Category Archives: Uncategorized

Authors: Krishna Teja Uppu, U.Srinivasarao

Abstract: In present day multi-tale structures in urban India, floating columns are a ordinary architectural function. Such functionalities need to not be universally used in systems constructed in seismically lively regions. This remark underscores the importance of figuring out the floating column in structural evaluation. We provide an change method for mitigating the unpredictable behaviour of floating columns. Achieving equilibrium between the principle and superior floors's stiffness is critical to this method. The hazards associated with inadequately constructed edifices and the destruction because of earthquakes are stark realities in several regions worldwide. Floating columns are a exclusive characteristic in numerous present day multi-story structures in India's predominant towns. The floating column exemplifies a vertical element supported by means of a beam at its base. To mitigate the risky inertia forces produced at various floor levels of a large shape, the burden transfer mechanism ought to be directed from the pinnacle to the lowest. Any departure or divergence from this channel will result in poor overall performance. Floating columns need to no longer be used within the design of systems located in seismically active areas. The donation research take a look at the unfavorable outcomes of the building's floating columns. This studies used body fashions to study the effect of unstable excitation on several structural traits in multi-story strengthened concrete systems, inclusive of herbal frequency, base shear, and horizontal displacement. The constructions are in comparison with and with out floating columns.The modern-day observe used ETABS 2018 for seismic evaluation and the layout of floating multi-tale buildings. This examination covers both inner and outside floating. To take a look at the effects on story go with the flow, shear pressure, bending moment, and structural torsion, we compared G+10 models with and with out floating columns.

 

 

Published by: vikaspatanker

Authors: Maddasani Balaji, U.Srinivasarao

Abstract: Concrete is the most widely used construction material; however, its inherent brittleness and low tensile strength limit its performance under dynamic loading conditions such as impact and fatigue. Structures including pavements, bridge decks, industrial floors, airport runways, and protective structures are frequently subjected to repeated cyclic loads and sudden impact forces, which can lead to progressive cracking, stiffness degradation, and premature failure in conventional concrete. To overcome these limitations, Fiber Reinforced Concrete (FRC) has emerged as an effective composite material that enhances the mechanical performance and durability of concrete under extreme loading conditions. Fiber Reinforced Concrete is produced by incorporating discrete fibers such as steel, polypropylene, glass, carbon, or natural fibers into the concrete matrix. These fibers act as crack arresters by bridging microcracks and restraining their propagation, thereby improving toughness, ductility, and post-cracking behavior. Under impact loading, the presence of fibers significantly increases the energy absorption capacity of concrete, delays crack initiation, and transforms brittle failure into a more ductile mode. Experimental studies have shown that FRC exhibits substantially higher impact resistance compared to conventional concrete, with improvements strongly influenced by fiber type, aspect ratio, volume fraction, and orientation. Under fatigue loading, Fiber Reinforced Concrete demonstrates superior performance by enhancing fatigue life and reducing the rate of crack growth under repeated stress cycles. Fibers help redistribute stresses across the cracked sections and maintain structural integrity even after matrix cracking. Steel fiber reinforced concrete, in particular, has been shown to exhibit excellent fatigue resistance, while synthetic fibers contribute to improved durability and crack control. The synergistic use of hybrid fiber systems further enhances fatigue performance by combining strength and ductility characteristics. Overall, the incorporation of fibers significantly improves the resistance of concrete to impact and fatigue loading, making Fiber Reinforced Concrete a promising material for applications subjected to dynamic and cyclic loads. The improved mechanical performance, enhanced durability, and extended service life of FRC contribute to safer, more resilient, and sustainable infrastructure. Continued research on optimized fiber combinations, numerical modeling, and long-term field performance is essential for wider adoption of Fiber Reinforced Concrete in modern construction practices.

 

 

