Muhammad Parikesit Wisnubroto, Eka Tarwaca Susila Putra, B. Kurniasih
Spent bleaching earth (SBE) is the largest waste produced by the palm oil industry. However, according to several studies, SBE and its recovery product DBE have the potential as filler materials in NPK fertilizers. This study examines the influence of NPK fertilizer with SBE and DBE as filler materials on soybean plants’ biochemical and agronomic properties. The field-based experiment was done in a single-factor randomized complete block design with 4 replicates. We tested fertilizers of 10% bentonite clay mineral using NPK on a filler basis (control), 5% bentonite clay mineral with 5% SBE of NPK on a filler basis, and 5% bentonite clay mineral with 5% DBE using NPK on a filler basis. The variables observed include soil chemical properties after applying fertilizer, which involves the concentrations of several heavy metals. Biochemical characteristics, including the content of hydrogen peroxide (H2O2) and peroxidase (POD), superoxide dismutase (SOD) activity, malondialdehyde (MDA), relative electrolyte leakage (REL), total phenolic content, and proline content. The agronomic characteristics of soybean plants, including root and shoot dry weight. The data were analyzed using ANOVA and tested using the least significant difference test at a 95% confidence interval. The results indicated that materials of SBE and DBE could partially substitute the filler elements in bentonite clay mineral of NPK fertilizer on a filler basis, and they had the same influence in SOD activity, H2O2 content, POD, MDA, REL, total phenolic, proline and root dry weight and shoot of soybean plants.
{"title":"Biochemical and Agronomic Responses of Soybean (Glycine max L. Merrill) to Spent and Deoiled Bleaching Earth of NPK Fertilization on Filler Basis","authors":"Muhammad Parikesit Wisnubroto, Eka Tarwaca Susila Putra, B. Kurniasih","doi":"10.47836/pjst.32.2.12","DOIUrl":"https://doi.org/10.47836/pjst.32.2.12","url":null,"abstract":"Spent bleaching earth (SBE) is the largest waste produced by the palm oil industry. However, according to several studies, SBE and its recovery product DBE have the potential as filler materials in NPK fertilizers. This study examines the influence of NPK fertilizer with SBE and DBE as filler materials on soybean plants’ biochemical and agronomic properties. The field-based experiment was done in a single-factor randomized complete block design with 4 replicates. We tested fertilizers of 10% bentonite clay mineral using NPK on a filler basis (control), 5% bentonite clay mineral with 5% SBE of NPK on a filler basis, and 5% bentonite clay mineral with 5% DBE using NPK on a filler basis. The variables observed include soil chemical properties after applying fertilizer, which involves the concentrations of several heavy metals. Biochemical characteristics, including the content of hydrogen peroxide (H2O2) and peroxidase (POD), superoxide dismutase (SOD) activity, malondialdehyde (MDA), relative electrolyte leakage (REL), total phenolic content, and proline content. The agronomic characteristics of soybean plants, including root and shoot dry weight. The data were analyzed using ANOVA and tested using the least significant difference test at a 95% confidence interval. The results indicated that materials of SBE and DBE could partially substitute the filler elements in bentonite clay mineral of NPK fertilizer on a filler basis, and they had the same influence in SOD activity, H2O2 content, POD, MDA, REL, total phenolic, proline and root dry weight and shoot of soybean plants.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"10 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140284040","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}
Cement industries are one of the fastest-growing economic sectors in developing nations like Ethiopia. It provides direct and indirect employment opportunities to a huge number of persons and contributes a major part to the nation’s gross domestic product. Thus, the main objective of this study was to analyze the usage of power consumption and rate of production in the particular cement industry. For this purpose, a comprehensive study was conducted in the Messebo cement factory in northern Ethiopia, one of Ethiopia’s key industries, which has unlimitedly contributed to Ethiopian economic development. It was achieved through primary and secondary data from the Messebo cement factory for the last seven years and compared with an actual and designed production rate and power consumption usage value. Besides money lost, profit and efficiency were analyzed based on the values of excess power used and production rate. From the results, the average usage of actual power and rated power has been observed to be 40.43 million kWh per year and 27.72 million kWh per year, respectively. In an average of seven years, the money lost due to excess power consumption and reduced production was estimated at roughly 4.4 million birr per year and 15 million birr per year, respectively.
