Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Open Access Aeroacoustic Noise Produced from Novel Wind Turbine Rotor Design for Small-scale Applications in Sri Lanka(SLIIT, 2022-02-11) Perera, M; Bandara, U. HGrowing concerns regarding non-renewable energy sources have driven academic and industrial scholars as well as global superpowers to seek sustainable, greener power generation alternatives. One such prominent renewable substitute is wind power which was initially utilized in harnessing electricity towards the late nineteenth century though archaeological evidence has proved that wind power had been employed for various purposes since predynastic Egypt. Extensive research and development has enabled the efficient operation of multi megawatt wind farms at present though inherent drawbacks still persist, of which aerodynamic noise, also referred to as aeroacoustic noise, is of major concern. This paper details the simulative investigation of the aeroacoustic sound levels produced by an optimized novel wind turbine design intended for the use in small scale applications with medium wind speed conditions in Sri Lanka, using ANSYS Fluent. A transient analysis using the Shear Stress Transport turbulence model was used to obtain the converged pressure fluctuations which subsequently revealed the sound pressure levels via Fast Fourier Transforms at six predetermined locations of interest. The results revealed the presence of acoustic vibrations within the Infrasonic and Low Frequency Noise range with sound pressure levels exceeding one hundred decibels, particularly up to a frequency of twenty five Hertz. Prolonged exposure to elevated levels of low frequency noise has been identified to cause severe discomfort to humans though further conclusive research is required. Finer mesh controls which incorporate minute boundary layer variations during motion and precisely encapsulate the turbine geometry could further improve the accuracy of the results, however this would require adequate computational capacity. The results of this research primarily serve as a basis for identifying possible improvements for the novel rotor design in addition to providing a comparative study for future research, both simulative and empirical, on the aerodynamic noise emissions associated with wind turbines.Publication Embargo IDairy: Intelligence and Secure E-Commerce Platform for Dairy Production and Distribution Using Block Chain and Machine Learning(IEEE, 2022-07-18) Liyanage, I; Madhuwantha, N; Perera, M; Ruhunage, S; Mahaadikara, M. D. J. T. H; Rupasinghe, LThe dairy industry plays an essential role in the Sri Lanka economy. The purpose of this study is to reduce the cost of import dairy products and increase the profit of the dairy industry. IDairy: Intelligence and secure e-commerce platform for dairy production and distribution using blockchain and machine learning has been suggested as a mobile application. As a first step, this research suggested four factors. Develop a business intelligence dashboard using predictive analysis and provide business solutions to dairy companies described the revenue for the coming month using machine learning and the earning data charts for years to come to display in the dashboard. Design IOT device to maintain the temperature of fresh milk cargo while transporting to productions and design smart contract to maintain the optimum temperature for the fresh milk harvest. Develop a system to identify the cows’ diseases using image processing the primary objective was identified cows’ Foot and Mouth diseases and provide notifications to milk farms about existing illnesses. Cows’ disease directly affects dairy productions. Develop a mobile application for farmers to store animal data, do profit calculation, including giving business solutions through the application with location tracking service. With this IDairy application, both farmers and production companies will be able to get an idea about their future profit and will be suggesting the business solutions.Publication Open Access Development of an underwater robotic arm using multibody dynamics approach(2022-02-05) Fernando, S; Perera, MUnderwater robotic arms are important devices that enables workers to carry out tasks remotely from a safe distance reducing or eliminating the risks that are involved with the task. The primary objective of the robotic manipulator is to perform maintenance and cleaning activities of the hull of a ship. However, the control of these devices underwater is quite complicated due to the numerous factors that make these systems unstable and non-linear. The aim of this study is to develop a multibody dynamic robotic manipulator model, integrated with a control strategy to optimize and obtain stable kinematics solutions. The hydrodynamic forces are integrated to the manipulator model considering buoyancy forces and surface drag forces. A basic algorithm is used to generate the joint angles using 7 geometrical parameters. The control of the manipulator was done to simply follow any path that represents the given coordinates. The P, I and D parameters are tuned individually to optimize the kinematic solution of the manipulator. 3-DOF articulated manipulator is the commonly used manipulator configuration. However, a 6-DOF manipulator configuration was selected in this study to allow for change in orientation using wrist motions.Publication Embargo Power Profiling: Assessment of Household Energy Footprints(IEEE, 2021-03-06) Wijesinghe, V; Perera, M; Peiris, C; Vidyaratne, P; Nawinna, D. P; Wijekoon, JReduced energy footprint is considered an indicator of efficiency around the world. Having insights into electricity consumption behavior of individuals or families across the day is very useful in efficient management of electricity. In this paper, we present s study that focused on identifying patterns in the monthly electricity consumption profiles of a single household with the K-means clustering algorithm. The data required for this study was collected through a survey in the Sri Lankan context. The survey mainly captured the factors affecting electricity consumption. After proving the demand of electricity is dependable on the data that has been collected, they will be keyed into data models/ profiles that will be built using clustering algorithms. A load profile will be designed using K-means to identify usage patterns of a household on a monthly basis. The parameters that affect the electricity consumption were tested and trained using the SVM algorithm. The outcomes of this study include; identifying the factors contributing to the electricity