes to the existing body of knowledge by providing empirical evidence on the relationship between engineering management practices and sustainability performance in mega-infrastructure projects. An evidence-based framework is proposed to guide practitioners and policymakers in improving sustainability outcomes through early design integration, effective stakeholder coordination, and the use of digital tools. Despite limitations related to sample size and geographic focus, the findings offer valuable insights for future research and practical implementation aimed at achieving net-zero emissions in large-scale infrastructure development.15 0Item Restricted Investigation into the Environmental Improvement of Passive Solar Design for Cooling (Comfort) in Residential Buildings in Saudi Arabia(Saudi Digital Library, 2025-01) Albalawi, Abeer; Grant, JohnThis dissertation investigates the environmental improvement of passive solar design for cooling residential buildings within Saudi Arabia’s unique climatic and cultural context. The research employs a mixed-methods approach, incorporating case studies and surveys, to evaluate the integration of passive solar techniques and renewable energy technologies, such as photovoltaic systems and heat pumps. Key findings reveal that hybrid systems combining passive solar design with photovoltaics can reduce energy consumption by up to 70.7%, while ground-source heat pumps achieve a 34% reduction in CO₂ emissions compared to air-source systems. The study also highlights the feasibility and cultural compatibility of integrating traditional architectural elements, like Mashrabiya, with modern sustainable solutions. These results underscore the potential of passive solar design and hybrid systems to align with Saudi Arabia’s Vision 2030 sustainability goals. However, challenges such as high initial costs, limited public awareness, and expertise gaps necessitate targeted policy interventions, capacity building, and public education initiatives. This research provides valuable insights into sustainable housing practices, offering actionable recommendations for enhancing energy efficiency, reducing carbon emissions, and advancing environmentally responsible construction in extreme climates.33 0Item Restricted Evaluation of Prefabricated Construction Systems and Materials' Thermal Performance with Reference to Housing Construction in Saudi Arabia.(University of Nottingham, 2025) Alkelani, Abdulaziz; Gadi, MohamedIn light of recent revisions to international standards, such as those advocated by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), the prioritisation of improved air circulation to support more energy-efficient ventilation systems has become evident. These systems simultaneously enhance occupant satisfaction and thermal comfort. Within this framework, the current research systematically examines the thermal performance and comfort of prefabricated houses in Saudi Arabia, a subject of increasing importance given the rise in summertime temperatures, consistent with the global increase in temperatures. The investigation distinctly outlines the implications of individual components of prefabricated buildings, particularly building envelope components, on the comprehensive thermal performance in the extreme climate conditions prevalent in Saudi Arabia. It ventures to shape innovative prospects in the Saudi prefabricated construction industry, emphasising the reduction of energy expenses while elevating the quality of the indoor environment through the introduction of high-performance prefabricated building components and systems. In Saudi Arabia, characterised by a harsh and hot climate, the residential sector accounts for nearly 50% of national energy consumption. With energy demand expected to rise further, this research investigates the thermal performance and thermal comfort potential of prefabricated housing as a sustainable alternative. The study prioritises optimising building envelope components, developing high-performance precast systems, and providing design guidelines to reduce energy consumption and enhance indoor thermal comfort. It is evident that the study centred its investigation on natural ventilation from the initial stage. Consequently, it revealed a significant reduction in total discomfort hours across various cities in Saudi Arabia. Optimal performance, characterised by minimal total discomfort hours, was observed in cities characterised by lower humidity levels. This suggests that cities with higher relative humidity, exemplified by Jeddah, exhibit extended discomfort hours and encounter challenges in achieving markedly low discomfort hours compared to drier cities like Riyadh, the capital city of Saudi Arabia. The research employs field observations of existing prefabricated houses in Saudi Arabia and simulation tools to evaluate and optimise thermal performance. Findings reveal substantial reductions in total discomfort hours across various zones, with optimisations achieving up to 32% reductions in specific zones. Key innovations include the use of phase change materials (PCMs) with a melting point of 23°C, improved insulation strategies, and optimised window-to-wall ratios, achieving reductions of up to 48% in cooling loads, 99.95% in heating loads, and 51.6% in annual energy consumption for air conditioning. The study culminates in a tangible design product: a high-performance precast system tailored for extreme climates, offering transformative solutions for sustainable construction practices in Saudi Arabia.64 0Item Restricted RUN-TIME CONFIGURABLE APPROXIMATE MULTIPLIER DESIGN(Saudi Digital Library, 2023-08-14) Haddadi, Ibrahim; Shafik, Rishad; Xia, Fei; Yakovlev, AlexThe complexity of arithmetic continues to be an issue in the design of high-performance and energy-efficient hardware. The problem is further exacerbated in systems powered by variable power levels can limit their computation capabilities. Multipliers constitute a major component of these applications with complex logic design and a large gate count compared to other arithmetic units. As such, there is significant interest in designing new approaches to low-complexity multipliers. Recently, approximate arithmetic, in particular approximate adders and multipliers, have shown notable advantages to benefit from a wide spectrum of naturally imprecise-tolerant applications, such as image processing, pattern recognition, and machine learning (ML). The concept of approximate arithmetic involves replacing system components of normal degrees of complexity with less complex components, which may provide reduced accuracy. Compared to the adder, the multiplier is a crucial component of these applications with complex logic design and a large gate count. This thesis investigates the possibility and profitability to trade accuracy for energy at run-time by using configurable approximate arithmetic hardware. In the first approach, a configurable adaptive approximation method for multiplication is proposed. The extra overheads associated with in the configuration circuits prove to be negligible compared to the multiplier’s costs. Central to the proposed approach is a significance-driven logic compression (SDLC) multiplier architecture that can dynamically adjust the level of approximation depending on the run-time power/accuracy constraints. The architecture can be configured to operate in the exact mode (no approximation) or in progressively higher approximation modes (i.e. 2 to 4-bit SDLC). In the second approach, a novel ML hardware design method centred around multiply–accumulate (MAC) units is presented. Core to the configurable MAC design is a configurable multiplier. In the third approach, a configurable modified activation function is proposed to minimize the prediction error of the configurable MAC design. To evaluate and validate the trade-offs, the three approaches (configurable multiplier, MAC unit and modified activation function) are designed in System-Verilog and synthesized using Synopsys Design Compiler, employing a UMC 90nm digital complementary metal-oxide semiconductor (CMOS) technology as well as on Field Programmable Gate Arrays (FPGAs), and then compared with other available methods. These improvements come at the expense of errors introduced into the circuit and investigated. The efficacy of the first approach (configurable multiplier) technique is evaluated with a real life image processing application, which consists of additions and multiplications using the proposed three multiplier configurations (Exact, 2- and 4-bit SDLC). The analysis considers the Gaussian blur filter since it is widely used in image processing application, typically to reduce image noise and artifacts by acting as a low-pass filter. Additionally, the second and third approaches are evaluated as the key processing blocks in a multi-layer perceptron (MLP) network in order to validate the dynamic tunability between accuracy and power consumption. As case studies, the MLP is trained using well-known machine learning (ML) datasets. The configurable multiplier design (first approach) can be suitably used for energy-efficient multiplier designs, where quality requirements can be relaxed. The second and the third approaches (configurable MAC unit and activation function) can also be used within the power-adaptive neuron modules with a minimal loss in output quality compared to those used in previous studies.41 0