Institutional-Repository, University of Moratuwa
Welcome to the University of Moratuwa Digital Repository, which houses postgraduate theses and dissertations, research articles presented at conferences by faculties and departments, university-published journal articles and research publications authored by academic staff. This online repository stores, preserves and distributes the University's scholarly work. This service allows University members to share their research with a larger audience.
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Recent Submissions
item: Thesis-Full-text
Investigating the effect of under sleeper pads and ballast mats in attenuation of train induced ground vibrations
(2025) Marasinghe, MMGC; Damruwan, HGH; Lewangamage, CS
First and foremost, I extend my heartfelt gratitude to my principal supervisor, Dr. H.G.H. Damruwan, from the Department of Civil Engineering at the University of Moratuwa, for his steadfast guidance, encouragement, and insightful mentorship throughout this research. His expertise, patience, and unwavering support have been pivotal in shaping the direction and quality of this thesis. I also wish to sincerely thank my co-supervisor, Prof. C. S. Lewangamage, for providing valuable guidance on various aspects throughout this study. I am grateful to the technical officer and supporting staff at Structural Dynamics and Health Monitoring Lav for their assistance during the field studies. I also wish to sincerely thank the Progress Review Committee, especially Dr. Lakshitha Fernando, for his critical feedback, thoughtful suggestions, and consistent support, which helped to enhance the depth and clarity of this work. I am also thankful to the academic staff of the Department of Civil Engineering, University of Moratuwa, including Prof. H.R. Pasindu, the MSc Research Coordinator, and especially the academic staff members of the Structural Division, for their continued academic guidance and encouragement throughout the MSc program. To my fellow researchers and colleagues, thank you for your collaboration, encouragement, and knowledge-sharing that enriched this journey and made it a truly collective effort. Finally, I am deeply grateful to my family and friends for their constant motivation, patience, and unwavering belief in me. Their love and emotional strength carried me through every challenge I faced along this path.
item: Thesis-Abstract
Energy efficiency of waste-based masonry materials
(2025) Thoradeniya, BRWMD; Jayasinghe, C; Ariyaratne, KPIE
The construction industry has been recognised as a major contributor to several environmental challenges, mainly due to rapid urbanisation and economic growth that have driven a substantial increase in housing demand. This demand has heavily relied on energy-intensive masonry materials, including cement sand blocks, and fired clay bricks, typically manufactured using depleting natural resources. Consequently, industrial growth often accompanies economic development, resulting in vast quantities of waste, much of which is disposed of in landfills, further exacerbating environmental concerns. In this context, applying circular economy principles to industrial waste by repurposing it into building materials can optimise the use of scarce natural resources and reduce the embodied energy involved in manufacturing processes. To address this, the energy efficiency of two waste-based masonry products, including autoclaved aerated concrete (AAC) blocks and expanded polystyrene (EPS) blocks, in comparison with conventional cement sand blocks, has been evaluated, which are readily available in Sri Lanka. Embodied energy was systematically quantified through a process-based analysis including raw material extraction, transportation, and manufacturing. Operational energy was compared using thermal simulations of a single-storey residential building, utilising empirically measured thermal properties of the materials. Although the waste-based masonry materials exhibited a comparable embodied energy to the conventional reference, the operational energy reductions observed throughout the lifespan of the buildings built using these materials demonstrated clear potential for net savings of energy. Therefore, waste- based masonry units emerged as viable solutions to reduce the total energy consumption in tropical climates and promote circular economic principles.