consumption, identifying electricity consumption patterns, identifying the energy footprint of individuals or families and predicting the future electricity requirements. The results of this study provide many advantages for both consumers and suppliers in efficient management of electricity. It also provides significant impacts in both micro and macro levels through enabling efficient decision-making regarding management of electricity.Publication Open Access Power Management Strategy of a Parallel Hybrid Three-Wheeler for Fuel and Emission Reduction(Multidisciplinary Digital Publishing Institute, 2021-01) Maddumage, W; Perera, M; Attalage, R; Kelly, PMillions of three-wheelers in large cities of Asia and Africa contribute to the already increasing urban air pollutants. An emerging method to reduce adverse effects of the growing threewheeler fleet is hybrid-electric technology. The overall efficiency of a hybrid electric vehicle heavily depends on the power management strategy used in controlling the main powertrain components of the vehicle. Recent studies highlight the need for a comprehensive report on developing an easyto-implement and efficient control strategy for hybrid electric three-wheelers. Thus, in the present study, a design methodology for a rule-based supervisory controller of a pre-transmission parallel hybrid three-wheeler based on an optimal control strategy (i.e., dynamic programming) is proposed. The optimal control problem for minimizing fuel, emissions (i.e., HC, CO and NOx) and gear shift frequency are solved using dynamic programming (DP). Numerical issues of DP are analyzed and trade-offs between optimizing objectives are presented. Since DP strategy cannot be implemented as a real-time controller, useful strategies are extracted to develop the proposed rule-based strategy. The developed rule-based strategy show performance within 10% of the DP results on WLTC and UDC-NEDC drive cycles and has the clear advantage of being near-optimal, easy-to-implement and computationally less demanding.Publication Open Access Power Management Strategy of a Parallel Hybrid Three-Wheeler for Fuel and Emission Reduction(Multidisciplinary Digital Publishing Institute, 2021-01) Maddumage, W; Perera, M; Attalage, R. A; Kelly, PMillions of three-wheelers in large cities of Asia and Africa contribute to the already increasing urban air pollutants. An emerging method to reduce adverse effects of the growing three-wheeler fleet is hybrid-electric technology. The overall efficiency of a hybrid electric vehicle heavily depends on the power management strategy used in controlling the main powertrain components of the vehicle. Recent studies highlight the need for a comprehensive report on developing an easy-to-implement and efficient control strategy for hybrid electric three-wheelers. Thus, in the present study, a design methodology for a rule-based supervisory controller of a pre-transmission parallel hybrid three-wheeler based on an optimal control strategy (i.e., dynamic programming) is proposed. The optimal control problem for minimizing fuel, emissions (i.e., HC, CO and NOx) and gear shift frequency are solved using dynamic programming (DP). Numerical issues of DP are analyzed and trade-offs between optimizing objectives are presented. Since DP strategy cannot be implemented as a real-time controller, useful strategies are extracted to develop the proposed rule-based strategy. The developed rule-based strategy show performance within 10% of the DP results on WLTC and UDC-NEDC drive cycles and has the clear advantage of being near-optimal, easy-to-implement and computationally less demanding.Publication Embargo Analyzing the Location Feasibility for Retail Businesses using Market Location Factors(IEEE, 2018-12-21) Marasinghe, L; Rupasinghe, M; Kumarasinghe, B; Perera, M; Thelijjagoda, SThe retail industry is a fast growing and a highly revenue generating industry. The location of a retail outlet is the most influencing factor for the success of the business. Therefore selecting a location for a retail store or an outlet is a challenging process. The purpose of this study is to define a method and develop a system to analyze the feasibility of a selected location for a retail store. The factors used in this method are location and market factors of a selected area. In order to define and test the method, we selected three different areas and five different retail store types. To retrieve location data, we used Google Maps web service. Consumer surveys were conducted in selected areas to get information about consumers' shopping patterns and selections. From the web service, we were able to identify transport modes, locations of competing stores and shopping areas. The findings of this study and the method described is useful in deciding the feasibility of any given location for a retail outlet. Also the specified method and model can be modified and extended to analyze different kinds of business locations.Publication Embargo Power Profiling: Assessment of Household Energy Footprints(IEEE, 2021-03-06) Wijesinghe, V; Perera, M; Peiris, C; Vidyaratne, P; Nawinna, D; Wijekoon, JReduced energy footprint is considered an indicator of efficiency around the world. Having insights into electricity consumption behavior of individuals or families across the day is very useful in efficient management of electricity. In this paper, we present s study that focused on identifying patterns in the monthly electricity consumption profiles of a single household with the K-means clustering algorithm. The data required for this study was collected through a survey in the Sri Lankan context. The survey mainly captured the factors affecting electricity consumption. After proving the demand of electricity is dependable on the data that has been collected, they will be keyed into data models/ profiles that will be built using clustering algorithms. A load profile will be designed using K-means to identify usage patterns of a household on a monthly basis. The parameters that affect the electricity consumption were tested and trained using the SVM algorithm. The outcomes of this study include; identifying the factors contributing to the electricity consumption, identifying electricity consumption patterns, identifying the energy footprint of individuals or families and predicting the future electricity requirements. The results of this study provide many advantages for both consumers and suppliers in efficient management of electricity. It also provides significant impacts in both micro and macro levels through enabling efficient decision-making regarding management of electricity.