Coal combustion residues valorisation:Research and development on compressed brick production

This paper presents the results of an experimental investigation on compressive strength of unfired compressed brick obtained with coal combustion residues (CCRs) produced by the Niger Coal Society. Preliminary physical and optical (XRD and SEM) characterisation of coal slag, including lixiviation tests, have been carried out. Cement powder, lateritic clayey soil and sand have been chosen as stabilizing agents for bricks. 12 dosages have been tested and about 300 bricks have been produced with a hand-operated press. Results show uniaxial compressive strengths (UCSs) ranging from 4 MPa to 27 MPa for the highest cement stabilisation ratio. UCS higher than 7.5 MPa have been observed for stabilisation with 20% of laterite +10% cement after 45 days of curing. Obtained bricks showed good mechanical resistance and low weight. No health threat has been detected for the obtained samples. Study developments are oriented towards the analysis of Pozzolanic properties of CCRs, properties of hydrated lime stabilisation, thermal properties and durability assessment.© 2012 Elsevier Ltd. All rights reserved.

Coal Combustion Residuals valorisation through the production of compressed masonry brick

The Niger Coal Society (Societé Nigérienne de Charbon – SONICHAR) produces electricity for local consumption in Tefereyre, 75 km north-west from Agadez, Niger. The coal combustion residuals production is about 150,000 tons per year. In order to reduce this environmental burden and to valorize these by-products, a study focusing on their physical and chemical features as well as on the mechanical resistance of compressed brick has been undertaken. Physical characterization of coal slag, chemical and lixiviation tests have been carried out, assessing the material main parameters, verifying the presence of hazardous composites and elements and comparing the obtained results with the findings of an in-deep literary review. Cement powder has been chosen as stabilizing agent as a preliminary option. Four different dosages have been tested and bricks have been produced with a hand-operated press. Compressive strength has been tested at different days of curing. Results show remarkable uniaxial compressive strengths (UCS) for all the mixes after cure, ranging from 4MPa up to more than 20MPa for the highest stabilization ratio. UCS higher than 5MPa have been observed for 20% and 30% cement stabilization ratios after only 7 days of cure, reaching respectively about 11MPa and 13MPa after 45 days. In conclusion obtained bricks show good mechanical resistance and low weight. No health threat has been detected from the obtained sample. Study developments are oriented towards the feasibility of the utilization of low-cost, locally available stabilization means, notably clay and cohesive soils, and on thermal properties assessment.

Reactions of nitrogen and oxygen surface groups in nanoporous carbons under inert and reducing atmospheres

The reactions of surface functional groups have an important role in controlling conversion of char nitrogen to NOx during coal combustion. This study involved an investigation of the thermal stability and reactions of nitrogen surface functional groups in nanoporous carbons. Four suites of carbons, which were used as models for coal chars, were prepared with a wide range of nitrogen and oxygen contents and types of functional groups. The porous structures of the carbons were characterized by gas adsorption methods while chemical analysis, X-ray photoelectron spectroscopy, and X-ray near edge structure spectroscopy were used to characterize the surface functional groups. Temperature programmed desorption and temperature programmed reduction methods were used to study the reactivity of the surface functional groups during heat treatment under inert and reducing conditions. Heat treatment studies show that the order of stability of the functional groups is quaternary nitrogen > pyridinic > pyrrolic > pyridine N-oxide. Pyridine N-oxide surface groups desorb NO and form N-2 via surface reactions at low temperature. Pyrrolic and pyridinic functional groups decompose and react with surface species to give NH3, HCN, and N-2 as desorption products, but most pyrrolic groups are preferentially converted to pyridinic and quaternary nitrogen. The main desorption product is N-2. Approximately 15-40 wt % of the original nitrogen was retained in the carbons mainly as quaternary nitrogen after heat treatment to 1673 K. The results are discussed in terms of decomposition ranges for surface functional groups and reaction mechanisms of surface species.

Inhibitory Effect of Phosphonium-Based Ionic Liquids on Coal Oxidation

To develop a chemical inhibitor that can efficiently suppress coal oxidation, nine tetraalkylphosphonium-based ionic liquids (ILs) and one imidazolium-based IL [1-allyl-3-methylimidazolium chloride ([AMIm]Cl)] were examined as additives. These ILs were used to treat and investigate the inhibitory effect on the oxidation activity and the structure of lignite coal. Characterization using thermogravimetric analysis showed that phosphonium-based ILs are able to inhibit coal oxidation up to 400 degrees C with the tributylethylphosphonium diethylphosphate ([P-4,P-4,P-4,P-2][DEP]) found to be the most effective. In contrast to the tetraalkylphosphonium-based ILs, inhibition using [AMIm]Cl was only found to be effective at temperatures below 250 degrees C, indicating that the tetraallcylphosphonium-based ILs may be more suitable for the future application of suppressing coal spontaneous combustion over a wide range of temperatures. Fourier transform infrared spectroscopic data showed that the various functional groups change in the coal following IL treatment, which are a decrease in the minerals and hydrogen bonds in all treated coals, while decreased aliphatic hydrocarbon and increased carbonyl bonds only appeared in some samples. During the oxidation of coal, the decomposition of aliphatic hydrocarbon groups is inhibited and the formation of carbonyl groups is delayed, so that the evolved gas concentration decreased, as shown by the temperature-programmed oxidation-mass spectrometry results. The deployment of the [P-4,P-4,P-4,P-2][ DEP] and tributylmethylphosphonium methylsulfate Its as additives also show good inhibitory effect on coal oxidation over the temperature range studied, and a relatively stronger interaction between [P-4,P-4,P-4,P-2] [DEP] and coal is demonstrated by the additive model.

Process simulation of co-firing torrefied biomass in a 220 MWe coal-fired power plant

Torrefaction based co-firing in a pulverized coal boiler has been proposed for large percentage of biomass co-firing. A 220 MWe pulverized coal-power plant is simulated using Aspen Plus for full understanding the impacts of an additional torrefaction unit on the efficiency of the whole power plant, the studied process includes biomass drying, biomass torrefaction, mill systems, biomass/coal devolatilization and combustion, heat exchanges and power generation. Palm kernel shells (PKS) were torrefied at same residence time but 4 different temperatures, to prepare 4 torrefied biomasses with different degrees of torrefaction. During biomass torrefaction processes, the mass loss properties and released gaseous components have been studied. In addition, process simulations at varying torrefaction degrees and biomass co-firing ratios have been carried out to understand the properties of CO₂ emission and electricity efficiency in the studied torrefaction based co-firing power plant. According to the experimental results, the mole fractions of CO ₂ and CO account for 69-91% and 4-27% in torrefied gases. The predicted results also showed that the electrical efficiency reduced when increasing either torrefaction temperature or substitution ratio of biomass. A deep torrefaction may not be recommended, because the power saved from biomass grinding is less than the heat consumed by the extra torrefaction process, depending on the heat sources. 

Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.