Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708570
K. Rajesh, J. Rao
In electrical power systems the application of Distributed Generation (DG) is quickly expanding because it provides a long-term solution to many distribution system challenges, like Management of Voltage and reduction in power loss. Power loss reduction is critical to the cost-effective operation of a power system. This paper investigated the suitable location and size of on-site generation using an optimization approach i.e the Particle Swarm Optimisation (PSO) and Genetic algorithm with the objective of reducing power loss and enhancing the voltage profile in distribution networks. The inability to properly find the DG position may have a contrary influence on the system’s efficiency. Appropriate location and size play a very effective and vital function in boosting system efficiency by decreasing active power loss and optimising the voltage on each and every bus in the system. The forward-backward sweep method is used in distribution load flow research. The results of the simulation show that PSO can produce the largest reductions in power loss.
{"title":"The optimal on-site generation allocation in a radial distribution system using GA and PSO","authors":"K. Rajesh, J. Rao","doi":"10.1109/ICSTCEE54422.2021.9708570","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708570","url":null,"abstract":"In electrical power systems the application of Distributed Generation (DG) is quickly expanding because it provides a long-term solution to many distribution system challenges, like Management of Voltage and reduction in power loss. Power loss reduction is critical to the cost-effective operation of a power system. This paper investigated the suitable location and size of on-site generation using an optimization approach i.e the Particle Swarm Optimisation (PSO) and Genetic algorithm with the objective of reducing power loss and enhancing the voltage profile in distribution networks. The inability to properly find the DG position may have a contrary influence on the system’s efficiency. Appropriate location and size play a very effective and vital function in boosting system efficiency by decreasing active power loss and optimising the voltage on each and every bus in the system. The forward-backward sweep method is used in distribution load flow research. The results of the simulation show that PSO can produce the largest reductions in power loss.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130277063","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708578
R. S. Upendra, M. R. Ahmed, A. Omkar, Jhanvi Goyal, V. Chaitra, H. Muskan, Pragati Kamath, K. Thirumala Akash
India is basically agriculture driven country and our GDP is principally directed by the yield of Rabi and Kharif crops. Most of the farmers of our country practices traditional way of agriculture. Since the amount of soil nutrients regulates the growth and quality of the crop, a systematic and quantitative analysis of soil nutrients is essential for good and adequate agricultural produce. Many small and large-scale farmers of the country India were not aware about the soil fertility nutrients and hence are unable to make use of their farming land efficiently for enhanced crop yield. The motive of the present work is to emphasize the significance of soil vitamins and the sensor based smart way of nutrient evaluation practices for measuring each essential nutrients i. e., Nitrogen, Phosphorus, and Potassium of Agri land. It was understood from the literature that, insufficient levels of essential elements (N, P, K) in farming lands can cause major issues connected with crop growth, productivity, and crop failure. To enlighten farmers and the readers with the smart farming practices, present study submitted a cumulative review on soil nutrient analysis methods with special emphasis on sensors based smart methods to measure the quantities of soil essential elements such as N, P, K. It has been concluded that potentiometric based electrochemical sensors are beneficial for soil testing and were found to be advantageous to farmers in keeping a constant check on their soil health, which intern enable the farmers to grow healthier crops and to maintain the surrounding soil biodiversity.
