http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/48 Post graduate dissertations (Theses) of Department of Civil Engineering (CE) 2026-11-05T04:37:02Z http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7392 Development of speed prediction models for urban primary road under heterogeneous traffic conditions Hadiuzzaman, Dr. Md.; Towhidul Alam, S.M.; 0422042202 P; 625.7950954922/TOW/2025 The primary roads of Dhaka are essential infrastructural components, similar to those in cities around the world. These roads facilitate major traffic movements within urban centers and between key municipal traffic generators. The operating speed of these roads has a significant impact on their performance. Speed is a crucial factor in urban primary roads, as it affects the density and volume of traffic streams. Recent studies have focused on developing speed prediction models for homogeneous traffic conditions on two- or multi-lane rural highways. However, there is a lack of research on urban primary roads under heterogeneous traffic conditions. In cities like Dhaka, there is a notable difference in behavior between heterogeneous and undisciplined traffic streams compared to conventional traffic flow. In Dhaka, traffic streams are mixed, with various vehicles occupying the same lane and moving freely wherever space permits. Thus, the primary road system in Dhaka warrants an in-depth study and the development of a speed prediction model to support efficient roadway management. This study aims to create simultaneous speed prediction models based on fundamental speed-density relationships in heterogeneous traffic conditions. The basic Greenshield’s equation, which relates speed to density, has been modified for mixed traffic compositions and the proportion of different vehicle types within the traffic stream. However, traditional fundamental speed-density models with the least squares fit method often struggle due to their few limitations. We applied the Maximum Likelihood Estimation (MLE) technique and Bayesian Inference to address these limitations. We selected a 400-meter section along Mirpur Road, Matikata Road, Airport Road, Toyenbee Circular Road, and Darus Salam Road, all of which exhibit uniform traffic operating conditions without access points. A longitudinal trap of 60 meters was set up in the middle of this section to measure flow and speed. Data was collected using a DJI AIR 3 drone equipped with a dual-camera system and 4K/60fps HDR video on a typical weekday from 8:00 a.m. to 6:00 p.m. Vehicles in the traffic stream were categorized into six groups: Standard Cars (SC), Utility Vehicles (UV), Heavy Vehicles (HV), Three-Wheelers (3W), Two-Wheelers (2W), and Non-Motorized Vehicles (NMV). A deep learning-based heterogeneous traffic measurement technique was utilized to analyze and detect vehicles. Vehicle trajectories were tracked using DeepSORT, while vehicle identification and classification were performed using YOLOv8. This study employed DEEGITS (Deep Learning Based Heterogeneous Traffic State Measurement), a comprehensive framework that utilizes YOLOv8 and DeepSORT for accurately detecting, classifying, and tracking vehicles. Several scripts were written in MATLAB to analyze the processed video data and extract relevant attributes, including vehicle type, speed, and flow rate, for each road section. Based on a comprehensive analysis of the traffic data collected from the selected urban primary road network segments, this study successfully developed a simultaneous speed prediction model to estimate vehicle speeds under heterogeneous traffic conditions. Using the developed model, the analysis thoroughly investigated traffic flow rates for different Dhaka City traffic stream compositions. Initially, with a vehicle mix of Standard Cars (SC), Utility Vehicles (UV), Heavy Vehicles (HV), three-wheelers (3W), two-wheelers (2W), and Non-Motorized Vehicles (NMV) at 30%, 10%, 10%, 10%, 10%, and 30%, the total vehicle volume showed better performance, but it did not maximize road capacity. A mix of 20%, 10%, 30%, 10%, 20%, and 10% yielded satisfactory results in an analysis at 4500 vehicles per hour. However, a composition of 25%, 25%, 15%, 15%, 15%, and 5% reached critical density at 6500 vehicles per hour. Finally, the optimal mix of 20%, 10%, 30%, 15%, 15%, and 10% demonstrated the best speed and roadway capacity optimization. The accuracy of the equations is checked by comparing the observed values of speed with the calculated speeds. The models developed in this research will enable transportation engineers to plan more effectively and improve road operation and safety management. These models could be integrated within Intelligent Transportation Systems (ITS) and utilized with Variable Message Signs (VMS) across Dhaka's primary road network. To achieve this, ITS would need to gather extensive data from UAVs monitoring the roadway and continually process the information using the established prediction models. 