Pub Date : 2024-02-02DOI: 10.59256/ijsreat.20240401003
Thanneeru Mahesh
This research delves into a comprehensive comparative study focused on predicting loan status through the application of various machine learning (ML) algorithms. The objective is to assess and compare the effectiveness of Decision Trees, Random Forest, Support Vector Machines (SVM), and Gradient Boosting models in determining the likelihood of loan approval or denial. Leveraging a dataset comprising historical loan application data, including applicant demographics, financial history, and loan characteristics, the study conducts rigorous analysis and interpretation of the models' performance. The results provide valuable insights into the strengths and weaknesses of each algorithm, offering a nuanced understanding of their predictive capabilities in the context of loan status determination. This research contributes to the growing body of knowledge in the application of ML algorithms in the financial sector, presenting practical implications for institutions seeking to enhance their loan approval processes. Key words: Predictive Analysis, Machine Learning Algorithms, Loan Status, Comparative Study, Utilization
本研究深入探讨了通过应用各种机器学习（ML）算法预测贷款状况的综合比较研究。目的是评估和比较决策树、随机森林、支持向量机 (SVM) 和梯度提升模型在确定贷款批准或拒绝可能性方面的有效性。该研究利用由历史贷款申请数据（包括申请人人口统计学特征、财务历史和贷款特征）组成的数据集，对模型的性能进行了严格的分析和解释。研究结果为了解每种算法的优缺点提供了有价值的见解，使人们对其在贷款状态确定方面的预测能力有了细致入微的了解。这项研究为金融领域应用 ML 算法方面不断增长的知识库做出了贡献，为寻求加强贷款审批流程的机构提供了实际意义。关键词预测分析、机器学习算法、贷款状况、比较研究、利用率
{"title":"A Comparative Study on Loan Status: Utilizing Machine Learning Algorithms for Predictive Analysis","authors":"Thanneeru Mahesh","doi":"10.59256/ijsreat.20240401003","DOIUrl":"https://doi.org/10.59256/ijsreat.20240401003","url":null,"abstract":"This research delves into a comprehensive comparative study focused on predicting loan status through the application of various machine learning (ML) algorithms. The objective is to assess and compare the effectiveness of Decision Trees, Random Forest, Support Vector Machines (SVM), and Gradient Boosting models in determining the likelihood of loan approval or denial. Leveraging a dataset comprising historical loan application data, including applicant demographics, financial history, and loan characteristics, the study conducts rigorous analysis and interpretation of the models' performance. The results provide valuable insights into the strengths and weaknesses of each algorithm, offering a nuanced understanding of their predictive capabilities in the context of loan status determination. This research contributes to the growing body of knowledge in the application of ML algorithms in the financial sector, presenting practical implications for institutions seeking to enhance their loan approval processes. Key words: Predictive Analysis, Machine Learning Algorithms, Loan Status, Comparative Study, Utilization","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"57 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139869872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.59256/ijsreat.20240401004
Nalabothu Raviteja
This study navigates the dynamic landscape of Financial Technology (Fintech) and its transformative impact on the banking industry, elucidating the symbiotic evolution that characterizes this intersection. Fintech, as the fusion of cutting-edge technologies with financial services, signifies a revolutionary leap, fundamentally reshaping the financial landscape. From ubiquitous mobile banking applications to the advent of blockchain, AI-driven analytics, and cryptocurrencies, Fintech embodies a spectrum of innovations redefining traditional banking norms.The symbiosis between Fintech and banking drives a profound transformation, compelling traditional institutions to embrace digital strategies for competitiveness. Open Banking initiatives foster collaboration, blurring the lines between established banks and nimble Fintech startups. This exploration delves into the intricate layers of this relationship, unraveling the evolution, challenges, and future trends shaping the financial ecosystem. Keywords: Fintech Integration, Banking Transformation, Digital Financial Services, Open Banking Initiatives, Symbiotic Evolution.
