Journal of Engineering and Sciences <p><strong>Journal of Engineering and Sciences</strong>, the official journal of the Research Management Cell (RMC), IOE Pashchimanchal Campus, Pokhara is devoted exclusively to science and technology advancements, especially on the innovative aspects of the multifaceted disciplines in engineering and sciences.</p> en-US <p>CC BY: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.</p> (Krishna Raj Adhikari) (Sioux Cumming) Tue, 04 Jun 2024 00:00:00 +0000 OJS 60 Enhancement in Anticancer Activity of Chitosan Tailored Imidazole-2-Thiosemicarbazones against MCF-7 Cancer Cell Line by Coordination with Copper(II) Ions <p>The coordination behavior of new batch synthesized chitosan imidazole-2-thiosemicarbazones tailored from both the low molecular weight commercial chitosan and high molecular weight crab shell chitosan was confirmed by Fourier Transform Infrared (FT-IR) and magnetic susceptibility measurements. Chlorine content in the complexes was estimated by potentiometric titration technique. The study showed the tridentate NNS tridentate coordination with copper (II) ion in a square planar orientation with the remaining valence satisfied by coordination with chloride ion. The MTT assay studies showed an enhancement in the anticancer activity of these chitosan thiosemicarbazone ligands upon their coordination with copper (II) ions against the human breast cancer (MCF-7) cell line <em>in vitro</em>. The minimal cytotoxicity of both the ligands and complexes against the normal mouse embryonic fibroblast (NIH3T3) cells revealed the selective attraction of these biomaterial chitosan derivatives towards the cancer cells with non-toxicity to healthy cells. There was only a marginal effect of molecular weight (M<sub>w</sub>) and degree of deacetylation (DDA) of chitosan upon the anticancer activity of these chitosan derivatives.</p> Hari Sharan Adhikari Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Sustainability Analysis of Community-Managed Rural Water Supply Project: A Case Study of Kaski District <p>After the 1992 International Conference on Water and the Environment in Dublin, a new approach to rural water supply was adopted being that the water should be managed at the lowest appropriate level, with users involved in the planning and implementation of projects. As per the data of DWSSM (2019) even though the basic level water supply coverage of Nepal is 87.22% among the water supply schemes providing service to the people only 28.13% of the schemes are fully functional. The lack of functionality questions the investment of different agencies as projects do not operate throughout project life and the public are facing the problem of not getting safe and reliable water. The main aim of this study was to assess the post-construction status of these projects in relation to their sustainable management. For this, six water supply projects completed over the last five years have been studied. During the study, the data was collected from the structured questionnaire, focal group discussion, Key informants’ interviews and field observations. These water supply projects were evaluated based on five main criteria namely economic, technical, social, institutional, and environmental factors. From the study it is observed that the sustainability score of Syaude Lifting WSP is 62.82%, Serokhola WSP is 66.74%, Lumre WSP is 64.25%, Sudame WSP is 54.97%, Bhachok WSP is 63.74% and Chisapani WSP is 76.90%. The economic and technical aspect of sustainability is found poor in all of these water supply projects. The major problem faced by the community is the lack of financial resources and technical capacity-building programs in the construction stage which have ultimately hampered the project's sustainability. Post-construction training, technical and capacity-building training, support policies and programs are important requirements for the sustainable development of rural water supply systems.</p> Abhinaya Poudel, Sundar Adhikari Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Multi-Directional Wind Turbine with Combined Savonius and Darrieus Rotors: A Comparative Performance Analysis <p>This study presents a comprehensive investigation into five distinct combinations of wind turbine configurations, each integrating Savonius and Darrieus rotors on a single shaft. The studied configurations include Single Stage Savonius and H-Darrieus, Two-Stage Savonius and D-Darrieus, Two-Stage Savonius and H-Darrieus, Helical Darrieus and Two-Stage Savonius, and Two-Stage Savonius and H-Darrieus in series. Our research uses Computational Fluid Dynamics (CFD) simulations conducted using ANSYS Fluent to meticulously analyze and optimize these turbine designs. Through rigorous computational modeling and flow analysis, we aim to elucidate the performance characteristics, including torque generation, torque nature, flow time, and power output, for each configuration. Following thorough comparison, our findings highlight the double-stage Savonius and D Darrieus turbine as exhibiting superior performance attributes. This research contributes valuable insights into the advancement of multi-directional wind turbine technology, facilitating enhanced energy harnessing from varying wind conditions.