Published by: vikaspatanker

Authors: Lattupalli Neelaveni, V.E.S.Mahendra Kumar

Abstract: The layout planning is a part of urban development it includes planning of residential houses, commercial complexes, service roads, primary health centers, school…& other amenities sewerage system for whole layout (includes treatment, sewer line, storm water drains), water distribution system. This project includes design& estimation of residential building in plot of layout planned. Designing involves identifying the loads which act upon a structure and the forces and stresses which arise within that structure due to those loads, perform analysis to get moments and shear forces on different elements of the structure and then design the structure for ultimate loads and moments. The loads can be self-weight of the structures, other dead loads, live loads, moving (wheel) loads, wind load, earthquake load, load from temperature change etc. Estimation includes finding the quantities of materials required for the construction of the structure and requirements of labor etc., finally determining the overall cost of the structure before execution of work by using Auto cad. Structural engineers are facing the challenge of striving for the most efficient and economical design with accuracy in solution, while ensuring that the final design of a building must be serviceable for its intended function over its design lifetime. This project attempts to understand the structural behavior of various components in the multi-storied building. Analysis, designing and estimation of multi-storied building has been taken up for Basement+G+2 Building, thereby depending on the suitability of plan, layout of beams and positions of columns are fixed. Dead loads are calculated based on material properties and live loads are considered according to the code IS875-part 2, footings are designed based on safe bearing capacity of soil. For the design of columns and beams frame analysis is done by limit state method to know the moments they are acted upon. Slab designing is done depending upon the type of slab (one way or two way), end conditions and the loading. From the slabs the loads are transferred to the beams, thereafter the loads from the beams are taken up by the columns and then to footing finally the section is checked for the components manually and for the post analysis of structure, maximum shear force, bending moment and maximum story displacement are computed. The quantitative estimation has been worked out. All the drafting was done using Auto cad.

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Published by: vikaspatanker

Authors: Chilaka Vijay, V.E.S.Mahendra Kumar

Abstract: Concrete has occupied an important place in the construction industry in the past few decades and it is used widely in all types of constructions ranging from small buildings to large infrastructural dams or reservoirs. Cement is a major ingredient of concrete. The cost of cement is increasing day by day due to its limited availability and large demand. At the same time global warming is increasing day by day. Manufacturing of cement releases carbon dioxide. In the present study an attempt has been made on concrete and an experimental investigation on the concrete by replacing cement with FLYASH and GGBS to decrease the usage of cement as well as emission of carbon dioxide. Experimental studies were performed on plain cement concrete and replacement of cement with Fly ash and GGBS was done. In this study the concrete mix was prepared by using fly ash, GGBS, sodium silicate, sodium hydroxide. A comparative analysis has been carried out for concrete to the Geo polymer concrete in relation to their compressive strength, workability, tests on aggregate. The Geo- polymer concrete is an innovative and eco-friendly in construction. To reduce carbon dioxide emission, we are making geo-polymer concrete. The concrete made with fly ash (50%) and GGBS (50%) performed well in term of compressive strength, shows higher performance at the age of 7,14,28 days than conventional concrete. slump cone, compaction factor test was conducted to find the workability of Geo-polymer concrete and normal concrete. And test conducted on aggregate such as crushing strength, abrasion test, impact test.

 

 

Published by: vikaspatanker

Authors: Joselin Mercy J, Rithu Kumari R, Dr. K. Geetha

Abstract: Traffic congestion has become a serious issue in rapidly growing cities, causing delays, increased fuel usage, and environmental damage. Traditional traffic systems rely on fixed signals and limited data, making them ineffective in handling real-time traffic variations. To overcome these limitations, this study introduces a smart traffic prediction system that combines Artificial Intelligence (AI) and the Internet of Things (IoT). The system gathers real-time data from devices such as traffic cameras, GPS trackers, and roadside sensors. This data is then analyzed using machine learning models, especially Long Short-Term Memory (LSTM), to predict future traffic conditions. The goal of this system is to improve traffic flow, reduce congestion, and support better decision-making for traffic authorities. With the help of cloud computing, the system can efficiently handle large amounts of data. Experimental results show that this approach performs better than traditional methods by improving prediction accuracy and reducing delays. Overall, this system contributes to smarter cities and better quality of life.

DOI: https://doi.org/10.5281/zenodo.19064146

Published by: vikaspatanker

Authors: Chinta Lakshmi Prasanna Kumar, Dr.K.Naga Sreenivasa Rao

Abstract: This paper presents a detailed laboratory-based experimental investigation on determining the optimum replacement levels of Fly Ash and Ground Granulated Blast Furnace Slag (GGBS) as supplementary cementitious materials in concrete. Ordinary Portland Cement (OPC) was partially replaced with GGBS at levels of 5%, 6%, 7%, 8%, 9%, and 10%, while Fly Ash was incorporated at replacement levels of 20%, 40%, and 60% of the total binder content. A constant water-to-cementitious materials ratio of 0.45 was maintained for all concrete mixes to ensure uniformity and comparability of results. The study was conducted on M25 grade concrete, designed with a mix proportion of 1:1.36:2.71.

