CVR Journal of Science and Technology

The abstract summarizes the research findings on lightweight self-compacting concrete (LWSCC) incorporating unburnt broken brick bats as partial replacements for natural gravel aggregates. Mechanical properties, including compressive, split tensile, and flexural strengths, were evaluated for LWSCC samples with replacement levels of 0%, 10%, 20%, and 30% by volume of natural gravel. The compressive strengths ranged from 28.133 to 33.85 N/mm², split tensile strengths ranged from 8.3 to 10.6 N/mm², and flexural strengths ranged from 3.24 to 5.73 N/mm² across the replacement levels. Additionally, fresh properties of the LWSCC have been assessed using L box, V funnel, and J ring tests to evaluate workability according to EFNARC guidelines. The results have indicated satisfactory workability properties for all replacement levels, confirming the feasibility of using unburnt broken brick bats in LWSCC mixtures. This research contributes to the understanding of incorporating alternative lightweight aggregates in concrete production, potentially reducing environmental impact and resource consumption associated with traditional aggregates. Furthermore, the mechanical properties demonstrate the potential of unburnt broken brick bats as a viable lightweight aggregate option in LWSCC formulations. These findings offer valuable insights for engineers and researchers seeking sustainable solutions in concrete technology and construction practices.

Index Terms: Broken Brick Bats, Environmental Impact, Lightweight Concrete, Mechanical Properties, Sustainable Aggregates, Workability Assessment

Evaluating the Performance of Concrete Containing Reclaimed Asphalt Pavement as Coarse Aggregate

Matsyapuri Bhagya Lakshmi — 2024-06-01

Reclaimed asphalt pavement is a recycled pavement material consisting of asphalt and aggregate that has been treated. The majority of RAP is recycled back into pavements; hence there is a general dearth of data on the properties of RAP in other prospective uses such as Portland cement concrete. In this work, the characteristics of Portland cement concrete with coarse RAP were examined in the laboratory. Further, basalt fibers have been employed in the concrete mix to enhance the properties of concrete. The different proportions of RAP have been added into the concrete as a replacement to coarse aggregate for finding the optimum dosage for enhancing strength and durability. All samples were tested for workability, compressive strength, flexural strength, and acid attack tests to investigate the impact of RAP as coarse aggregate on concrete performance. The test results indicate that the inclusion of RAP makes concrete more workable while decreasing its strength. The reason for this is the inadequate adhesion between the cement matrix and RAP aggregate. Additionally, the durability and strength of RAP concrete are improved by the incorporation of basalt fibers. In addition to RAP as a partial substitute for coarse aggregate, the investigation suggests employing basalt fibers.

Index Terms: Reclaimed asphalt pavement, workability, Strength, Durability, Replacement, Fly ash, Sustainability

Base Isolation and Energy Dissipating System in Earthquake Resistant Building Design

Ramavath Rambabu — 2024-06-01

The utilization of base isolation is a crucial strategy for enhancing seismic resilience in structures. The method involves installing isolators and energy-absorbing devices beneath a building's superstructure to mitigate the destructive effects of earthquakes. When base isolation is implemented in a building, it not only makes the structure stronger and more stable, but also helps to safeguard lives and properties. This technique is particularly valuable for seismic retrofitting of historical buildings. In the present study, software called simulation of seismic isolation systems in structural analysis is employed, considering isolator characteristics, whether they exhibit nonlinear or equivalent linear behavior. Adhering to the IS 1893:2016 Code, the analysis utilized the SAP 2000 software package. A study was carried out to compare the effectiveness of base isolation systems versus fixed-base buildings in dealing with seismic activity. The study focused on analyzing various seismic indicators such as joint displacement, shear force, bending moment, building torsion, and the period of natural frequency. Results showed that models utilizing base isolation systems had significantly higher base shear values than those with a fixed-base building configuration. However, there was a significant 35% reduction in story shear values for the rubber isolation system and a 40% decrease for the friction pendulum model. Additionally, there was a 25% reduction in story drift for the rubber base model and a 30% decrease for the friction pendulum model. The friction pendulum model demonstrated the most effective control of these parameters across various seismic zone conditions.