</p> Swarnim Duwadi, Pawan Khanal, Abhishek Pandey Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Urban Roadside Flooding Analysis Using SWMM: A Case Study of a Road Section in Pokhara Metropolitan City, Nepal <p>Pokhara City, in Nepal, experiences heavy rainfall during four months of monsoon, causing stress on drainage infrastructures. This situation is exacerbated by poor drainage systems, ineffective urban planning, and rapid urbanization. This study aims to develop mitigation strategies for urban roadside flooding in the Barahi Chowk region in Pokhara City. The focus is to identify the causes and potential solutions for the recurring issue of urban roadside flooding. For this purpose, the study utilizes Storm Water Management Model (SWMM) computer modeling to analyze the hydraulic capacity of existing drainage systems during peak flows. The SWMM modeling reveals that the current drainage usage is between 80% and 100% during peak times, leading to flooding. Consequently, resizing or expanding various drainage sections using SWMM modeling is suggested. The study introduces Low Impact Development (LID) controls, such as rain gardens and permeable pavements, to manage surface runoff. Implementing rain gardens on just 3% of the impervious area in each sub-catchment showed an average 21.5% reduction in peak runoff and an average 6.68% reduction in the total runoff while implementing 5% in each sub-catchment, permeable pavements reduced peak runoff by 22-26% and total runoff by 8-11%. The research explores the impact of land use and land cover change and unplanned urban growth on roadside flooding, resulting in impermeable urban surfaces that disturb the natural drainage system and infiltration pattern. Thus, the outcomes of this study should be carefully considered by policymakers and stakeholders to address issues through sustainable urban planning and infrastructure development. Also, implementing measures like resizing drains and LID controls appears to be effective in controlling flooding during the study period and should be considered for future studies as well.</p> Aavas Jung Shahi, Madan Pokhrel, Shankar Lamichhane Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Machine Learning-Based Social Media Review Analysis for Recommending Tourist Spots <p>In recent years, the tourism industry has witnessed significant growth, resulting in an increased demand for effective and personalized tourist place recommendation systems. In this study, a tourist spot recommendation system is proposed which is built by developing a machine learning model based on a Support Vector Machine (SVM), Decision Tree (DT), and k-Nearest Neighbors(k-NN). Public experiences and opinions regarding the various spots available in popular social media sites such as TripAdvisor, Google, Instagram, and TikTok are utilized to train the model. The system matches the probability of the user query with the predicted probability of reviews for a particular spot. The SVM algorithm, known for its robustness in handling high-dimensional data, is adapted to model the complex relationships between users' reviews, spots, and their attributes. Real-world data is used to evaluate the system's performance, demonstrating its ability to significantly improve the user experience and contribute to the sustainable growth of the tourism sector. The system's capability was demonstrated as it achieved a notable F1-Score of 0.78 when SVM was implemented. Additionally, a promising accuracy rate of 93.023% was observed when random queries were used for tourism spot prediction, emphasizing that SVM outperformed DT and k-NN.</p> Prakash Lahagun, Bidur Devkota, Sakchham Giri, Parbat Budha Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Analysis of Land Deformation using Small Baseline Subset (SBAS) INSAR Technique in Pokhara, Nepal <p>Pokhara Valley lies in the geographic region rich in karst and the increase in urbanization with natural processes like sinkholes has led to the deformation of land causing socio-economic and physical effects on the people and the geography. Likewise, minimal research using the InSAR approach has been done in the context of the Pokhara Valley. So, this study focuses on the determination of land deformation in Pokhara Metropolitan from 2017 to 2022 using the SBAS technique. Sentinel 1A SLC images were adopted using ascending data acquisition mode. The result shows a cumulative displacement of 1578.97 mm to -1052.65 mm in ascending mode. For validation, SBAS-generated data points of the WRC regions were validated with GNSS value. The Pearson R value was found significant at a 5% significance level and the RMSD value was between 0.8 to 1.73. Thus, the results and the validation process indicate the suitability of SBAS for the determination of land displacement using SBAS.</p> Pramod Devkota, Netra Bahadur Katuwal Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Concrete Compressive Strength Prediction by Ensemble Machine Learning Approach <p>The prediction of concrete compressive strength is a crucial aspect of ensuring the structural integrity and durability of construction projects. In recent years, machine learning approaches have improved upon the limitations of empirical formulas and laboratory testing methods for predicting concrete compressive strength. This study utilizes ensemble machine-learning techniques, such as Bagging, XGBoost, and Stacking models, to enhance the accuracy of concrete compressive strength prediction models. A five-fold cross-validation technique was applied to mitigate the problems of underfitting or overfitting in the regression model. Furthermore, various statistical indices were employed to compare the forecasting performance of these ensemble techniques. The prediction performance of this research revealed that XGBoost achieved the highest R-squared value of 93%, followed by Stacking and Bagging regression models at 92%. Consequently, this research underscores the potential of ensemble techniques as valuable tools in the domain of civil engineering, paving the way for more reliable and efficient construction practices.