2025-06-21T00:00:00Z http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7389 Performance of concrete prepared with Geopolymer aggregate from sewage sludge ash and incinerated medical ash Dr. Tanvir Ahmed; Rafiqul Islam, Md.; 0422042131; 624.183/RAF/2025 The recent boom in infrastructural development in Bangladesh has triggered the exceptional demand for clay burnt brick aggregate as the country's supply of natural aggregates cannot meet the high demand. However, the production process of brick creates significant environmental issues. On the flip side of the construction industry, the increase of industrial by-products and waste (e.g., coal fly ash (CFA), sewage sludge ash (SSA), and incinerated medical ash (IMA), constantly taking up virgin lands for disposal, mainly through landfills. The recycling of the above-mentioned three ashes reduces the environmental impact in terms of soil contamination, and air and water pollution. Geopolymer coarse aggregate (GCA) can provide an effective solution that simultaneously reduces the production of bricks and promotes sustainable hazardous waste management, which has pozzolanic capacity. GCA was produced by geopolymerization process from a combination of waste materials consisting of 50% SSA, 45% CFA, and 5% IMA using alkaline activator (e.g. Sodium hydroxide (NaOH) and Sodium silicate (Na2SiO3)). In this study, concrete specimens were prepared by utilizing GCA as a replacement of brick coarse aggregate (BCA) at five different GCA replacement ratio of 0%, 25%, 50%, 75%, and 100%. Different fresh, physical, mechanical, and durability properties of geopolymer aggregate concrete (GAC) were investigated. Microstructural analysis, failure modes, cost and CO2 footprint analysis were also evaluated. Simplified regression equations have been proposed to predict various mechanical properties of GAC mixtures. Total incorporation of GCA in concrete decreased the slump value of fresh concrete up to 36.4%. However, GAC remains high degree workable. The compressive strength decreased with an increase in GCA percentage. Higher than 30 MPa concrete can be produced by using 100% GCA content, and it can be 40 MPa if the GCA content is limited to 50%. Furthermore, when the specimens are heated to 400°C the compressive strength was drastically reduced from 42% to 61%. Though all the GAC specimens provide comparatively lower splitting tensile and flexural strengths, the 50% GCA content presented a marginal reduction of 8.7% and 8.5%, respectively, compared to the control one. All the GAC mixes have a lower density than the BAC mix and fall within the limiting value of lightweight concrete. The leaching behavior of the specified heavy metals (Pb, Cr, Cd, Cu, and Ni) has been analyzed using the Toxicity Characteristics Leaching Procedure (TCLP). The heavy metal concentrations obtained from the TCLP test results for all GCAs and GACs are far below the USEPA regulatory limits. The strength-CO2 analysis results showed that all the GAC specimens provide more strength in terms of CO2 footprint compared to control specimens. Overall, the findings presented in this study will aid in advancing sustainable artificial aggregate concrete as well as mitigate the environmental and economic burden of waste. 2025-03-18T00:00:00Z http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7388 Behaviour of peripheral t-shaped shear wall in framed tube structures in moderate seismic zones of Bangladesh Al Amin Siddique, Dr Mohammad; Mallick, Debashis; 0419042349; 624.176/MAL/2025 Bangladesh is a small country with a high population density. Due to the demand for massive urbanization, more high-rise buildings need to be constructed in major cities. The framed tube structural system can be an effective framing technique for this case. This system comprises tightly spaced peripheral columns connected by deep spandrel beams. The total system works as a giant vertical cantilever. This study analyzes six reinforced concrete framed tube buildings of varying heights and peripheral configurations. The structures are categorized into two groups based on their peripheral members: (a) those with square columns and (b) those with T-shaped shear walls. The research examines three building heights, 20, 40, and 60 stories, corresponding to 81.5 m, 161.5 m, and 241.5 m, respectively. A regular plan configuration is considered for all building models to assess structural behaviour under various conditions. The reduced cost of columns, walls, and beams of square-shaped framed tube structures with peripheral T-shaped walls compared to the column