China
Africa
Explore chapters and articles related to this topic
Force-System Resultants and Equilibrium
Published in Richard C. Dorf, The Engineering Handbook, 2018
The more efficient, higher-capacity axial flow compressor is used on most gas turbines (e.g., Figure 69.2 and Figure 69.3). An axial compressor is made up of a number of stages, each stage consisting of a row of rotating blades (airfoils) and a row of stationary blades (called stators) configured so the gas flow is compressed (adverse or unfavorable pressure gradient) as it passes through each stage. It has been said that compressor operation can founder upon a metaphoric rock, and that rock is called stall. Care must be taken in compressor operation and design to avoid the conditions that lead to blade stall, or flow separation. The collective behavior of blade separation can lead to compressor stall or surge, which manifests itself as an instability of gas flow through the entire gas turbine.
Axial Flow Compressors and Fans
Published in Ahmed F. El-Sayed, Aircraft Propulsion and Gas Turbine Engines, 2017
A typical axial compressor depicted in Figure 13.1 has a series of rotating “rotor” blades followed by a stationary “stator” set of blades that are concentric with the axis of rotation. The compressor blades/vanes are relatively flat in section. Each pair of rotors and stators is referred to as a “stage,” and most axial compressors have a number of such stages placed in a row along a common power shaft in the center. The stator blades are required in order to ensure reasonable efficiency; without them the gas would rotate with the rotor blades resulting in a large drop in efficiency. The axial compressor compresses the working fluid (here only air will be treated) by first accelerating the air and then diffusing it to obtain a pressure increase. The air is accelerated in the rotor and then diffused in the stator. This is illustrated in Figure 13.1 where the absolute velocity (C) increases in the rotor and decreases in the diffuser. For successive stages, a saw-teeth pattern for the velocity is obtained, while the static pressure continuously increases in both of the rotor and stator rows of all stages.
Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application
Published in Fuzzy Information and Engineering, 2021
Nadji Hadroug, Ahmed Hafaifa, Abdelhamid Iratni, Mouloud Guemana
The model parameters of the gas-examined turbine were identified with a series of operational data during start-up, shutdown and during phases of normal operation. This identification is necessary for the overall breakdown of the gas turbine system into several subsystems including the axial compressor, high pressure (HP) and base pressure (LP) turbine and the exhaust system. Hence, the reliability tests were carried out on the basis of the historical gas turbine data of failure events and overhauls, given in Table A1 in the appendix, occurring during the operation of this turbine during two years of operation (2018 and 2019). This provides operating data to quantify the reliability of this turbine. As a result of this work, the reliability modeling of twin-shaft Solar TITAN 130, using an approach based on an adaptive neuro-fuzzy inference system will be performed, compared with the usual reliability laws, using real data collected from the operation of this machine.
Evaluation of novel-objective functions in the design optimization of a transonic rotor by using deep learning
Published in Engineering Applications of Computational Fluid Mechanics, 2021
A. Zeinalzadeh, M.R. Pakatchian
Since there was more concern about a reliable numerical simulation of the polar diagrams over compressor airfoils, a comparison between FLUENT® and MISES simulations is also conducted for an arbitrary airfoil of the axial compressor. Figure 4 represents the polar diagrams of an arbitrary thin airfoil simulated by MISES and FLUENT® at . From the figure, there is a remarkable discrepancy in the calculated loss and outflow angles at higher inflow angles and Mach numbers, respectively, which is due to the Kutta condition on the trailing edge of the airfoil which prevents the flow being completely solved in this region at high inflow angles and Mach numbers. In short, it can be inferred that MISES is reliable in predicting the aerodynamic performance of airfoils, and consequently a numerical dataset of the design optimization process is built.
Axial-flow compressor analysis under distorted phenomena at transonic flow conditions
Published in Cogent Engineering, 2018
G Srinivas, K Raghunandana, Shenoy B Satish
An axial compressor is a compressor that can continuously pressurize gases. Transonic axial-flow compressors are extensively used in aircraft engines to produce maximum pressure ratios per stage. An airplane flying at speed of sound creates a disturbance in the air and sends out pressure pulses in all directions and is termed as transonic. High stage pressure ratios are important because they make it possible to reduce the engine weight and size and, hence the investment and operational costs. Performance of transonic compressors has today reached a high level. A small increment in efficiency, for instance, can result in huge savings in fuel costs and determine a key factor for product success. Another important target is the improvement of rotor stability, resulting in a wider working range. The flow field that develops inside a transonic compressor rotor is extremely complex and presents many challenges to compressor designers.