Abstract: This paper presents computational fluid dynamic (CFD) analysis of a natural draft top-lit up-draft (TLUD) biomass cookstove which is acting as a micro pyrolyzing reactor to produce biochar. The effect of the top end geometry, the number of primary and secondary air inlets and their hole patterns, and the number of secondary air outlets and their hole patterns were considered in the design to optimize the performance. Seven different cookstove geometries were simulated to analyse the temperature and air distribution. ANSYS Fluent 16.0 was used to simulate the simplified 3D computational domains of the cookstove designs. The design with uniform air distribution and proper mixing of secondary air and the producer gas was selected as the best cookstove design to fabricate. Experiments were performed with the selected design and the results were compared with the predicted simulation results for evaluating the model. Results revealed a good correlation of 96.67% and a higher R2 (coefficient of determination) value of 0.9344 for the temperature inside the combustion chamber. Thus, this modelling methodology can be used for the optimization of existing biomass cookstoves and for evaluating naval cookstove designs. Published on 2021-12-30 00:00:00
Abstract: Generally, one of the most vulnerable road user categories that could be recognized is pedestrians, thus their susceptibility to high injury severities in road vehicle crashes. In Sri Lanka, the risk of pedestrian safety near school zones has increased rapidly with the growth of areas such as infrastructure development, socio-economic development, etc. This research was focused to address the pedestrian safety issues based on behaviour risk of school children near Colombo zone. The data collection for this study was conducted under three categories which include: a road inventory data collection, road crash data collection and a pedestrian road risk behaviour data collection. Moreover, two factors were given priority: the user behaviour at pedestrian crossings and user behaviour at sidewalks. The data collection on the pedestrian behaviour risk was done manually, focusing on school uniformed children. Past road crash data from the Sri Lankan Traffic Police database were also used to estimate normalized values. Behaviour risk value for each school zone was estimated in order to identify whether any safety improvements were required. Vulnerability for not using sidewalks was 15% on average and the vulnerability for not using pedestrian crossings was less than 10% for all school gates considered in both morning and afternoon times. Results indicated that the vulnerability risk is low compared to studies found in literature. Published on 2021-12-30 00:00:00
Abstract: The COVID-19 pandemic has created a shift in all our lives, turning in-class traditional educational systems into distance learning systems. Since distance learning is inevitable nowadays, the hands-on experience from in-class, particularly in practical sessions, is lacking. While there is a wide range of tools and technologies to enrich the student learning experience, the application of Augmented Reality (AR) is remarkable. This paper proposes a mobile app assisted with AR technology aimed to support the engineering faculty students to enhance their knowledge regarding the lathe machine and lathe operations during this pandemic period. The application consists of the augmented content of the separate parts of the lathe machine, exploded view and augmented animated content of the operations. The objective of this AR app is to guide the students regarding machineries and operations, and to introduce AR technologies to the local universities as a step of enhancing digital education. The adaptability of the AR app was experienced and verified by 72 students and the responses and feedback revealed their interest towards this educational approach. Conclusively, this study shows the effectiveness and importance of AR application specially for Manufacturing Engineering field during this distance learning period. Published on 2021-12-30 00:00:00
Abstract: Wind is a random movement of air particles in both time and space, which produces very complicated dynamic loading scenario on flexible structures like tall buildings. Modern tall buildings are becoming more slender, flexible, lightweight and irregular in shape due to revolution of associated technologies. Consequently, analysis of tall buildings considering complicated nature of wind loading and dynamic response of the structural system is an important role in design of tall buildings. Wind tunnel test is the most reliable tool for the estimation of dynamic wind loading on tall buildings. However, due to the cost and time involved, wind design codes are generally used during the preliminary design stage. Thus, understanding the background of dynamic wind loading and procedures adopted in wind design standards to represent the dynamic effects is vital to arrive at an efficient, safe and economical structural system during the preliminary design stage. This paper presents an overview on background of dynamic wind loadings and provisions of four international wind codes frequently referred to in Sri Lanka, British Standard (BS), European Standard (BS EN), Australian Standard (AS/NZS) and Standard of Architectural Institute of Japan (AIJ). Further, the concept of equivalent static load derived based on the “gust-factor” method adopted in most of the international wind design codes is discussed. At the end, a forty-six storied wall-frame structure was used as the numerical example for the explanation of dynamic wind loading and its influence on the structural design. Published on 2021-12-30 00:00:00