</p> Jyoti Thapa Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Applying machine learning algorithms to estimate PM 2.5 using satellite data and metrological data <p>Air pollution, particularly fine Particulate Matter (PM 2.5), poses significant health risks and environmental challenges worldwide. Therefore, it is essential to monitor air pollution to act on it. In this study, PM 2.5 was estimated using meteorological data and Sentinel-5P air pollution data using machine learning algorithms. The Sentinel-5P data are &nbsp;&nbsp;and the meteorological data utilized are air temperature, Relative Humidity (RH), and Wind Speed (WS).&nbsp;The three Air Quality Monitoring (AQM) stations in Kathmandu, Nepal, were chosen as a study area for this research. The effectiveness of several machine learning methods, such as K-Nearest Neighbors (KNN), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Random Forest (RF), were evaluated. Both RF and XGBoost consistently performed better than SVM and KNN in terms of PM 2.5 estimation accuracy. RF got the highest R<sup>2</sup> value of 0.80 and SVM with the lowest R<sup>2 </sup>value of 0.62 in the Sentinel-5P dataset only. The addition of meteorological data further improved the model's performance. After including metrological data in Sentinel-5P data the RF demonstrated the maximum R<sup>2</sup> score of 0.816 and XGBoost with R<sup>2</sup> score of 0.814. Hence, this study demonstrated machine learning algorithms can be used to estimate PM 2.5 by utilizing satellite and meteorological data, providing important information for air quality monitoring and management.</p> Ishwor Thapa, Bidur Devkota Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Comparative Study on Efficiency Analysis of Fixed and Dual-Axis Solar Tracking System <p>Solar energy is a crucial renewable energy source, offering sustainable solutions to address energy demands and combat climate change. Maximizing the efficiency of solar energy harvesting is essential for widespread adoption and integration into the energy landscape. Solar tracking systems play an important role in increasing the efficiency of solar panels by optimizing their orientation towards the sun throughout the day. This research presents a comparative analysis of the efficiency of dual-axis solar tracking systems using Light-Dependent Resistors (LDRs) as input devices. A closed-loop tracking technique is implemented to adjust the position of the solar panels based on real-time sensor feedback. A comparative study between LDRs demonstrates their effectiveness in detecting the sun's position, despite limitations such as susceptibility to ambient light conditions and saturation to light intensity. Through experimental evaluation and data analysis, this study provides valuable insights into the power output and assessment of efficiency variation of dual-axis solar tracking systems offering applications for optimizing solar energy harvesting in practical scenarios.</p> Ajay Oli, Saugat Sharma, Pratham Adhikari, Deepak Neupane, Santosh Khanal, Shacheendra Kishor Labh Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Study of Two-wheel Vehicle’s fuel consumption under the Influence of tire Inflation Pressure <p>The value of air pressure in the tire not only supports the entire weight of the vehicle, it also plays a crucial role in improving the vehicle’s performance, reducing friction, providing comfort, boosting economy and enhancing safety. This study deals with the influence of tire inflation pressure on fuel consumption at various road conditions and speeds. The experimental test was performed riding a motorcycle of 180cc and using a mileage measuring kit to find the effect of tire pressure on three different road surfaces i.e., highway, earthen and graveled. The standard tire pressure for both front and rear tires recommended by the manufacturing company was also evaluated to observe the change in mileage. The results showed that the highest mileage of 55.97 km/L was obtained on the highway among the defined three road conditions and a linear drop of 5psi in tire pressure led to loss of mileage up to 6.11% in highway, 5.35% in earthen and 2.80% in graveled road. Also, the variation in speed resulted to compensation of mileage by nearly 39.9% maximum. These results highlight the importance of keeping the correct value of tire inflation pressure in relation to fuel consumption.