Conference Publications
Permanent URI for this collection
Browse
Recent Submissions
1 - 5 of 69
-
PublicationArtificial neural network models for wastewater treatment plant(AIP Publishing, 2023)In water treatment plant decision support systems, the study of the treatment problem(s), information acquisition and representation, and the assessment and evaluation of parameters guiding the selection of optimal treatment systems are all critical. Water treatment plants have been an essential feature of the National Integrated Water Resources Management Strategy (NIWRMP), which is consistent with the 10th Malaysia Plan's National Transformation Programme (NTP). Thus, it is appropriate to focus on the water treatment management. This research aims to develop models for Wastewater Treatment Plant (WWTP) via artificial neural network (ANN). The dataset is secondary data obtained from UCI Machine Learning repository system, which originally aims to characterize the plant's operating condition to forecast faults using the plant's statevariables at each point of the treatment phase. The data were derived from regular sensor readings at a city wastewater treatment facility. Four models were eventually developed using multilayer perceptron (MLP) neural network. The models are: (i) globalperformance input biological demand of oxygen, (ii) global performance input chemical demand of oxygen, (iii) global performance input suspended solids, and (iv) global performance input sediments. The models' performances were evaluatedusing Sum of Square Error (SSE). Policymakers may then use the suggested awareness model to enhance water quality evaluation control. It provides insight into the public's understanding of treated water quality care in their neighbourhood and thus, helping decision-makers to appreciate better whether people may or may not be aware of the importance of conducting water quality treatment. This research is in accordance with SDG 6 - Clean Water and Sanitation - of global Sustainable Development Goals (SDGs).
1 3 -
PublicationDevelopment of fragility curves for bridge(AIP Publishing, 2023)This study presents the development of fragility curves for a three-span reinforced concrete box girder bridge. The model was designed based on ASSTHO LRFD 2017 standard. CSiBridge software was used as the main tool for nonlinear time history analysis (NTHA) which is also referred to as incremental dynamic analysis (IDA). Seven ground motions from the real earthquake were used to generate IDA curves. All the ground motions were converted to acceleration response spectrum and scaled up or down depending on the fundamental period, T1 of the bridge according to the Eurocode 8 (EC8) elastic respond spectrum to suit the characteristic of the ground motion to the soil type. The performance level was identified based on IDA curves. These performance levels include operational phase (OP), immediate occupancy (IO), damage control (DC), live safety (LS) and collapse prevention (CP). These levels will be used to observe the structural performance of the bridge. Results show that piers with 5 m height have better performance than those with 7 m height. The fragility curves were then developed for 5 m and 7 m pier height. Fragility curves show the probability of exceeding the performance levels is higher for 7 m pier height.
-
PublicationStudy of albumen as foaming agent for use in self-healing high strength concrete(AIP Publishing, 2023)Self-healing is an effective solution for sustainable maintenance for concrete to increase its durability against to sensitivity of cracking. As recently, the method of introducing bacterial agent in concrete were modified because of harsh environment in concrete such as small size of pore which cause squeezing of bacteria. In this research, the albumen from egg was used as foaming agent to create voids in concrete matrix. The aerated concrete matrix offer voids to bacteria as concrete will become dense and bacteria would squeezed during hydration process. The effect of albumen as foaming agent in concrete was studied while achieving the high strength aerated concrete type towards its compressive strength, splitting tensile strength and study the voids dissolution (visual) in concrete matrix when incorporation of albumen as foaming agent. The albumen of 2%, 4% and 6% is used as foaming agent (FA) to produce the high strength aerated concrete (HSAC). After 28 days of curing, the compressive and splitting tensile strength of HSAC reduced with the increased of albumen used in concrete. The highest compressive and splitting tensile strength of HSAC were 95.40 MPa and 6.67% respectively with 2% FA in comparison to control. The results of water absorption of HSAC also decreased when higher concentration of albumen used. The sizes of voids created in all samples were less than 15 mm. It can deduced that 2% of foaming agent was ideal to produce optimum characteristics in strength, uniform and size of voids in high strength aerated concrete.
-
PublicationImproving Indoor Environmental Quality (IEQ) and comfortability of lecture rooms: case study – UniCITI Alam Campus, Padang Besar, Malaysia(IOP Publishing, 2020)UniCITI Alam is a mixed development of commercial buildings and medium rise apartments. The whole development was designed based on the integration of student residential community with the combined commercial centre and temporary campus. The lecture rooms are located at the second floor of the triple-storey shop house. To improve the indoor environmental quality and comfortability of the teaching and learning activities, physical measurements of the indoor environment parameters (air temperature, relative humidity and carbon dioxide (CO2) concentration) and light intensity are the main methods applied in the presented case study. Data collected will be compared with Malaysian Standard MS 1525: 2007 (Code of Practice on Energy Efficiency and Use of Renewable for Non Residential Building) and DOSH. The finding will be used for improving the environmental quality of the lecture rooms and enhancing the ecology circle.
-
PublicationInfluence of various sand gradation on mechanical properties and concrete quality of High Performance Concrete (HPC)(IOP Publishing, 2020)High Performance Concrete (HPC) has a few characteristics: high strength, high early strength, high modulus of elasticity, high durability and long life in severe environments, low permeability and diffusion, resistance to chemical attack, toughness and impact resistance and so on. Almost 70 to 80% of the volume of the concrete is occupied by aggregate which have a great impact on characteristics and properties of a concrete. Not only course aggregate but fine aggregate also contributes a lot toward the performance of HPC. Thus, this research studied on the influence of various sand gradations on mechanical properties and concrete quality of HPC. The sand gradation utilized in the study are normal size sand, sand passing through sieve size 1180µm, sand passing through sieve size 600µm and sand passing through sieve size 300µm. The mechanical properties of HPC being studied are compressive strength and splitting tensile strength while the concrete quality of HPC is determined by using water absorption and Ultrasonic Pulse Velocity (UPV) test. The results show that the mechanical properties and concrete quality increased as the size of sand particles decreased. The optimum sand gradation is the sand passing through sieve size 300µm which achieved highest mechanical properties and concrete quality showing the highest result of compressive strength (123.9MPa), splitting tensile strength (8.91N/mm2), lowest percentage of water absorption (0.55%) and highest UPV value (7743N/mm2).
6 1