{"title":"Financial Technology (Fintech) and Banking Industry Transformation: A Symbiotic Evolution into the Digital Era","authors":"Nalabothu Raviteja","doi":"10.59256/ijsreat.20240401004","DOIUrl":"https://doi.org/10.59256/ijsreat.20240401004","url":null,"abstract":"This study navigates the dynamic landscape of Financial Technology (Fintech) and its transformative impact on the banking industry, elucidating the symbiotic evolution that characterizes this intersection. Fintech, as the fusion of cutting-edge technologies with financial services, signifies a revolutionary leap, fundamentally reshaping the financial landscape. From ubiquitous mobile banking applications to the advent of blockchain, AI-driven analytics, and cryptocurrencies, Fintech embodies a spectrum of innovations redefining traditional banking norms.The symbiosis between Fintech and banking drives a profound transformation, compelling traditional institutions to embrace digital strategies for competitiveness. Open Banking initiatives foster collaboration, blurring the lines between established banks and nimble Fintech startups. This exploration delves into the intricate layers of this relationship, unraveling the evolution, challenges, and future trends shaping the financial ecosystem. Keywords: Fintech Integration, Banking Transformation, Digital Financial Services, Open Banking Initiatives, Symbiotic Evolution.","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"97 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139810361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.59256/ijsreat.20240401001
Bommireddy Srikanth Reddy
Machine learning, a specialized subset of artificial intelligence, imparts the ability to machines to learn, while artificial intelligence (AI) encompasses the broader field dedicated to emulating human capabilities. Within AI, machine learning employs computational techniques to instruct computers on learning from their historical experiences. Unlike models based on predetermined equations, machine learning algorithms derive insights directly from data, progressively improving their performance as the volume of learning examples grows. This paper presents a comprehensive overview of the domain, exploring diverse machine learning methodologies such as supervised, unsupervised, and reinforcement learning, along with an examination of various programming languages employed in machine learning applications. Keywords: Machine learning, Artificial intelligence, Computational techniques, Historical experiences, Learning examples, Supervised learning, Unsupervised learning, Reinforcement learning, Programming languages, Machine learning applications
{"title":"Advancements in Machine Learning: A Comprehensive Exploration of Methods, Applications, and Future Perspectives","authors":"Bommireddy Srikanth Reddy","doi":"10.59256/ijsreat.20240401001","DOIUrl":"https://doi.org/10.59256/ijsreat.20240401001","url":null,"abstract":"Machine learning, a specialized subset of artificial intelligence, imparts the ability to machines to learn, while artificial intelligence (AI) encompasses the broader field dedicated to emulating human capabilities. Within AI, machine learning employs computational techniques to instruct computers on learning from their historical experiences. Unlike models based on predetermined equations, machine learning algorithms derive insights directly from data, progressively improving their performance as the volume of learning examples grows. This paper presents a comprehensive overview of the domain, exploring diverse machine learning methodologies such as supervised, unsupervised, and reinforcement learning, along with an examination of various programming languages employed in machine learning applications. Keywords: Machine learning, Artificial intelligence, Computational techniques, Historical experiences, Learning examples, Supervised learning, Unsupervised learning, Reinforcement learning, Programming languages, Machine learning applications","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139869963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.59256/ijsreat.20240401002
Gorantla Prasanna
As we stand on the precipice of 2024, the technological landscape is abuzz with the convergence of two revolutionary forces: MLOps (Machine Learning Operations) and Generative AI. This potent cocktail promises to reshape the very fabric of artificial intelligence (AI), ushering in a new era of streamlined workflows, boundless innovation, and redefined value delivery. MLOps, a paradigm shift inspired by DevOps principles, emerges as the knight in shining armor, poised to vanquish the challenges plaguing the machine learning lifecycle. By fostering seamless collaboration, agile deployment, vigilant monitoring, and efficient management of models, MLOps lays the groundwork for robust organizational AI strategies. In this paper, we delve deep into the intricate world of MLOps, exploring its genesis, its potential to revolutionize business operations, and its pivotal role in shaping the future of AI. Keywords: MLOps, Machine Learning, Artificial Intelligence, DevOps, Automation, Collaboration, Deployment, Monitoring, Management, Generative AI, Innovation, Value Delivery, Business Optimization.
