Advanced monitoring necessitates employing fault diagnostics in solar photovoltaic (SPV) systems, as these diagnostics can alert users to potential catastrophic failures or heightened risks. Analyzing various flaws in photovoltaic systems is essential because these defects can cause energy shortfalls, system malfunctions, and fire hazards, which are often challenging to avert. To provide green and clean energy through solar power, this work aims to enhance efficiency by conducting further research. This includes modeling the Solar Photovoltaic system, estimating its parameters, and examining the different types of Solar Photovoltaic failures.
{"title":"Advancements in Modeling, Estimation Techniques, and Fault Analysis in Solar Photovoltaic Systems: A Comprehensive Review","authors":"Manju, Rajendra Kumar, Soma Rajwade, Praveen Kumar Yadaw, Akash ingle, Mukendra Kumar Sahu","doi":"10.56556/jtie.v3i2.917","DOIUrl":"https://doi.org/10.56556/jtie.v3i2.917","url":null,"abstract":"Advanced monitoring necessitates employing fault diagnostics in solar photovoltaic (SPV) systems, as these diagnostics can alert users to potential catastrophic failures or heightened risks. Analyzing various flaws in photovoltaic systems is essential because these defects can cause energy shortfalls, system malfunctions, and fire hazards, which are often challenging to avert. To provide green and clean energy through solar power, this work aims to enhance efficiency by conducting further research. This includes modeling the Solar Photovoltaic system, estimating its parameters, and examining the different types of Solar Photovoltaic failures.","PeriodicalId":502950,"journal":{"name":"Journal of Technology Innovations and Energy","volume":" 1089","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363657","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}
Several studies in the theory of sampling survey have established the fact that the use of auxiliary information at the planning and estimation stages helps in enhancing the efficiency of estimators for estimating population parameters like population mean, population variance, standard deviation etc. as compared to the estimators which use not auxiliary information. In the present study, four estimators for estimating the population coefficient of variation of the study variable using auxiliary information were proposed. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of approximation using Taylor series approach. Numerical analysis was conducted to justify the efficiencies of the proposed estimators and the results revealed that the proposed estimators are more efficient than the existing estimators considered in the study.
{"title":"On Modification of Some Estimators using Parameters of Auxiliary Information for the Estimation of the Population Coefficient of Variation","authors":"Awwal Adejumobi, Mojeed Abiodun Yunusa, Abdulrahman Rashida, Ahmed Babatunde Issa, Kabiru Abubakar","doi":"10.56556/jtie.v3i1.729","DOIUrl":"https://doi.org/10.56556/jtie.v3i1.729","url":null,"abstract":"Several studies in the theory of sampling survey have established the fact that the use of auxiliary information at the planning and estimation stages helps in enhancing the efficiency of estimators for estimating population parameters like population mean, population variance, standard deviation etc. as compared to the estimators which use not auxiliary information. In the present study, four estimators for estimating the population coefficient of variation of the study variable using auxiliary information were proposed. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of approximation using Taylor series approach. Numerical analysis was conducted to justify the efficiencies of the proposed estimators and the results revealed that the proposed estimators are more efficient than the existing estimators considered in the study.","PeriodicalId":502950,"journal":{"name":"Journal of Technology Innovations and Energy","volume":"23 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139803309","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}
Several studies in the theory of sampling survey have established the fact that the use of auxiliary information at the planning and estimation stages helps in enhancing the efficiency of estimators for estimating population parameters like population mean, population variance, standard deviation etc. as compared to the estimators which use not auxiliary information. In the present study, four estimators for estimating the population coefficient of variation of the study variable using auxiliary information were proposed. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of approximation using Taylor series approach. Numerical analysis was conducted to justify the efficiencies of the proposed estimators and the results revealed that the proposed estimators are more efficient than the existing estimators considered in the study.
{"title":"On Modification of Some Estimators using Parameters of Auxiliary Information for the Estimation of the Population Coefficient of Variation","authors":"Awwal Adejumobi, Mojeed Abiodun Yunusa, Abdulrahman Rashida, Ahmed Babatunde Issa, Kabiru Abubakar","doi":"10.56556/jtie.v3i1.729","DOIUrl":"https://doi.org/10.56556/jtie.v3i1.729","url":null,"abstract":"Several studies in the theory of sampling survey have established the fact that the use of auxiliary information at the planning and estimation stages helps in enhancing the efficiency of estimators for estimating population parameters like population mean, population variance, standard deviation etc. as compared to the estimators which use not auxiliary information. In the present study, four estimators for estimating the population coefficient of variation of the study variable using auxiliary information were proposed. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of approximation using Taylor series approach. Numerical analysis was conducted to justify the efficiencies of the proposed estimators and the results revealed that the proposed estimators are more efficient than the existing estimators considered in the study.","PeriodicalId":502950,"journal":{"name":"Journal of Technology Innovations and Energy","volume":"44 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139863055","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}
The present study aims to determine the best and most economical material for a gas turbine blade, which operates under high-temperature conditions and experiences high static structural and thermal loads. To achieve this objective, three different types of material alloys, namely Titanium alloy Ti6AL4V, Magnesium alloy AZ80, and Aluminum alloy 7075-T6, were selected for comparison. A turbine blade model was designed using Solid Works software, and structural and thermal analyses were performed using ANYAS 15.0 under steady-state conditions. The structural analysis aimed to determine the stress, strain, and deformation results on turbine blades by applying high pressure, while the thermal analysis aimed to determine the temperature distribution influences and heat flux generation by applying high temperatures. Based on the results obtained from both analyses of the three different materials, Titanium alloy Ti6AL4V is the best and most economical material. This material showed low stress, strain, and little deformation and the best material properties at high temperatures when compared to Magnesium alloy AZ80 and Aluminum alloy 7075-T6.
{"title":"Investigation of Gas Turbine Blade Materials for Efficient Energy System","authors":"Irfan Ullah, Najma Bashir","doi":"10.56556/jtie.v2i4.680","DOIUrl":"https://doi.org/10.56556/jtie.v2i4.680","url":null,"abstract":"The present study aims to determine the best and most economical material for a gas turbine blade, which operates under high-temperature conditions and experiences high static structural and thermal loads. To achieve this objective, three different types of material alloys, namely Titanium alloy Ti6AL4V, Magnesium alloy AZ80, and Aluminum alloy 7075-T6, were selected for comparison. A turbine blade model was designed using Solid Works software, and structural and thermal analyses were performed using ANYAS 15.0 under steady-state conditions. The structural analysis aimed to determine the stress, strain, and deformation results on turbine blades by applying high pressure, while the thermal analysis aimed to determine the temperature distribution influences and heat flux generation by applying high temperatures. Based on the results obtained from both analyses of the three different materials, Titanium alloy Ti6AL4V is the best and most economical material. This material showed low stress, strain, and little deformation and the best material properties at high temperatures when compared to Magnesium alloy AZ80 and Aluminum alloy 7075-T6.","PeriodicalId":502950,"journal":{"name":"Journal of Technology Innovations and Energy","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139209601","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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