Traditional methods for performance prediction of a turbomachinery are usually based on certain computations from a set of data obtained in limited experiment measurements of the machine, or the machinemodels. Since t...Traditional methods for performance prediction of a turbomachinery are usually based on certain computations from a set of data obtained in limited experiment measurements of the machine, or the machinemodels. Since the computational (mathematical) models used in such performance prediction are often crude, most of the predicted results are only correct in very small ranges around the known data points. Beyond the limited ranges, the accuracy of the resultant predictions decrease abruptly. Therefore, an alternative approach, neural network technique, is studied for performance prediction of turbomachinery. The new approach has been applied to two typical performance prediction cases to verify its feasibility and reliability.展开更多
The article describes an approach to building a self-learning diagnostic algorithm. The self-learning algorithm creates models of the object under consideration. The models are formed periodically through a certain ti...The article describes an approach to building a self-learning diagnostic algorithm. The self-learning algorithm creates models of the object under consideration. The models are formed periodically through a certain time period. The model includes a set of functions that can describe whole object, or a part of the object, or a specified functionality of the object. Thus, information about fault location can be obtained. During operation of the object the algorithm collects data received from sensors. Then the algorithm creates samples related to steady state operation. Clustering of those samples is used for the functions definition. Values of the functions in the centers of clusters are stored in the computer’s memory. To illustrate the considered approach, its application to the diagnosis of turbomachines is described.展开更多
A massive parallel aeroelastic simulation platform has been built to investigate the first1.5-stage fan of an aeroengine at rotating stall.The Computational Fluid Dynamics(CFD)solver and Computational Structural Dynam...A massive parallel aeroelastic simulation platform has been built to investigate the first1.5-stage fan of an aeroengine at rotating stall.The Computational Fluid Dynamics(CFD)solver and Computational Structural Dynamics(CSD)solver are coupled directly by non-matching mesh interfaces.The unsteady rotor/stator interaction is solved by the Sliding Mesh Interface method.The original rotor blades are shrouded by the midspan shrouds.An unshrouded fan is also created to investigate the effects of the midspan shrouds.Both the shrouded fan and unshrouded fan have stable aeroelasticity at the designed state.At rotating stall,the stalled region rotates at 30%of the rotor speed on the absolute reference frame.The energy spectrum of the rotating stalled flow is measured quantitatively.It shows that the first two order excitations are much stronger than the higher order excitations.In the flow of rotating stall,the fifth backward travelling wave mode of shrouded fan is resonated by the fifth excitation of the rotational stalled flow because the rotational speed of the stalled region coincides with the modal rotational speed,while for the unshrouded fan,the first bending mode is resonated by the second excitation of the rotational stalled flow,forming two waves in the circumference of the annulus blades.At rotating stall,the vibration of the shrouded blades is still under control but the vibration of the unshrouded blades is diverged and out of control.A novel tool,i.e.,resonance map,is proposed to predict the resonance.It provides a perspective to explain the effects of midspan shrouds at a theoretical level,and it would also be helpful in the structural design of blades.展开更多
An optimization method to design turbine airfoils using a Genetic Algorithm (GA) design shell coupled directly with a viscous CFD (Computational Fluid Dynamics) analysis code is proposed in this paper. The blade geome...An optimization method to design turbine airfoils using a Genetic Algorithm (GA) design shell coupled directly with a viscous CFD (Computational Fluid Dynamics) analysis code is proposed in this paper. The blade geometry is parameterized and the optimization method is used to search for a blade geometry that will minimize the loss in the turbine cascade passage. The viscous flow prediction code is verified by the experimental data of cascade, which is typical for a gas turbine rotor blade section. A comparative study of the blades designed by the optimization technique and the original one is presented[展开更多
文摘Traditional methods for performance prediction of a turbomachinery are usually based on certain computations from a set of data obtained in limited experiment measurements of the machine, or the machinemodels. Since the computational (mathematical) models used in such performance prediction are often crude, most of the predicted results are only correct in very small ranges around the known data points. Beyond the limited ranges, the accuracy of the resultant predictions decrease abruptly. Therefore, an alternative approach, neural network technique, is studied for performance prediction of turbomachinery. The new approach has been applied to two typical performance prediction cases to verify its feasibility and reliability.
文摘The article describes an approach to building a self-learning diagnostic algorithm. The self-learning algorithm creates models of the object under consideration. The models are formed periodically through a certain time period. The model includes a set of functions that can describe whole object, or a part of the object, or a specified functionality of the object. Thus, information about fault location can be obtained. During operation of the object the algorithm collects data received from sensors. Then the algorithm creates samples related to steady state operation. Clustering of those samples is used for the functions definition. Values of the functions in the centers of clusters are stored in the computer’s memory. To illustrate the considered approach, its application to the diagnosis of turbomachines is described.
文摘A massive parallel aeroelastic simulation platform has been built to investigate the first1.5-stage fan of an aeroengine at rotating stall.The Computational Fluid Dynamics(CFD)solver and Computational Structural Dynamics(CSD)solver are coupled directly by non-matching mesh interfaces.The unsteady rotor/stator interaction is solved by the Sliding Mesh Interface method.The original rotor blades are shrouded by the midspan shrouds.An unshrouded fan is also created to investigate the effects of the midspan shrouds.Both the shrouded fan and unshrouded fan have stable aeroelasticity at the designed state.At rotating stall,the stalled region rotates at 30%of the rotor speed on the absolute reference frame.The energy spectrum of the rotating stalled flow is measured quantitatively.It shows that the first two order excitations are much stronger than the higher order excitations.In the flow of rotating stall,the fifth backward travelling wave mode of shrouded fan is resonated by the fifth excitation of the rotational stalled flow because the rotational speed of the stalled region coincides with the modal rotational speed,while for the unshrouded fan,the first bending mode is resonated by the second excitation of the rotational stalled flow,forming two waves in the circumference of the annulus blades.At rotating stall,the vibration of the shrouded blades is still under control but the vibration of the unshrouded blades is diverged and out of control.A novel tool,i.e.,resonance map,is proposed to predict the resonance.It provides a perspective to explain the effects of midspan shrouds at a theoretical level,and it would also be helpful in the structural design of blades.
文摘An optimization method to design turbine airfoils using a Genetic Algorithm (GA) design shell coupled directly with a viscous CFD (Computational Fluid Dynamics) analysis code is proposed in this paper. The blade geometry is parameterized and the optimization method is used to search for a blade geometry that will minimize the loss in the turbine cascade passage. The viscous flow prediction code is verified by the experimental data of cascade, which is typical for a gas turbine rotor blade section. A comparative study of the blades designed by the optimization technique and the original one is presented[