Key words: The topic of discussion pertains to Seismic Isolation with Rubber Bearing System and the Friction Pendulum Technique. Additionally, it includes SAP2000 Analysis, Story Drift Measurement, and Shear Force Evaluation in relation to these techniques.

Implementation of 5G New Radio Secondary Synchronization on FPGA

Dr. Aytha. Ramesh Kumar — 2024-06-01

5^th Generation New Radio (NR) cellular technology operates at low latency, and higher bandwidths, and makes use of a large number of antennas. NR communication is compatible with a wide range of machine- and human-centered applications. The cell search procedure plays a crucial role in establishing a synchronized connection with the base station (gNodeB) when the user equipment (UE) is enabled, or in the on state. The procedure for cell search finds the physical cell identity of the base station with primary synchronization and secondary synchronization for 3rd Generation Partnership Project (3GPP) 5G NR standards. This paper focuses on identifying the secondary synchronization of Physical Cell Identity (PCI) in the 3rd Generation Partnership Project (3GPP) 5G NR system. Field Programmable Gate Arrays are reprogrammable, flexible, reconfigurable computing circuits and simple to design at very peak frequencies. This suggested architecture employs Secondary Synchronization Signal detection and aims for low power consumption and high speed. The secondary synchronization block has been designed and executed on the Xilinx Zynq FPGA board.

Index Terms: 5G New Radio, FPGA, Cell search, Physical Cell Identity, Primary and Secondary synchronization (SS).

IR Sensor based Smart Parking System

Dr. Humaira Nishat — 2024-06-01

Nowadays congestion of traffic level increased with the increase in population. As the population increases, the utilization of vehicles also increases. It's becoming a difficult task to find a slot to park the vehicle. To overcome this problem, a smart parking system is introduced. Previously, there were some approaches to this system where Bluetooth and GPS tracker were used to find the empty slots, and different sensors were used for indoor and outdoor parking. In some approaches there was no security for the user’s details. Whereas in the proposed system, every slot has a number which makes it easier for the user to find out the empty slot. IR sensors are used to detect the vehicle and the empty slot is displayed on LCD as well as cloud server where the user’s details are secured. Smart parking system is an IoT based system which includes Raspberry pi, LED display, Cloud Server, Monitor and IR Sensors that are available in each parking slot. The proposed system leverages the advantages of IR sensor technology to accurately detect the presence of vehicles in parking spaces, provides real-time information to the users, and improves overall parking efficiency. The paper discusses the system architecture, sensor deployment strategies, and implementation, thereby showcasing the potential benefits of IR sensor-based smart parking systems.

Index Terms: camera, cloud, parking, Raspberry Pi, sensors, vehicles

GSM-Enabled Home Automation and Security System: A Comprehensive Investigation and Implementation

