Post graduate dissertations (Theses) of Department of Civil Engineering (CE) http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/48 2026-05-24T01:51:36Z 2026-05-24T01:51:36Z Kaysaru Zaman Kawshiq, A S M. http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7324 2026-05-19T04:04:18Z 2025-03-15T00:00:00Z

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 Shahin Kadir, Md. http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7318 2026-05-19T03:06:51Z 2024-06-29T00:00:00Z

Development of cementitious grout and semi-rigid asphalt mix to improve semi-rigid pavement characteristics Hossain, Dr. Moazzem; Shahin Kadir, Md.; 1015042413; 625.85/SHA/2024 This study is aimed at improving semi-rigid asphalt mix properties through development of suitable cementitious grout mix composition and appropriate porous asphalt mix skeleton impregnated with the developed grout. The methodology for the study involves carrying out mechanical tests to evaluate the influence and effects of fluidity and compressive strength of cementitious grout on semi-rigid asphalt mix. Four types of cement grout mixtures are experimented with varying mix proportions of cement, chemical admixtures, including accelerating and retarding agents. Laboratory tests are carried out to measure properties such as porosity, flexural strength, and Marshall stability for the semi-rigid pavement specimens. Trial mixes are also tested for their workability and compressive strength, with workability determined by measuring flowability. Additionally, a porous asphalt skeleton is developed to be impregnated with developed cementitious grout to improve the durability and strength of the asphalt mix, to be known as semi-rigid asphalt mix. The experimental investigation of Marshall Mix Design, volumetric and stability properties is carried out using Marshall samples and the same of flexural strength using rectangular section beam are conducted in the laboratory. The stability of Densely Graded (average 20 kN) and semi-rigid asphalt sample (average 35 kN) is explored; results indicating an increase in resistance to deformation with higher stability values for semi-rigid mix. Asphalt mix may be considered sound in moisture resistance with tensile strength ratios (TSR) value above 0.8; in present study, semi-rigid mix has shown higher TSR (93%), suggesting better moisture resistance and resilience while Densely Graded Asphalt has just meet 0.8 criteria. Semi-rigid mix exhibit higher flexural loads and modulus of rupture values compared to Densely Graded Asphalt mix (about 176% increase), indicating improved strength and rigidity. Results from present study show potential of suggested semi rigid asphalt mix to be used for pavements in tropical climate carrying high volume of heavy traffic as found in Bangladeshi highways’ condition.

2024-06-29T00:00:00Z Fayjul Bari, Md. http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7314 2026-05-04T03:57:22Z 2025-03-15T00:00:00Z

