Behavioral Studies on Sorptivity of the Concrete Blended with Nano Silica
Optimization of Lane Based Signalized Intersections through VISSIM at Outer Ring Road Bengaluru
Trend Analysis of Rainfall Data using Mann-Kendall Test and Sen's Slope Estimator
A Review on Sustainable Utilization of Bauxite Residue (Red Mud) for the Production of Mortar and Concrete
A Critical Review of Experimental Research on the Durability of Cement Modified with Partial Steel Slag Replacement
Estimating the Soil Moisture Index using Normalized Difference Vegetation Index (NDVI) And Land Surface Temperature (LST) for Bidar and Kalaburagi District, Karnataka
Roughness Evaluation of Flexible Pavements Using Merlin and Total Station Equipment
Site Suitability Analysis for Solid Waste Dumping in Ranchi City, Jharkhand Using Remote Sensing and GIS Techniques
Unsaturated Seepage Modeling of Lined Canal Using SEEP/W
Strengthening and Rehabilitation of RC Beams with Openings Using CFRP
A Seasonal Autoregressive Model Of Vancouver Bicycle Traffic Using Weather Variables
Prediction of Compressive Strength of Concrete by Data-Driven Models
Predicting the 28 Days Compressive Strength of Concrete Using Artificial Neural Network
Measuring Compressive Strength of Puzzolan Concrete by Ultrasonic Pulse Velocity Method
Design and Analysis of Roller Compacted Concrete Pavements for Low Volume Roads in India
Estimation of rainfall for a given return period is of utmost importance for planning and design of minor and major hydraulic structures. This can be achieved through Extreme Value Analysis (EVA) of rainfall by fitting probability distributions viz., 2-parameters Normal, 2-parameters Log Normal, Pearson Type-3, Log Pearson Type-3, Extreme Value Type-1 (EV1) and Generalized Extreme Value (GEV) to the series of annual 1-day maximum rainfall. Based on the intended applications and the variate under consideration, Method of Moments (MoM), Maximum Likelihood Method (MLM) and L- Moments (LMO) are used for determination of parameters of the distributions. The adequacy of fitting six probability distributions adopted in EVA of rainfall for Afzalpur, Aland and Kalaburagi sites is quantitatively assessed by Goodness-of- Fit (viz., Chi-square and Kolmogorov-Smirnov) and diagnostic test (viz., D-index) tests, and qualitatively assessed by the fitted curves of the estimated rainfall. The outcomes of the study indicates that the GEV (LMO) is better suited amongst six distributions studied in EVA for rainfall estimation for Afzalpur and Kalaburagi whereas EV1 (MLM) for Aland.
Corrosion of embedded steel plays a vital role in deterioration of Reinforced Concrete (RC) members that affects the service life of RC structures reducing the strength and load carrying capacity of the structural elements. Many of the researchers around the world have focused mostly on the prediction of the residual flexural strength of corroded RC beams. There is comparatively lesser data available on prediction of the residual shear strength of corroded RC beams, although it is well known that shear failure of RC beam is a brittle sudden failure and is catastrophic in nature. The steel stirrups present in RC beam are more vulnerable to surrounding environment due to the thinner concrete cover around them as compared to the main reinforcement bars. The present study has been focused towards the prediction of the residual shear strength of RC beams after corrosion. In this study various experimental tests data for establishing the shear capacity of uncorroded and corroded RC beams have been collected and a large database has been prepared. The existing models in the research studies for prediction of the shear strength of RC corroded beams have also been collected. Predicted residual shear strength of corroded values from different models for different experimental studies were validated and cross checked. Prediction of residual shear strength of a corroded RC beam in one of the existing RC framed structure was performed with the most appropriate model based upon the outcome of the analysis of results obtained.
In K-NN model, cross validation is a technique to estimate the optimum number of nearest neighbors with minimum cross validation error. However the trial and error procedure followed in this technique makes it very rigorous and time consuming. Therefore, to overcome the disadvantages associated in the existing cross validation technique, a new cross validation technique has been proposed in this study which is based on independent variables of the system. To predict daily discharge of five monsoon months of Tikarpada gauging station of Mahanadi basin, K-NN models have been applied with the proposed cross validation technique. In this technique, based on good correlation between daily discharge of Tikarpada and that of other gauging stations of Mahanadi basin, independent variable of the system were selected and number of nearest neighbors of the K-NN models were fixed according to number of independent variables. High discharge prediction performance of the K-NN models indicated high efficiency of the proposed cross validation technique. Therefore, the proposed cross validation technique can be adopted for developing K-NN models for other gauging stations of Mahanadi basin and also for other basins.
In this analysis, the goal is to determine the durability quality such as water absorption, sorptivity and the acid attack of flyash metakaolin based SCGC and to study its microstructural behaviour with varying NaOH concentrations like 8M, 10M and 12M. In this investigation, fly-ash was swapped using metakaolin to the order of 0%, 10%, 20%, and 30% by mass. Fluids to binder ratio of 0.47 by mass and constant binding content of 400 kg/m3 were kept constant for all the molarities. S.P dosage of 3% was kept consistent for all the mixes from M1 to M12 and the water content was changed accordingly. The samples were moulded and cured for 24 hours in a 70 °C oven, after which climatic healing was backed until the testing days. Water absorption and sorptiveness increased when metakaolin content rose compared to the control mix, regardless of molarity. The greater molarity was attributed to the tougher structure, which prevented absorption. When compared to other replacement levels, the water absorption value for 10% replacement of fly-ash by metakaolin after 28 days was the lowest. And the strength loss was extremely low when preserved at 5% concentration in the sulphuric acid media. Regardless of molarity, a 10% substitution of metakaolin exhibited greater resistance to sulfuric acid attack. As a result, this could be a better alternative to traditional OPC concrete in terms of structural applications, as well as CO2 reductions.
The compressive strength of masonry, whether brick or concrete block masonry is an important parameter in the design of masonry structure. The compressive strength of masonry depends on many parameters including strength and modulus of elasticity of the unit and mortar. Experimental determination of compressive strength of masonry is time consuming, labour intensive and expensive. The numerical and analytical approach is an effective alternative to experimental investigations. This work aims to simulate the behaviour of block masonry under compression using ABAQUS and ANSYS software. The results obtained from the experimental investigation are used as input to carry out numerical analysis in the above-mentioned software. The results obtained from each of these software are in line with the experimental findings and is promising.