N. Swapna — 2024-06-01

This research project focused on integrating home control and security through advanced Home Automation Systems. A thorough analysis and practical implementation of home automation technology were conducted, utilizing Global System for Mobile Communication (GSM) modems to manage various home appliances, including fans, air conditioning systems, and security systems. The system relied on Short Message Service (SMS) text messages for control and monitoring. Key features included an entrance security mechanism to promptly notify homeowners of unauthorized access, bolstering overall security. Additionally, an anti-theft reporting system employed alarms and SMS notifications to inform owners of security breaches. The system also integrated safety protocols for fire or gas leakage, dispatching SMS notifications and activating alarms to alert homeowners. The use of GSM technology provided wireless access to control connected devices, enhancing system efficiency and convenience. This research contributed to the smart home technologies field by presenting an advanced system that harmonized automation, security, and safety, with potential applications across diverse residential settings. While numerous home automation systems were available in the market, the significance of the proposed home automation system lay in its advanced features and comprehensive approach to integrating control and security functions. Unlike many existing systems, which may have offered basic automation capabilities, the proposed system went beyond simple automation by seamlessly integrating security measures using GSM technology. This allowed homeowners to effectively manage a wide range of home appliances, including fans, air conditioning systems, and security systems, all through the convenience of SMS text messages. Key features of the proposed system, such as the entrance security mechanism and anti-theft reporting system, addressed critical security concerns and provided homeowners with real-time notifications of unauthorized access or security breaches. Additionally, the integration of safety protocols for fire or gas leakage further enhanced the system's utility and value by prioritizing homeowner safety. Moreover, the utilization of GSM technology offered wireless access to control connected devices, significantly enhancing system efficiency and convenience compared to traditional wired systems. This wireless connectivity ensured that homeowners could remotely monitor and control their home environment from anywhere, at any time, providing them with peace of mind and control over their living space. Overall, the proposed home automation system represented a significant advancement in the field of smart home technologies by offering a comprehensive solution that harmonized automation, security, and safety. Its potential applications across diverse residential settings underscored its importance and relevance in meeting the evolving needs of modern homeowners.

Index Terms: Short Message Service (SMS), GSM modems, Safety protocols, Gas leakage detection.

Enhanced Safety Measures for Accident Prevention in Mountainous Regions

V. Shekar Reddy — 2024-06-01

In mountainous terrains, road safety is a paramount concern exacerbated by challenging conditions such as sharp turns and obscured visibility due to deep excavations. Forward Collision Warning (FCW) systems, employing ultrasonic sensors, serve as critical tools in identifying potential hazards, including vehicles, and issuing timely alerts to drivers. This paper introduces a controller-based approach integrating Arduino Nano and Atmega328 microcontrollers, with a specific emphasis on ultrasonic sensors, to address accident mitigation on mountainous roadways. Developing nations confront substantial road safety hurdles, with accidents emerging as a primary cause of fatalities. Embracing road design methodologies observed in developed nations like the Netherlands and Denmark holds promise for enhancing safety standards. Notably, buses and trucks are disproportionately vulnerable to accidents owing to deficient safety protocols, leading to significant loss of life. Deploying daytime lighting, high-mounted stop lamps, reflectors, and vivid attire has proven effective in mitigating accidents attributable to poor visibility. The proposed solution advocates for the strategic placement of ultrasonic sensors and LED lights ahead of and following sharp curves, respectively. Upon vehicle detection, the sensor activates the LED light, alerting oncoming traffic and empowering drivers to adjust their speed accordingly. This proactive strategy aims to curtail accidents and elevate road safety levels across mountainous regions.

Index Terms: Forward Collision Warning (FCW), Mountainous terrains, high-mounted stop lamps, LED lights.

Area-Delay-Power Efficient VLSI Architecture 2D FIR Filter using Modified Multipliers and Adders

Dr. Venkata Krishna Odugu — 2024-06-01

In this paper, a low power, area, and delay 2D Finite Impulse Response (FIR) filter architecture is derived from an analysis of a memory-efficient design. The completely direct-form 2D FIR filter is where the idea of parallel processing is first presented. As a result, the FIR filter may make better use of its memory by reusing its contents. With a block size of L and a filter length of N, a non-separable 2D FIR filter structure is developed and implemented. The FIR filter's arithmetic module makes use of high-speed, low-power multipliers and Carry Look Ahead (CLA) adders, with the output calculated by a pipelined adder unit. Verilog HDL code is used to represent the proposed architecture, and the CADENCE environment's NC Simulator and RTL Compiler synthesis tool are used to verify the design. Existing memory-efficient 2D FIR filter hardware architectures are compared to the produced area, power, and delay reports. Using Modified CLA (MCLA) adders and pipelining, we were able to cut down on power consumption by 44% and delay by 20%.