Geotechnical characterization and stability of embankment at selected floodplain areas Ansary, Dr. Mehedi Ahmed; Fayjul Bari, Md.; 0417042203; 624.162/FAY/2025 Embankments can significantly shield people, farms, and livestock from flooding during floods. Embankment stability analysis is necessary to evaluate structural integrity and prevent flood-induced failures because of its high susceptibility to flooding. This study aims to evaluate the geotechnical stability of the existing embankments at specific floodplain locations. For this study, the Ganges-Padma (Noria and Rajbari) and Brahmaputra-Jamuna (Jamalpur) River systems, three of Bangladesh's most flood-prone river regions, have been chosen. SPT and ERT assessments have been conducted, and soil samples are collected from each embankment location. In the laboratory, various geotechnical parameters have been analyzed, including wash sieve analysis, hydrometer tests, liquid limit tests, direct shear tests, one-dimensional consolidation tests, and UU tri-axial tests. One of the main goals is to correlate the resistivity results from the ERT with the data from the boring logs, which has enhanced the accuracy of subsurface characterization and given a comprehensive understanding of soil strata. In this study, a non-homogeneous embankment section with an impermeable foundation modeled in Geo-Studio has been successfully verified for validation purposes using GEO5 2D. Later, the GEO5 program has been used to simulate the existing embankments numerically. The slope stability analysis using GEO5 software has been carried out to evaluate the factor of safety (FoS) under different water levels, rapid drawdown, and surcharge conditions. Under various surcharges, the embankment shows a critical instability, posing a high risk of failure. The lowest factor of safety (FoS) has been observed in steep slopes, while flatter slopes demonstrated higher stability. For every study location, the impact of severe flood-induced seepage is also examined by assuming the water level on the riverbank at 1.5 m lower than the crest level. In the Jamalpur study area, the results of the slope stability analysis indicate that an increase in water level leads to a decrease in the factor of safety, whereas a decrease in water level causes the factor of safety to increase. For different analyses methods, the FoS vary from 4.04 to 14.91 for a normal water table of 10 m. Rapid drawdown conditions also have an impact on the factor of safety. When the groundwater table (GWT) is 10 meters and the original water table (OWT) is 17 meters, the FoS vary from 1.59 to 16.9. In a similar way, the findings indicate that the factor of safety decreases with increasing surcharge and increases with decreasing surcharge. The Bishop method shows a peak factor of safety of 11.46 for a circular slip surface with no surcharge, whereas the Janbu method shows the lowest factor of safety of 1.1 for a polygonal slip surface under the maximum surcharge of 150 kN/m2. According to the seepage analysis, pore water pressure increases at a rate that is parallel to the water level; additionally, the pore water pressure decreases when the water height falls. The lowest measured pore water pressure is 265.3 kPa at a reduced water height of 7 meters, while the highest recorded pore water pressure is around 416.9 kPa at an 18-meter water height. The seepage investigation also demonstrates that suction rises with rising water levels. Conversely, a low water level results in high suction. Suction values are -96.07 kPa at an 18-meter water height and -183.4 kPa at a low water level of 7 meters. It has been found that the amount of point inflow or outflow increases as the water level rises. The inflow and outflow are maximum at 30.92 m3/m/day when the water level is 18 meters, and they are lowest at 1.86 m3/m/day when the water level is 7 meters. The results of the slope stability analysis in the Rajbari study area show that the FoS fluctuates as the water level changes. Based on the stability analysis results, the Janbu method provides the lowest factor of safety (FoS) of 1.44 for a polygonal slip surface at a high water level of 10.5 m, while the Sarma method yields the maximum FoS of 3.27 for a normal water table of 5 m. According to the stability analysis for rapid drawdown conditions, when the groundwater table (GWT) is 3 meters and the original water table (OWT) is 7.7 meters, the highest factor of safety (FoS) for polygonal slip surfaces is 2.94 for Sarma method, while the lowest FoS for polygonal slip surfaces is 1.37 for Janbu method. As the surcharge decreases, the stability study results show that the FoS increases. A polygonal slip surface under a maximum surcharge of 150 kN/m2 provides a minimum FoS of 0.99 for Janbu method, but a polygonal slip surface without a surcharge has a maximum FoS of 9.56 for Sarma method. According to the seepage analysis, as the water level rises, the rate of pore water pressure also rises. The pore water pressure reaches its maximum of approximately 381 kPa at a water height of 8 meters, while the lowest is 304.6 kPa at a low water height of 1 meter. The seepage research also shows that as water levels rise, suction falls. It has been observed that the suction value is -116.54 kPa at a low water level of 5 meters and -55.8 kPa at an 8-meter water height. When the water level is 10 meters, the inflow/outflow is high at 2.17 m3/m/day; when the water level is 1 meter, it is 0.06 m3/m/day. In the Shariatpur study area (Noria), a river bank stability analysis has been carried out. There are no embankments in this area. Therefore, a riverbank slope and an apparent surcharge of 30 and 60 kN/m2 are considered for the stability analysis. The findings of the stability analysis demonstrate that the Bishop method provides a maximum FoS of 6.49 for a circular slip surface without surcharge, whereas a minimum FoS of 2.15 under a polygonal slip surface subjected to the maximum surcharge of 60 kN/m2 for Janbu method. It has also been shown that for a normal water table of 2 m, the Spencer method for a circular slip surface provides the maximum FoS at 5.69 for the water level variation. In contrast, a polygonal slip surface at a high water table of 3.5 m yields a FoS of 1.77 using the Morgenstern-Price method. For rapid drawdown conditions, when the groundwater table (GWT) is at -2 meters and the original water table (OWT) is at 3.5 meters, the stability analysis indicates that the highest FoS for the polygonal slip surfaces using the Morgenstern-Price method is 3.99, whereas the lowest FoS using the Janbu method is 1.77 for circular slip surfaces. The seepage analysis results have shown that the pore water pressure increases with the water level. At a minimum water level of -3 meters, the pore water pressure measures 177.5 kPa, while at a maximum water level of 3.5 meters, the pore water pressure reaches approximately 261.10 kPa. It also reveals that the suction value is -49.77 kPa at a water height of 3.5 meters and -99.51 kPa at a low water level of -3 meters. It has been demonstrated that the amount of point inflow or outflow increases as the water level rises. When the water level is 3.5 meters, the inflow/outflow is high at 4.68 m3/m/day, and when the level is -3 meters, it is 0.13 m3/m/day. The results of the seepage analysis have shown that the seepage velocity and water pressure have a major impact on the slope stability. The findings of the numerical study demonstrate that the high water levels substantially affect seepage conditions, which may cause failure during floods. Although field tests, laboratory investigations, and numerical studies can identify potential risks and failure processes, these studies clearly cannot offer total confidence regarding the long-term stability of an embankment. To ensure the stability of an embankment, steps to lessen the effects of floods, such as better drainage systems, better embankment designs, early warning systems, frequent monitoring, proper geotechnical assessment methods, and improved disaster mitigation planning for Bangladesh's flood-prone areas are needed.

