MPhil

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Theses and Dissertations of the Sri Lanka Institute of Information Technology (SLIIT) are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .

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Eco-hydraulic Signature of Colombo Dutch Canals and Implications for Rehabilitation
(2020) Ganegoda Kankanamge, D.
Dutch canals (DC) in Colombo, the commercial hub of Sri Lanka, playa significant role in surface drainage. Although flood control is the contemporary ise of urban waterways such as DC, their importance in provision of ecological services is started to value and is the case with the changing socio-economic and environmental requirements. Once the basic economic development is achieved and ur an dwellers are satisfied, need for a better environment (also referred as green nvironment) emerges - this is one important socio-economic need legislative authorities of developed countries have to work on. Even though yet to be realised, Sri Lankan government agencies tinie to time have shown commitment 01 ecological rehabilitation of DC. Ecological rehabilitation can be defined as -ehabilitation strategies that make the canal self-sustainable, whilst providing ecosystems services similar to a pristine stream/river. One major constraint faced in canal ecological rehabilitation is a lack of a reference state. Reference conditions would define a feasible status quo of the rehabilitated canal with estimations of thresholds of governing variables. Identification of optimum conditions in engineered systems or laboratory are not new, yet, ecosystems, especially those threatened by anthropogenic activities are rather unfound or limited to developed countries, which is particularly t'ie case with running water (Iotic) ecosystems. Those countries have straightened and concrete lined urban waterways, in many cases with fast moving waters whic 1 are close to super critical conditions. Ecological rehabilitation studies dealing subcritical urban waterways are rare, and this study's focus is on such a lotic system. DC is subject to rather somewhat basic maintenance - such activities only consider f1 od safety and have largely decreased the natural variability of the flow regime and channel ....ite.~~ morphology. However, no acbons taken so far have introduced co-hydraulic functions that would make canals self-viable and provide ecosyst m amenities expect from a natural stream/river. The aim of this study was to investigate the eco hydraulic signature of C to identify optimum eco-hydraulic conditions that correspond to an ecologically healthy canal. The specific objectives were to investigate eco hydraulic data against varying spatial and temporal scales to identify the impact of space and time on macroinvertebrate responses, model eco-hydraulic data with macroinvertebrate responses to derive optimum eco-hydraulic conditions and compile guidelines based on tho e optimum conditions that can be used in ecological rehabilitation works. Three canals including DC within urban, peri-urban (Talangama cana : TC) and rural-urban fringe (Heen canal: HC) catchments were studied for a two year period against different spatiotemporal scales. The methodology involved a comprehensive set of field observations and data analysis. Targeted optimum conditio 1S for ecohydraulic variables (hydraulic, habitat quality and water quality parameters) were derived according to the response of macroinvertebrate (diversity, and pollution tolerance index (PTI)) data. Hydraulic variables included velocity, depth. discharge, Froude number etc.; and habitat quality variables included a set of varia les such as epifaunal substrate, pool substrate characterization, channel alteration etc. that can be observed in situ. Water quality variables included dissolved oxyge , electrical conductivity (EC), pH, turbidity etc. Relationships among eco-hydraulic variables and macroinvertebrate responses were built firstly via multiple linear regression followed by bivariate models using curve estimation regression. Statistically acceptable (co-efficient of determination (R2) > 0.3 and P < 0.1) relationships were solved for a targeted PTI of 11. PTI was decided as the m st suitable macroinvertebrate index, amongst macroinvertebrate indices, as it was more generic and representative. HC showed the greatest spread of diversity, PTI and richness; an indication that macroinvertebrate composition was dynamic than TC or DC. A majority of macroinvertebrates in DC belonged to the most pollution tolerant category, while they were mostly under intolerant category in HC. TC had a mixed composition of all four categories of pollution t5ferance. Habitat quality of DC was always lower than TC and HC; therefore, belonged to poor, marginal and sub optima categories, respectively. Based on water quality parameters, HC had better water uality than TC and DC, where in many cases with a statistical significance at P < 0.05. Twodimensional variation of EC and turbidity of three canals suggested th dominance of molecular diffusion in longitudinal as well as lateral directions. Patchy distribution of turbidity ofHC indicated that attenuation also playing a major role 01 the fate of pollutants. According to the grey water footprint analysis, the urban and sem -urban canals have already exceeded their natural assimilation capacities and the s tuation was critical in DC.The study revealed that