{"title":"Energy Utilization and Production Assessment in a Cement Industry","authors":"Tsegay Gebru, Narayanan Kalamegam Millerjothi, Nagarajan Mohan Raj, Soundararajan Seenivasan","doi":"10.47836/pjst.32.s1.04","DOIUrl":"https://doi.org/10.47836/pjst.32.s1.04","url":null,"abstract":"Cement industries are one of the fastest-growing economic sectors in developing nations like Ethiopia. It provides direct and indirect employment opportunities to a huge number of persons and contributes a major part to the nation’s gross domestic product. Thus, the main objective of this study was to analyze the usage of power consumption and rate of production in the particular cement industry. For this purpose, a comprehensive study was conducted in the Messebo cement factory in northern Ethiopia, one of Ethiopia’s key industries, which has unlimitedly contributed to Ethiopian economic development. It was achieved through primary and secondary data from the Messebo cement factory for the last seven years and compared with an actual and designed production rate and power consumption usage value. Besides money lost, profit and efficiency were analyzed based on the values of excess power used and production rate. From the results, the average usage of actual power and rated power has been observed to be 40.43 million kWh per year and 27.72 million kWh per year, respectively. In an average of seven years, the money lost due to excess power consumption and reduced production was estimated at roughly 4.4 million birr per year and 15 million birr per year, respectively.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"60 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502935","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}
Mukesh Raju, Theerthamalai Pakkiri, Praveenkumar Marankumar, Prashanth Marankumar, Inamul Hasan
This study represents the aerodynamic design of an Unmanned aerial vehicle intended for surveillance or agriculture with a maximum take weight of 125 kg. Weight estimation and constraint analysis were done based on the Mission profile. Design of Computer-Aided Design (CAD) models were generated for three different configurations using CATIA V5R20 as a high wing, mid-wing, and low wing. Flow analysis was done for the above configurations at various angles of attack. ANSYS 15 was used for the flow Analysis. A Tetrahedron element meshed the model with the minimum required orthogonal quality. Five microns were given to the initial layer height of the prism mesh. Spalart Allmaras model is used as the Turbulence model in the solver. The aerodynamic characteristics of the above configuration obtained from Computational Fluid Dynamics (CFD) results were compared with the DATCOM program and validated with the wind tunnel experimental test data. The open-circuited suction-type Subsonic wind tunnel was employed for the test. The aerodynamic properties for the angle of attack in the range of -2° to 14° angle of attack are calculated using a six-component balance. The study aims to find the Unmanned Aerial Vehicle (UAV) configuration based on the aerodynamic characteristics obtained from the CFD and DATCOM results. High-wing UAVs have better aerodynamic efficiency than the other two configurations.
{"title":"Design and Analysis of UAV Profile for Agriculture and Surveying Application","authors":"Mukesh Raju, Theerthamalai Pakkiri, Praveenkumar Marankumar, Prashanth Marankumar, Inamul Hasan","doi":"10.47836/pjst.32.s1.01","DOIUrl":"https://doi.org/10.47836/pjst.32.s1.01","url":null,"abstract":"This study represents the aerodynamic design of an Unmanned aerial vehicle intended for surveillance or agriculture with a maximum take weight of 125 kg. Weight estimation and constraint analysis were done based on the Mission profile. Design of Computer-Aided Design (CAD) models were generated for three different configurations using CATIA V5R20 as a high wing, mid-wing, and low wing. Flow analysis was done for the above configurations at various angles of attack. ANSYS 15 was used for the flow Analysis. A Tetrahedron element meshed the model with the minimum required orthogonal quality. Five microns were given to the initial layer height of the prism mesh. Spalart Allmaras model is used as the Turbulence model in the solver. The aerodynamic characteristics of the above configuration obtained from Computational Fluid Dynamics (CFD) results were compared with the DATCOM program and validated with the wind tunnel experimental test data. The open-circuited suction-type Subsonic wind tunnel was employed for the test. The aerodynamic properties for the angle of attack in the range of -2° to 14° angle of attack are calculated using a six-component balance. The study aims to find the Unmanned Aerial Vehicle (UAV) configuration based on the aerodynamic characteristics obtained from the CFD and DATCOM results. High-wing UAVs have better aerodynamic efficiency than the other two configurations.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"8 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502863","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}
Dhanya Prakash R Babu, Madhesh Devasenan, Ganeshan Pushpanathan, Mukesh Raju
Investigation of ground effects on Unmanned Aerial Vehicle (UAV) are limited. The UAV's ground effect on the water surface and irregular surfaces has not been studied well. The principal objective of this research is to apply numerical solutions to investigate the flow physics and aerodynamic characteristics of selected NACA4412 airfoil for different h/c and surface roughness conditions in the ground effect scenario. The k-ω turbulence model and compressible RANS equations are solved using the Finite Volume Method (FVM). The simulated data is authenticated with the reference data and compared with the DATCOM data. The results express that the lift coefficient variations for various surface roughness are affected by the h/c proportion. The drag coefficient for various roughness has the same pattern for different ratios and almost has the same difference from high to lower values. The result shows that the DATCOM code cannot predict the aerodynamic characteristics with ground effects.
