AUS Repository

Recent Submissions

  • Item
    Assessing Key CE Strategies to Advance UAE Construction Circular Economy Practices
    (2025-05) Wasef, Mark Moheb; El-Sayegh, Sameh; Yehia, Sherif
    Concrete being the most utilized material in the world will face many issues in the future and overcoming them will need the implementation of circular economy strategies. Though research interest in creating Circular Economy (CE) strategies for concrete is growing quickly, much of it has concentrated on technical and environmental problems at the material and product scale. However, there has not been clear strategies identified and their method of implementation in various stages of a construction project. Furthermore, there has not been holistic approaches on how CE will contribute towards achieving the Sustainable Development Goals (SDGs). The main objective of this study is to identify and rate the relative importance of CE strategies, contributing towards achieving CE in the UAE construction sector. This could be achieved by identifying and assessing the CE strategies that shape how these CE strategies can be achieved and integrating them into construction practices. After an extensive literature review, 17 CE strategies were identified that can be utilized by construction leaders to adopt CE in construction projects. Furthermore, a cross-sectional survey was conducted among various local and international construction firms and 60 responses from experienced professionals in the industry were obtained. Relative importance index and principal component factor analysis (PCFA) were adopted to evaluate the obtained data. Key significant CE strategies for construction professionals to propel circular construction were identified such as specification writing for components and materials, designing for multiple-use cycles, and designing for near-zero energy buildings, among others. Three components were extracted from the PCFA which served as guidelines for enhancing the CE strategies of construction professionals, namely, Effective Collaboration and Coordination Techniques, Sustainable Project and Operations Management, and Sustainable Design Practice. In addition, to enhance its practical implications, a competency implementation framework was also developed for construction professionals of developing economies to propel the adoption and evaluation of their competency skills toward circular construction.
  • Item
    Exploring the Transformative Potential of Generative AI in Mechanical Engineering Education
    (2025-04) Alghazo, Mohannad; Ahmed, Vian; Bahroun, Zied
    The advent of Generative Artificial Intelligence (GAI) presents new opportunities and challenges in Mechanical Engineering Education (MEE). However, literature lacks the exploration of GAI’S application in this field. Therefore, this research highlights this gap by evaluating various free versions of GAI tools, including Code Copilot, ChatGPT/ScholarGPT, Gemini, Claude, and ChatPDF, across various aspects of the MEE curriculum. The study classifies and analyzes these tools according to their effectiveness in computational/conceptualization problems, theoretical problem-solving, image analysis & schematics, research, CAD drawing, simulation, and coding. Subsequently, a mixed exploratory research approach was deployed, incorporating qualitative and quantitative methodologies. Variables were identified through a systematic literature review and expert interviews and were then validated through surveys data analysis. Statistical techniques, including Relative Importance Index (RII), Cronbach’s α, Confirmatory Factor Analysis (CFA), and Partial Least Squares Structural Equation modeling (PLS-SEM), were conducted to identify the most significant factors and validate them, as well as to assess the relationships between enablers, challenges, strategies, psychological factors, and faculty and student perceptions of GAI. Findings suggest that Code Copilot is the most effective for computational tasks and coding related applications, while ChatGPT excels in theoretical problems, CAD drawing, and simulation, ChatPDF is particularly valuable for research, whereas Gemini and Claude demonstrate moderate effectiveness across multiple domains. PLS-SEM results confirm that enablers, challenges, and strategies influence faculty and student perceptions of GAI integration. Moreover, survey data underscores a preference for gradual GAI implementation, focusing on design, simulation, coding, and academic writing in prior to full-scale integration. Future research should expand the participant pool to include more ME faculty and students, explore advanced GAI versions, and examine direct integration of GAI tools within engineering software to enhance learning experiences.
  • Item
    Analysis of Fat-track Projects in the Public Sector in the United Arab Emirates
    (2025-04) Alsuwaidi, Mariam; Shamayleh, Abdulrahim
    The United Arab Emirates (UAE) has emerged as a global leader in large-scale public infrastructure projects, driven by an ambitious national development agenda. To meet pressing deadlines and accommodate growing demands, many governmental projects adopt a fast-tracking approach. Although this method shortens delivery timelines, it also brings about significant challenges, including cost overruns, quality risks, coordination difficulties, and heightened safety concerns. This study investigates the practical application of fast-track project management in the UAE public sector using a mixed-methods approach. It incorporates literature review, in-depth regional case studies, a structured survey of UAE-based project managers, and advanced analysis using Bayesian Belief Networks to uncover relationships between key success factors.The results reveal that frequent changes in project requirements, limited adoption of digital tools, and gaps in stakeholder communication are major barriers to success. Technologies like Building Information Modeling (BIM), Artificial Intelligence (AI), Machine Learing (ML), and Internet of Things (IoT) remain underutilized despite their potential to improve project performance. Recommendations include developing structured fast-track frameworks, promoting technology integration, enhancing contingency planning, and utilizing post-project evaluations. The findings offer practical guidance for improving fast-track execution and provide a foundation for future research into sustainable and technology-driven project delivery.