{"title":"Smart Approaches to Measure Soil Fertility for Sustainable Agriculture","authors":"R. S. Upendra, M. R. Ahmed, A. Omkar, Jhanvi Goyal, V. Chaitra, H. Muskan, Pragati Kamath, K. Thirumala Akash","doi":"10.1109/ICSTCEE54422.2021.9708578","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708578","url":null,"abstract":"India is basically agriculture driven country and our GDP is principally directed by the yield of Rabi and Kharif crops. Most of the farmers of our country practices traditional way of agriculture. Since the amount of soil nutrients regulates the growth and quality of the crop, a systematic and quantitative analysis of soil nutrients is essential for good and adequate agricultural produce. Many small and large-scale farmers of the country India were not aware about the soil fertility nutrients and hence are unable to make use of their farming land efficiently for enhanced crop yield. The motive of the present work is to emphasize the significance of soil vitamins and the sensor based smart way of nutrient evaluation practices for measuring each essential nutrients i. e., Nitrogen, Phosphorus, and Potassium of Agri land. It was understood from the literature that, insufficient levels of essential elements (N, P, K) in farming lands can cause major issues connected with crop growth, productivity, and crop failure. To enlighten farmers and the readers with the smart farming practices, present study submitted a cumulative review on soil nutrient analysis methods with special emphasis on sensors based smart methods to measure the quantities of soil essential elements such as N, P, K. It has been concluded that potentiometric based electrochemical sensors are beneficial for soil testing and were found to be advantageous to farmers in keeping a constant check on their soil health, which intern enable the farmers to grow healthier crops and to maintain the surrounding soil biodiversity.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124683282","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708555
F. Azam, Arun Biradar, Neeraj Priyadarshi, S.Vijaya kumari, Shrikant S. Tangade
Technology advances through time and fast development accompanies over the time. Telecommunications and wireless technology are pioneers among the emerging technologies. Vehicular Ad-hoc Network is the most progressive and foreseen research field under wireless communications as they are able to provide a large variety of ubiquitous services. They are a growing technology which provides a vast range of safety applications for the vehicle passengers. With an increase in such services, there will be an increase in the vulnerabilities which could be compromise the VANET communication. Successfully defending against such VANET’s attacks is continuously under research and growth. Blockchain offers decentralized, distributed, collective maintenance to counter malicious attacks. In view of the aforesaid issues, in this paper a dedicated discussion of various research works related to privacy and authentication schemes in VANETS using Blockchain has been made.
{"title":"A Review of Blockchain Based Approach for Secured Communication in Internet of Vehicle (IoV) Scenario","authors":"F. Azam, Arun Biradar, Neeraj Priyadarshi, S.Vijaya kumari, Shrikant S. Tangade","doi":"10.1109/ICSTCEE54422.2021.9708555","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708555","url":null,"abstract":"Technology advances through time and fast development accompanies over the time. Telecommunications and wireless technology are pioneers among the emerging technologies. Vehicular Ad-hoc Network is the most progressive and foreseen research field under wireless communications as they are able to provide a large variety of ubiquitous services. They are a growing technology which provides a vast range of safety applications for the vehicle passengers. With an increase in such services, there will be an increase in the vulnerabilities which could be compromise the VANET communication. Successfully defending against such VANET’s attacks is continuously under research and growth. Blockchain offers decentralized, distributed, collective maintenance to counter malicious attacks. In view of the aforesaid issues, in this paper a dedicated discussion of various research works related to privacy and authentication schemes in VANETS using Blockchain has been made.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128512793","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708587
V. C. S. Rao, Pulyala Radhika, Niranjan Polala, Siripuri Kiran
In this age of globalization, the unstoppable spreading of fake news via the internet is unstoppable. The spread of false news cannot be supported due to the negative consequences. Society is extremely concerning. In addition, itleads to more serious problems and possible threats, like confusion, misunderstandings, defamation and falsehoods that induce users to share inflammatory content. With the convenience and tremendous increase in information gathering on social networks, it is becoming difficult to differentiate between what is false and what is real. Information can be easily disseminated through sharing, which has contributed to the exponential growth of their forgeries. Machine learning played an important role, in classifying information, although there are some limitations. This article explores various machine learning techniques used to detect fake and fabricated messages. The limitations are discussed using deep learning implementation. In this project, the methodology used is model development and Logistic Regression classifier is considered to detect false news. Based on previous research, this classifier performed well in classification tasks. In this approach, TF-IDF feature is used for the construction of this fake news model to get higher accuracy. The goal of this project is to detect false news using NLP and Machine Learning based on the news content of the article. Following the development of the appropriate Machine Learning model to detect fake/true news, it is deployed into a web interface using Python Flask.
