Hydrothermal carbonization of millet stalk and dilute-acid-impregnated millet stalk: combustion behaviors of hydrochars by thermogravimetric analysis and a novel mixed-function fitting method

Fuel ◽  
2020 ◽  
Vol 273 ◽  
pp. 117734 ◽  
Author(s):  
Xiangyuan Dong ◽  
Shuqing Guo ◽  
Minyang Ma ◽  
Huifan Zheng ◽  
Xinjie Gao ◽  
...  
Keyword(s):  
Thermogravimetric Analysis ◽  
Hydrothermal Carbonization ◽  
Dilute Acid ◽  
Function Fitting ◽  
Fitting Method ◽  
Combustion Behaviors

scholarly journals Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors

1993 ◽  
Vol 296 (2) ◽  
pp. 423-433 ◽  
Author(s):  
J R Small
Keyword(s):  
Random Errors ◽  
Flux Control ◽  
Graph Method ◽  
Function Fitting ◽  
Fitting Method ◽  
Simple Extrapolation ◽  
Experimental Errors ◽  
Flux Control Coefficients ◽  
Fitted Function ◽  
Control Coefficients

This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed.

Thermogravimetric studies on co-pyrolysis of raw/torrefied biomass and coal blends

2020 ◽  
Vol 38 (11) ◽  
pp. 1259-1268
Author(s):  
NL Panwar ◽  
Bhautik Gajera ◽  
Sudhir Jain ◽  
BL Salvi
Keyword(s):  
Thermogravimetric Analysis ◽  
Thermal Degradation ◽  
Physicochemical Properties ◽  
Model Fitting ◽  
Cotton Stalk ◽  
Fitting Method ◽  
Torrefied Biomass ◽  
Three Stages ◽  
Thermogravimetric Studies ◽  
Kinetics Of

The pyrolysis and co-pyrolysis behaviours of cotton stalk (CS), torrefied cotton stalk (TCS) and mined coal, as single fuels, and their blends, have been examined through thermogravimetric analysis. Biomass has been torrefied at 250°C for 45 min to enhance physicochemical properties, and then mixed with mined coal for co-pyrolysis. Thermal degradation of CS and TCS is characterized by a reaction. However, this is not the case for mined coal, which shows a single-stage reaction. The thermal degradation of all blends was done in three stages: dehydration; biomass and small mined coal; and lignin or mined coal. A similar trend emerged for mass loss of individual fuels, which depended mainly on their ratios in the blend. The kinetics of pyrolysis and co-pyrolysis of all fuels were calculated at 20°Cmin−1 heating rate using the Coats−Redfern model-fitting method.

A Study of the Peak Boundary Method and Effect Evaluation Based on NaI(TI) Detector for γ-Spectrum Analysis

2013 ◽  
Vol 347-350 ◽  
pp. 1006-1011
Author(s):  
Yao Zong Yang ◽  
Fang Fang ◽  
Jian Feng He ◽  
Jun Jun Ran
Keyword(s):  
Spectrum Analysis ◽  
Gaussian Function ◽  
Comparison Method ◽  
Convergence Result ◽  
Weighting Factor ◽  
Gamma Energy ◽  
Common Boundary ◽  
Function Fitting ◽  
Qualitative Detection ◽  
Fitting Method

In order to accurately analyze the result, which comes from quantitative and qualitative detection based on gamma energy spectrum of NaI(T1) detector, peak boundary has become one of the main factors which influence the spectrum analysis. By implementing some common boundary determining algorithms in the Matlab such as simple comparison method, derivative method, symmetry zero-area method, the full width method and gaussian function fitting method, as well as comparing effectiveness among those algorithm, priority of those boundary algorithms is evaluated. At the same time, because the boundary determining algorithm based on traditional gaussian fitting is not ideal, the new boundary determining algorithm based on the least squares fitting of gaussian function with weighting factor is proposed. The practice verifies that this method is stability and can obtain preferable convergence result in boundary determining of unimodal or combination peaks.

Voltage Sag Source Localization Based on the Voltage Distance Function in Distribution Network

2013 ◽  
Vol 391 ◽  
pp. 607-610 ◽  
Author(s):  
Yu Liu ◽  
Jin Hao Wang ◽  
Chao Ying Yang
Keyword(s):  
Least Squares ◽  
Source Localization ◽  
Distance Function ◽  
Distribution Network ◽  
Voltage Sag ◽  
Sorting Algorithm ◽  
Line Voltage ◽  
Function Fitting ◽  
Fitting Method ◽  
Bus Voltage

To realize voltage sag source localization in distribution network, the paper proposes a function fitting method based on the least squares. Establish a voltage distance function in response to fault distance changes by the line voltage. According to the voltage distance function, combine with the bus voltage after fault to find out likely fault section and distance. Through the sorting algorithm to sort all possible results, weaken the effect of pseudo fault point on the judgment result. Finally the simulation verifies the effectiveness of the method.

Research on Matlab Simulation Output of Optical Current Transformer

2014 ◽  
Vol 981 ◽  
pp. 133-136
Author(s):  
Tao Shen ◽  
Chao Hu ◽  
Qian Ru Yang ◽  
Ming Xin Song ◽  
Xin Lao Wei
Keyword(s):  
Simulation Analysis ◽  
Noise Analysis ◽  
Current Transformer ◽  
Theory Model ◽  
Matlab Simulation ◽  
Arm Processor ◽  
Quartic Curve ◽  
Function Fitting ◽  
Fitting Method ◽  
The Relationship

The theory model of the reflective optical current transformer (OCT) has been established using Jones matrix method, and the proper devices have been chose. According to the characteristics of the transformer’s output, signal processing circuits including photoelectric translating circuit, preamplifier, correlation detector, lowpass filter and ARM processor have been designed. The simulation mode was established in the Matlab environment. The simulation analysis as well as the noise analysis was carried out. Finally, the analysis of the relationship between transformer's input and output was analyzed by using function fitting method. The fitting coefficients and error were given and quadratic or quartic curve fitting was proposed.

Extract Characteristic Parameters of FID Signal Combining Autocorrelation Function with the Least Absolute Value

2012 ◽  
Vol 239-240 ◽  
pp. 1108-1112
Author(s):  
Hui Cui Hao ◽  
Jun Lin ◽  
Bao Feng Tian ◽  
Qi Wan
Keyword(s):  
Autocorrelation Function ◽  
Least Squares Method ◽  
Measurement Data ◽  
Characteristic Parameters ◽  
Absolute Value ◽  
Nonlinear Fitting ◽  
Least Absolute Value ◽  
Function Fitting ◽  
Parameters Extraction ◽  
Fitting Method

FID signal is the envelope of magnetic resonance signal, and the extraction accuracy of characteristic parameters directly influence the accuracy of the hydrogeologic parameters of the inverse interpretation. In order to improve the accuracy of characteristic parameters extraction, made simulation and study combined the autocorrelation function fitting with the least absolute value nonlinear fitting method in different SNR and different noise in this paper. The simulation results showed that, the characteristic parameters fitting error using this method was smaller than that using linear, nonlinear fitting method or the autocorrelation function with the least squares method, within 7% in lower SNR. The field measurement data and inversion results verified the method validity.

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