http://dspace.dtu.ac.in:8080/jspui/handle/123456789/46 2026-04-28T04:03:58Z 2026-04-28T04:03:58Z JAYANT, HARSHIT KUMAR http://dspace.dtu.ac.in:8080/jspui/handle/repository/22524 2025-12-29T08:45:57Z 2025-06-01T00:00:00Z

Title: CFD ANALYSIS OF HYDRAULIC JUMP UNDER VARYING CHANNEL CONDITIONS Authors: JAYANT, HARSHIT KUMAR Abstract: Hydraulic jumps are commonly observed phenomena in open channels, including rivers, canals, spillways, and weirs, where they serve a significant function in dissipating excess energy. The observed phenomenon is characterised by the interaction between a high-velocity water flow and a comparatively slower water flow, leading to an abrupt increase in water depth and the subsequent release of a substantial amount of energy. Hydraulic jumps are significant part of various hydraulic processes, as most often they are used not only as energy dissipation tool but also as tool for water aeration and, thus, as chemical mixing agents or as hydraulic jumpers which can lift water levels downstream. Consequently, much research has been conducted with a view of understanding and improving hydraulic jumps. Hydraulic jump type stilling basin came into knowledge to reduce a large amount of kinetic energy of the flowing fluid in the downstream of the hydraulic structure. This design feature is important in order to exclude the possibility of bed erosion and to achieve the rational use of protective aprons. Within these basins, the water's kinetic energy undergoes a process of transformation, resulting in the generation of turbulence. This turbulence, over time, is dissipated as both heat and sound energy. In order to accomplish this objective, stilling basins are outfitted with various components, including baffle blocks and chutes. Prior research has investigated the behaviour of hydraulic jumps over uneven surfaces in order to improve their characteristics downstream. The present investigation is oriented around examining the influence of different strip macroroughness shapes, their aspect ratios, and arrangements on the characteristics of hydraulic jumps using numerical simulation. This particular area of study has not been extensively explored in previous research activities. This computational study applied the Computation Fluid Dynamics (CFD), which allowed for an understanding of both types of hydraulic jumps, namely, free and viii submerged hydraulic jumps. Key characteristics, such as tail-water depth, sequent depth, jump length, roller length, velocity profiles, flow patterns within the cavity region, Turbulent kinetic energy (TKE), and energy loss are examined over both smooth and macrorough beds. CFD involves predicting fluid flow by solving mathematical equations through simulation. This study takes the advantage of Ansys Fluent software where Reynolds-averaged Navier-Stokes (RANS) equations and standard k-ε, re-normalization group (RNG) k-ε, realizable k-ε, and shear stress transport (SST) k-ω turbulence models are used to predict the mean flow characteristics in turbulent flows. The interface between two immiscible fluids is represented using Volume of Fluid (VOF) model. To ensure the accuracy of the numerical models, sensitivity analyses of the mesh and turbulence models are performed, and the results are compared with experimental findings for three channel conditions: smooth bed, triangular strip macrorough bed, and trapezoidal strip macrorough bed. Among the various turbulence models RNG k- ε model outperforms for predicting both free and submerged hydraulic jumps. Additionally, the standard deviation between the numerically derived results and experimental findings for basic hydraulic jump parameters, such as sequent depth ratio and tailwater depth ratio, is reported below 6%. These findings suggest that Ansys Fluent is a reliable tool for predicting complex phenomena like hydraulic jumps over smooth and rough beds. To numerically study the hydraulic jump phenomenon, it is crucial to optimize the combination of flow domain and boundary conditions to simulate real-world fluid flow phenomenon cost-effectively, a topic not fully addressed in previous research. In this regard, two approaches are tested for forming hydraulic jumps in a horizontal rectangular smooth channel numerically. The first approach considered the effect of a reservoir just upstream of the sluice gate, while the second approach ignored the reservoir entirely. The results indicated no significant differences in the hydraulic jump's flow behaviour between the two approaches. However, the second approach reduced computational time by up to 50% due to the smaller computational flow domain. ix Further investigations were conducted in a prismatic rectangular channel with strip macrorough elements on the downstream bed. Eight distinct macrorough shapes, namely triangular, rectangular, trapezoidal, semicircular, and four new non-regular shapes were compared for their effect on free and submerged hydraulic jump characteristics. It is reported that rough beds generally improve jump characteristics compared to smooth beds. While the shape of the macroroughness has a minor influence on jump characteristics, the triangular strip macrorough shape is the most effective in enhancing hydraulic jump characteristics. Given the effectiveness of the triangular strip macroroughness, further studies are carried out to explore how the height-to-base width ratio and height-to-wavelength ratio, as well as the arrangement of the strips, affected jump characteristics. The results indicated that varying the height-to-base width ratio does not significantly impact the jump characteristics. However, better energy dissipation is achieved in submerged hydraulic jumps by altering the arrangements of the macrorough elements. Additionally, increasing the spacing between consecutive macrorough elements or decreasing the height-to-wavelength ratio improved the jump characteristics. Overall, strip type macrorough beds are found effective in enhancing the jump characteristics and a well-designed model can improve the efficiency of hydraulic jump type stilling basins. Further, the numerical simulation technique is well able to predict the complex fluid flow phenomenon and can be beneficial in hydraulic designs.