{"title":"Logistic Regression versus XGBoost: Machine Learning for Counterfeit News Detection","authors":"V. C. S. Rao, Pulyala Radhika, Niranjan Polala, Siripuri Kiran","doi":"10.1109/ICSTCEE54422.2021.9708587","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708587","url":null,"abstract":"In this age of globalization, the unstoppable spreading of fake news via the internet is unstoppable. The spread of false news cannot be supported due to the negative consequences. Society is extremely concerning. In addition, itleads to more serious problems and possible threats, like confusion, misunderstandings, defamation and falsehoods that induce users to share inflammatory content. With the convenience and tremendous increase in information gathering on social networks, it is becoming difficult to differentiate between what is false and what is real. Information can be easily disseminated through sharing, which has contributed to the exponential growth of their forgeries. Machine learning played an important role, in classifying information, although there are some limitations. This article explores various machine learning techniques used to detect fake and fabricated messages. The limitations are discussed using deep learning implementation. In this project, the methodology used is model development and Logistic Regression classifier is considered to detect false news. Based on previous research, this classifier performed well in classification tasks. In this approach, TF-IDF feature is used for the construction of this fake news model to get higher accuracy. The goal of this project is to detect false news using NLP and Machine Learning based on the news content of the article. Following the development of the appropriate Machine Learning model to detect fake/true news, it is deployed into a web interface using Python Flask.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115104910","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708556
S. Karunakaran, P. Snehith
Using adiabatic logics, we proposed the design and evaluation of a 1:16 Multiplexer and a 16:1 De-Multiplexer in this paper. We used traditional static CMOS logic to implement a 1:16 Multiplexer and a 16:1 De-multiplexer to compare the strength of static cmos logic and adiabatic logic. In many vlsi designs, power consumption is the most important factor. We used adiabatic logics to implement a 1:16 Multiplexer and 16:1 Demultiplexer in static CMOS logic to minimize power consumption. The adiabatic logics are 2N2P and 2N2N2P where in both the adiabatic logics use cross-coupled transistor for adiabatic operation. Adiabatic logic uses reverse logic and energy recovery technique that results in less power dissipation when compared to static CMOS logic. In static CMOS logic, we will give constant power source as Vdd. So, the total energy gets dissipated across the resistor, the energy stored by the capacitor will be very less because of this energy recovery is not happened as in case of static CMOS logic. In adiabatic logic we will give slowly varying ramp signal as vdd. So, the total energy is not dissipated across resistor and the capacitor starts charging. In the discharging phase the energy stored by the capacitor is sent back to the source because of this energy consumption is reduced. This is the energy recovery technique which happens in adiabatic logics.
