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Bayesian causal relation effect in quantiles regression models
Full text linkAnalysis of causal relationships held an important part of the theoretical and empirical contribution in quantitative economic theory. This research explored the performance of Bayesian quantile regression with Granger causality showing that Bayesian inference can be undertaken in the context of quantiles regression. Causality Bayesian inferences in the context of quantile regression were achieved by applying the framework of the generalized linear model using asymmetric Laplace distribution for the error term. The developed scheme allows assessing the impact of the explanatory variables on all quantiles range of the conditional distribution of GDP growth. In Practical usage of macroeconomics variables, the scheme can be used to estimate parameters with causality effect which is synonyms to time series data. This research contributed to the versatile application of quantile regression in the contest of statistical research, the study estimated the regression quantiles parameter estimate applying Bayesian procedures. Furthermore, compared to frequentist estimates, Bayesian estimates established the superiority of the Bayesian regression method to the frequentist approach
Production of Premium Motor Spirit (PMS) additive from acetone and D-limonene
Full text linkA PMS additive containing acetone, D-limonene and a synthetic two stroke oil was produced. This additive improves the efficiency of fuel it is used in and also serves as an injector cleanser in engines due to the presence of D-limonene. This product prevents the destruction of parts of engine (metal parts and rubbers) that occurs due to ethanol softening. This invention also eradicates the chances of water collection and phase separation that is present in ethanol use. ASTM test analysis revealed that a sample of our prototype has a cloud point of 34°F, Kinematic viscosity of 4.8 mm2/s, Carbon residue of 0.2 and Research Octane number (RON) of 89. Manual test was also carried out to show the duration our PMS blended mixture which was 305 minutes and it lasts longer than pure PMS bought at a filling station which was 282 minutes
Study on Economic Plausibility of Electric Vehicle Charging Stations in Nepal
Full text linkNepal is targeting to produce 15,000 MW of electrical energy by 2030, and there shall be abundant energy in the country. Electric Vehicle (EV) charging stations can play a vital role in the consumption of the electricity generated within the country, and this can be achieved by adequately installing EV charging stations in different regions across the major highways in Nepal so that EVs can access them easily. This study compares petrol and diesel engine vehicles with an EV (Nissan Leaf) on the cost of energy consumption per kilometer to determine the economic prospect of EVs in Nepal. The total number of EV charging stations required was calculated based on the charging requirements (considering a discharge of 65%). The vehicles were compared based on the energy cost incurred per kilometer factor for a range of 20,000 kilometers. Furthermore, the payback period for setting up an EV charging station was determined based on the charging stipulations for the EVs, cost incurred, and the total revenue in a year. Wherever relevant, the data were adopted from other countries due to insufficient data from Nepal. Results suggest that setting up a total of 64 EV charging stations shall yield a peak power demand of 17.5 MW. Additionally, Nissan Leaf (EV in our study) is found to be the best alternative costing 2.4 Nepalese Rupees (NRs) per kilometer compared to that of petrol and diesel engine vehicles with the cost of 11.2 and 8.7 NRs per kilometer respectively. Also, the return on investment for setting up a single charging station has been determined within a payback period of 3 to 4 years. This study is one of its first kind to determine the prospect of EV charging stations in Nepal and could offer valuable information to control fossil fuel import in the future
Design, Fabrication and Testing of River Water Pump for Rural Communities
Full text linkThis paper presents development of river water pump that can operate without fuel and electricity mostly applicable in rural communities that are close to a water stream. The river water pump consists of a propeller, drum, hose, rotary coupling and helical coil. The pump is driven by a propeller which is rotated by moving water. Because these pumps do not require any external energy or fuel, the operating cost for irrigation, as well as for other household purposes can be minimized. In this study, two different shaped pumps were fabricated and tested. Although the general mathematical relations for the design of the pump was kept constant for the two pumps, the variation of the shape of the drum was incorporated for comparing the performances. The main purpose of this study was to compare performance of the cylindrical shaped and conical shaped pump. It was found from this study that by making a conical shape of the drum, the total discharge could be maximized. However, the design of the supporting structure to withhold the pump on the river needs to be modified to balance the unsymmetrical distribution of the mass caused due to the conical shape. Compared to the conventional coil pump, this study also uses double layer of coil to enhance the overall performance of the pump. Thus, this study is expected to support in the product development within this family of the pump
