The investigation of mechanisms in environmental catalysis using time-resolved methods

The formation of nitrogen oxides (NOx) during a combustion process is difficult to avoid because of the large exotherm and the consequent problem of avoiding local high-temperature spikes. Consequently, for many applications, such as for automotive power generation, there will be a continuing need to use catalytic after-treatment to reduce harmful emissions. The investigation of the mechanisms of the key catalytic reactions in environmental catalysis can provide an insight into the action of the catalyst, and time-resolved methods offer a powerful means to study these processes under realistic conditions. The use of Temporal Analysis of Products (TAP) and Steady State Isotopic Transient Kinetic Analysis (SSITKA) methods to investigate the reduction of NOx under various experimental conditions is described. From a detailed analysis of the SSITKA profiles, it is shown that at low temperatures the mechanism for the formation of N-2 and N2O from NO may differ from the conventional high-temperature mechanism. This is supported by density functional theory calculations, which show that the barrier to the formation of N2O from the reaction of N(ads) and NO(ads) may be too high to allow this process to occur at low temperatures. The alternative reaction of NO(ads) + NO(ads) = N2O(g) + O(ads) is shown to be much more favorable and is consistent with the SSITKA analysis. The remarkable effect of hydrogen as a reductant at low temperatures is described, and alternative interpretations of the role of hydrogen are discussed.

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.

Fault Diagnostics for Internal Combustion Engines – Current and Future Techniques

The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

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. 

The reaction path of CO and Fe2O3 in a chemical-looping combustion system

The reaction mechanism of CO and Fe₂O₃ in a chemical-looping combustion (CLC) was studied based on density functional theory (DFT) at B3LYP level in this paper. The structures of all reactants, intermediate, transition structures and products of this reaction had been optimized and characterized. The reaction path was validated by means of the intrinsic reaction coordinate (IRC) approach. The result showed that the reaction was divided into two steps, the adsorbed CO molecule on Fe ₂O₃ surface formed a medium state with one broken Fe-O bond in step1, and in step2, O atom broken here oxidized a subsequent CO molecule in the fuel reactor. Thus, Fe₂O₃ molecule transport O from air to oxide CO continually in the CLC process. The activation energy and rate coefficients of the two steps were also obtained.

An optimized process design for oxymethylene ether production from woody-biomass-derived syngas

The conversion of biomass for the production of liquid fuels can help reduce the greenhouse gas (GHG) emissions that are predominantly generated by the combustion of fossil fuels. Oxymethylene ethers (OMEs) are a series of liquid fuel additives that can be obtained from syngas, which is produced from the gasification of biomass. The blending of OMEs in conventional diesel fuel can reduce soot formation during combustion in a diesel engine. In this research, a process for the production of OMEs from woody biomass has been simulated. The process consists of several unit operations including biomass gasifi- cation, syngas cleanup, methanol production, and conversion of methanol to OMEs. The methodology involved the development of process models, the identification of the key process parameters affecting OME production based on the process model, and the development of an optimal process design for high OME yields. It was found that up to 9.02 tonnes day1 of OME3, OME4, and OME5 (which are suitable as diesel additives) can be produced from 277.3 tonnes day1 of wet woody biomass. Furthermore, an optimal combination of the parameters, which was generated from the developed model, can greatly enhance OME production and thermodynamic efficiency. This model can further be used in a techno- economic assessment of the whole biomass conversion chain to produce OMEs. The results of this study can be helpful for petroleum-based fuel producers and policy makers in determining the most attractive pathways of converting bio-resources into liquid fuels.