{"title":"High Performance VLSI Architecture of Multiplexer and Demultiplexer Using various Adiabatic Logic","authors":"S. Karunakaran, P. Snehith","doi":"10.1109/ICSTCEE54422.2021.9708556","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708556","url":null,"abstract":"Using adiabatic logics, we proposed the design and evaluation of a 1:16 Multiplexer and a 16:1 De-Multiplexer in this paper. We used traditional static CMOS logic to implement a 1:16 Multiplexer and a 16:1 De-multiplexer to compare the strength of static cmos logic and adiabatic logic. In many vlsi designs, power consumption is the most important factor. We used adiabatic logics to implement a 1:16 Multiplexer and 16:1 Demultiplexer in static CMOS logic to minimize power consumption. The adiabatic logics are 2N2P and 2N2N2P where in both the adiabatic logics use cross-coupled transistor for adiabatic operation. Adiabatic logic uses reverse logic and energy recovery technique that results in less power dissipation when compared to static CMOS logic. In static CMOS logic, we will give constant power source as Vdd. So, the total energy gets dissipated across the resistor, the energy stored by the capacitor will be very less because of this energy recovery is not happened as in case of static CMOS logic. In adiabatic logic we will give slowly varying ramp signal as vdd. So, the total energy is not dissipated across resistor and the capacitor starts charging. In the discharging phase the energy stored by the capacitor is sent back to the source because of this energy consumption is reduced. This is the energy recovery technique which happens in adiabatic logics.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121338791","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708592
Valaparla Rohini, Kuchipudi Prasanth Kumar
One of the diseases that affects humans is brain tumor. It is a type of malignancy disease. A brain tumor is aberrant brain cells that has grown out of control in the brain. This sickness affects many people, and it might be difficult to survive in large groups. When allowing people for early detection of brain tumor, it will help to survive and reduce the death rate of people. Detection of aberrant cells formation in brain is very difficult in medical imaging. The Detection is done by using magnetic resonance imaging (MRI). In this paper, ConvNet architecture is proposed with transfer learning to detect tumor and it aims to differentiate the tumor area by using ROI and non-ROI. The data set is taken from open source Kaggle repository. This model obtained 98.1% accuracy on test data set. This model performed state of the art work.
{"title":"ConvNet Based Detection and Segmentation of Brain Tumor from MR Images","authors":"Valaparla Rohini, Kuchipudi Prasanth Kumar","doi":"10.1109/ICSTCEE54422.2021.9708592","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708592","url":null,"abstract":"One of the diseases that affects humans is brain tumor. It is a type of malignancy disease. A brain tumor is aberrant brain cells that has grown out of control in the brain. This sickness affects many people, and it might be difficult to survive in large groups. When allowing people for early detection of brain tumor, it will help to survive and reduce the death rate of people. Detection of aberrant cells formation in brain is very difficult in medical imaging. The Detection is done by using magnetic resonance imaging (MRI). In this paper, ConvNet architecture is proposed with transfer learning to detect tumor and it aims to differentiate the tumor area by using ROI and non-ROI. The data set is taken from open source Kaggle repository. This model obtained 98.1% accuracy on test data set. This model performed state of the art work.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116722783","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708579
B. Chatterjee, Subhrajyoti Sarkar
This study proposes a fault detection and classification algorithm for IEEE 9-bus system using discrete Fourier transform (DFT) and sequence component analysis (SCA). This scheme makes use of only voltage data from single-end of the line. Wide range of simulation has been run to asses the utility and robustness of the scheme. Simulation results reveal that this scheme can be successfully applied on a test system, as fault classification accuracy is 100%.
{"title":"A Discrete Fourier Transform Based Fault Identification Scheme for IEEE 9-bus System","authors":"B. Chatterjee, Subhrajyoti Sarkar","doi":"10.1109/ICSTCEE54422.2021.9708579","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708579","url":null,"abstract":"This study proposes a fault detection and classification algorithm for IEEE 9-bus system using discrete Fourier transform (DFT) and sequence component analysis (SCA). This scheme makes use of only voltage data from single-end of the line. Wide range of simulation has been run to asses the utility and robustness of the scheme. Simulation results reveal that this scheme can be successfully applied on a test system, as fault classification accuracy is 100%.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126181916","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708573
M. Ramesh, S. Mandapati, B. Prasad, B. Kumar
The electrocardiogram (ECG) is a graphical representation of the heart’s electrical activity generated by contraction and relaxation of the heart muscle. An ECG is a vital tool for diagnosing heart conditions. The ECG flag is required for patient care. Early detection of heart disease allows specialists to differentiate between heart illnesses. A growing number of heart diseases necessitated the development of automatic abnormality detection techniques to relieve physicians. Cardiac magnetic resonance (CMR) images are becoming increasingly important in the diagnosis and monitoring of cardiovascular diseases in the nanomaterial of the kernels. As a result of the large amount and diversity of the data available, there are still many unanswered questions when it comes to the description and characterization of nanomaterial. Biomaterials characterization requires minimal information, which can be provided by AI and machine learning algorithms. These representations are also intended to provide an estimate of the CMR image quality in order to facilitate better interpretation and analysis of the CMR images. Also investigated, how quantitative analysis can be used to benefit from the use of these learned image representations during the process of image synthesis.
