scholarly journals THERMAL AND EMISSION CHARACTERISTICS OF CARBONISED AND UNCARBONISED RICE HUSK BRIQUETTE, A COMPARATIVE APPROACH

2021 ◽  
Vol 36 (2) ◽  
pp. 10-19
Author(s):  
E.M Ejikeme ◽  
M.S Enemuo ◽  
P.C.N Ejikeme
Keyword(s):  
Rice Husk ◽  
High Power ◽  
International Workshop ◽  
Thermal Characteristics ◽  
Hydraulic Press ◽  
Comparative Approach ◽  
Emission Characteristics ◽  
Water Boiling Test ◽  
Sample Average ◽  
Burning Rates

Production of briquettes from carbonized and uncarbonized rice husk using a locally fabricated hydraulic press was studied. Proximate and Fourier Transform Infrared Spectroscopy (FTIR) analyses, thermal characteristics, and emission properties of the briquettes were determined. Thermal and emission characteristics were determined in real-time measurements during Water Boiling Test (WBT) using Laboratory Emissions Monitoring System (LEMS) equipment. The burning rates of the uncarbonized and carbonized briquettes were 14.35541g/min and 6.478456g/min respectively. The specific fuel consumptions of the briquettes were 96.5502g/L and 80.12107g/L for uncarbonized and carbonized respectively.The energy consumption rate of uncarbonized briquette was 203.4046KJ/min while that of carbonized was 157.6007KJ/min. It took uncarbonized sample average cooking power of 1.598235KW and 0.543518KW for thecarbonized briquette. High power particulate matter of uncarbonized briquette was 13.20391mg/MJ while that of carbonized was 0.510256mg/MJ. High power carbonmonoxide of uncarbonized and carbonized briquette were 0.443276g/MJ and -0.00964g/MJ respectively. Both briquettes were categorized as tier four in line with the International Workshop Agreement (IWA), International Organization for Standardization (ISO) standard specification for stove testing. Keywords: Briquette, Carbon Monoxide, Carbonization, Cassava Starch, Rice Husk

Transient Thermal Characteristics of Heat Capacity High Power Diode Lasers

2016 ◽  
Vol 37 (4) ◽  
pp. 422-427
Author(s):  
贾冠男 JIA Guan-nan ◽  
尧 舜 YAO Shun ◽  
高祥宇 GAO Xiang-yu ◽  
兰 天 LAN Tian ◽  
邱运涛 QIU Yun-tao ◽  
...  
Keyword(s):  
Heat Capacity ◽  
High Power ◽  
Diode Lasers ◽  
Thermal Characteristics ◽  
Transient Thermal ◽  
Power Diode

scholarly journals Airborne Particulate Matter from Sparkling Fireworks

2017 ◽  
Vol 6 (1) ◽  
pp. 19
Author(s):  
Haruki Shimazu
Keyword(s):  
Particulate Matter ◽  
Burning Rate ◽  
Airborne Particulate Matter ◽  
Emission Characteristics ◽  
Particulate Matters ◽  
Burning Time ◽  
Airborne Particulate ◽  
Suspended Particulate ◽  
Burning Rates ◽  
The Mean

The present study examines the emission levels of particulate matters (PM) from sparkling fireworks and to know the emission characteristics of PM. Particulate matter <2.5 microns (PM2.5) and suspended particulate matter (SPM) were determined while burning six brands of sparkling fireworks. The average PM concentrations before burning were levels of 10 μg/m3, but the average concentrations after burning were 741 μg/m3 for PM2.5 and 810 μg/m3 for SPM. The mean ratio of the concentrations of PM2.5 and SPM after burning in all of the sparkling fireworks was 0.890. The emissions per firework ranged from 6.5 mg to 151 mg for PM2.5, and from 7.1 mg to 160 mg for SPM. The means of the emissions per combustible amount of the firework ranged from 0.017 to 0.066 mg/mg for PM2.5, and from 0.018 to 0.071 mg/mg for SPM. The influences of the burning time, burning rate and combustible amount of the fireworks on the PM emissions were investigated. As a result, PM2.5 and SPM emissions tend to increase with the burning rates. This suggests that the burning rate of firework have an influence on the PM emissions.

scholarly journals Analysis and Prediction of Thermal Resistance for High Power LED Using GA-SVR

2012 ◽  
Vol 4 ◽  
pp. 153-160
Author(s):  
De Huai Zeng ◽  
Yuan Liu ◽  
Li Li ◽  
De Gui Yu ◽  
Gang Xu
Keyword(s):  
Service Life ◽  
Thermal Resistance ◽  
High Power ◽  
Thermal Characteristics ◽  
Junction Temperature ◽  
Support Vector ◽  
Mean Squared Errors ◽  
Absolute Relative Error ◽  
High Power Led ◽  
Key Factor

With the development of high power LED technology, junction temperature as a key factor constrains the performance and the service life of LED, and the main parameter of junction temperature is thermal resistance. Therefore, how to measure the thermal resistance of high power LED quickly and accurately plays an important part in improving the performance and the service life of LED. In this paper the accurate and fast measurement equipment was applied to study the thermal characteristics of high power LED. The forward-voltage based method was conducted to measure the junction temperature of high power. Then, support vector regression (SVR) combined with genetic algorithm (GA) for its parameter optimization, was proposed to establish a model to predict the thermal resistance of high power LED. The prediction performance of GA-SVR was compared with those of BPNN model. The result demonstrated that the estimated errors GA-SVR models, such as Mean Absolute Relative Error (MARE) and Root Mean Squared Errors (RMSE), all are smaller than those achieved by the BPNN applying identical samples.

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