Index Terms: Memory reuse, 2D-FIR filter, Low Power Multiplier, Parallel Prefix Adder, Carry Look Ahead adder, and pipelining.

Comparative Analysis of 5-Level and 7-Level Single-Phase Cascaded H-bridge Multilevel Inverters

Dr. S. Venkateshwarlu — 2024-06-01

The demand for high-performance, efficient, and reliable power electronic systems has been steadily increasing in various industrial applications, including renewable energy systems, electric vehicles, and smart grids. In response to this demand, the Cascaded H-Bridge Multi-level Inverter (CHB-MLI) has emerged as a promising solution, offering advantages such as improved voltage waveform quality, reduced harmonic distortion, and enhanced power handling capabilities. The CHB-MLI is characterized by its modular structure, comprising multiple H-bridge cells cascaded in series. Each H-bridge cell operates with a separate DC power source, enabling the generation of stepped voltage levels at the inverter output. By intelligently controlling the individual H-bridge cells, the CHB-MLI achieves the synthesis of a high-quality multilevel output voltage waveform. The different multi-level inverter topologies are Diode-Clamped MLI, Capacitor-Clamped MLI and Cascaded H-bridge MLI. This paper focused on key aspects like design, simulation, control strategies, performance evaluation, overall comparison and analysis of 5-level and 7-level CHB-MLIs. By addressing these aspects, this paper aimed to contribute to the advancement of power electronics technology and promote the adoption of the CHB-MLI in real-world applications, fostering energy efficiency and sustainability in power conversion systems.

Index Terms: Inverter, Multi-level inverter, CHBMLI, switching, SPWM, MCSPWM, gate signal, waveform, harmonics, THD, MATLAB.

Review on Electric Vehicles Battery Swapping Technology

Dr. G. Sree Lakshmi — 2024-06-01

The goal of research and development organizations is to intelligently design the architecture of battery swapping stations (BSSs), with the hope of offering a reliable platform for the successful installation of a large fleet of electric vehicles (EVs) and hybrid electric vehicles (HEVs). The BSS can calibrate its subsystem for the deployment of electric vehicles (EVs) by implementing a similar concept to those found in current gas stations, which involve exchanging or swapping out discharged batteries for partially or fully charged ones after a short while. Because it gives the relevant stakeholders a more comprehensive understanding of the business prospects, the BSS approach has emerged as a promising technological alternative to the conventional EV recharging station approach. This paper addresses the introduction to BSS, covering its methods, infrastructure, advantages over charging stations, and main obstacles.

Index Terms: Battery Swapping Station (BSS), Battery Charging Stations (BCS), Electric Vehicles (EVs), Hybrid Electric Vehicles (EHVs).

Navigating the Present and Future Dynamics of Electric Vehicle Fast Charging and its Impact on Grid

Dr. M. Chiranjivi — 2024-06-01

As electric vehicle (EV) adoption surges worldwide, the need for fast charging infrastructure becomes paramount. Fast charging technology alleviates range anxiety and bolsters EV practicality. This comprehensive analysis delves into current challenges and future prospects surrounding EV fast charging and its grid impact. Examining the state of fast charging technology, it scrutinizes charging standards, connector types, and power levels across global regions. Emphasis is placed on key market players and the imperative for interoperability and standardization to seamlessly integrate EVs into the power grid. Voltage fluctuations, harmonics, and power factor issues stemming from rapid, high-power charging pose technical hurdles. Solutions like advanced power electronics, grid management tactics, and enhanced communication between EVs and the grid are explored to uphold stability and power quality. Consideration is given to energy sources fueling fast chargers, including renewable integration and environmental repercussions. Economic facets, encompassing infrastructure deployment costs and grid upgrade analyses, are examined amidst escalating electricity demand and potential grid expansion needs. A forward-looking perspective addresses future challenges and opportunities. This includes advancements in battery tech, smart grid solutions, and bidirectional power flow potential between EVs and the grid.