{"title":"Machine Learning based Cardiac Magnetic Resonance Imaging (CMRI) for Cardiac Disease Detection","authors":"M. Ramesh, S. Mandapati, B. Prasad, B. Kumar","doi":"10.1109/ICSTCEE54422.2021.9708573","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708573","url":null,"abstract":"The electrocardiogram (ECG) is a graphical representation of the heart’s electrical activity generated by contraction and relaxation of the heart muscle. An ECG is a vital tool for diagnosing heart conditions. The ECG flag is required for patient care. Early detection of heart disease allows specialists to differentiate between heart illnesses. A growing number of heart diseases necessitated the development of automatic abnormality detection techniques to relieve physicians. Cardiac magnetic resonance (CMR) images are becoming increasingly important in the diagnosis and monitoring of cardiovascular diseases in the nanomaterial of the kernels. As a result of the large amount and diversity of the data available, there are still many unanswered questions when it comes to the description and characterization of nanomaterial. Biomaterials characterization requires minimal information, which can be provided by AI and machine learning algorithms. These representations are also intended to provide an estimate of the CMR image quality in order to facilitate better interpretation and analysis of the CMR images. Also investigated, how quantitative analysis can be used to benefit from the use of these learned image representations during the process of image synthesis.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129343341","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708585
Sharath Umesh, L. S. Rajan, VV Lakshmi Pathi, Pramod Bandiwad, S. Elumalai, K. Sriram
Cryogenic liquid level detection plays a significant role during the filling of fuel (liquid hydrogen/liquid oxygen) to cryogenic stage in launch vehicles. Optical fiber sensors have been employed for cryogenic liquid level detection utilizing either intensity modulation by refractometry method or wavelength modulation by heat exchange efficiency method. The present study reports a novel wavelength modulation methodology employing multiplexed Fiber Bragg Grating (FBG) Sensors to assess the cryogenic liquid level in a storage tank. Two FBGs bonded over a resistance heater rod 20cm apart act as the sensing element, which will be immersed in the cryogenic fluid. The temperature of the sensing element is periodically increased and corresponding thermal responses of both the FBG sensors are acquired. Heat conductance capacity of cryogenic fluid is higher in liquid state than in gaseous state. The thermal responses of the FBG sensor obtained by assessing the heat transfer characteristics of the surrounding environment, will ascertain its existence in liquid or gaseous cryogenic fluid. By experimental investigation, it is observed that the thermal responses of the FBGs can actively discern between the liquid and gaseous states of cryogenic fluids. Further, with multiplexing capability, numerous FBGs can be fabricated in a single strand of fiber which can be discreet sensing points in order to assess the cryogenic liquid level.