</p> Samir Ali Roy Bhat, Shraddha Bhandari, Durga Bastakoti Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Computational Evaluation of Pulsating Heat Pipe for Fluid Flow Behavior and its Thermal Performance <p>Computational fluid analysis of a single circuit heat pipe was undertaken to ascertain the thermal efficiency of water at various fill ratios, specifically 40%, 50%, and 60% under varying heating conditions. The analysis employed the ANSYS Fluent computational fluid dynamics software, utilizing a k-epsilon to the heat pipe as the solver. The analysis was carried out on a copper tube with an internal diameter measuring 3/16 inches. During the analysis, the thermal inflow at the adiabatic region was adjusted to zero, while the condenser region’s temperature remained constant at 25°C. Meanwhile, the heat input at the evaporator region was systematically adjusted to 105°C, 110°C, 115°C, and 120°C. Key Performance characteristics of heat pipe i.e. thermal resistance, and water volume fraction were evaluated during analysis. The temperature variations noted in both regions affirmed that the pulsating pipe’s performance was influenced by the phase transition between liquid and vapor. Furthermore, the concentration of volume within the evaporator section was monitored, confirming the presence of a dual-phase phenomenon within the heat pipe. Through the analysis, it was noted that the thermal resistance of the water is minimized at a 50% fill ratio for each level of heat input. Notably, the promising results were obtained at an input temperature of 120°C with a value of 1.025°C /W which was 7.3% and 9.8% lower than thermal resistance at 40% and 60% fill ratios, respectively. The reduced thermal resistance in this scenario is attributed to the flow dynamics within the capillary, propelled by rapid phase change mechanisms. This shows the importance of Pulsating Heat Pipes (PHPs) in thermal control, as well as the intricacies of their operating mechanisms. Experimental and theoretical investigations have investigated numerous elements influencing PHP performance, with numerical modeling providing insight into thermal resistance and water volume fraction dynamics under varying heating temperatures and fill ratios.</p> Prakash Badu, Kushal Guragain, Durga Bastakoti Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Mitigation of Harmonics Due to Electric Vehicle Charging <p>The increasing adoption of electric vehicles (EVs) has led to an increase in demand for charging infrastructure. However, EV charging can introduce harmonic distortion into the electrical distribution network, causing power losses, reduced efficiency, and equipment damage. This project developed an EV charging system with harmonic reduction to ensure a stable and efficient charging process. The research methodology allowed the team to develop an EV charging system with harmonic reduction that was effective in reducing the total harmonic distortion (THD) level from 56.3% to 1%. The system was also found to be stable and efficient during charging. The findings of this project have the potential to make a significant contribution to the development of EV charging infrastructure. The proposed system can help to mitigate the negative impacts of EV charging on the electrical distribution network, while also ensuring a stable and efficient charging process.</p> Rasik Neupane, Sunil Thapa Magar, Manish Pandey, Abhishek Simkhada, Bhrigu Raj Bhattarai Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Stability Challenges and Remedial Practices in Himalayan Hydro-power Tunnels – A Review <p>The instability in tunnels is mainly affected by geological anomalies, rock mass quality, complex geological structures, active tectonics, and stress anisotropy. This review article presents challenges associated with stability and applied remedial measures prevailing in hydropower tunnels in the Himalayas. The review covers nine hydropower tunnels located in different parts of the Himalayas. The review found that rock bursting/spalling frequently occurs when the tunnel passes through a high overburden with good rock mass quality. On the other hand, plastic deformation (squeezing) occurs when a tunnel passes through the weak and schistose rock mass. It has been found through the review that the tunnel crew was able to successfully solve instability challenges. Effective planning, design, and selection of appropriate construction techniques help to complete tunneling projects in the Himalayas.</p> Tek Bahadur Katuwal, Krishna Kanta Panthi Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000 Enhanced Rock Slope Stability Analysis: Integrating the Partial Factor Method into the Limit Equilibrium Method <p>Rock slope stability is crucial for sustainable design. Especially concerning natural or artificial rock-cut slopes. The stability of these slopes depends largely on features of rock mass, particularly discontinuities. Failure modes are determined by these features and are evaluated using kinematics analysis with stereographic projections. Various methods exist for analyzing rock slopes, including the limit equilibrium method (LEM), which assesses stability based on a factor of safety (FS). Conversely, the partial factor method (PFM), predominantly used in Europe, offers a more reliable and probabilistic approach, incorporating uncertainty factors. Although Eurocode, which employs the PFM, is widely utilized, it faces disputes and undergoes updates based on ISRM recommendations. The partial factor method is considered more conservative than the limit equilibrium method due to its comprehensive probabilistic approach. The choice between methods depends on project requirements, data availability, and expertise. This study compares the limit equilibrium and partial factor methods for rock slope analysis, concluding that the partial factor method is more conservative and sustainable for long-term stability assessment. Whereas, the traditional method is often used for short-term assessments.</p> Hare Ram Timalsina Copyright (c) 2024 The Author(s) Tue, 04 Jun 2024 00:00:00 +0000