{"title":"Optimizing the Future: Unveiling the Significance of MLOps in Streamlining the Machine Learning Lifecycle","authors":"Gorantla Prasanna","doi":"10.59256/ijsreat.20240401002","DOIUrl":"https://doi.org/10.59256/ijsreat.20240401002","url":null,"abstract":"As we stand on the precipice of 2024, the technological landscape is abuzz with the convergence of two revolutionary forces: MLOps (Machine Learning Operations) and Generative AI. This potent cocktail promises to reshape the very fabric of artificial intelligence (AI), ushering in a new era of streamlined workflows, boundless innovation, and redefined value delivery. MLOps, a paradigm shift inspired by DevOps principles, emerges as the knight in shining armor, poised to vanquish the challenges plaguing the machine learning lifecycle. By fostering seamless collaboration, agile deployment, vigilant monitoring, and efficient management of models, MLOps lays the groundwork for robust organizational AI strategies. In this paper, we delve deep into the intricate world of MLOps, exploring its genesis, its potential to revolutionize business operations, and its pivotal role in shaping the future of AI. Keywords: MLOps, Machine Learning, Artificial Intelligence, DevOps, Automation, Collaboration, Deployment, Monitoring, Management, Generative AI, Innovation, Value Delivery, Business Optimization.","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139869682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.59256/ijsreat.20240401004
Nalabothu Raviteja
This study navigates the dynamic landscape of Financial Technology (Fintech) and its transformative impact on the banking industry, elucidating the symbiotic evolution that characterizes this intersection. Fintech, as the fusion of cutting-edge technologies with financial services, signifies a revolutionary leap, fundamentally reshaping the financial landscape. From ubiquitous mobile banking applications to the advent of blockchain, AI-driven analytics, and cryptocurrencies, Fintech embodies a spectrum of innovations redefining traditional banking norms.The symbiosis between Fintech and banking drives a profound transformation, compelling traditional institutions to embrace digital strategies for competitiveness. Open Banking initiatives foster collaboration, blurring the lines between established banks and nimble Fintech startups. This exploration delves into the intricate layers of this relationship, unraveling the evolution, challenges, and future trends shaping the financial ecosystem. Keywords: Fintech Integration, Banking Transformation, Digital Financial Services, Open Banking Initiatives, Symbiotic Evolution.
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This study presents the mathematical Modeling of gait. This model is for the lower limb exoskeleton. The exoskeleton has wide scope in hospitals, physical training, and army. The comfortable gait with exoskeleton requires a good mathematical model of gait. This Modeling of this study starts with a C3D file which is taken from a hospital. This Modeling uses MLS viewer, MOKKA, Any Body, and Matlab software. The basic information of the C3D file read with the MLS viewer software. This software tells the type of force plate, name of maker points, the number of force plate and marker points use in the gait analysis. The motion of marker points visualizes in MOKKA software. These visuals in MOKKA software give the position of all marker points. The MOKKA software also gives information about the starting frame number and last frame number for the gait on the force plates. The information collected from the MLS viewer and MOKKA software uses for modification of Any Script of the inbuilt model of Any Body software. The kinematic and inverse dynamic analysis of C3D file data performs in Any Body software after proper changes in Any Script of the model. The linear position and velocity data obtained from kinematic analysis use in Mat lab Modeling. Mat lab Modeling has two-step: curve fitting and curve plotting. The sum of sine equation fits on this linear position and velocity data using the curve fitting app of Mat lab. Another velocity equation is evaluated by the differentiation of the position equation. These equations of linear position and velocity simulate using Mat lab software. The plot of kinematic analysis data and plot of modeled equations compare in the Mat lab software. The goodness of the results of all these equations is decided based on root mean square error (RMSE). Keywords: Gait Analysis; Biomechanics; C3D files; Anybody Software; Root mean square error (RMSE); Electromyography(EMG); Open Sim; Mokka Analysis; Any Body Analysis; MLS viewer; Mat Lab Modeling.