2025-06-01T00:00:00Z DIKSHA http://dspace.dtu.ac.in:8080/jspui/handle/repository/22507 2025-12-29T08:44:19Z 2025-07-01T00:00:00Z

Title: STUDIES ON EFFECT OF GGBFS CONTENT ON THE PERFORMANCE OF GEOPOLYMER CONCRETE Authors: DIKSHA Abstract: Geopolymer concrete (GPC) is an innovative, sustainable, cementless, and eco-friendly material that significantly reduces carbon emissions by entirely replacing cement in concrete production. Cement manufacturing is a major contributor to CO₂ emissions, and GPC offers a viable alternative. In this experimental investigation, the fresh, chemical, and mechanical properties of GPC were evaluated across various parameters to determine the optimum mix design. The study examined fly ash-to-GGBFS (alccofine) ratios ranging from 100/0 to 75/25, liquid-to-binder (L/B) ratios from 0.35 to 0.65, superplasticizer contents from 0.5% to 2.0%, sodium hydroxide molarity from 8M to 14M, and sodium silicate-to-sodium hydroxide ratios from 0.5 to 3. Durability tests included exposure to seawater, magnesium sulfate (sulfate attack), acid attack, and wetting-drying conditions. Workability was assessed using slump and density tests, while mechanical properties were evaluated through compressive strength, splitting tensile strength, flexural strength, elastic modulus, and rebound hammer tests. Durability tests measured residual compressive strength, visual inspections, and density variations. The results revealed that oven-cured samples consistently outperformed ambient- cured samples, with the 75/25 fly ash-to-alccofine ratio achieving the highest engineering strength. The compressive strength peaked at an L/B ratio of 0.55, with strength increasing up to this point before declining randomly at higher ratios. A mix containing 1.5% superplasticizer and a 0.45 L/B ratio demonstrated superior strength compared to other combinations. Increasing the NaOH molarity up to 12M enhanced compressive strength, but strength declined beyond this point under both curing conditions. Similarly, strength improved with higher alkaline ratios, peaking at a ratio of 2, before decreasing. Mechanical strength also increased with curing temperature, reaching an optimum at 100°C, after which it began to decrease. Durability tests showed that seawater exposure initially increased strength and density but led to degradation after 12 weeks. Alccofine-based GPC exhibited better resistance to seawater and sulfate attacks compared to other compositions. Both types of specimens followed similar patterns of strength and mass loss under these conditions, with alccofine-based samples demonstrating superior stability. Under wetting-drying cycles, alccofine-based GPC also exhibited greater durability and resistance to degradation. For the final optimum values, the Advanced machine learning techniques, including Artificial Neural Networks (ANN), Gene Expression Programming (GEP), Support Vector Regression (SVR), Bi-LSTM, and Self-Improved Jelly Search Optimization (SIJSO), demonstrated significant v potential in predicting the mechanical properties of GPC. These methods offer powerful tools for optimizing mix designs and enhancing performance. This study underscores the potential of Alccofine as a high-performance supplementary material and highlights the role of advanced ML techniques in advancing sustainable construction practices.