Index Terms: Battery electric vehicles (BEVs), Grid, Fast Charging, plug-in hybrid electric vehicles (PHEVs).

EcoCharge: Wireless Power Hub for Electric Vehicles

Varikuppala Manohar — 2024-06-01

This research paper presents the creation of the "EcoCharge," a cutting-edge wireless charging station designed exclusively for electric cars (EVs). By offering a smooth and eco-friendly charging experience, the system seeks to transform the infrastructure for EV charging. The suggested approach, which makes use of state-of-the-art technology, allows for simple charging in the absence of bulky cables or physical connectors. EcoCharge incorporates cutting-edge wireless power transfer techniques, such resonant or inductive coupling, to guarantee effective energy transmission with a minimum of losses. It also has smart features that optimize charging processes and guarantee compatibility with different EV models and battery sizes. By using dynamic charging algorithms, power management may be made more effective, increasing charging efficiency and cutting down on charging times. The system also places a high priority on sustainability, reducing its negative effects on the environment by using eco-friendly materials and energy-efficient components.

Index Terms: Wireless charging station, Electric vehicles (EVs), EcoCharge, Inductive coupling, Charging efficiency.

An IoT based Low-cost Artificial Mechanical Ventilator for Patients

V. Sreelatha Reddy — 2024-06-01

This paper presents the construction of a low-cost, open-source mechanical ventilator. The motto behind making this type of ventilator comes from the global shortage of ventilators to treat patients suffering with Covid-19. This paper presents a digital method to monitor the lung status of patients. This is achieved by determining pressure measurements from the inspiratory arm and alerts clinicians if the patient is in a healthy or unhealthy condition. The common symptoms of Covid-19 that can be easily identified are body temperature, blood oxygen level and heart rate that we must check to identify the virus. Hence this system can help in case a patient is unable to meet the doctor or requires frequent monitoring. These are going to develop a system which can monitor, and all the monitored data is stored in the cloud. When people suffer from breathing problems, this can be used for emergencies. The ventilator will be able to monitor the patient's blood oxygen levels and exhaled lung pressure while avoiding high pressure. Designed using Arduino, the ventilator meets all these requirements, creating an affordable ventilator to help during a pandemic. A motor mechanism is used to push the air bag. When the oxygen level counts are low, this mechanism is utilized. LCD screens are used to display oxygen levels. Whenever a patient faces a dangerous position, a buzzer sounds to notify a nearby caretaker. The entire system is driven by an Arduino microcontroller and a buzzer is fitted to detect any low levels of oxygen count.

Index Terms: Oxygen, Covid-19, Ventilator, Lung pressure, Air bag.

An Analysis on Recent Approaches for Image Captioning

Qazi Anwar — 2024-06-01

Image captioning is an interdisciplinary area that uses techniques from computer vision and natural language processing to provide a textual description of a picture. The Image captioning task is the process of understanding the scene present in the image by identifying objects and associated actions present to create a meaningful human-like caption which can be used for wide range of applications, including image retrieval, video indexing, assistive technology for the visually impaired, content-based image search, biomedicine, and autonomous cars. Formerly, Machine Learning was utilized for this purpose which will be extensive use of hand-crafted features such as Scale-Invariant Feature Transform (SIFT), Local Binary Patterns (LBP), the Histogram of Oriented Gradients (HOG), and combinations of these features. Extracting handmade characteristics from huge datasets is not straightforward or viable. Many deep learning-based techniques were later proposed. Deep Learning retrieval and template-based approaches were presented; however, both had drawbacks such as losing crucial objects. Recent breakthroughs in deep learning and natural language processing have resulted in considerable increases in image captioning system performance which involves adopting attention mechanisms, transformer-based architectures, multi modal connections, Object-Detection based encoder-decoder and many others. In this survey will explore some of the most recent techniques for image captioning, the datasets and evaluation measures that have been employed in deep learning-based automatic image captioning. The ultimate intention of this study is to act as a guide for researchers by emphasizing future directions for research work.

