Browsing by Author "Bandara, T"

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    Cloud movement analysis using Lucas Kanade method
    (Institute of Electrical and Electronics Engineers, Inc., 2021-09) Weligamage, SU; Ravindu, HM; Bandara, T; Ranathunga, L; Abeykoon, AMHS; Velmanickam, L
    Weather forecasting is an important task as it helps people to manage their work.Cloud movement is a major factor for the variation of the weather. Along with the other factors, cloud movement scan beused to predict the weather changes. This paper propose a method to analyze the cloud movements and calculate the motion vectors using Lucas Kanade method. Cloud velocity vector scan beused with cloud types, wind and thermal data to predict the cloud patterns which helps to forecast weather changes. Proposed method has implemented on a software plat form and experiments has been carried out to validate the system.
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    Heat transfer enhancement in microchannels with liquid - liquid slug flow using al2o3 nanoparticles
    (IEEE, 2022-07) Siriwardana, G; Bandara, T; Ranasinghe, C; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
    Non–mixing two-phase flows in microchannels have become a popular technique for cooling applications due to their thermal performance and flow generation simplicity. Slugflow is one of the regimes in two-phase flow that has higher rates of heat and mass transfer in microchannels compared to other types because of the internal fluid recirculation within the slugs. The addition of nanoparticles to one of the phases in slug-flow could further increase the heat transfer rates. Therefore, in this research, nanofluid-based liquid-liquid slug-flow was studied. Studies were carried out numerically using ANSYS Fluent®. A series of studies were carried out to investigate the effect of nanoparticles on heat transfer. Aluminium oxide (Al 2 O 3 ) was selected as nanoparticles due to its physical and chemical stability along with its high thermal conductivity. Numerical results were validated with the experimental data available in the literature. Interface capturing of two-phase flow was done using VOF (Volume-of-Fluid) and Eulerian–Eulerian mixture models. The results showed a significant heat transfer enhancement when using nanoparticles in either phase. Two-phase slug-flow itself has shown up to four-times the increase in heat transfer in terms of Nusselt Number in the literature. This could be increased by more than eightfold by incorporating nanoparticles into the secondary phase.
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    A programming framework for robot swarms
    (IEEE, 2020-07) Dassanayaka, M; Bandara, T; Adikari, N; Nawinne, I; Ragel, R; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RP
    Swarm robotics is a well-evolved research area over the past couple of decades. In this paper, we introduce a framework for programming swarm robots in a novel approach based on behaviour categorization, pheromone communication, and state representation. The framework is packaged with a set of well defined and tested behaviours that are structured based on the level of interactions between robots. These behaviours can be combined and integrated into the user code when implementing new behaviours. Robots function in a user-defined state and perform actions attributed to that state. We have used a behaviourbased bottom-up design approach for designing these behaviours which eventually alleviate the debugging and implementation process. The efficacy of our work is validated using results obtained from a custom-built simulation platform. These results include tests involving an random movement behaviour, an object finding behaviour, and implementation of an aggregation behaviour.
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    A systematic literature review on applications of bioinspired mxenes structures
    (Department of Chemical and Process Engineering, University of Moratuwa, 2024-06-27) Fernando, T; Bandara, T; Subasinghe, T
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    User Profiling Based Proactive Interaction Manager for Adaptive Human-robot Interaction
    (IEEE, 2023-12-09) Rajendran, H; Ravindu, HM; Bandara, T; Jayasekara, AGBP; Chandima, DP; Abeysooriya, R; Adikariwattage, V; Hemachandra, K
    Proactive interaction is a highly researched topic in the robotics arena. By using its proactive ability, a robot can decide intelligently in specific situations, taking particular attributes into account, to offer a certain service to the user. We propose a proactive interaction manager to suggest suitable reading suggestions to the user. User profiling is used as a tool to identify the nature and preferences of each user. A user’s profile is based on multiple attributes that determine whether a user chooses a particular genre for reading. This is developed as a strategy to identify the preferences of users. Since the user’s preferences may change over time, an algorithm to adaptively provide reading suggestions to the user considering their changes in preferences is also proposed. We conducted two experiments to evaluate the performance of the proposed proactive interaction manager. The results of the experiments show that the proposed approach is satisfactory for a domestic service robot based application.