{"title":"Performance Evaluation of UAV Airfoil Under Various Ground Conditions","authors":"Dhanya Prakash R Babu, Madhesh Devasenan, Ganeshan Pushpanathan, Mukesh Raju","doi":"10.47836/pjst.32.s1.02","DOIUrl":"https://doi.org/10.47836/pjst.32.s1.02","url":null,"abstract":"Investigation of ground effects on Unmanned Aerial Vehicle (UAV) are limited. The UAV's ground effect on the water surface and irregular surfaces has not been studied well. The principal objective of this research is to apply numerical solutions to investigate the flow physics and aerodynamic characteristics of selected NACA4412 airfoil for different h/c and surface roughness conditions in the ground effect scenario. The k-ω turbulence model and compressible RANS equations are solved using the Finite Volume Method (FVM). The simulated data is authenticated with the reference data and compared with the DATCOM data. The results express that the lift coefficient variations for various surface roughness are affected by the h/c proportion. The drag coefficient for various roughness has the same pattern for different ratios and almost has the same difference from high to lower values. The result shows that the DATCOM code cannot predict the aerodynamic characteristics with ground effects.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"402 1-3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502521","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}
Narayanan Kalamegam Millerjothi, Mulualem G. Gebreslassie, Thangavel Nithyanandhan, Barathy Sachuthananthan
One of the most crucial components in any industrial operation is energy. However, the supply is not limitless. One of the key ingredients in cement production is energy, whose cost share ranges from 8 to 15% of overall production costs in developed nations but is much more in undeveloped nations. Therefore, the objective of this extensive research was to carry out a thorough energy conservation audit at the Sheba leather factory, located in the city of Mekelle, in the north region of Ethiopia. The specific objective of this research was to analyse the patterns of power consumption, identify energy-saving techniques, as well as to propose energy-saving recommendations for their implementation. It was obtained using primary and secondary data from the industry personnel. As a result, a total of 19 recommendations for energy saving were found and were forwarded for consideration. These recommendations have the potential to save a total of about $ 29900 annually, but their implementation would cost close to $ 15900, with a payback period of seven months. These recommendations also cover the utilities of the boiler, motors, blower, air compressors, cooling tower, and lighting. In order to lower their energy use, economic benefits are also considered.
{"title":"Assessment of Detailed Energy Conservation Potentials: The Case of the Ethiopian Leather Industry","authors":"Narayanan Kalamegam Millerjothi, Mulualem G. Gebreslassie, Thangavel Nithyanandhan, Barathy Sachuthananthan","doi":"10.47836/pjst.32.s1.03","DOIUrl":"https://doi.org/10.47836/pjst.32.s1.03","url":null,"abstract":"One of the most crucial components in any industrial operation is energy. However, the supply is not limitless. One of the key ingredients in cement production is energy, whose cost share ranges from 8 to 15% of overall production costs in developed nations but is much more in undeveloped nations. Therefore, the objective of this extensive research was to carry out a thorough energy conservation audit at the Sheba leather factory, located in the city of Mekelle, in the north region of Ethiopia. The specific objective of this research was to analyse the patterns of power consumption, identify energy-saving techniques, as well as to propose energy-saving recommendations for their implementation. It was obtained using primary and secondary data from the industry personnel. As a result, a total of 19 recommendations for energy saving were found and were forwarded for consideration. These recommendations have the potential to save a total of about $ 29900 annually, but their implementation would cost close to $ 15900, with a payback period of seven months. These recommendations also cover the utilities of the boiler, motors, blower, air compressors, cooling tower, and lighting. In order to lower their energy use, economic benefits are also considered.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"447 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502692","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}
L. Savarimuthu, Kirubakaran Victor, Preethi Davaraj, Ganeshan Pushpanathan, Raja Kandasamy, Ramshankar Pushpanathan, M. Vinayagam, Sachuthananthan Barathy, Vivek Sivakumar
The technological advancement in all countries leads to massive energy demand. The energy trading companies struggle daily to meet their customers’ power demands. For a good quality, disturbance-free, and reliable power supply, one must balance electricity generation and consumption at the grid level. There is a profound change in distribution networks due to the intervention of renewable energy generation and grid interactions. Renewable energy sources like solar and wind depend on environmental factors and are subject to unpredictable variations. Earlier, energy distribution companies faced a significant challenge in demand forecasting since it is often unpredictable. With the prediction of the ever-varying power from renewable sources, the power generation and distribution agencies are facing a challenge in supply-side predictions. Several forecasting techniques have evolved, and machine learning techniques like the model predictive controller are suitable for arduous tasks like predicting weather-dependent power generation in advance. This paper employs a Model Predictive Controller (MPC) to predict the solar array’s power. The proposed method also includes a system identification algorithm, which helps acquire, format, validate, and identify the pattern based on the raw data obtained from a PV system. Autocorrelation and cross-correlation value between input and predicted output 0.02 and 0.15. The model predictive controller helps to recognize the future response of the corresponding PV plant over a specific prediction horizon. The error variation of the predicted values from the actual values for the proposed system is 0.8. The performance analysis of the developed model is compared with the former existing techniques, and the role and aptness of the proposed system in smart grid digitization is also discussed.
