Analysis of Labor Productivity of Brick Masonry Work in Building Construction in Kathmandu Valley

Construction labor productivity is the most determinant of success of any construction project. Labor is considered as more variable and unpredictable cost component for the successful accomplishment of construction projects. The main aim of this research is to develop an artificial neural network (ANN) model to predict the production rate for brick masonry work by assessing the various factor affecting labor productivity. Out of forty-four factors selected from a literature review, the top thirteen factors were selected for model development after the questionnaire survey and ranking them based on Relative Importance Index (RII). The model was developed in Neurosolution version 7.1.1.1 using the various input data set collected from active construction site of brick masonry. 65% of data set were used for training, 20 % of data set were used for cross-validation and remaining 15 % of data set were used for testing. The error between actual productivity and estimated productivity was computed using Mean Square Error (MSE) which was 0.019 which verified that the estimated production rate was within an acceptable range. After the successful testing of model, a sensitivity analysis was performed to analyze the order of most influencing factors affecting labor productivity. The developed ANN model can be used for estimating the labor productivity of brick masonry work for any building construction project by incorporating the influence of selected parameters or factors.

Deterministic and Probabilistic Analysis of Dasdhunga Soil Slope along Narayangarh-Mugling Road Section

Instability of slopes is usually governed by a combination of intrinsic and extrinsic factors. The inherent variability of parameters make the problem probabilistic rather than a deterministic one. This research deals with evaluation of stability of slopes with the calculation of the factor of safety of Dasdhunga soil slope along Narayangarh- Mugling road section under different rainfall conditions through the use of coupled finite element and limit equilibrium method in GeoStudio and the determination of probability of failure by sliding, modeled as infinite slopes by using Monte Carlo simulation in R-Studio. Mean, standard deviation, minimum and maximum values of the parameters like- friction angle, cohesion and unit weight were computed from eight samples of the slope. The pore water pressure developed and its corresponding statistical data for different rainfall conditions were computed from FEM based SEEP/W simulation. The above parameters are assumed to follow truncated normal probability distribution function and the geometric parameters like height and slope angle are regarded as constant parameters. It was observed that the safety factors for theslopeis low in high intensity-low duration rainfalls and the probability of failure is high. The tendency to fail increases as the return period of rainfall increases and viceversa. Sensitivity analysis performed in both deterministic and probabilistic methods showed that friction angle is the most sensitive.

Q-Analogue of Holder’s and Minkowski’s Integral Inequalities on Finite Intervals and Generalization

In recent years, the topic on Holder’s and Minkowski’s inequalities has been studied by several researchers and variety of new results has been developed on their variants, extensions and generalizations. In this paper we give the extension to the generalized q- Holder’s integral inequality and by using it we also establish the generalization on q- Minkowski’s integral inequality on the finite interval [a, b]

Computational and Experimental Study of the Effect of Solidity and Aspect Ratio of a Helical Turbine for Energy Generation in a Model Gravitational Water Vortex Power Plant

Gravitational Water Vortex power plant is a relatively new plant used to generate hydropower from low head rivers and canals. There has been an increase in research in the field of runner design and canal design for GWVPPs throughout the world. As no definite equations are formulated in case of runners used in a GWVPP, they are currently produced by hit and trial method. This research focuses on studying about the use of a pure reaction turbine, Gorlov turbine, to generate power from a GWVPP. ANSYS Fluent was used to perform computational study while the experimental study was done using helical turbine blades fabricated using a 3-D printer. The energy generated is very low compared to the impulse turbines. Both the computational and experimental study shows that when increasing the aspect ratio of the turbine but keeping the solidity same, the efficiency is increased significantly. However, the studies also show that on increasing the solidity, the efficiency seems to decrease. All the turbines used submerged to 3 different depts and all the results show that increasing the submergence increased the efficiency.