hydraulic and habitat quality parameters dominated over water quality in explaining the response of macroinvertebrates. Some of tile ecohydraulic variables showed a significant relationship with diversity, but only a few parameters from that showed a significant relationship with PTI and most of them were from He. Having a positive correlation only with diversity suggested that the pollution tolerant species had contributed to the diversity more than the p lIution intolerant species. Furthermore, .numerous significant relationships were observed in dry season than that of wet season. Eco-hydraulic variable response curves that gave significant relationships either in linear or quadratic forms were solved with the targeted PTI of 11 and solutions were suggested as target conditions that can be incorporated in ecological rehabilitation. Out of 24 eco-hydraulic variables, dry season gave 15 feasible sol utions, whereas wet season gave on ly six. Most of the feasible solutions were from hydraulic and habitat quality parameters. The study gave optimum ranges for velocity, standard deviation of velocity, Froude rumber, depth, number of mesoscale physical habitats, diversity and percentage areal coverage of transverse vegetation, score of epifaunal substrate, pool substrate characterization, bank vegetative protection, riparian vegetative zon width, electrical conductivity, dissolved oxygen, ammoniacal nitrogen and pH. Iso, the study validated some generic understanding of interrelationships within lotic ecosystems such as the fact that increased mesoscale physical habitats p sitively correlate with a healthy canal. The study gave quantifiable target conditions that could be vital in rehabi I tation of DC. Results would be applicable oot>zOnlyfor DC, but also similar canals ithin the same climatic conditions in Sri Lanka and elsewhere. It is recommended to liaise with government agencies in pilot studies, and in tandem making knowledge and data transfer with similar research groups. As future studies, it is recommended to validate the models and/or solutions obtained in this study with more lotic waters within the same geo-climatic conditions, and develop similar target conditions for different geo-climatic zones.
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Developing Safety Performance Functions for Urban Intersections in Sri Lanka
(2022) Gunathilaka, Udaha Wadiya Ralle Sarala Lasanthi
Crash frequency modeling is a good approach in identifying factors that influence on crash frequency at road ways or intersections. This research study aimed at developing Safety Performance Functions (SPFs) for urban intersections in Sri Lanka based on crash frequency modeling. This is a novel approach in the local context. The study accommodated 369 urban intersections. For each intersection, crash data, geometric data and traffic related data were collected. Out of 369 urban intersections, 107 intersections were located in Colombo district. An intersection was the unit of analysis in crash frequency modeling. Data were obtained for the period from 2015 to 2019. Police reported crash data under all severity levels were considered for the study. Geometric variables included width of lanes, shoulder, median, side walk and existence of geometric features at an intersection. Vehicle Kilometers of Travel (VKT) data were considered in terms of traffic data. VKT data were collected through an island-wide paper-based travel survey. As timely VKT data are not available with the relevant authorities in the country, estimating VKT is one of key contributions to the existing literature. Count data modeling methods; Poisson and Negative Binomial regression models were adopted to develop crash frequency models. In the study, two different SPFs were developed for Colombo district and the entire country. Out of 36 independent variables that related to geometry and traffic characteristics of urban intersections, few variables were remained statistically significant in the developed crash frequency models. Existence of left turn lanes on major leg, bus halting places, traffic signal lights, illegal road side parking, roads connected to minor leg and average shoulder width of major road variables were remained statistically significant in the Colombo district crash frequency model. In the model that was developed for urban intersections in Sri Lanka, VKT, existence of left turn lanes in minor leg, right turn lanes in major leg, traffic signal lights, road hand rails, presence of approach lanes in the minor leg, existence of kerbs in the minor leg, existence of roads connected to the minor leg, road signs and width of median in the major road variables were found statistically significant. Those variables were recommended to appear in the SPFs. Identifying influencing traffic and geometric variables on crash frequency at urban intersections in Sri Lanka is another key contribution from this study. SPFs illustrated crash frequency at urban intersections in terms of statistically significant variables with a link function. This is the ultimate output of the research study that allowed to propose and compare the most suitable countermeasures in improving safety at urban intersections. Also, limitations and recommendations of the study were discussed that can effectively be adopted in future research studies for a better approach in determining crash frequency at urban intersections in Sri Lanka.