item: Thesis-Abstract
Advanced finite element formulations for accurate and efficient topology optimization of 2D continuum structures
(2025) Jayaweera, JANN; Herath, HMST
Finite element analysis is crucial for topology optimization. Most implementations use 4-noded membrane elements (Q4) despite low accuracy from membrane locking. This highlights the need for alternatives balancing accuracy and computational cost. This work presents algorithms to implement advanced finite elements into topology optimization. The advanced elements include Pian-Sumihara (PS) and Allman elements, and quadratic membrane element (Q8). Three problem types are addressed: volume-constrained compliance minimization, stress-constrained volume minimization, and stress- and volume-constrained compliance minimization. Performance of different finite elements is analyzed and compared using multiple criteria: accuracy, convergence characteristics, and computational cost. For compliance minimization with uniform regular meshes, PS delivers the most accurate layouts. Its solutions closely resemble Mitchell's truss theory and follow load paths effectively. PS converges to the lowest compliance with smooth black-and-white designs. Q8 matches closely but yields slightly higher objective values. For distorted mesh problems, Q8 shows superior performance. For stress-constrained volume minimization, PS elements achieved optimal results with 0.226 volume fraction compared to Q4's 0.245. Allman and Q8 values are 0.241 and 0.237. Similar behavior occurred for volume- and stress-constrained compliance minimization. PS showed the most optimal design, while Q8 produced similar designs. Allman and Q4 failed to reach optimal designs, showing gray regions. Average computation times relative to Q4 vary: 1.06-1.19× for PS, 1.39-1.74× for Q8, and 1.55-2.54× for Allman. Q4 is fastest but provides lower accuracy. With adequate h-refinement, Q4 can achieve results similar to advanced elements. PS elements are recommended for uniform regular meshes requiring high accuracy. Q8 elements are preferred for distorted mesh problems. Allman elements suit moderate accuracy requirements.
item: Thesis-Abstract
Integrated form-finding and optimization of grid-shell structures using coupled iterative algorithms and specialized graph neural networks
(2025) Abeyrathna, HMAM; Herath, HMST
A primary inefficiency in the design of complex grid-shell structures arises from the separation of form-finding and member sizing into distinct stages. This decoupled approach is problematic because the optimal structural form is directly dependent on the dimensions of its members, making the optimization process computationally demanding. This research addresses these challenges through two primary contributions. First, it introduces an enhanced iterative algorithm that couples form- finding, based on the Potential Energy Method, with member sizing optimization. This methodology is implemented in two novel MATLAB-based software tools, providing a flexible design environment that accommodates arbitrary geometries, materials, and loading conditions, which were validated against established analytical methods. Secondly, to significantly accelerate this workflow, the study explores the application of Graph Neural Networks for near-instantaneous prediction of optimal forms and member properties. A generalized Graph Neural Network model trained on a diverse dataset of mixed topologies struggled with generalization, showing limited accuracy. In contrast, a specialized Graph Neural Network model trained exclusively on dome- type grid-shells demonstrated outstanding predictive accuracy, with coefficient of determination values exceeding 0.99 for both final nodal coordinates and optimal member properties. This specialized model drastically reduces computational time compared to traditional iterative simulations. The findings demonstrate that while the developed software provides a robust tool for detailed analysis, a topology-specific Graph Neural Network approach offers a robust and viable strategy for real-time structural feedback in the conceptual design phase. This work lays the groundwork for integrating physics-informed machine learning into structural engineering to create more efficient and intuitive design tools.
item: Thesis-Abstract
A Machine learning-based design approach for optimising impedance-graded multi-metallic systems subjected to shock wave propagation
(2025) Vandabona, NT; Fernando, PLN
I wish to extend my sincere gratitude to the Faculty of Graduate Studies, University of Moratuwa, for offering the Master of Science (Major Component of Research) programme, which has provided me with the opportunity to pursue this research degree. My sincere thanks go to the Department of Civil Engineering, University of Moratuwa, for providing a stimulating and resourceful environment that greatly facilitated the successful completion of this research. I also wish to express my heartfelt gratitude to Prof. U.P. Nawagamuwa, Head of the Department, and Prof. H.R. Pasindu, Department Research Coordinator, for their guidance and encouragement in achieving this milestone. I am especially indebted to my supervisor, Dr. Lakshitha Fernando, whose expertise, constructive feedback, and patient guidance were invaluable in shaping the direction and quality of this research. I also extend my appreciation to Dr. Damith Mohotti, Dr. Kasun Wijesooriya, and Mr. Pasindu Meddage of the University of New South Wales, Canberra, for their valuable support and insights throughout this research journey. Finally, I am thankful to all who assisted me in various ways during the completion of this project. This thesis stands not only as a reflection of my efforts but also as a testament to the collective support and encouragement I have received.