本研究介绍了步态数学模型。该模型适用于下肢外骨骼。外骨骼在医院、体能训练和军队中有着广泛的应用。外骨骼的舒适步态需要一个良好的步态数学模型。本研究的建模从医院的 C3D 文件开始。建模过程中使用了 MLS viewer、MOKKA、Any Body 和 Matlab 软件。通过 MLS 查看器软件读取 C3D 文件的基本信息。该软件可显示受力板的类型、标记点的名称、受力板的数量以及步态分析中使用的标记点。标记点的运动在 MOKKA 软件中可视化。MOKKA 软件中的这些可视化信息给出了所有标记点的位置。MOKKA 软件还提供了力板上步态的起始帧数和最后帧数。从 MLS 查看器和 MOKKA 软件中收集的信息可用于修改 Any Body 软件内置模型的 Any Script。对模型的 Any Script 进行适当修改后，在 Any Body 软件中对 C3D 文件数据进行运动学和反动力学分析。运动分析获得的线性位置和速度数据将用于 Mat lab 建模。Mat lab 建模有两个步骤：曲线拟合和曲线绘制。使用 Mat lab 的曲线拟合应用程序对线性位置和速度数据进行正弦方程拟合。另一个速度方程则通过位置方程的微分来计算。这些线性位置和速度方程使用 Mat lab 软件进行模拟。在 Mat lab 软件中比较运动分析数据图和建模方程图。根据均方根误差（RMSE）判定所有这些方程结果的优劣。关键词步态分析；生物力学；C3D 文件；Anybody 软件；均方根误差（RMSE）；肌电图（EMG）；Open Sim；Mokka 分析；Any Body 分析；MLS 查看器；Mat Lab 建模。
{"title":"Mathematical Modeling of Gait for Lower Limb Exoskeleton","authors":"Takeshwar kaushik, Khemanshu kumar Sahu, Deepak Sharma","doi":"10.59256/ijsreat.20230306002","DOIUrl":"https://doi.org/10.59256/ijsreat.20230306002","url":null,"abstract":"This study presents the mathematical Modeling of gait. This model is for the lower limb exoskeleton. The exoskeleton has wide scope in hospitals, physical training, and army. The comfortable gait with exoskeleton requires a good mathematical model of gait. This Modeling of this study starts with a C3D file which is taken from a hospital. This Modeling uses MLS viewer, MOKKA, Any Body, and Matlab software. The basic information of the C3D file read with the MLS viewer software. This software tells the type of force plate, name of maker points, the number of force plate and marker points use in the gait analysis. The motion of marker points visualizes in MOKKA software. These visuals in MOKKA software give the position of all marker points. The MOKKA software also gives information about the starting frame number and last frame number for the gait on the force plates. The information collected from the MLS viewer and MOKKA software uses for modification of Any Script of the inbuilt model of Any Body software. The kinematic and inverse dynamic analysis of C3D file data performs in Any Body software after proper changes in Any Script of the model. The linear position and velocity data obtained from kinematic analysis use in Mat lab Modeling. Mat lab Modeling has two-step: curve fitting and curve plotting. The sum of sine equation fits on this linear position and velocity data using the curve fitting app of Mat lab. Another velocity equation is evaluated by the differentiation of the position equation. These equations of linear position and velocity simulate using Mat lab software. The plot of kinematic analysis data and plot of modeled equations compare in the Mat lab software. The goodness of the results of all these equations is decided based on root mean square error (RMSE). Keywords: Gait Analysis; Biomechanics; C3D files; Anybody Software; Root mean square error (RMSE); Electromyography(EMG); Open Sim; Mokka Analysis; Any Body Analysis; MLS viewer; Mat Lab Modeling.","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"142 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138981423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-06DOI: 10.59256/ijsreat.20230306001
Akassh G, Arnesh J, Jernik Galidine L
With their variety of vocalizations, birds contribute significantly to the acoustic fabric of our natural surroundings. Their songs and calls offer important clues in to the health of ecosystems and biodiversity. Contributions from the project include the creation of effective and trustworthy systems for classifying bird species, which may find use in ecological studies, biodiversity monitoring, and ornithology. A system like this could be useful for monitoring migratory patterns, evaluating changes in bird populations, and supporting conservation initiatives. The domains of artificial intelligence and ornithology are connected by this research. Keywords: Biodiversity, Acoustic fabric, Conservation, Vo- calizations, Ornithology
{"title":"Bird Species Identification Using Audio Processing Embedded With Translator","authors":"Akassh G, Arnesh J, Jernik Galidine L","doi":"10.59256/ijsreat.20230306001","DOIUrl":"https://doi.org/10.59256/ijsreat.20230306001","url":null,"abstract":"With their variety of vocalizations, birds contribute significantly to the acoustic fabric of our natural surroundings. Their songs and calls offer important clues in to the health of ecosystems and biodiversity. Contributions from the project include the creation of effective and trustworthy systems for classifying bird species, which may find use in ecological studies, biodiversity monitoring, and ornithology. A system like this could be useful for monitoring migratory patterns, evaluating changes in bird populations, and supporting conservation initiatives. The domains of artificial intelligence and ornithology are connected by this research. Keywords: Biodiversity, Acoustic fabric, Conservation, Vo- calizations, Ornithology","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"60 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138597147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-03DOI: 10.59256/ijsreat.20230305001
Hridya R P, Aromal K R, Anu Treesa C Y, Aljo T J, Elizabeth S Edattukaran