Index Terms: image captioning, computer vision, deep learning, Textual description, natural language processing.

Detection and Classification of Brain Tumor in MRI Images using EPCMA+ML-ELM

Dr. M. Deva Priya — 2024-06-01

Substantial clinical statistics along with analytical features can be extracted from brain tumor images. The identified quantitative measures of exact tumor regions aid physicians and radiologists in effective treatment. Magnetic Resonance Imaging (MRI) images of the brain are considered. Handling these images is challenging mainly owing to variance in addition to complexity in detecting tumors. In this paper, images are segmented using Enhanced Possibilistic C-Means Algorithm (EPCMA) and classified using Multi-Layered Extreme Learning Machine (ML-ELM). System performance is observed based on classification accuracy, sensitivity and specificity.

Index Terms: Brain Tumor, Possibilistic C-Means Algorithm, Extreme Learning Machine, MRI

Enhanced Call Admission Control based on History in BWA Networks

Dr. A. Christy Jeba Malar — 2024-06-01

WiMAX is a wireless technology that supports many blooming applications. To efficiently assign resources to traffic flows, bandwidth allocation and Connection Admission Control (CAC) modules are included in MAC layer and Burst Allocation (BA) module is added to PHY layer. It is essential to lessen delay and effectively schedule requests for BA. In this paper, CAC-based on History (CACH) and scheduler based on Delay Tolerance (SDT) for BA are proposed for WiMAX networks. CACH accepts/ rejects connections based on values in Contention Window (CW) in former Time Frame (TF). SDT and a Bucket-based BA (BBA) assign resources to flows with least amount of DT. Performance is analyzed based on throughput, Packet Loss Ratio (PLR) and delay.

Index Terms: WiMAX, Contention Window, Contention Delay, Delay Tolerance, Traffic Priority, Connection Admission Control, Burst Allocation

A Study on Handwritten Text Recognition Classification using Diverse Deep Learning Techniques and Computation of CTC Loss

Ratnam Dodda — 2024-06-01

Handwriting recognition encompasses the conversion of hand-written text images into digital text, where input images yield predicted textual output. Optical Character Recognition (OCR) technology has conventionally fulfilled this role. With surging mobile phone usage, leveraging text detection via mobile cameras gains significance in fields like medical script processing and exam evaluation. To enhance image quality, noise reduction techniques like binarization and thresholding are applied. Image processing entails letter segmentation and extraction. In this paper, we propose a neural network classifier model amalgamating Convolution Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. Leveraging an existing feature dataset, the model is trained. Input images are evaluated through the neural network, yielding recognized words in a text document format. Ultimately, the predicted output is derived via Connectionist Temporal Classification (CTC)- based loss computation.

Keywords: Handwritten Recognition, Deep Learning Techniques, Optical Character Recognition.

Predictive Modeling of Diabetes Mellitus Utilizing Machine Learning Techniques

N Nagarjuna — 2024-06-01

Diabetes mellitus represents a persistent metabolic condition distinguished by elevated levels of blood sugar, which results from the inadequacy of the body to secrete and respond to insulin, leading to health risks and frequent hospitalizations. Accurate predictive models are vital for targeted interventions to reduce readmissions and improve healthcare quality and cost. Early prediction can mitigate its impact, aid in control, and potentially save lives. Machine learning algorithms show promise in medical applications, including diabetes prediction and diagnosis. Limited data quality hinders accurate diabetes prediction due to missing values and inconsistencies. This paper investigates machine learning's potential for predicting and diagnosing diabetes, aiming to enhance accuracy and efficiency in disease management. Feature engineering techniques are applied to preprocess the data and extract relevant features for model development. To address class imbalance, SMOTE (Synthetic Minority Oversampling Technique) is employed. Various machine learning algorithms, including logistic regression, Naïve Bayes, random forests, support vector machines (SVM), K-Nearest Neighbors (KNN), and eXtreme Gradient Boosting (XGBoost), are utilized to build predictive models. The performance evaluation employs standard metrics such as accuracy, recall, precision, and F1-Score. Notably, Random Forest achieves an accuracy of 82% followed by XGBoost(80%) , surpassing other ML algorithms utilized.