is in the range of 3-8%. The shear lag factor for the ground floor is also reduced from 32% to 54% for structural configurations considered in the study. The concrete quantity with peripheral T-walls is reduced by 1-6%. The longitudinal reinforcement quantity is also reduced by 6-22%. The seismic performance level of buildings with peripheral T-walls is Immediate Occupancy (IO) for the hazard level corresponding to Service Level Earthquake (SLE), Design Basis Earthquake (DBE), and Maximum Covered Earthquake (MCE), while IO to Life Safety (LS) for the considered buildings having the peripheral columns. The plastic hinge formation of considered buildings with peripheral columns ranges from 2% to 14%, while those with peripheral T-walls are negligible. Therefore, for high-rise construction in Bangladesh, T-shaped shear walls in framed tube structures may offer better seismic performance and cost savings, making them an efficient alternative to traditional peripheral column systems. 2025-02-24T00:00:00Z http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7324 Development of standard design methodology for slopes reinforced with plastic pins and Vetiver Grass Shariful Islam, Dr. Mohammad; Kaysaru Zaman Kawshiq, A S M.; 0421042201; 624.162095492/KAY/2025 Slope stability is a critical concern in geotechnical engineering, particularly in regions prone to erosion, shallow failures, and infrastructure instability. This research presents the development of a design methodology for slope stabilization using Vetiver grass and Recycled Plastic Pins (RPP) as a sustainable, cost-effective, and environmentally friendly alternative to conventional stabilization techniques. The study integrates laboratory testing, field monitoring, numerical modeling, and predictive modeling to evaluate the effectiveness of Vetiver and RPP in improving slope stability. The research begins with soil characterization through laboratory testing, assessing index properties, engineering properties, and chemical characteristics of different soil samples. Three soil types were analyzed: Tahirpur soil, classified as clayey silt with high plasticity, consisting of 84% silt and 16% clay, requiring pH adjustment for optimal vegetation growth. Dacope soil, categorized as lean clay with moderate plasticity, contained 73% silt and 27% clay but exhibited high salinity (ECe = 9 dS/m), making it challenging for plant survival. Chilmari soil, identified as silty sand with 60% sand, 35% silt, and 5% clay. Field monitoring of Vetiver growth at two sites, Dacope (Khulna) and Chilmari (Kurigram), demonstrated Vetiver’s ability to thrive in saline and nutrient-deficient soils. Survival rates exceeded 75% in high-salinity conditions and reached 95% in sandy soil. Growth data indicated shoot lengths of up to 213 cm and root penetration extending to 70 cm, confirming Vetiver’s strong anchorage and effectiveness in erosion control. To enhance real-time assessment of soil movement, moisture content, and reinforcement performance, an IoT-based monitoring framework was conceptually introduced. Numerical analysis using PLAXIS 2D was performed to assess the effectiveness of Vetiver and RPP reinforcement. The results were validated against conventional method of slices. A parametric study was conducted to evaluate the influence of slope geometry, soil strength, reinforcement depth, plant age, and spacing on stability. The findings revealed that increasing the slope angle from 20° to 60° led to a 61% decrease in FS, indicating the vulnerability of steeper slopes to failure. Soil cohesion played a crucial role in stability, as an increase from 0 to 20 kPa resulted in a 126% improvement in FS, confirming that cohesive soils provide better stability. The effectiveness of Vetiver reinforcement was strongly correlated with plant age, with a 62% increase in stability observed after two years due to deeper root penetration. Denser Vetiver and RPP spacing configurations contributed to higher FS values, while wider spacing reduced reinforcement effectiveness. The optimal RPP length was determined to be up to 2.0 meters for RPP alone, beyond which additional length yielded diminishing returns, but with vetiver deeper RPP lengths provided additional 16% improvement of FS when length was increased from 2 to 3 meters. To develop a practical design tool, Multi-Linear Regression (MLR) and Artificial Neural Network (ANN) models were formulated for FS prediction. A cost analysis demonstrated that Vetiver and RPP reinforcement was significantly more economical than conventional concrete-based stabilization methods, reducing costs by up to 56%. The Vetiver and RPP hybrid system had more cost-to-performance ratio, making it a viable solution for large-scale slope protection projects. 2025-03-15T00:00:00Z