Nonlinear uncertainty impact of geometric variations on aerodynamic performance of low-pressure turbine blades with ultra-high loading under extreme operational conditions

Uncertainty impact of random geometric variations on the aerodynamic performance of low-pressure turbine blades is considerable,which is further amplified by the current ultra-high-lift design trend for weight reduction.Therefore,this uncertainty impact on ultra-highly loaded blades under extreme operational conditions near the margins with potential large-scale open separation is focused on in this study.It is demonstrated that this impact is significant,unfavourable,and nonlinear,which is clearly severer under extreme conditions.In addition to the overall attenuation and notable scattering of specific performance,the operational margins with open separation are also notably scattered with great risk of significant reduction.This scattering and nonlinearity are dominated by the variations in leading-edge thickness.The thinning of leading edge triggers local transition,enhancing downstream friction and reducing resistance to open separation,which is further exacerbated by operational deterioration.However,the opposite thickening yields less benefit,implying nonlinearity.This unfavourable impact highlights the need for robust aerodynamic design,where both a safer operational condition and a more robust blade are indispensable,i.e.,a compromise among performance,weight,and robustness.Besides the necessary limitation of loading levels,a mid-loaded design is recommended to reduce adverse pressure gradients in both the leading edge and rear region of the suction side,which helps to decrease the susceptibility of the transition and open separation to random perturbations.Similar improvements can also be achieved by appropriately thickening the leading edge.

Uncertainty analysis of measured geometric variations in turbine blades and impact on aerodynamic performance

Inevitable geometric variations significantly affect the performance of turbines or even that of entire engines;thus,it is necessary to determine their actual characteristics and accurately estimate their impact on performance.In this study,based on 1781 measured profiles of a typical turbine blade,the statistical characteristics of the geometric variations and the uncertainty impact are analyzed,and some commonly used uncertainty modelling methods based on Principal-Component Analysis(PCA)are verified.The geometric variations are found to be evident,asymmetric,and non-uniform,and the non-normality of the random distributions is non-negligible.The performance is notably affected,which is manifested as an overall offset,a notable scattering,and significant deterioration in several extreme cases.Additionally,it is demonstrated that the PCA reconstruction model is effective in characterizing major uncertainty characteristics of the geometric variations and their impact on the performance with almost the first 10 PCA modes.Based on a reasonable profile error and mean geometric deviation,the Gaussian assumption and stochasticprocess-based model are also found to be effective in predicting the mean values and standard deviations of the performance variations.However,they fail to predict the probability of some extreme cases with high loss.Finally,a Chi-square-based correction model is proposed to compensate for this deficiency.The present work can provide a useful reference for uncertainty analysis of the impact of geometric variations,and the corresponding uncertainty design of turbine blades.

GENERATION AND APPLICATION OF VARIATIONAL GEOMETRIC CONSTRAINTS NETWORK BASED ON ISO'S FEATURE

The concept of variantional geometric constraints network is presented. Basedon ISO's feature, three kinds of variational geometric constraints are defined. The concepts ofmate tree (MT) and loop circuit (LC) are presented. The generation method of well-constrainedvariational geometric constraints network (VGCN) is studied. The network can be applied ingeneration of well-constrained tolerance types and tolerance chains. A simple example is analyzed toshow the scheme to be effective.

Effect of variation in gas distribution on explosion propagation characteristics in coal mines

In order to investigate the effect of variation in the distribution of gas on explosion propagation characteristics in coal mines, experiments were carried out in two different channels with variation in gas concentration and geometry. Flame and pressure transducers were used to track the explosion front velocity. The flame speed (Sf) showed a slight downward trend while the methane concentration varied from 10% to 3% in the experimental channel. The peak overpressure (Pmax) dropped dramatically when compared with normal conditions. As well, the values of Pmax and Sf decreased when the methane concentration dropped from 8% to 6%. The flame speed in the channel, connected to a cylinder with a length varying from 0.5 to 2 m, was greater than that in the normal channel. The peak overpressure was also higher than that under normal conditions because of a higher flame speed and stronger pressure piling up. The values of Pmax and Sf increased with an increase in cylinder length. The research results indicate that damage caused by explosions can be reduced by decreasing the gas concentration, which should be immediately detected in roadways with large cross-sections because of the possibility of greater destruction caused by more serious explosions.

Improved Quality Prediction Model for Multistage Machining Process Based on Geometric Constraint Equation

Product variation reduction is critical to improve process efficiency and product quality, especially for multistage machining process（MMP）. However, due to the variation accumulation and propagation, it becomes quite difficult to predict and reduce product variation for MMP. While the method of statistical process control can be used to control product quality, it is used mainly to monitor the process change rather than to analyze the cause of product variation. In this paper, based on a differential description of the contact kinematics of locators and part surfaces, and the geometric constraints equation defined by the locating scheme, an improved analytical variation propagation model for MMP is presented. In which the influence of both locator position and machining error on part quality is considered while, in traditional model, it usually focuses on datum error and fixture error. Coordinate transformation theory is used to reflect the generation and transmission laws of error in the establishment of the model. The concept of deviation matrix is heavily applied to establish an explicit mapping between the geometric deviation of part and the process error sources. In each machining stage, the part deviation is formulized as three separated components corresponding to three different kinds of error sources, which can be further applied to fault identification and design optimization for complicated machining process. An example part for MMP is given out to validate the effectiveness of the methodology. The experiment results show that the model prediction and the actual measurement match well. This paper provides a method to predict part deviation under the influence of fixture error, datum error and machining error, and it enriches the way of quality prediction for MMP.

The Moduli Space in the Gauged Linear Sigma Model

This is a survey article for the mathematical theory of Witten's Gauged Linear Sigma Model, as developed recently by the authors. Instead of developing the theory in the most general setting, in this paper the authors focus on the description of the moduli.