Comparative Numerical and Experimental Study of Golden Angle and Conventional Agitator Impellers
Full text linkConventional agitator impellers are found to be implemented in mixing tanks of various industries. The performance of these impellers is measured by the quality of the mixture and the cost of mixing in terms of the required power and time. This paper studies the possibility of replacing the conventional impellers with golden angle impellers for a better performance. The golden angle creates a natural spiral shaped impeller, which is an energy-efficient alternative for mixing tanks due to its natural tendency of minimizing the energy. A golden angle impeller has been designed in this study from CAD modelling and computed through CFD. The average velocity, torque, and power number are determined using numerical simulations from Solidworks 2020. The FloXpress solver is used to compute CFD and results from the golden angle impeller are compared with the same diameter of conventional agitator impeller. The results of CFD showed increase in the power output and the average velocity of the flow in the golden angle impeller to be 12.4% and 66.36% more than that of the marine impeller respectively. Moreover, the results from the simulation are validated through experiments by testing conductivity after mixing fine particles of blue vitriol in water, using 3D printed models of the impellers. The experimental study showed an average increase of the conductivity of the mixture and power consumption to be 5.39% and 17.6% more for the case of golden angle impeller respectively which was due to higher turbulence in golden angle impeller than marine impeller. After comparing the performance of the two impellers, it is found that the mixing process can be optimized significantly by using the golden angle impeller. By the given study it is concluded that the golden angle impeller is more preferrable where mixing process plays a significant role like during the production of pharmaceuticals, cosmetics, waste water management, dairy where manufacturing takes a very long time or when the rotational speed is quite low. The paper is aimed to determine the factors that yield the better performance, energy conservative and efficiency of the crafted golden angle impeller model with respect to widely commercialized impellers (marine impeller), addressing the prospects of minimizing the energy required. 
Performance and emission characteristics of diesel engine fueled with blends of Neem biodiesel
Full text linkIn this research, biodiesel produced from locally available Neem seed was used on the direct injection variable compression ratio (VCR) diesel engine without any modification. Neem seed, which contains 30-60% oil, was transformed into biodiesel through acid-base transesterification. The 1:6 of methanol to oil ratio, 1.2% (v/v) sulfuric acid during pretreatment and KOH as alkali catalyst for optimum yield was used. The characterization of prepared biodiesel was done according to ASTM standard. The effect of Neem biodiesel blends such as 10% Neem biodiesel and 90% conventional diesel (NBD10), 15% Neem biodiesel and 85% conventional diesel (NBD15), and 20% Neem biodiesel and 80 % conventional diesel (NBD20) were prepared and their performance and emission characteristics were studied. The test was performed at 17:1 compression ratio and 230 bar injection pressure with varying loads of 1 kg, 3 kg, 6 kg, 9 kg and 12 kg. The brake thermal efficiency (BTE), specific fuel consumption (SFC), torques and exhaust gas temperature (EGT) were analyzed on those different loads. The BTE for conventional diesel, NBD10, NBD15 and NBD20 were recorded as 8.12%, 7.23%, 6.56% and 6.23% respectively, at same loadings. These efficiencies increase with increment of load up to 31.25%, 28.96%, 27.56% and 27.35% respectively. The difference for specific fuel consumption (SFC) in pure diesel and NBD20 was recorded as 21.66% at 1 kg load whereas at 12 kg load this difference was 19.23%. The EGT for NBD20 was recorded higher than diesel for entire loading condition. The CO emission decreases with the increment of load and the proportion of biodiesel, whereas HC shows just reverse result. The smoke opacity was found better for NBD20 in comparison to conventional diesel. The performance and emission characteristics demonstrate that the blend of Neem biodiesel up to 20% with conventional diesel can be used as an alternative fuel in diesel engine without any change in the engine
Study of Surge Phenomena in a Hydropower Plant: A Numerical Approach
Full text linkSudden closure and opening of valves might cause unwanted water hammering effects in hydropower plants. In many cases, surge shafts are used as pressure neutralizers to dampen out the generated pressure pulsations. This study focuses on analyzing the surge phenomena and effects of using simple surge and restricted orifice surge on the flow behavior during the closing and opening of turbine inlet valves. A case of a Nepalese hydropower plant was taken and calculations were done over a simplified water transportation system of the plant. Analytical result was compared with the result obtained from an open-source CFD toolbox, OpenFOAM. A 3D fluid domain was made in SolidWorks and the mesh was created using snappyHexMesh utility of OpenFOAM. This study uses a multiphase solver called interFoam with the implementation of κ-ω SST turbulence model. The analytical result for maximum increase in water level in the surge shaft was calculated as 18.68 meters assuming