{"title":"Cryogenic liquid level detection using fiber Bragg grating sensor","authors":"Sharath Umesh, L. S. Rajan, VV Lakshmi Pathi, Pramod Bandiwad, S. Elumalai, K. Sriram","doi":"10.1109/ICSTCEE54422.2021.9708585","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708585","url":null,"abstract":"Cryogenic liquid level detection plays a significant role during the filling of fuel (liquid hydrogen/liquid oxygen) to cryogenic stage in launch vehicles. Optical fiber sensors have been employed for cryogenic liquid level detection utilizing either intensity modulation by refractometry method or wavelength modulation by heat exchange efficiency method. The present study reports a novel wavelength modulation methodology employing multiplexed Fiber Bragg Grating (FBG) Sensors to assess the cryogenic liquid level in a storage tank. Two FBGs bonded over a resistance heater rod 20cm apart act as the sensing element, which will be immersed in the cryogenic fluid. The temperature of the sensing element is periodically increased and corresponding thermal responses of both the FBG sensors are acquired. Heat conductance capacity of cryogenic fluid is higher in liquid state than in gaseous state. The thermal responses of the FBG sensor obtained by assessing the heat transfer characteristics of the surrounding environment, will ascertain its existence in liquid or gaseous cryogenic fluid. By experimental investigation, it is observed that the thermal responses of the FBGs can actively discern between the liquid and gaseous states of cryogenic fluids. Further, with multiplexing capability, numerous FBGs can be fabricated in a single strand of fiber which can be discreet sensing points in order to assess the cryogenic liquid level.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128105307","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 : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708548
Satyadhyan Chickerur, P. Ashish
Computational fluid dynamics (CFD) is the visualisation of how a fluid moves and interacts with things as it passes by using applied mathematics, physics, and computational software. The project is designed to simulate fluid flow of a particle based on provided boundary conditions using High Performance Computing (HPC), with two-dimensional picture files as input to the software and fluid flow of a particle generated based on these image data. The Naiver Stokes Equation and the Lattice Boltzmann Equation are used to create these fluid flow particles.The governing equations based on the conservation law of fluid physical characteristics lead the primary structure of thermofluids investigations. Fluid flow is created depending on the item using the three governing equations from the conservation laws of physics. CFD simulation, on the other hand, which is a Iterative process is frequently computationally costly, memory-intensive, and time-consuming. A model based on convolutional neural networks, is proposed for predicting non-uniform flow in 2D to over come these disadvantages. The proposed approach thus aims to aid the behaviour of fluid particles on a certain system and to assist in the development of the system based on the fluid particles that travel through it. At the early stages of design, this technique can give quick feedback for real-time design revisions. In comparison to previous approximation methods in the aerodynamics domain, CNNs provide for efficient velocity field estimate and took less time then the previous approximation method. As CFD based CNN model is more effective to 2D design(2D aeroplane dataset) as it is in research stage lot more experiments have to be made for 3D designs. Designers and engineers may also use the CFD based CNN model directly in their 2D design space exploration.
{"title":"A Convolutional Neural Network Based Approach for Computational Fluid Dynamics","authors":"Satyadhyan Chickerur, P. Ashish","doi":"10.1109/ICSTCEE54422.2021.9708548","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708548","url":null,"abstract":"Computational fluid dynamics (CFD) is the visualisation of how a fluid moves and interacts with things as it passes by using applied mathematics, physics, and computational software. The project is designed to simulate fluid flow of a particle based on provided boundary conditions using High Performance Computing (HPC), with two-dimensional picture files as input to the software and fluid flow of a particle generated based on these image data. The Naiver Stokes Equation and the Lattice Boltzmann Equation are used to create these fluid flow particles.The governing equations based on the conservation law of fluid physical characteristics lead the primary structure of thermofluids investigations. Fluid flow is created depending on the item using the three governing equations from the conservation laws of physics. CFD simulation, on the other hand, which is a Iterative process is frequently computationally costly, memory-intensive, and time-consuming. A model based on convolutional neural networks, is proposed for predicting non-uniform flow in 2D to over come these disadvantages. The proposed approach thus aims to aid the behaviour of fluid particles on a certain system and to assist in the development of the system based on the fluid particles that travel through it. At the early stages of design, this technique can give quick feedback for real-time design revisions. In comparison to previous approximation methods in the aerodynamics domain, CNNs provide for efficient velocity field estimate and took less time then the previous approximation method. As CFD based CNN model is more effective to 2D design(2D aeroplane dataset) as it is in research stage lot more experiments have to be made for 3D designs. Designers and engineers may also use the CFD based CNN model directly in their 2D design space exploration.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127570689","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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