Index Terms: Diabetes mellitus, Machine learning, Prediction, SVM, logistic regression, Accuracy.

Design and Analysis of Plastic Injection Mold for Hexagon Socket Head Cap Screw

Neeraj Kumar Jha — 2024-06-01

Plastic is a majorly used material for making customer goods. It is appealing to customers as well as manufacturers. Properties like durability, light weight and moldability make it a suitable choice for consumer goods which are made by mass production. Plastic materials are soft, but they possess adequate strength to be utilized for different engineering applications. After the development of various grades of plastic, it has replaced metals from different engineering applications in the recent past. This article aims at analyzing the suitability of making Hexagon Socket Head Cap Screws (HSHCS) out of a plastic material by injection molding processes. These screws are widely used as threaded fasteners at different places. They are preferably made of ferrous metals and possess semi complex design. They are mass produced by following a series of manufacturing operations. This article will observe the manufacturability of HSHCS by injection molding process. Based on the observation a model mold will be prepared to make HSHCS. The software used for modeling the parts is Autodesk Fusion 360 and that for the simulation of process parameters is Autodesk Moldflow Adviser 2023.

Index Terms: Hexagon Socket Head Cap Screws, plastic mold, manufacturability, threaded fasteners, injection molding, simulation.

Biomechanical Analysis of a Femur Bone

C. Sai Kiran — 2024-06-01

In this paper, a CAD model of human femur bone was generated and was analysed which is useful for medical industry for implementing the correct size and correct plate that can withstand the stresses developed by the user. The purpose of the work is to find a suitable material which can withstand the maximum stress made by the user. In this paper internal fixation is analysed. The image of femur bone is generated by using the 3D slicer where CT scan data in form of DICOM files is sent to the software to generate 3D model and the Bone plate, screws are modelled by using SolidWorks, the dimensions of the plate and screws are taken according to the generated femur bone. The function of the bone was analyzed for four different materials i.e. Nylon, PMMA, SS316L, TI-6Al-4V by using Ansys software and when the body is physically active. Total deformation and von-misses stress analysis help to choose the material which can withstand the max stress under different activities.

Index Terms: Femur, 3D Slicer, SolidWorks, Ansys, Von-mises stress.

Modeling and Thermal Analysis of Engine Block

Sk. Mohammad Shareef — 2024-06-01

In the realm of internal combustion engines, the engine block plays a pivotal role, where the combustion of the air-fuel mixture occurs. Due to this combustion process, high heat is released and transferred to the walls of the engine block. If this heat is not dissipated properly to the outside, it will affect the engine's performance. Hence the heat should be removed from the engine block. The heat removal rate from the engine block mainly depends on the material's thermal conductivity. Hence, this study endeavors to conduct thermal analysis on an engine block composed of various materials using ANSYS Workbench software, and modeling was done in Creo Parametric. The findings are meticulously analyzed to identify the material offering superior heat transfer performance.

Index Terms: Engine block, modeling, thermal analysis, Creo Parametric, and Ansys Workbench.

In the next issue (vol. 27, December 2024)

Dr. K. Lal Kishore — 2024-06-01

In the next issue (vol. 27, December 2024)

Template - CVRJST

Dr. K. Lal Kishore — 2024-06-01

Template - CVRJST

About the college

Dr. K. Lal Kishore — 2024-06-01

About the college