This project presents an innovative solution for automatic water pumping and real-time quality monitoring using the Blynk platform. It's designed to enhance water quality and pumping efficiency, ideal for hydroponics, aquaponics, and irrigation. Key components include an Arduino Uno, ultrasonic sensor for liquid levels, a relay for pump control, and a pH sensor. The system maintains water levels within defined thresholds and monitors pH levels, activating the pump when needed. Keywords: Automatic water pumping; Quality monitoring; Arduino UNO; pH sensor; Blynk platform
{"title":"Automatic Water Pumping and Quality Monitoring System","authors":"Hridya R P, Aromal K R, Anu Treesa C Y, Aljo T J, Elizabeth S Edattukaran","doi":"10.59256/ijsreat.20230305001","DOIUrl":"https://doi.org/10.59256/ijsreat.20230305001","url":null,"abstract":"This project presents an innovative solution for automatic water pumping and real-time quality monitoring using the Blynk platform. It's designed to enhance water quality and pumping efficiency, ideal for hydroponics, aquaponics, and irrigation. Key components include an Arduino Uno, ultrasonic sensor for liquid levels, a relay for pump control, and a pH sensor. The system maintains water levels within defined thresholds and monitors pH levels, activating the pump when needed. Keywords: Automatic water pumping; Quality monitoring; Arduino UNO; pH sensor; Blynk platform","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122456516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-21DOI: 10.59256/ijsreat.20230304003
S. S. M, Y. Jadhav
In this paper, the U-type symmetric sandwich beams with three layers are analyzed. Variations in the ratio of Young's modulus between the skin and core, as well as the curvature radius (R/H), parameters are considered for the U-type beams. The study investigates the influence of various core materials on the U-type beams. The stress analysis is conducted through numerical simulations utilizing the Finite Element Method software ANSYS. Keywords: U type beam, Sandwich, ANSYS
{"title":"Stress analysis of U-type layered sandwich beams","authors":"S. S. M, Y. Jadhav","doi":"10.59256/ijsreat.20230304003","DOIUrl":"https://doi.org/10.59256/ijsreat.20230304003","url":null,"abstract":"In this paper, the U-type symmetric sandwich beams with three layers are analyzed. Variations in the ratio of Young's modulus between the skin and core, as well as the curvature radius (R/H), parameters are considered for the U-type beams. The study investigates the influence of various core materials on the U-type beams. The stress analysis is conducted through numerical simulations utilizing the Finite Element Method software ANSYS. Keywords: U type beam, Sandwich, ANSYS","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127436640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-16DOI: 10.59256/ijsreat.20230304002
S. S. M, Patil V. P
The domain of engineering and structural mechanics has undergone a transformative shift, courtesy of composite materials, attributing to their remarkable strength-to-weight ratio and versatile design adaptability. Amid the diverse array of composite applications, significant attention has been directed towards composite shells fortified with stiffening elements. These configurations seamlessly amalgamate the merits of composite materials with the augmented load-bearing capabilities conferred by the incorporation of stiffeners. This research undertaking aims to dissect orthotropic multilayered shells manifesting distinct stiffening configurations. The analytical exploration is carried out through the utilization of the Finite Element Analysis (FEA) software ANSYS. The ensuing analysis embraces several stiffening patterns: no stiffener, edge beam, central stringer, three equidistant stringers, central ring, and ring with stringer. The inherent diversity in the natural frequencies is reflective of the variance in these stiffening arrangements. Keywords: Laminated Composite Shells, Finite Element Method, Stiffeners, ANSYS.
{"title":"Dynamic analysis of laminated composite cylindrical shells with stiffeners","authors":"S. S. M, Patil V. P","doi":"10.59256/ijsreat.20230304002","DOIUrl":"https://doi.org/10.59256/ijsreat.20230304002","url":null,"abstract":"The domain of engineering and structural mechanics has undergone a transformative shift, courtesy of composite materials, attributing to their remarkable strength-to-weight ratio and versatile design adaptability. Amid the diverse array of composite applications, significant attention has been directed towards composite shells fortified with stiffening elements. These configurations seamlessly amalgamate the merits of composite materials with the augmented load-bearing capabilities conferred by the incorporation of stiffeners. This research undertaking aims to dissect orthotropic multilayered shells manifesting distinct stiffening configurations. The analytical exploration is carried out through the utilization of the Finite Element Analysis (FEA) software ANSYS. The ensuing analysis embraces several stiffening patterns: no stiffener, edge beam, central stringer, three equidistant stringers, central ring, and ring with stringer. The inherent diversity in the natural frequencies is reflective of the variance in these stiffening arrangements. Keywords: Laminated Composite Shells, Finite Element Method, Stiffeners, ANSYS.","PeriodicalId":310227,"journal":{"name":"International Journal Of Scientific Research In Engineering & Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117211840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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