Abstract: In this experimental research, the effects of gray-level quantization and tiling window size on 22 gray-level co-occurrence matrix features were investigated in the context of automated woven fabric defect detection. A dataset comprising 1426 128×128 images was used, in which defective and the defect-free images were split in a 50:50 ratio. Experiments were carried out with seven quantization levels ( Published on 2021-12-30 00:00:00
Abstract: Waste polyethylene creates serious environmental and social problems in Sri Lanka. The amount of waste polyethylene increases daily, further aggravating environmental and social issues. Finding out the most suitable solution for this is a vital requirement. This research focuses on investigating the possibilities to convert this waste polyethylene as a sustainable construction material by combining it with readily available coconut fibre. A preliminary investigation was carried out on thermoplastic/coconut fiber composites to evaluate their suitability in the construction industry. Composite sheets, 2.5 mm and 3.2 mm thick, were developed by varying coir fibre weight with a suitable polymer matrix using a hot press machine. In this step, mechanical properties of the composite material were measured through tensile and bending tests. The tests were carried out complying with ASTM D3039 and ASTM D790, respectively. The surface morphology of coir fiber and the fractured surface of failure material were investigated through Scanning Electron Microscopy (SEM). Maximum tensile strength was observed as 6.75 N/mm2 when the coir wt. fraction is inbetween 20-30% by total weight. The maximum bending strength was 29.85 N/mm2 when the coir fraction is almost 25% by total weight. The corresponding mechanical properties are compared with the available materials in the industry. Published on 2021-12-30 00:00:00
Abstract: Hardness is not a fundamental property of a material but it is related to the elastic and plastic properties of the material. Hardness of a material can be determined from indentation hardness tests. Brinell hardness test is one of the commonly used macro-indentation hardness test types to quantify the hardness of a material. In this study, the sensitivity of Brinell Hardness Number (BHN) to the material properties of structural steels that exhibit a plastic plateau in their true stress-strain curve is analysed. Four basic structural steel material properties, Young’s modulus ( Published on 2021-12-30 00:00:00
Abstract: Activity based transport demand models are used to model complex human behavioural responses to policy decisions. Activity pattern formulation is an important aspect of the model development process. The travel demand models developed and used currently in Sri Lanka are the traditional trip-based models. These models, although can be enhanced, have limitation of being unresponsive to disaggregate level changes. With the increasing demand for the models to be more responsive for policy decision and project formulation, there is a need to move towards disaggregate level modelling, thus the need for an activity-based model (ABM). Understanding the activity pattern groups of the study area is a priori and the first step towards building ABM. But, there has not been any previous work for Sri Lanka to understand the activity pattern groups. Therefore, this research develops a method for representation of activity patterns of individuals for Western province of Sri Lanka. The home visit survey (HVS) data collected as part of CoMTrans study done in 2013 has been used. Each member’s activity pattern was developed with spatial and temporal representation. 1,106 unique activity patterns were identified with education based and work-based patterns having the highest frequency. These were categorised into three main categories (Education, Work and Other), and each member was assigned a category based on pattern’s main trip. These categories were further divided based on number of tours, purpose, diversions and time of travel. The main activity pattern of each subgroup was also identified. Further analysis of the subgroups provided behavioural aspects that are relevant to each tour purpose. The study identified 17 subgroupsconsisting of 5 work, 4 educational and 8 other pattern groups. Published on 2021-12-30 00:00:00
Abstract: Deaf and Mute people cannot communicate efficiently to express their feelings to ordinary people. The common method these people use for communication is the sign language. But these sign languages are not very familiar to ordinary people. Therefore, effective communication between deaf and mute people and ordinary people is seriously affected. This paper presents the development of an Android mobile application to translate sign language into speech-language for ordinary people, and speech into text for deaf and mute people using Convolution Neural Network (CNN). The study focuses on vision-based Sign Language Recognition (SLR) and Automatic Speech Recognition (ASR) mobile application. The main challenging tasks were audio classification and image classification. Therefore, CNN was used to train audio clips and images. Mel-frequency Cepstral Coefficient (MFCC) approach was used for ASR. The mobile application was developed by Python programming and Android Studio. After developing the application, testing was done for letters A and C, and these letters were identified with 95% accuracy. Published on 2021-12-30 00:00:00
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