2025-07-01T00:00:00Z BANSAL, VAISHNAVI http://dspace.dtu.ac.in:8080/jspui/handle/repository/22502 2025-12-29T08:43:51Z 2025-06-01T00:00:00Z

Title: SLOPE STABILITY ASSESSMENT IN KALIMPONG REGION OF DARJEELING HIMALAYAS Authors: BANSAL, VAISHNAVI Abstract: The Darjeeling Himalayas, particularly the Kalimpong region, experience frequent landslides due to a complex interplay of geological, hydrological, seismic, and anthropogenic factors. This research provides a comprehensive slope stability assessment of Kalimpong using a multidisciplinary approach that integrates geotechnical investigation, numerical modeling, and geospatial analysis. The study begins with a detailed review of the region’s geology, geomorphology, and historical landslide activity. Field investigations were conducted to collect soil and rock samples, and extensive laboratory tests were performed to determine key geotechnical parameters such as cohesion, internal friction angle, unit weight, and permeability. Using these inputs, slope stability was evaluated through GeoStudio SLOPE/W software, applying the Morgenstern-Price method under various conditions—static and dynamic, dry and saturated. The results revealed that many natural slopes in Kalimpong are marginally stable under dry conditions but exhibit critical instability when subjected to rainfall infiltration and seismic forces. The Factor of safety (FOS) significantly dropped below 1.0 for several slopes under dynamic-saturated scenarios, indicating a high probability of failure. Furthermore, stabilization strategies such as soil nailing were modelled and validated in SLOPE/W, showing significant improvements in FOS values and thus enhancing slope resilience. To complement the site-specific analyses, the study incorporated GIS-based landslide susceptibility mapping using the Frequency ratio (FR) model. Geospatial layers representing conditioning factors—including slope angle, aspect, elevation, lithology, proximity to roads and faults, and rainfall intensity—were developed using Shuttle Radar Topography Mission (SRTM) Digital Elevation model (DEM) and remote sensing data. The FR model quantified the correlation between historical landslide events and each parameter, producing a susceptibility zonation map that classified the region into low, moderate, and high-risk zones. Approximately 38% of the study area fell into vi moderate-to-high susceptibility classes, aligning with known landslide-prone corridors and anthropogenic ally disturbed slopes. This dual approach—merging deterministic Limit Equilibrium method (LEM) based modelling with probabilistic geospatial assessment—allowed for both micro and macro-scale understanding of slope instability in the region. The study also outlines policy recommendations, emphasizing the integration of slope stability analysis in infrastructure planning, particularly in seismic zones and monsoon-affected terrains. Overall, the thesis delivers a robust framework for landslide hazard mitigation in the Kalimpong region and sets the foundation for future research incorporating machine learning models, real-time monitoring, and climate change projections for improved early warning and slope management strategies.

2025-06-01T00:00:00Z KALRA, MANOJ KUMAR http://dspace.dtu.ac.in:8080/jspui/handle/repository/22189 2025-09-02T06:40:54Z 2025-06-01T00:00:00Z