Land Use Land Cover (LULC) Change Projection in Kathmandu Valley using the CLUE-S Model

In the past few decades the urbanization pattern of the Kathmandu valley has rapidly increased and the process was sensed through the increase in the urban facilities, population growth, and changed LULC pattern. The historical LULC change was analyzed using the generated map and the future scenario was found through the CLUE-S LULC change model and processed in GIS environment. Five scenarios and nine driving forces were considered for the sensitivity and future analysis of the model. Based on the evaluation of the historical maps and the conservation matrix, the built-up area is found to be increased nearby by 5% and the agricultural area decreased by 6.5% during 2010 to 2018. It is concluded that the normal LULC conservation scenario provides more reliable information for the future projection. The simulation result highlights that nearly 4 km2 of fertile and open area will be converted to built-up areas due to the rapid urbanization per decade. This increase in urbanization process leads to more challenges in urban environment management in future.

Assessment of Relationship between Road Roughness and Pavement Surface Condition

Pavement evaluation is the most significant procedure to minimize the degradation of the pavement both functionally and structurally. Proper evaluation of pavement is hence required to prolong the life year of the pavement, which thus needs to be addressed in the policy level. By this, the development of genuine indices are to be formulated and used for the evaluation. In context of evaluating the pavement indices for measuring the pavement roughness, International Roughness Index (IRI) is used, whereas for calculating the surface distress, indices as such Surface Distress Index (SDI) and Pavement Condition Index (PCI) are used. Past evaluating schemes used by Department of Roads (DOR) were limited to IRI for evaluating the pavement roughness and SDI for measuring the surface distress, which has least variability in categorizing the pavement according to the deformation. Apart from these, PCI which has wide range of categories for evaluating pavement, is not seen in practice in Nepal due to its cumbersome field work and calculations. In this paper the relationship is developed relating PCI with IRI and SDI using regression analysis by using Microsoft excel. In the other words, the pavement roughness index is compared with the surface distress indices. In 2017, 23.6Km of feeder roads in various locations of Kathmandu and Lalitpur districts were taken for this study which comprised of 236 sample data, each segmented to 100m. For this, IRI was sourced as secondary data, obtained from Highway Maintenance and Information System (HMIS) unit, Kathmandu, whereas, PCI and SDI were calculated from the field data obtained from the survey carried out in those sections manually. Then after, among 236 samples, 189 samples were taken for the relationship development which was then validated using 47 remaining samples. Furthermore, in the year, 2019 additional 3 Km of data was taken for validating the obtained relationships. It was done to improve the numerical predictions of data with such variation and thus satisfactory relationships were developed among the indices discussed in this study. The regression relationships between the two indices, IRI-PCI and IRI-SDI were thus significantly obtained. It has been found that the R² value for these relationships developed were statistically significant with 5% level of significance. The R² value for all the relationships showed that these relationships could be used for predicting the indices which would help in evaluating the pavement.

Artificial Neural Network Based Approach for Voltage Stability Analysis of for Sustained Operation of Power System

For reliable and secure power system, the stability analysis is recognized as an important problem. Voltage stability is the capacity of a power system to maintain steady acceptable voltages at all buses in the system. Voltage stability index (VSI) evaluation for a situation of power system can act as an accurate and fast indicator of the proximity of the system to voltage instability. Recently there has been considerable interest in intelligent methods based on artificial neural network (ANN), fuzzy logic and genetic algorithm to voltage stability assessment problem. ANN, with the ability to provide non-linear input/output mapping, parallel processing, learning and generalization have the potential to make them ideally suited for estimating VSI’s of a power system without solving the governing power system equations. This paper is to purpose an alternative method using ANN for finding the closeness of system operating point to voltage collapse that would be claimed to have better computational speed, accuracy, efficiency and reliability. Voltage Stability Analysis (VSA) using VSI is performed for different alternate loading strategies of power network building ANN models for every different scenario. The outcome found working satisfactorily in analyzing voltage stability problem, basically in ranking the network buses according vulnerability order.