  • Item
    Queuing-Based Optimization of EV Charging Stations: A Case Study of Manama City, Bahrain
    (2025-04) Albinali, Hamad A.Rahman; Hariga, Moncer; As’ad, Rami
    The transition to electric mobility necessitates proper strategic planning of charging infrastructure to ensure efficiency, accessibility, and user satisfaction. Today, Electric vehicle (EV) charging stations (CSs) must be strategically located to maximize user satisfaction, enhance accessibility, and balance costs for both charging station owners (CSOs) and electric vehicle users (EVUs). However, most existing mathematical models overlook real-world service constraints, often assuming unlimited waiting capacity at CSs. Another often-overlooked aspect in planning EV charging infrastructure is the blocking cost incurred when EVUs arrive at a station that has neither available charging slots nor waiting space. This situation can lead to inefficient and suboptimal infrastructure planning decisions. Additionally, research on the Charging Station Location Problem (CSLP) remains limited in the Middle East, where countries such as the Kingdom of Bahrain (KoB) face significant barriers to EV adoption, such as inadequate charging infrastructure, range anxiety, and policy uncertainty. To address these gaps, this study develops an optimization model for CS deployment considering CSOs and EVUs costs while explicitly accounting for a queuing behavior having a finite queue length. The problem is formulated as a highly complex Mixed-Integer Nonlinear Programming (MINLP) model. To effectively solve this problem, we propose an iterative solution procedure that initially optimizes CSs without considering queuing aspects, including only CSO related and access costs in the objective function. The resulting relaxed problem is formulated as a Mixed Integer Linear Programming (MILP) model and solved through CPLEX optimizer. Subsequently, the results of this MILP model are iteratively refined to incorporate queuing effects, and the process is terminated once no further cost improvements are attained. A case study of Manama City, the capital of the KoB, was conducted to test the model’s ability in identifying the optimal locations for establishing CSs. The results offer practical insights for policy makers and industry stakeholders to develop sustainable and effective EV charging networks in the KoB.
  • Item
    Cost Effective Transition Toward Electric Bus Fleets in Urban Transport
    (2025-04) Mohamed, Mohamed Ali Hassan; Ben-Daya, Mohamed; As'ad, Rami
    The transition to electric bus (EB) fleets signifies a critical shift in urban transportation, curbing the pressing environmental issues caused by traditional diesel buses. To ensure a successful transition, transit authorities must overcome challenges such as limited EB driving range, the need for charging infrastructure, and the resulting strain on the electrical grid—while also capturing opportunities including bus fare increases, government subsidies, and environmental and social benefits. This research develops a multi-period mixed-integer linear programming model, which optimizes long-term EB transition through the integration of key inherent transition planning elements: (1) Financial planning, addressing internal, environmental and social costs along with revenue generation and budget limitation; (2) Technical and infrastructure requirements, covering EB and charging infrastructure selection and placement; (3) Existing bus network operations, analysing route and fleet characteristics; (4) multiple stakeholder perspectives, from government subsidy provision to electric utility grid capacity alignment; and (5) Modelling elements, considering time-dependent factors, fleet age, and a flexible optimization model. This comprehensive approach addresses a notable gap in existing literature. The model's effectiveness is validated using simulated and practical data drawn from Dubai's Roads & Transport Authority, with scenario testing to assess robustness and adaptability. Major findings highlight the importance of long-term transition planning, revealing that: (1) dwell time significantly affects total cost and full electrification feasibility; (2 profit maximization—via fare adjustments, subsidies, and environmental/social benefits—emerges as a primary objective; (3) a pure EB purchasing policy accelerates full fleet electrification by a decade, with minimal financial impact; and (4) enforced electrification targets carry significant financial implications and directly shape the transition plan. The developed model provides transit authorities with a valuable tool to evaluate trade-offs, optimize fleet and infrastructure investments, assess policy levers, and develop realistic electrification targets. Future work may explore interplay of bus requirements, dwell time, and route frequency, enhance data accuracy, and analyse electrification rate trade-offs.

Communities in AUS Repository

Select a community to browse its collections.

Now showing 1 - 5 of 9