Demonstration of plasma excited atomic resonance line spectroscopy for on-line measurement of alkali metals in a 20kW bubbling fluidized bed

Fuel ◽  
2004 ◽  
Vol 83 (7-8) ◽  
pp. 791-797 ◽  
Author(s):  
Ville Häyrinen ◽  
Rolf Hernberg ◽  
Martti Aho
Keyword(s):  
Fluidized Bed ◽  
Resonance Line ◽  
Alkali Metals ◽  
Atomic Resonance ◽  
Line Measurement ◽  
Bubbling Fluidized Bed ◽  
On Line

Co-Firing of Steam Coal With High Sulfur Content Lignite in a Bubbling Fluidized Bed Combustor

2005 ◽  
Author(s):  
Nevin Selc¸uk ◽  
Yusuf Gogebakan ◽  
Hakan Altindag
Keyword(s):  
Fluidized Bed ◽  
Molar Ratio ◽  
So2 Emissions ◽  
Molar Ratios ◽  
High Sulfur Content ◽  
Bubbling Fluidized Bed ◽  
On Line ◽  
Emission Behavior ◽  
Nitrogen Contents ◽  
Fluidized Bed Combustor

Combustion and emission behavior of 100 % steam coal (SET 1) and a mixture of 80 % by weight steam coal and 20 % by weight local lignite, characterized by high sulfur and ash contents, (SET 2) were investigated in the 0.3 MWt Middle East Technical University (METU) Atmospheric Bubbling Fluidized Bed Combustor (ABFBC) Test Rig. Experiments were performed with limestone addition at various Ca/S molar ratios with fines recycle. In both sets of experiments, parameters other than Ca/S molar ratio were held as nearly constant as possible. On-line measurements of O2, CO2, CO, SO2, NOx emissions were carried out. Comparisons between the emissions show that lower NOx and SO2 emissions are obtained from combustion of steam coal/lignite mixture compared to those from steam coal only despite higher sulfur and almost equal nitrogen contents of the mixture. Calculated combustion efficiencies were found to be around 98 and 96 % for SET 1 and SET 2, respectively. As for the sulfur retention efficiencies, up to three times higher efficiencies were achieved when steam coal is co-fired with high sulfur lignite.

Capture of Alkali Metals by Kaolin

2003 ◽  
Author(s):  
Khanh-Quang Tran ◽  
M. Kristiina Iisa ◽  
Britt-Marie Steenari ◽  
Oliver Lindqvist ◽  
Magnus Hagstro¨m ◽  
...  
Keyword(s):  
Alkali Metal ◽  
Fluidized Bed ◽  
Alkali Metals ◽  
Fixed Bed ◽  
Capture Efficiency ◽  
Fixed Bed Reactor ◽  
Fluidized Bed Combustion ◽  
Biomass Fuels ◽  
Metal Source ◽  
On Line

Alkali metals present in biomass fuels may cause increased bed agglomeration during fluidized bed combustion. In worst case this may lead to complete defluidization of the bed. Other problems caused by alkali metals include increased fouling and slagging. One possibility to reduce the impact of alkali metals is to add sorbents, e.g. aluminosilicates, to the bed for the capture of alkali metals. In the current investigation, the capture of vapor phase potassium compounds by kaolin was investigated in a fixed bed reactor. The reactor consisted of an alkali metal source placed at a variable temperature from which gaseous potassium compounds were generated, a fixed bed holding the kaolin, and an on-line detector for the alkali metal concentration. The on-line alkali metal detector was based on ionization of alkali metals on hot surfaces and is capable of detecting alkali metals down to ppb levels. This makes it possible to perform experiments at alkali metal concentrations relevant to fluidized bed combustion of biomass fuels. In the experiments, KCl was used as the alkali metal source with inlet concentrations of 0.5–3.5 ppm. The experiments were performed at reactor temperatures of 800–900°C and a contact time of 0.26 s. The capture efficiencies of KCl were always above 97%. The capture efficiency was somewhat higher in oxidizing than in reducing gas atmospheres. In the oxidizing gas atmosphere, the conversion was slightly higher with H2O addition than without. The capture efficiency decreased slightly as temperature or KCl concentration was increased.

scholarly journals On line diagnostics and self-tuning method for the fluidized bed temperature controller

2016 ◽  
Vol 37 (1) ◽  
pp. 31-46
Author(s):  
Jan Porzuczek
Keyword(s):  
Fluidized Bed ◽  
Experimental Verification ◽  
Experimental Studies ◽  
Statistical Process ◽  
Temperature Controller ◽  
Tuning Method ◽  
Bed Temperature ◽  
Bubbling Fluidized Bed ◽  
Self Tuning ◽  
On Line

Abstract The paper presents the method of on-line diagnostics of the bed temperature controller for the fluidized bed boiler. Proposed solution is based on the methods of statistical process control. Detected decrease of the bed temperature control quality is used to activate the controller self-tuning procedure. The algorithm that provides optimal tuning of the bed temperature controller is also proposed. The results of experimental verification of the presented method is attached. Experimental studies were carried out using the 2 MW bubbling fluidized bed boiler.

Reactivity and kinetics of furfural residue air gasification based on-line gas releasing behaviors in a bubbling fluidized bed

2022 ◽  
Vol 237 ◽  
pp. 111871
Author(s):  
Zhenting Zha ◽  
Zefeng Ge ◽  
Yuna Ma ◽  
Mingxun Zeng ◽  
Yujie Tao ◽  
...  
Keyword(s):  
Fluidized Bed ◽  
Furfural Residue ◽  
Bubbling Fluidized Bed ◽  
On Line ◽  
Kinetics Of

Thickness Measurement in the AEM by Macintosh-Based Analysis of Two-Beam Convergent Beam Patterns

1990 ◽  
Vol 48 (2) ◽  
pp. 504-505
Author(s):  
John F. Mansfield ◽  
Douglas C. Crawford
Keyword(s):  
Electron Microscope ◽  
Video Camera ◽  
Thickness Measurement ◽  
Specimen Thickness ◽  
Crystalline Materials ◽  
Beam Dynamic ◽  
Line Measurement ◽  
On Line ◽  
Image Position ◽  
Convergent Beam

A method has been developed that allows on-line measurement of the thickness of crystalline materials in the analytical electron microscope. Two-beam convergent beam electron diffraction (CBED) patterns are digitized from a JEOL 2000FX electron microscope into an Apple Macintosh II microcomputer via a Gatan #673 CCD Video Camera and an Imaging Systems Technology Video 1000 frame-capture board. It is necessary to know the lattice parameters of the sample since measurements are made of the spacing of the diffraction discs in order to calibrate the pattern. The sample thickness is calculated from measurements of the spacings of the fringes that are seen in the diffraction discs. This technique was pioneered by Kelly et al, who used the two-beam dynamic theory of MacGillavry relate the deviation parameter (Si) of the ith fringe from the exact Bragg condition to the specimen thickness (t) with the equation:Where ξg, is the extinction distance for that reflection and ni is an integer.

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