An Experimental Investigation to Determine the Failure Load of Optimal Hammer Head Pier Cap and Interpolate using Univariate Splines Machine Learning Algorithm
Assessment of Radius of Curvature along the Existing Road Networks
Sustainable Urban Infrastructure: A Comprehensive Review of Environmental Safety Practices in Civil Engineering
Experimental Investigation on the Influence of Recycled Aggregate on the Durability and Mechanical Properties of Concrete
A Step by Step Analysis to Solve the Equation of Motion in Space and Time using Basis Splines - A Class Room Example
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
Strengthening and Rehabilitation of RC Beams with Openings Using CFRP
Unsaturated Seepage Modeling of Lined Canal Using SEEP/W
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
Assessment of extreme rainfall for a given return period is considered as one of the important aspects while planning, design and management of hydraulic and civil structures, which can be estimated through deterministic, probabilistic and transformation methods. This paper presents a study on intercomparison of five data transformation methods such as Square Root, Cube Root, Logarithmic, Box-Cox and modified SMEMAX (Small, MEdian, MAXimum) applied in assessing the extreme (i.e., 1-day maximum) rainfall of Gaganbawada, Lanja and Radhanagari sites. The adequacy of fitting transformation methods to the observed data was evaluated through a non-parametric Goodness-of-Fit test, Kolmogorov-Smirnov (KS) while the Relative Mean Squared Error (RMSE) was used for the selection of most suitable method for estimation of rainfall. The outcomes of the study with KS test results and RMSE values showed that the Square Root transformation is better suited method for the assessment of extreme rainfall for all three sites.
Road Roughness/Unevenness is an important parameter for the evaluation of the surface condition of a road. Roughness affects the vehicle operating cost, speed, riding comfort, safety, fuel consumption, and tire wear and tear. Every road user desires to have a smooth and comfortable riding. Roughness measurement is an important activity on highways based on which maintenance decisions are taken. IRC (Indian Road Congress) manual specifies roughness measurements to be taken at every 6 months on highways and based on the roughness index the functional overlay requirements are decided on highways. Roughness measurements using profilometers, namely Rod and Level, Dipstick, Merlin, Profiler, LiDAR, etc., give detailed surface profile measurements but are time-consuming. An alternative to profilometers is Response Type Road Roughness Measurement Systems (RTRRMS) which are installed on vehicles and measure how the vehicle responds to the pavement profile. A car-mounted fifth wheel Bump Integrator developed by CRRI in India is commonly used to measure roughness. The fifth wheel bump integrator system works through mechanical instruments producing 'bumps,' a binary, 'true or false' information, instead of 'range based' analog information produced by digital accelerometers commonly found in smartphones. Due to the difficulty in the calibration process, towing for longer distances, and complexity in recording, analyzing, and possible manual errors in recording the data, Cell Phone-based systems are becoming popular for their simplicity in measuring roughness using accelerometers embedded in the cell phone. RoadBounce is one such technology using Cell phone-based mobile Apps to measure roughness. This paper intends to present the findings of testing and evaluation of App-based roughness measurement technology for its accuracy and usability using different vehicles and mobile phones under different speeds, tire pressures, gradients, etc.
Engineered Cementitious Composite (ECC) is an advanced construction material that combines cement, fine aggregates, and specially designed fibers to create a highly ductile and durable building material. ECC is renowned for its exceptional tensile strain capacity, allowing it to undergo significant deformation while retaining its structural integrity. This characteristic makes ECC particularly suitable for applications where flexibility and durability are paramount, such as in earthquake-resistant structures and infrastructure repairs. This study investigates the tensile and flexural properties of ECC using Polyvinyl Alcohol Fibers (PVA) and compares these properties with those of regular mortar. Various sizes of PVA are available, and for this study, we utilized 12mm PVA fibers. The trial concrete mix design used was M30, with a watercement ratio of 0.3. The mixing process for traditional concrete and ECC is similar. Initially, the dry combination of ingredients is mixed for one to two minutes, followed by the addition of High Range Water Reducer (HRWR), and the mixture is further stirred for an additional three minutes. Finally, fibers are incorporated to achieve a stable condition for mixing. The samples used for testing consisted of 15 beams and 15 cylinders. The beam dimensions were (500 X 100 X 100) mm, while the cylinder dimensions were 100 mm in diameter and 200 mm in height. These samples were tested after 28 days of curing. The experimental findings indicate that PVA-enhanced concrete exhibits greater tensile and flexural strength when compared to conventional concrete, with results varying based on the percentage of PVA used. The split tensile strength of 1.5% PVA ECC cylinders was enhanced by approximately 46.8%. In terms of flexural strength, there was a decrease observed in 0.5% and 1% PVA fiber beams compared to ordinary concrete beams. However, the 1.5% PVA fiber beam exhibited a 43.45% improvement over the 0% fiber beam and showed a 9.4% increase compared to the 2% PVA beam. Additionally, the 1% PVA sample in the soundproof test reduced sound by up to 21.2%.
A critical aspect of designing road pavements is accurately estimating the expected traffic load. It's important to note that not all vehicles use the same wheel path when traveling on a road. Many factors, including the Lane Distribution Factor (LDF), can affect the lateral shift of the load applied to the pavement. LDF is a crucial factor in designing flexible pavements, as it helps transportation planners and highway engineers estimate lane usage relative to the total traffic volume. This information is essential for understanding how pavements respond to wheel loads and fatigue behavior. The IRC: 37 - 2018 guidelines provide a set of LDFs for estimating the design traffic in terms of Million Standard Axle Loads. However, to ensure the accuracy of these LDFs, a study was conducted on rural and urban highways with two and four lanes to identify the lateral distribution of the vehicles.
Corrosion of steel is one of the major problems concerning construction field which becomes more severe when the structures are subjected to harsh environment which is harmful to structure as well as costs high for repair. Hence, deviating to alternate building materials is essential in upcoming years. One of the latest findings among them is replacement of steel with Glass Fiber Reinforced Polymer (GFRP) bars. Experimental and numerical studies on various strength parameters of these bars are being undertaken to examine their replacement to steel. This work contains experimental investigations on bond performance of Glass Fiber Reinforced Polymer (GFRP) bars. In the present study the bond behavior GFRP bars with and without wrapping of binding wire embedded in polypropylene fibers reinforced concrete and conventional steel rebar embedded in plain concrete was tested. The grade of concrete used for investigation was M40 and for bond testing 10, 12 mm diameter steel and GFRP bars were used in this experimental work. Pull-out test was conducted in Universal Testing Machine (UTM). It was observed that bond behavior of GFRP bar and concrete were lesser than steel bar by 41.06 % for 10 mm diameter bars and by 31.63 % for 12 mm diameter bars. Although it was observed that GFRP bar wrapped with binding wire possessed lesser bond stress than steel bars, it has improved bond stress compared to GFRP without wrapping by 16.06 % for 10 mm diameter bar and by 14.22 % for 12 mm diameter bars. Also maximum slippage was observed for GFRP than steel bar and GFRP with binding wire wrapping. GFRP bar slippage of 10 mm and 12 mm diameter is 130.88 % and 63.64 % and respectively higher than steel bars. The bond strength and maximum slippage of GFRP bar is found to be decreased with increase in diameter.