2025-03-15T00:00:00Z Nadia Binte Mohammad http://lib.buet.ac.bd;localhosthttp://:8080/xmlui/handle/123456789/7234 2026-01-06T04:04:03Z 2025-06-14T00:00:00Z

Predicting cargo throughput at the Chittagong port using time series data Shamsul Hoque, Dr. Md.; Nadia Binte Mohammad; 0422042401; 626.82450954923/NAD/2025 Accurate forecasting of port cargo throughput is critical for efficient logistics and strategic planning in global trade networks. This thesis presents an integrative study that employs multiple state-of-the-art forecasting methods both in univariate and multivariate settings to forecast total cargo volume at the Chittagong Port of Bangladesh. The methods include Long Short-Term Memory (LSTM) networks, Vector Autoregression (VAR), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Transformer-based models to predict total cargo volume at Chittagong Port, Bangladesh. In addition, the research incorporates key economic indicator which is Gross Domestic Product (GDP) of Bangladesh, Export Cargo Volume and Import Cargo Volume as variables in a multivariate forecasting framework. An innovative component of this study is the incorporation of chaos theory to analyze the intrinsic nonlinear dynamics and sensitivity to initial conditions of the cargo throughput time series. To uncover the underlying data dynamics, chaos theory is applied. By calculating Lyapunov exponents, Hurst Exponent and Entropy analysis, this thesis characterizes the degree of chaos, randomness, and complexity within the cargo throughput series. These non-linear analytical methods also provide an insight into the time frame of our data in terms of forecasting ability. This analysis provides critical insights into the stability and predictability of the system, further guiding model selection and parameter tuning. Moreover, the presence of chaotic behavior justifies the use of deep learning models like LSTM and Transformer, which are more tailored to capturing nonlinearity within the time series compared to traditional ARIMA methods. This research commenced with a thorough exploratory dive into the monthly cargo statistics from Chittagong Port. Initial assessments, drawing upon foundational concepts of chaos theory, indicated that the cargo volume time series is not merely linear but instead displays moderately intricate dynamics. These dynamics are characterized by seasonal fluctuations, shifts and trends, and behaviors strongly suggestive of chaotic processes. Given these inherent complexities, the data clearly call for more sophisticated modeling approaches, as conventional linear methods would likely prove inadequate for capturing such nuanced patterns. To address these challenges, we proposed a hybrid forecasting method incorporating a sophisticated signal processing technique named Discrete Wavelet Transformer (DWT) and two deep learning models- Long Short Term Memory (LSTM) networks and another one is Transformer Network. Multiple settings were used in this research for forecasting. A univariate forecasting framework using individual models (ARIMA, LSTM) to predict cargo volume solely based on its historical values. Concurrently, a multivariate approach is implemented using the VAR model, LSTM model with external economic inputs (GDP, export, and import data). Then finally the hybrid model is introduced to the data for univariate settings. The focus of this thesis is to identify the adaptability of a hybrid forecasting method which DWT-LSTM and DWT-Transformer method, commonly known as Wavenet, which is the most recent analytical method invented. Also, this dual strategy allows for an assessment of model performance in isolated versus integrated settings with various other forecasting models. Moreover, all the models also help identify the additional predictive power of economic indicators. In evaluating the performance of the various models, several metrics are employed, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE). These criteria not only quantify forecast accuracy but also facilitate the comparative analysis between univariate and multivariate configurations. The results show that the forecasting accuracy is the highest for DWT-LSTM (a MAPE value of 5.41%) followed by multivariate LSTM (a MAPE value of 6.32%), DWT- Transformer (a MAPE value of 7.01%), ARIMA (8.88%), univariate LSTM (11.19%) and finally VAR (11.97%). The results consistently through other metrices show that, while traditional ARIMA models provide a baseline level of accuracy, advanced models, particularly the hybrid LSTM approach, offer superior performance over all other models in capturing both long-term trends and short-term fluctuations. The findings from this research offer some meaningful takeaways for port authorities and logistics planners. When forecasting is more accurate, it becomes easier to manage resources, schedule operations, and respond to demand shifts without unnecessary delays or bottlenecks. One particularly interesting insight is the presence of chaotic patterns in the cargo data. This suggests that the system is not just noisy or random rather it may actually follow a complex but deterministic path, which means sudden shifts could happen even when things seem stable. That kind of behavior makes a strong case for using adaptive strategies in port management, especially in environments as unpredictable as global trade. From an academic perspective, this study shows how blending machine learning techniques with tools from chaos theory can open up new ways of modeling complex logistics systems. Comparing univariate and multivariate models revealed that hybrid setups especially when paired with wavelet decomposition can capture more nuance and deliver better forecasts. Adding macroeconomic indicators like GDP, import, and export values added another layer of depth, helping to explain some of the broader trends behind cargo movements. And the chaos analysis, though more abstract, offered a deeper look into the structural behavior of the system over time. In short, this thesis tries to bridge the gap between technical modeling and real-world application. It not only contributes to ongoing research in forecasting methods but also provides actionable insights that could genuinely help improve how ports operate in uncertain and dynamic conditions.

2025-06-14T00:00:00Z