Due to the increase in the number of failures in the wind turbine generators, the condition monitoring system plays a significant role in overcoming the negative effects resulting from the difficult operation conditions. Mechanical and electrical properties can be combined to detect the faults coming from wind turbine generators by analyzing their behavior under different (normal and abnormal) operation conditions. Studying the trend and effect of the electrical torque pulsations on wind turbine generators under different conditions allows for a proper condition monitoring. In this paper, different methodology has been adopted to develop a proper condition monitoring system on the wind generators by evaluating the generator electrical torque based on mechanical torque and taking into account the acceleration torque, which has not been considered in previous work. Using the electric torque with respect to the rotor angular speed of the generator, when it is running under different operation conditions, indicates the generator health, which is the main methodology of the proposed work. A case study, which is based upon collected data from actual measurements, is presented in this work in order to demonstrate the adequacy of the proposed model.

Due to the increase in the failures of the wind generators, Condition Monitoring System (CMS) plays a significant role in overcoming these failures resulting from the harsh operation conditions. The mechanical, thermal, and electrical analyses can be utilized to detect the faults, which are coming from the wind generators by monitoring the changes in their characteristics under different (normal and abnormal) operation conditions. Observing the trend of the electrical torque pulsations of the wind generators under different conditions is beneficial to perform proper condition monitoring. In this paper, different methodology has been adopted to implement a proper condition monitoring system on the wind generators by evaluating the generator electrical torque based on the mechanical and the acceleration torque. Then, in order to specify the generator faults, the trend of the electrical torque with respect to the rotor angular speed of the wind generator under different operation conditions is analyzed. Further, the rate of change in the generator temperature is considered as well as an indicator to define the health of the wind generators with respect to the induced electrical torque, because of the negative effect of the elevated generator temperature on the induced electrical torque. Case study, which is based upon collected data from actual measurements, is presented in this work in order to demonstrate the adequacy of the proposed model.

This paper presents an application of a condition-monitoring system (CMS) based on a polynomial regression model (PRM) to study the influence of heat loss on a wind generator’s temperatures. Monitoring the wind generator temperatures is a significant for efficient operation, and plays a key role in an effective CMS. Many techniques, including prediction models can be utilized to reliably forecast a wind generator’s temperature during operation and avoid the occurrence of a failure. PRMs are widely used in situations when the relationship between the response and the independent variables are curve-linear. These techniques can be used to construct a normal behavior model of an electrical generator’s temperatures based on recorded data. Many independent variables affect a generator’s temperature; however, the degree of influence of each independent variable on the response is dissimilar. In many situations, adding a new independent variable to the model may cause unsatisfactory results ;therefore, the selection of the variables should be very accurate. A generator’s heat loss can be considered a significant independent variable that greatly influences the wind generator with respect to the other variables. A generator’s heat loss can be estimated in intervals by analyzing the exchange in the heat between the hot and cold fluid through the heat exchangers of wind generators. A case study built on data collected from actual measurements demonstrates the adequacy of the proposed model. 

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.

Abstract –Wings are the main lift generating sources for any aerospace vehicle. The performance of an airborne vehicle largely depends on its wing design. That is why it is important to understand and be able to calculate wing characteristics in every design process. The analysis of the 3 dimensional transonic flow over ONERA M6 wing at two Mach numbers and angles of attack from 0 to 6 degrees and operating Reynolds number of 11x106 is presented. Computational Fluid Dynamics CFD as a widely used analysis and design tool still need to be validated by comparison with experiment. Ansys/Fluent is used to solve the governing equations with k-SST turbulence model. The validation is done through comparing pressure coefficient distributions over wing surfaces at seven span locations, with experimental measurement . Wing geometry is successfully modeled inside Ansys geometry modeler and unstructured mesh is generated with Ansys mesh modler. Results show good agreement with experimental data at Mach number of 0.84 and 3 degrees angle of attack. On the other hand, as Mach number and angle of attack are increased, numerical results show poor accuracy in capturing shock wave position. 

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.

The characteristics of composite materials are of high importance to engineering applications; therefore the increasing use as a substitute for conventional materials, especially in the field of aircraft and space industries. It is a known fact that researchers use finite element programs for the design and analysis of composite structures, use of symmetrical conditions especially in complicated structures, in the modeling and analysis phase of the design, to reduce processing time, memory size required, and simplifying complicated calculations, as well as considering the response of composite structures to different loading conditions to be identical to that of metallic structures. Finite element methods are a popular method used to analyze composite laminate structures. The design of laminated composite structures includes phases that do not exist in the design of traditional metallic structures, for instance, the choice of possible material combinations is huge and the mechanical properties of a composite structure, which are anisotropic by nature, are created in the design phase with the choice of the appropriate fiber orientations and stacking sequence. The use of finite element programs (conventional analysis usually applied in the case of orthotropic materials) to analysis composite structures especially those manufactured using angle ply laminate techniques or a combination of cross and angle ply techniques, as well considering the loading response of the composite structure to be identical to that of structures made of traditional materials, has made the use of, and the results obtained by using such analysis techniques and conditions questionable. Hence, the main objective of this paper is to highlight and present the results obtained when analyzing and modeling symmetrical conditions as applied to commercial materials and that applied to composite laminates. A comparison case study is carried out using cross-ply and angle-ply laminates which concluded that, if the composition of laminate structure is pure cross-ply, the FEA is well suited for predicting the mechanical response of composite structure using principle of symmetry condition. On the other hand that is not the case for angle-ply or mixed-ply laminate structure.

Abstract: This paper presenting the effect of corrugation geometry on the crushing behavior, energy absorption, failure mechanism, and failure mode of woven roving glass fibre/epoxy laminated composite tubes subjected to lateral compression load. A comprehensive experimental program has been carried out on three geometrically different types of composite tubes: radial corrugated composite tubes, cylindrical composite tubes, and corrugated surrounded by cylindrical tubes. The three structures are made of woven roving glass fibre/epoxy 600 g/sqm. All specimens fabricated under the same conditions with a fixed number of layers equal to six.

Modeling of take-off and landing motion for a fixed wing (UAV) is necessary for developing an automatic take off and landing control system (ATOL). Automatic take off and landing system becomes an important system due to wide spread of unmanned aerial vehicles in different applications ranging from intelligence, surveillance, up to missile firing. Automatic take off and landing system reduces damage to an unmanned aerial vehicle and its payload that may be caused by human pilot errors. Furthermore, training human pilot to a sufficient level of skill and experience for takeoff and landing may take several years and significant cost. A human pilot also may impose additional restrictions for UAV operation especially at night time or dusty desert conditions. Although, ATOL adds complexity to the system, it reduces the long run cost and risk caused by takeoff and landing process, and makes UAV takeoff from different runways and at different atmospheric conditions. A mathematical model for takeoff is successfully developed for a small fixed wing UAV. A Matlab/Simulink simulation model is prepared for the ground roll phase, and some simulation results are also shown.