Abstract

Fuel flexibility will drive the energy demand in the near future. The use of different syngas compositions from various sources will play a major role in the global fuel mix. CO2 in the blends will also be added as a mechanism to improve carbon capture and storage technologies. However, this can trigger instabilities such as thermoacoustics, flashback, autoignition and blowoff. In terms of blowoff, the phenomenon is still not entirely understood. This project presents a series of experiments to determine the behaviour and impact on the blowoff process at various swirl numbers, nozzle geometries and gas compositions. The Central Recirculation Zone was analyzed just before blowoff. The results show how the strength and size of the recirculation zones are highly influenced by these parameters. However, it seems that the CRZ dimensions/strength does not play an important role in the blowoff, whilst the composition of the mixture shows high correlation. Nevertheless, the CRZ intensity using these compositions can increase residence time, important for combustion improvement of other blends.

Effective cooling is required in power generation, processing, and distribution to avoid failure that could occur during operations. As heat loads continue to increase, manufacturers of wind turbines are turning to improve the cooling system to remove high intensity heat loads from many active parts particularly in the generator part. Wind generators need an effective cooling system due to the large amount of heat that is released during power production. Many large wind turbines (more than 5MW rated power) particularly offshore wind turbines where the water is available, heat exchangers with water-air cooling system is used, in which the water is utilized to cool the hot air. This type of heat exchangers are desired, since they are more efficient and reliable than the air-air heat exchangers, which are used in small wind turbines. Because of the growing number of failures that occurred in wind turbine generators due to high generator’s temperatures owing to power losses of generator, applying condition monitoring system on wind generators depending on heat transfer analysis through the heat exchangers of wind generators plays an effective role. This helps avoid failures and maintain wind turbines to be protected. In this paper new methodology has been applied by considering the heat transfer and fluid mechanics analysis through a heat exchanger of wind generator, which uses water to air cooling system. Case study based on data collected from actual measurements demonstrates the adequacy of the proposed model. 

The development and implementation of condition monitoring system become very important for wind industry with the increasing number of failures in wind turbine generators due to over temperature especially in offshore wind turbines where higher maintenance costs than onshore wind farms have to be paid due to their farthest locations. Monitoring the wind generators temperatures is significant and plays a remarkable role in an effective condition monitoring system. Moreover, they can be easily measured and recorded automatically by the Supervisory Control and Data Acquisition (SCADA) which gives more clarification about their behavior trend. An unexpected increase in component temperature may indicate overload, poor lubrication, or possibly ineffective passive or active cooling. Many techniques are used to reliably predict generator's temperatures to avoid occurrence of failures in wind turbine generators. Multiple Linear Regression Model (MLRM) is a model that can be used to construct the normal operating model for the wind turbine generator temperature and then at each time step the model is used to predict the generator temperature by measuring the correlation between the observed values and the predicted values of criterion variables. Then standard errors of the estimate can be found. The standard error of the estimate indicates how close the actual observations fall to the predicted values on the regression line. In this paper, a new condition-monitoring method based on applying Multiple Linear Regression Model for a wind turbine generator is proposed. The technique is used to construct the normal behavior model of an electrical generator temperatures based on the historical generator temperatures data. Case study built on a data collected from actual measurements demonstrates the adequacy of the proposed model.

Abstract

The turbine of an automotive turbocharger is essentially one acoustic element in the exhaust system which lies between the primary noise source, the gas pulsations through the exhaust valves, and the primary noise radiation element, the exhaust tailpipe orifice. As such, like every other acoustic element of the exhaust system, it has a passive effect on the propagation of the primary exhaust noise. Thus if a comprehensive model of the acoustic propagation through the entire exhaust system of a turbocharged engine is sought, an acoustic model of the turbine is a prerequisite.

This paper presents a preliminary attempt to create such a model. The model is a purely fluid mechanic one, without recourse to any empiricism such as a turbine map. The nonlinear equations of the fluid flow are developed and solved for steady flow, to determine the mean convective flow effects upon the noise. The full time-domain equations are then linearised and solved for a single frequency of sound.

Results are given from both the steady flow and the acoustic analyses. The latter are presented in terms of both transmission loss and four-pole parameters. The model is found to give a rational representation of the passive effect of a turbine rotor.

Abstract

This paper presents a one-dimensional acoustic model for prediction of the frequencies of

self-excited oscillation and acoustic mode shapes in combustion systems. The impedance of

the combustion system is represented in terms of a frequency response function (FRF).

Impedances of the settling and combustion chambers are predicted by using the acoustic

model, taking into account the temperature distribution in the combustion chamber. Reasonably

good agreement between measured and predicted acoustic resonance frequencies and

mode shapes was achieved. Some data on stability regimes are discussed.

# 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Combustion; Instability; Eigen-frequencies; Prediction; Measurement

Abstract

Experimental investigations have been carried out to measure axial effective thermal conductivities of

packed beds for a number of particles and catalyst pellets. Measurements were made for three gases (air,

nitrogen and carbon dioxide) in beds packed with ball bearings, copper chromite, chromia alumina, alumina

hollow cylinders and alumina spheres. A glass vacuum vessel was employed for most measurements,

but a thin wall stainless steel vessel was used in a few experiments.

Empirical correlations to predict the axial effective thermal conductivity of packed bed reactors have

been derived from the experimental results.

2002 Elsevier Science Ltd. All rights reserved.

Keywords: Axial thermal conductivities; Packed beds