Energy Security Assessment of Nepal for the Period 2005-2030

Energy is an important driver of all economic activities and it is necessary for the production of goods and the provision of services. Thus, a secure supply of energy to meet national demand on both the short term and long term is important for any country. As a net importer of petroleum products from only one supplier country of petroleum products (i.e. India), supply and demand gap of energy, frequent price fluctuations of petroleum products and poor diversification of primary energy supply, policies regarding energy security should be developed for Nepal. This study aims to assess the energy security index of Nepal so as to provide a picture of the historical performance of the country in terms of energy security for the past years 2005-2015 and in the future 2016-2030 under different scenarios. A set of 24 energy security indicators were selected based on literature review and relevant to national energy policies and grouped under 5 dimensions which are availability, affordability, accessibility, efficiency and acceptability. It can be seen that energy security for Nepal has been following a declining trade since 2005/06 to 2015/16, the causes of which could be attributed to the increase in energy consumption, increase in imports of petroleum products, increase in electricity deficit from the year 2008/09, increase in price of petroleum products. However, the value of energy security index is on the higher side (near to 10) which is mainly due to the fact that energy supply of Nepal is mostly dependent on traditional sources which is domestically supplied. There is a need to incorporate energy security in the national energy policy of Nepal with more emphasis on diversification of primary energy sources (other than traditional resources), reduction on import dependency especially on fossil fuel resources, strategic fuel reserves, diversification of energy resources uses in different energy consumption sectors like transport, industries, increase in energy supply from renewable energy sources, etc.

Study on Mechanical Properties of TMT Bars Manufactured in Nepal

Three grades of deformed steel bar are presently available in Nepal for concrete reinforcement. The deformed bars are graded according to their specified yield strength. These are Fe415, Fe500 and Fe500D. CTD bars of grade more than Fe415 are scarcely available in market. However, TMT bars of Fe500 grade are easily available in market. This study is undertaken to evaluate the variability of the mechanical properties of reinforcing steel granted with NS Mark and to analyze the degree to which these rolling mills satisfy the minimum requirements established by product national standard NS:191. The data obtained from test results are statistically analyzed to evaluate the variability in the mechanical properties of TMT bars. For the tested mechanical properties, the parameters evaluated for each bar size, and grade at confidence level at 95 % are mean, standard deviation, coefficient of variation, minimum, maximum, skewness. The samples were collected from NBSM reference sample store room of FY 2073-74 and FY 2074-75. These samples were from nineteen industries and twenty-two different brands. Total 745 numbers of TMT bars of grade Fe500 and Fe500D were tested at NBSM mechanical testing laboratory. The mechanical properties determined from the tested samples are: mass per meter run, yield stress, tensile stress, percentage elongation, UTS/YS ratio, total elongation at maximum force, and bond value.The tested data and obtained statistics of different mechanical properties for the separate and combined data takes on an important practical significance and may be used in calibrating local specifications and designs.

Urban Energy Scenario of Household Sector in Bhaktapur Municipality for Sustainable Energy Development

This study aims to analyse energy scenarios of Bhaktapur Municipality through primary data survey of 165 houses as a function of household's characteristics. Three scenarios are considered business-as-usual (BAU), Sustainable Energy scenario (SED) and Accelerated Growth Scenario (AGS). BAU, SED and AGS show an expected energy growth at annual rates of4.08%, 3.71% and 4.01%; with economic growth of 4.6%, 7.0% and 9.2% respectively. Whereas, the electricity consumption per household in the SEDand AGS are 3,840KWh and 4,698KWh respectively, lies in tier-5 as per SDG. Fuel imported cost NRs. 471 million and NRs. 523 million can be saved in SED and AGS Scenarios respectively as compare to BAU scenario. Overall, under all three scenarios, it was found that total GHG emission in 2018 was 7.59 kilotons to nil in 2030 for SED and AGS.Furthermore,NPV value in AGS and SED scenarios are in negative value which means both scenarios is economically viable.