{"title":"Solar Energy Prediction Based on Intelligent Predictive Controller Algorithm","authors":"L. Savarimuthu, Kirubakaran Victor, Preethi Davaraj, Ganeshan Pushpanathan, Raja Kandasamy, Ramshankar Pushpanathan, M. Vinayagam, Sachuthananthan Barathy, Vivek Sivakumar","doi":"10.47836/pjst.32.s1.05","DOIUrl":"https://doi.org/10.47836/pjst.32.s1.05","url":null,"abstract":"The technological advancement in all countries leads to massive energy demand. The energy trading companies struggle daily to meet their customers’ power demands. For a good quality, disturbance-free, and reliable power supply, one must balance electricity generation and consumption at the grid level. There is a profound change in distribution networks due to the intervention of renewable energy generation and grid interactions. Renewable energy sources like solar and wind depend on environmental factors and are subject to unpredictable variations. Earlier, energy distribution companies faced a significant challenge in demand forecasting since it is often unpredictable. With the prediction of the ever-varying power from renewable sources, the power generation and distribution agencies are facing a challenge in supply-side predictions. Several forecasting techniques have evolved, and machine learning techniques like the model predictive controller are suitable for arduous tasks like predicting weather-dependent power generation in advance. This paper employs a Model Predictive Controller (MPC) to predict the solar array’s power. The proposed method also includes a system identification algorithm, which helps acquire, format, validate, and identify the pattern based on the raw data obtained from a PV system. Autocorrelation and cross-correlation value between input and predicted output 0.02 and 0.15. The model predictive controller helps to recognize the future response of the corresponding PV plant over a specific prediction horizon. The error variation of the predicted values from the actual values for the proposed system is 0.8. The performance analysis of the developed model is compared with the former existing techniques, and the role and aptness of the proposed system in smart grid digitization is also discussed.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"46 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502988","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}
Revathy Subbiah Rajaram, Padaga Kumar Babu, Kirubakaran Victor, Raja Kandasamy, Ganeshan Pushpanathan, Vivek Sivakumar, Ramshankar Pushpanathan, M. Vinayagam, Sachuthananthan Barathy
Solar photovoltaics has become the most popular renewable energy source due to its simplicity in installation and maintenance. However, the dependence on the availability of solar energy at the instant makes its operation non-linear. Various optimizing solutions are proposed to rule out this disadvantage. This paper dwells on a machine language approach to solve this problem. A maximal tracker for power points relies on fuzzy logic control. An embedded power optimizer is designed and tested under different environmental conditions through simulation. The results presented allow researchers to test various artificial intelligence techniques for renewable energy extraction processes.
{"title":"Fuzzy Logic-based Power Optimizer for Solar Photovoltaic Power Systems","authors":"Revathy Subbiah Rajaram, Padaga Kumar Babu, Kirubakaran Victor, Raja Kandasamy, Ganeshan Pushpanathan, Vivek Sivakumar, Ramshankar Pushpanathan, M. Vinayagam, Sachuthananthan Barathy","doi":"10.47836/pjst.32.s1.06","DOIUrl":"https://doi.org/10.47836/pjst.32.s1.06","url":null,"abstract":"Solar photovoltaics has become the most popular renewable energy source due to its simplicity in installation and maintenance. However, the dependence on the availability of solar energy at the instant makes its operation non-linear. Various optimizing solutions are proposed to rule out this disadvantage. This paper dwells on a machine language approach to solve this problem. A maximal tracker for power points relies on fuzzy logic control. An embedded power optimizer is designed and tested under different environmental conditions through simulation. The results presented allow researchers to test various artificial intelligence techniques for renewable energy extraction processes.","PeriodicalId":517913,"journal":{"name":"Energy Industry and Industrial Design (Innovations in Energy Utilization and Equipment Design)","volume":"18 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140503241","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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