 

 

Published by: vikaspatanker

Authors: Dr. Bayomock Linwa André Claude, Mr. Bakayoko Moussa

Abstract: This project proposes an innovative architecture that aims to ensure inter-mobile network financial transactions inside a specific country or between different countries. The architecture is a micro-service oriented. The architecture uses infrastructure as mobile server, gateways, that ensure interoperability, transparency and secure transactions between 2 separate mobile operators. Web technologies have been used to implement the solution. The architecture uses foundation principles of an open, efficient and inclusive financial ecosystem.

DOI: https://doi.org/10.5281/zenodo.19063263

Published by: vikaspatanker

Authors: Mr. Dr.M.Veerabhadra Rao, Munasa Satya Bhaskar

Abstract: The increasing use of social media platforms has created vast amounts of user-generated textual data that reflect personal emotions, thoughts, and behavioural patterns. These digital footprints provide valuable insights into an individual’s psychological state and can be leveraged for early detection of mental health conditions. However, traditional mental health assessment methods rely heavily on clinical interviews and self-reported questionnaires, which may not always provide timely or scalable solutions. This study proposes an intelligent hybrid machine learning framework for early mental health risk prediction using social media text analytics. The system integrates conventional machine learning models and deep learning architectures to perform multiclass classification of mental health conditions such as anxiety, depression, stress, and other psychological states. The framework incorporates comprehensive text preprocessing techniques, including cleaning, tokenization, stop-word removal, and feature extraction using advanced vectorization methods. Multiple classifiers such as Support Vector Machines (SVM), Random Forest, Logistic Regression, XGBoost, and a hybrid BiLSTM-CNN deep learning model are implemented and evaluated. To enhance performance, the proposed system applies hyperparameter optimization and dynamic model selection strategies. Experimental results demonstrate that the hybrid framework achieves high predictive accuracy and balanced performance across precision, recall, and F1-score metrics. The system provides a scalable and automated approach for mental health analysis, offering potential support for early intervention and preventive healthcare strategies.

DOI: https://doi.org/10.5281/zenodo.19063137

Published by: vikaspatanker

Authors: Challa Prasad, Sk.Abdulkareem

Abstract: Concrete is the most widely used construction material in the world, but its inherent brittleness and low tensile strength often limit its performance in structural applications. To overcome these limitations, the addition of fibres into the concrete mix has emerged as an effective technique to improve mechanical properties such as tensile strength, ductility, toughness, and impact resistance. This study investigates the mechanical behaviour of hybrid fibre-reinforced concrete (HFRC) incorporating a combination of steel fibres and polypropylene fibres. Steel fibres are known for their high tensile strength and crack-bridging capacity, while polypropylene fibres enhance post-crack behaviour and resistance to plastic shrinkage cracking. The experimental program includes the preparation of various concrete mixes with different proportions of hybrid fibres, followed by testing for compressive strength, split tensile strength, and flexural strength. The results demonstrate that the synergistic effect of steel and polypropylene fibres significantly enhances the mechanical performance of concrete compared to conventional plain concrete and single-fibre mixes. The research highlights that an optimal hybrid fibre ratio exists, which maximizes strength and ductility without compromising workability. The study provides valuable insights for structural engineers and researchers aiming to improve the durability and performance of modern concrete structures.

 

 

Published by: vikaspatanker

Authors: Mr. G. Harsha Vardhan, Shaik Kareem Ahmed

Abstract: The rapid expansion of digital media platforms has significantly increased the spread of misinformation, posing serious threats to public opinion, political stability, and social harmony. The automated identification of fake news has therefore become a critical research challenge in the fields of machine learning and natural language processing. This paper presents an intelligent and robust fake news detection framework that leverages advanced textual feature extraction and ensemble learning techniques to improve classification performance. The proposed system incorporates comprehensive data preprocessing, including text normalization, stop-word removal, tokenization, and vectorization using TF-IDF representations. Multiple supervised machine learning algorithms such as Logistic Regression, Support Vector Machine (SVM), Random Forest, and Gradient Boosting are trained and evaluated using stratified cross-validation to ensure reliability and generalization. To enhance predictive accuracy and reduce model bias, an ensemble-based voting mechanism is employed. Performance evaluation is conducted using metrics including accuracy, precision, recall, F1-score, and ROC-AUC to address class imbalance and misclassification risks. Experimental results demonstrate that the ensemble framework achieves superior performance compared to individual classifiers, providing a scalable and dependable solution for real-time misinformation detection in digital environments. The proposed approach contributes toward building trustworthy information ecosystems through automated and explainable fake news classification.

DOI: https://doi.org/10.5281/zenodo.19062457

Published by: vikaspatanker