prediction of higher heating values of biomass

Prediction of Higher Heating Value Bioorganic Fraction of

There are various correlation models that have been developed previously to prediction gross calorific value (higher heating value, HHV) of solid fuels including biomass waste from

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Prediction of regional agro-industrial wastes

The use of energy from biomass is becoming more common worldwide. This energy source has several benefits that promote its acceptance; it is bio-renewable, non-toxic and biodegradable. To predict its behavior as a fuel during thermal treatment, its characterization is necessary.

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Estimating Heating Values for Gasification Waste-Derived

Introduction. The heating value (lower or higher) is a physical property that is necessary to calculate the ideal gas enthalpy of formation of the coal, which is a parameter of high importance when performing energy calculations around gasification unit operations. In

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Higher heating value prediction of torrefaction char

Higher heating value prediction of torrefaction char produced from non-woody biomass Nitipong SOPONPONGPIPAT( ),Dussadeeporn SITTIKUL,Unchana SAE-UENG Department of Mechanical Engineering, Faculty of Engineering and Industrial Technology,

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C. Y. Yin, Prediction of Higher Heating Value of Biomass

C. Y. Yin, Prediction of Higher Heating Value of Biomass from Proximate and Ultimate Analyses, Fuel, Vol. 90, No. 3, 2011, pp. 1128-1132.

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Prediction of the Heating Value of Biomass Fuel from IR

Spectroscopy is a promising alternative to time-consuming calorimetric experiments for determining an important prop-erty of a fuel: its heating value. This study aims at developing PLS calibration models for the prediction of higher heating values of wood and

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A Simple Prediction Model for Higher Heat Value of Biomass

According to the modified reductance degree, HHV per gram of oxygen consumed of one biomass was identified to be nearly a constant. Thus, two theoretical prediction models for the biomass with and without sulfate (HHV = 873.52(C/3 + H + S/8), HHV = 874.08(C/3 + H)) were established.

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Which One Does Better Predict the Heating Value of Biomass

Which One Does Better Predict the Heating Value of Biomass?Dry Based or As-Received Based Proximate Analysis Results? A. Ozyuguran, H. Haykiri-Acma and S. Yaman [ + -

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The prediction of gross calorific value using infrared (IR

The gross calorific value (GCV) of a fuel, also known as the higher heating value (HHV) or gross heat of combustion, is the amount of heat released by a specified quantity (initially at 25°C) once it is com-busted and the products returned to that temperature.

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Prediction of livestock manure and mixture higher heating

Higher heating value studies have been established related to the HHV estimation of Dried samples were mixed using a steel blade and screened plant biomass (peanut shell, rice straw, corn straw, olive cake, through an 80 mesh screen.

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Higher heating value prediction of torrefaction char

For prediction using proximate analysis data, the mass fraction of fixed carbon and volatile matter had a strong effect on the higher heating value prediction of torrefaction char of non-woody biomass.

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C. Y. Yin, Prediction of Higher Heating Value of Biomass

C. Y. Yin, Prediction of Higher Heating Value of Biomass from Proximate and Ultimate Analyses, Fuel, Vol. 90, No. 3, 2011, pp. 1128-1132.

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Municipal solid waste higher heating value prediction from

Municipal solid waste higher heating value prediction from ultimate analysis using multiple regression and genetic programming techniques (2013) Prediction of higher heating value of solid biomass fuels using artificial intelligence formalisms. BioEnergy Research 7: 681-692. doi: 10.1007/s12155-013-9393-5 Google Scholar.

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Prediction of Higher Heating Value Bioorganic Fraction of

The calorific value is the amount of heat released when a unit mass of material burned completely. Calorific values are generally expressed in two terms, higher heating value (HHV) or gross heating value and lower heating value (LHV) or net heating value.

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Prediction of Higher Heating Value of Solid Biomass Fuels

Dec 13, 2013· Abstract. The higher heating value (HHV) is an important property defining the energy content of biomass fuels. A number of proximate and/or ultimate analysis based predominantly linear correlations have been proposed for predicting the HHV of biomass fuels.

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Prediction of higher heating values of biomass from

Two new empirical correlations based on proximate and ultimate analyses of biomass used for prediction of higher heating value (HHV) are presented in this paper. The correlations have been developed via step-wise linear regression method by using data of biomass samples (from the open literature) of varied origin and obtained from different geographical locations.

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Which One Does Better Predict the Heating Value of Biomass

Ten different linear/nonlinear equations that contain proximate analysis ingredients including or excluding the moisture content were tested by means of least-squares method to predict the HHV (higher heating value). Prediction performance of each equation was evaluated considering the experimental and the predicted values of HHV and the criteria of MAE (mean absolute error), AAE (average absolute error),

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Higher heating value prediction of torrefaction char

Higher heating value prediction of torrefaction char produced from non-woody biomass Nitipong SOPONPONGPIPAT( ),Dussadeeporn SITTIKUL,Unchana SAE-UENG Department of Mechanical Engineering, Faculty of Engineering and Industrial Technology,

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Prediction of higher heating values of biomass from

Two new empirical correlations based on proximate and ultimate analyses of biomass used for prediction of higher heating value (HHV) are presented in this paper. The correlations have been developed via step-wise linear regression method by using data of biomass samples (from the open literature) of varied origin and obtained from different geographical locations.

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Prediction of the Heating Value of Biomass Fuel from IR

Spectroscopy is a promising alternative to time-consuming calorimetric experiments for determining an important prop-erty of a fuel: its heating value. This study aims at developing PLS calibration models for the prediction of higher heating values of wood and

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