R. Krishnan, L. Hauchhum, Rajat Gupta, S. Pattanayak
{"title":"利用近似和终极分析预测生物质较高热值的方程","authors":"R. Krishnan, L. Hauchhum, Rajat Gupta, S. Pattanayak","doi":"10.1109/EPETSG.2018.8658984","DOIUrl":null,"url":null,"abstract":"Biomass is the organic matter produced by photosynthesis which exists on the surface of the earth. They include all waste biomass such as municipal solid waste, municipal bio solids, animal wastes, forestry and agricultural wastes and some types of industrial wastes. Fossil fuels are the main energy resources of the earth. The only natural occurring substitute for fossil fuels is biomass. The main disadvantage of this energy is that it gives only low calorific value. So, calorific value is an important factor to evaluate the fuel quality of a special biomass material in energy applications. Using the values of proximate and ultimate analysis, many predicted equations are available in several literature to predict the higher heating value (HHV)of biomass. In this context, four different biomass species such as paddy straw, paddy husk, coconut husk and coconut shell have been characterized by proximate analysis and ultimate analysis. Further, thirty-one other varieties of biomass material characterization data have also been taken from existing literature for comparison and establishment of trend in variation of behavior. After that, various empirical equations which contain linear and nonlinear terms have taken into consideration for predicting the higher heating values (HHV)of full sample set from both analysis results. Finally validate the predicted HHV with actual HHV.","PeriodicalId":385912,"journal":{"name":"2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Prediction of Equations for Higher Heating Values of Biomass Using Proximate and Ultimate Analysis\",\"authors\":\"R. Krishnan, L. Hauchhum, Rajat Gupta, S. Pattanayak\",\"doi\":\"10.1109/EPETSG.2018.8658984\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Biomass is the organic matter produced by photosynthesis which exists on the surface of the earth. They include all waste biomass such as municipal solid waste, municipal bio solids, animal wastes, forestry and agricultural wastes and some types of industrial wastes. Fossil fuels are the main energy resources of the earth. The only natural occurring substitute for fossil fuels is biomass. The main disadvantage of this energy is that it gives only low calorific value. So, calorific value is an important factor to evaluate the fuel quality of a special biomass material in energy applications. Using the values of proximate and ultimate analysis, many predicted equations are available in several literature to predict the higher heating value (HHV)of biomass. In this context, four different biomass species such as paddy straw, paddy husk, coconut husk and coconut shell have been characterized by proximate analysis and ultimate analysis. Further, thirty-one other varieties of biomass material characterization data have also been taken from existing literature for comparison and establishment of trend in variation of behavior. After that, various empirical equations which contain linear and nonlinear terms have taken into consideration for predicting the higher heating values (HHV)of full sample set from both analysis results. Finally validate the predicted HHV with actual HHV.\",\"PeriodicalId\":385912,\"journal\":{\"name\":\"2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EPETSG.2018.8658984\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 2nd International Conference on Power, Energy and Environment: Towards Smart Technology (ICEPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPETSG.2018.8658984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of Equations for Higher Heating Values of Biomass Using Proximate and Ultimate Analysis
Biomass is the organic matter produced by photosynthesis which exists on the surface of the earth. They include all waste biomass such as municipal solid waste, municipal bio solids, animal wastes, forestry and agricultural wastes and some types of industrial wastes. Fossil fuels are the main energy resources of the earth. The only natural occurring substitute for fossil fuels is biomass. The main disadvantage of this energy is that it gives only low calorific value. So, calorific value is an important factor to evaluate the fuel quality of a special biomass material in energy applications. Using the values of proximate and ultimate analysis, many predicted equations are available in several literature to predict the higher heating value (HHV)of biomass. In this context, four different biomass species such as paddy straw, paddy husk, coconut husk and coconut shell have been characterized by proximate analysis and ultimate analysis. Further, thirty-one other varieties of biomass material characterization data have also been taken from existing literature for comparison and establishment of trend in variation of behavior. After that, various empirical equations which contain linear and nonlinear terms have taken into consideration for predicting the higher heating values (HHV)of full sample set from both analysis results. Finally validate the predicted HHV with actual HHV.