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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2014 - 20207

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Subject: search.filters.subject.Simulation

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Now showing 1 - 7 of 7
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    Simulation of ionomer membrane fatigue under mechanical and hygrothermal loading conditions
    (Elsevier, 2015-04-01) Khorasany, R. M. H; Kjeang, E; Wang, G. G; Rajapakse, R. K. N. D
    Understanding the fatigue lifetime of common perfluorosulfonic acid (PFSA) ionomer membranes under fluctuating hygrothermal conditions is essential for the development of durable fuel cell technologies. For this purpose, a finite element based fatigue lifetime prediction model is developed based on an elastic–plastic constitutive model combined with a Smith-Watson-Topper (SWT) fatigue formulation. The model is validated against previously reported experimental results for a membrane under cyclic mechanical loadings. The validated model is then utilized to investigate the membrane fatigue lifetime in ex-situ applications under cyclic humidity and temperature conditions. The simulations suggest that the membrane fatigue lifetime is shorter under fluctuating humidity loadings than for temperature loadings. Additionally, the membrane fatigue lifetime is found to be more sensitive to the amplitude of the strain oscillations than to the mean strain under hygrothermal cycling. Most notably, the model predicts that simultaneous humidity and temperature cycling can exacerbate the fatigue process and reduce the fatigue lifetime by several orders of magnitude compared to isolated humidity or temperature cycling. The combination of measured mechanical fatigue data and the present numerical model provides a useful toolkit for analysis of membrane fatigue due to hygrothermal variations, which can be costly and time-consuming when addressed experimentally.
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    PublicationOpen Access
    Revisiting Feller Diffusion: Derivation and Simulation
    (2019-07-13) Munasinghe, R; Kanthan, L; Kossinna, P
    We propose a simpler derivation of the probability density function of Feller Diffusion using the Fourier Transform and solving the resulting equation via the Method of Characteristics. We also discuss simulation algorithms and confirm key properties related to hitting time probabilities via the simulation
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    Augmented Reality Based Platform for Simulation of 3D Models, Generated with a Series of 2D Images, on Real Environment
    (IEEE, 2014-10-21) Ashinshanie, S. A. D. N. N; Hazari, A; Rupasinghe, H. N; Hettiarchchi, D. P; De Silva, D. I
    With the need of an Augmented Reality based platform for simulation of three dimension models, generated with a series of two dimension images, on real environment, the main objective of this project is to build a platform for users to use both these functionalities. This is a mobile application which helps people to decide when they are buying household items, whether that item fits their desired place in the house. Three dimension models can be downloaded using the application and it will be simulated in the real time environment using the concept of Augmented Reality. A desktop application will be implemented for sellers to upload their three dimension models and to generate three dimension models using photographs. With the use of the technology people can make their lives easier, and this is another step the development team has taken to help that cause. Main goal is that with the use of this application people will be able to make their decisions easily when they are going to buy large household items.
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    On The Effectiveness of Using Machine Learning and Gaussian Plume Model for Plant Disease Dispersion Prediction and Simulation
    (IEEE, 2020-05-29) Miriyagalla, R; Samarawickrama, Y; Rathnaweera, D; Liyanage, L; Kasthurirathna, D; Nawinna, D; Wijekoon, J
    Agriculture plays a vital role in the economic development of the entire world. Similarly, in Sri Lanka, 6.9% of the national GDP is contributed by the agricultural sector and more than 25% of Sri Lankans are employed in the field of agriculture. But the frequent fluctuations of climate conditions have caused the spread of diseases such as late blight which eventually has led to the devastation of entire plantations of Sri Lankans. To this end, this paper proposes to forecast the possible dispersion pattern and assist the farmers in identifying the possibility of the disease getting dispersed to nearby crops to provide early warning. Eventually, it leads the farmers to take precautions to save the plants before reaching a critical stage. The yielded results show that the proposed method successfully performed disease diagnosis and disease progression level identification with 90-94 % accuracy and dispersion pattern analysis.
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    Simulation of the Influence of environmental factors related to Greenhouses using Augmented Reality
    (IEEE, 2019-12-05) Shaleendra, T; Wishvamali, B. T; Gunarathne, N; Hareendran, S; Abeygunawardhana, P. K. W
    With the vast growth of the population, increased production of agricultural products is necessary. Although the amount of land available for agriculture is limited, the demand for food products based on agriculture is expanding. The Organic food supply is scarce in the current food market; hence, their retail prices are higher than the other agricultural products which were produced with the use of pesticides. In this context, Greenhouse production is widely used all over the world with minimal pesticides and weedicides including Sri Lanka. Automated Greenhouses can be used to increase production with a minimum amount of human labor. With less use of human hours, it will produce more harvest than conventional Greenhouses which need constant human attention and care. The installation of automated Greenhouses is costly although their long-term benefits are higher than a conventional one. For this reason, introducing the concept to cultivators would be difficult, as they are reluctant to invest their money on unfamiliar technology. There is a hesitance to embrace technology since they don't have the first-hand experience in operating an automated Greenhouse. Therefore, in this paper, we present a simulated model of automated Greenhouse using Augmented reality, through which a client can visually experience the workings of IoT Greenhouse based on theoretical models beforehand to make an informed decision to invest in automated Greenhouses.
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    On the effectiveness of using machine learning and Gaussian plume model for plant disease dispersion prediction and simulation
    (IEEE, 2019-12-05) Miriyagalla, R; Samarawickrama, Y; Rathnaweera, D; Liyanage, L; Kasthurirathna, D; Nawinna, D; Wijekoon, J. L
    Agriculture plays a vital role in the economic development of the entire world. Similarly, in Sri Lanka, 6.9% of the national GDP is contributed by the agricultural sector and more than 25% of Sri Lankans are employed in the field of agriculture. But the frequent fluctuations of climate conditions have caused the spread of diseases such as late blight which eventually has led to the devastation of entire plantations of Sri Lankans. To this end, this paper proposes to forecast the possible dispersion pattern and assist the farmers in identifying the possibility of the disease getting dispersed to nearby crops to provide early warning. Eventually, it leads the farmers to take precautions to save the plants before reaching a critical stage. The yielded results show that the proposed method successfully performed disease diagnosis and disease progression level identification with 90-94 % accuracy and dispersion pattern analysis.
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    PublicationOpen Access
    An improved approach to line balancing for garment manufacturing
    (Faculty of Management Studies and Commerce, University of Sri Jayewardenepura, 2016-06-01) Wickramasekara, A. N; Perera, H. S. C
    Production managers in the apparel industry frequently face the issue of being unable to complete the orders at the scheduled time. One of the reasons for this issue is the unavailability of a Line Balancing procedure that could encompass the stochastic nature of the sewing process, which is manifested through the likes of variability of sewing times, machine breakdowns, correcting defective products, and operator breakings such as for changing bobbins and drinking water. The objective of this research is to introduce a diverse approach to Line Balancing through giving due consideration to the stochastic nature of the process. The improved approach was developed through case study approach. Having selected a sewing line in an apparel factory, the process times of operations, major random events and the times elapsed between random events were recorded. Then the whole production cycle was simulated using ARENA software. By attempting and analysing different scenarios, a different approach for line balancing was introduced. The initial steps of the algorithm developed includes: collecting processing times and necessary information on manufacturing process, fitting standard probability distributions to both value added and non-value added activities, developing the precedence diagram, developing an initial algorithm for balancing a production line and finally, making necessary adjustments to the algorithm analyzing different scenarios. In order to check the validity of the algorithm, a production line was balanced for two different daily production targets. Thus, the application of proposed algorithm to balance the production line reduces the gap between the expected production target and the real achievement.