a case of U-tube oscillation. The calculations neglected the presence of penstock pipes and assumed instantaneous closure thus giving a maximum value for upsurge height. Similar physical condition was recreated in OpenFOAM but with the presence of penstock, and a change in surge height with respect to time was analyzed. The obtained CFD result showed the average water level height in surge shaft to be 11.23 meters, which is less than the analytical result as expected. Then, the time of closure and time of opening were increased to 6 seconds and 30 seconds respectively and the effect of surge with and without orifice were visualized with respect to mass oscillations, pressure inside penstock and velocity of water in headrace tunnel. The numerical techniques used in this study can be applicable to other hydropower plants, which could provide a basis for the verification of the analytical designs
Design and Analysis of Industrial Safety Helmet
Full text linkThe safety of the workers is a valuable asset in every organization. A safety helmet is one of the personal protective equipment to ensure the user’s head against the impact of heavy loads in work sites. This study presents the optimized design of the shell of locally used safety helmets in Nepal’s industries and works sites. The study is based on the cohesive findings from qualitative and quantitative research. The interviews were carried out in Mahindra Auto Works Pvt. Ltd. and Dhulikhel Hospital. Questionnaire data were collected from Udayapur Cement Industries Ltd., Balaju Industrial Area and Patan Industrial Area, which helped identify the problems in Nepal’s existing safety helmets. The issues identified were headache due to extra weight, insufficient ventilation, adjustment and fitting problem, insufficient peak, inadequate aesthetic look, tight chin strap. The data from Dhulikhel Hospital interpreted anatomy of head and was considered to proceed with the new design of helmet shell. The 3D design of the shell of the newly designed helmet and the existing helmet was done in SolidWorks, and their simulation was carried out in ANSYS Workbench 15. The comparison of old and new models was done for static, dynamic and compression test considering the varying cases and force magnitudes. This study concludes that the total deformation and equivalent stress of the new model were less than that of the old model. 
A Review of Solar Assisted Radiant Heating System: Experimentation and Simulation Approach
Full text linkThe rate of energy consumption on the household level for heating and cooling is increasing annually. Due to economic growth and improved living standard, there is a sense of urgency of heating and cooling system for thermal comfort. Considering the thermal comfort, energy consumption, and impact on the environment, researchers and engineers need to focus on innovative heating and cooling solutions. The radiant heating system, which is popular among the Nordic countries, can be a promising future heating solution for Nepali buildings. This paper provides a brief overview of the solar-assisted floor heating system (SAFHS), experimentation, and simulation approach. Three types of paper included for review, the first type- experimental investigation on the floor heating system (FHS), the second type- simulation using ANSYS, and the third type- numerical analysis using TRNSYS. Out of forty-two papers selected for the study. The maximum papers used an experimental approach (11 articles) or TRNSYS (13 documents) to conduct temperature measurement, performance analysis, economic analysis, and estimate the solar fraction. ANSYS Fluent for the simulation of heat flux out of the system (9 papers), temperature field (11 articles), and the thermal comfort analysis (9 documents). 13 articles performed experiments combined with simulation under a standard protocol to validate the model. Both tools provide accurate results with an error below 10 %. The experimental study should be under the standard protocol, while TRNSYS should study the energy performance analysis, economic analysis, etc. The ANSYS Fluent simulates the thermal performance, temperature field, velocity field and conducts thermal comfort analysis. Based on the review, future research should be on taking combined advantages using the coupled-simulation approach
Short-term electricity demand forecasting for Kathmandu Valley, Nepal
Full text linkAccurate electricity demand forecasting for a short horizon is very relevant aspect for managing day-to-day operation control, scheduling, and planning. The deterministic variables such as type of days, and weather variables such as temperature are the major factors that affect the forecasting accuracy. Since the automation systems are continuously increased and implemented by smart meters and internet of things, static models computations are replacing accordingly by dynamic real time robust forecasting models. Therefore, time series, regression, machine learning, and deep learning models are designed and implemented on the electricity demand dataset of Kathmandu Valley, Nepal. Accuracy improvement is also considered during model design. The result shows that the deep learning model, long short term memory (LSTM) performs outstanding performance in-terms of mean absolute percentage error (MAPE) value 1.56%, and root mean square error (RMSE) value 3.12 MW. While analyzing the regression coefficients, electricity demand during Dashain shows the lowest variation while Tihar (Dipawali/Laxmi Puja) shows the highest (peak) demand variation