Title: INVESTIGATION OF RUT PATTERNS IN DIFFERENT TERRAIN CONDITIONS FOR VEHICULAR MOVEMENTS Authors: KALRA, MANOJ KUMAR Abstract: The movement of vehicles on an unpaved terrain is a common requirement in many fields including agriculture, forestry, automobile, planetary rovers and defence. Other than surface topographical features, the most important parameter to the movement of vehicles is the underlying soil condition. Acquiring the data by conventional methods is laborious and cumbersome task. The alternative means have therefore been explored by various researchers. One of the most effective ways employed for anlysing the prevalent soil condition is by monitoring the rut formed by vehicular movement in the area. Many soil parameters like soil condition, its gradation, moisture content, soil strength etc. impact the vehicular rut. Vehicle loading conditions like tyre size, vehicle weight, its speed, curvatures, and repeated passes also influence the rut shapes. Although many parametric studies have been conducted to characterize and model the rut shapes based on all these, yet several aspects are still to be studied. One aspect of the issues pertains to modelling and evaluation of rut depth. Most of the literature focuses on evaluating the rut depth. Certain issues are however typical in different scenarios which need to be addressed. The rut in desertic terrain has been observed to get filled by the sand pouring from sides. Similarly, the rut profile has been observed to become eccentric on the curves. This aspect demands for mapping the shapes of rut profiles in different terrain-vehicle running conditions. Moreover, with advent of technology, the rut profile measurement tools too have moved from manual to advanced laser-based sensors. The laser profiler on one hand measures the rut profile with precision, however, it needs heavy memory devices for storage and interpretation of data. The optimization aspect of rut profile data needs to be explored for efficient movement decisions. Further, a number of models are developed that try to characterize the influence of different causative factors on rut. While selection of appropriate model is one aspect, the overall impact of all causative factors on the maximum soil distress levels in any area is important to be studied for ascertaining the suitability of the terrain for any emergency movement. Another aspect of rutting research pertains to addressing the issues in wider spatial domain. While evolving suitable spatial models governing trafficability potential is an important aspect, the validation of interpreted information is another important area needing attention. Here, identification of track impressions that look like edges in coarse resolution images can provide useful information about identifying the trafficable zones. Identifying the tracks manually being tedious, alternate means need to be explored. Moreover, the rut tracks formed by the leading vehicle is said to provide useful information for the rut following robotic vehicles, v defence, and forestry. The delineation of track impressions form surrounding terrain and visibility conditions is an important consideration needing attention. In this research work, rut has been investigated from different perspectives. One aspect focuses on the experimental studies of rut profiles in different fields while the other one tries to address the issue of delineation of rut tracks by collating various image processing techniques. In the field based experimental studies, various shapes of rut profiles on different types of soil and vehicle running conditions were investigated. The rut profile data was captured using both manual and laser-based systems. The most common rut shapes observed in field are identified and grouped in different categories. Attempt was then made to devise better ways for optimal storage of most common rut profiles. By using the proposed mathematical formulations, an additional compression of more than 80% over the conventional compression techniques could be achieved on straight patches and 71% on turnings. In another experimental study, soil distress level was investigated using multiple vehicular passes on varied terrain conditions. This study paves the way for identifying and mapping the unpaved areas suitable for planning emergency support. Another part of study focused on visual enhancement and detection of rut-based track impressions. In order to detect edges like track features in satellite images, various edge detection algorithms are explored. The comparative study of different algorithms revealed that the Canny Edge detection method gives relatively better results. Further studies are however needed for improved detection and delineation of tracks. It is observed that the tracks formed by vehicular rut impressions appear like thin edges in images of coarse-resolution. However, when using the fine resolution images, the same features appear like elongated areas. In such a scenario, the edge detection filters and even the conventional contrast enhancement techniques are able to delineate these features to a limited extant. The role of texture of these tracks that can differentiate these tracks from their surroundings has been explored in this study. Gray level co-occurrence matrix (GLCM) which is a texture measurement technique has been employed here. To compare the effectiveness of various techniques in enhancement of track contrast in a given surrounding, a new quantitative track index (TI) based measure has been proposed in this study. Here, the effectiveness of technique in enhancing the track contrast has been evaluated. Various forms of track indices as proposed in this study have been compared. The proposed track index effectively sorts correctly the contrast images to the level of 88%. The proposed track index-based technique is seen as effective means for sorting the images based on track contrast. This method can bring in improved fidelity of decisions for the sustainable operations. The study was extended further and a new technique based on track index has been developed that is seen as adaptive for enhancing the track contrast in a given surrounding. The outcome of above research has been presented in various chapters of this thesis. The approach of bringing in optimization in data storage is a step towards making efficient decisions about trafficability condition of the terrain. The evaluation of maximum soil distress level under different dynamic conditions sets another way of identifying and mapping the safe trafficable zones for planning emergency vi movement. The image analysis-based improved identification of rut tracks is an important contribution in visual analytics-based systems on-board vehicles. The mobility decisions could be made better and efficient using this track index based technique. The edge detection algorithm could set the way for improved identification of unpaved tracks in satellite images. Further research is however needed for automated delineation of rut tracks for inferring trafficable zones. The machine learning approach could be explored here.

2025-06-01T00:00:00Z