Open Access
Synthesis and Characterization of Novel Nanomaterials for Removal of Textile Dyes in Industrial Wastewater
(SLIIT, 2022-02) Usgodaarachchi, L
Inefficient treatments and uncontrolled pollutants generation to the environment has been significantly affected the living standards in the ecosphere. The advancement in nanotechnology resulted in the effective treatment of all of the pollutants generated in the environment. In the field of textile dye removal, the special features of nanomaterials are gaining attention due to their enhanced physical, chemical and mechanical properties. Rice husk is an agricultural waste material that is used for the production of adsorbents in this study. Mesoporous silica nanoparticles were successfully synthesized by using rice husk as the raw material via a sol-gel pathway using cetyltrimethylammonium bromide (CTAB) as the structure-directing agent. The functionalization of silica nanoparticles was taken place in two pathways, such as in-situ and post functionalization methods by using 3-aminopropyltriethoxysilane (APTES) as the functionalization agent. Mesoporous silica nanoparticles were able to effectively adsorb methylene blue dye from aqueous solutions. The adsorption of MB could be best described by the pseudosecond-order model and well fitted to the Langmuir equation, with a maximum monolayer capacity of 19.26 mg/g. Photocatalytic decomposition of the organic pollutants gains emerging attention after the discovery of water splitting ability by TiO2. The high purity (98.8%, TiO2) rutile nanoparticles were successfully synthesized using ilmenite sand as the initial titanium source. This novel synthesis method was cost-effective and straightforward due to the absence of the traditional gravity, magnetic, electro statistic separation, ball milling and smelting processes. Also, highly corrosive environmentally hazardous acid leachate generated during the leaching process of ilmenite sand was effectively converted into highly efficient photocatalysts. The most efficient photocatalysts were composed of anataseTiO2/rutile-TiO2/Fe2O3, α-Fe2O3/Fe2TiO5/TiO2 and Fe2TiO5/TiO2. The synthesized nanocomposites were characterized by microscopic (SEM and TEM) and spectroscopic (XRD, Raman, XPS, FT-IR and DRS) analytical techniques. These nano heterostructures were catalytically active for the photodegradation of methylene blue upon irradiation by a light source (LED or sunlight). Efficient charge separation and limiting electron-hole recombination in photocatalyst surfaces resulted in the overall performance of synthesized material. Reduced iv graphene oxide (r-GO) has lately attracted a lot of attention to overcome limitations associated with photocatalysts. The honeycomb sp2 network structure of r-GO improves charge separation and transportation through the surface of the catalyst. The fabricated GO/Fe3O4 heterogeneous photocatalyst shows very efficient degradation performance by overcoming the limitations associated with the narrow bandgap of Fe3O4 (0.1 eV). Finally, the synthesis of graphene like materials by catalytic graphitization of sucrose by using Fe and Ti transition metals studied in this study. Herein, we reported that Fe and Ti metal oxides promoted to the graphitization process at low temperature. Sucrose mixed with only uncalcined Fe2O3 produced Fe3C, Fe, Fe3O4 dispersed on graphitic carbon, while sucrose mixed with only Fe2TiO5/TiO2 product, and mixed with uncalcined Fe2O3 and Fe2TiO5/TiO2 led to the production of TiO2, Fe3C, Fe, Fe3O4 dispersed on graphitic carbon. The most outstanding photocatalyst synthesized material composed with TiO2/Fe3C/Fe/Fe3O4–Graphitic carbon which is sun light sensing photocatalyst.
Open Access
Development of Queue Estimation Algorithms for Urban Intersections in Mixed Traffic Conditions
(Department of Civil Engineering Sri Lanka Institute of Information Technology, 2023-12) Jayatilleke, J.A. D.S.S
Traffic congestion has increased globally due to rapid urbanization and expedited economic developments in many countries. Vehicle queues are a governing aspect of traffic congestion, studied over the past decades. Most of the existing queue estimation approaches are limited to homogeneous traffic conditions. However, the traffic conditions in many developing countries are heterogeneous and are heavily influenced by mixed vehicle composition, lane changing, and gapfilling behaviors. This study aims to estimate the queue length at signalized intersections having heterogeneous traffic conditions. The methodology employed in this study integrates both statistical and neural network analyses utilizing a time-series approach. A key innovation in this research lies in the incorporation of heterogeneity considerations, where Passenger Car Units (PCU) are assimilated into the measurements of traffic flow and lane-changing movements within the analyzed road section. The influential factors impacting queue length were examined, encompassing arrival flow, discharge flow, outbound lane change, inbound lane change, and signal configuration. The statistical analysis was undertaken through an econometric approach, representing another novel contribution to queue estimation studies. Vector Auto Regression (VAR) models were developed to estimate queue lengths for signalized and unsignalized intersections. The VAR estimation results demonstrated heightened accuracy in queue estimation and practical applicability for prediction, capturing the traffic characteristics of the formed vehicle queue. However, limitations were identified, particularly in terms of lower prediction times, which impeded the practical utilization of the model for traffic management. Consequently, to address this limitation, neural network analysis using the Long Short-Term Method (LSTM) was incorporated to enhance queue predictions over longer time sequences. While the neural network exhibited promise, challenges in data collection contributed to lower accuracy in predictions. Notwithstanding the challenges, the methodological development in this thesis presents a promising direction for queue estimations under heterogeneous conditions. This advancement brings the scientific and research field one step closer to improved queue estimation methods within this specific scope.