Search

Your search keyword '"Yang, Shixi"' showing total 165 results
Start Over Author "Yang, Shixi"
165 results on '"Yang, Shixi"'

1. A neural network-based scale-adaptive cloud-fraction scheme for GCMs

Author

Chen, Guoxing, Wang, Wei-Chyung, Yang, Shixi, Wang, Yixin, Zhang, Feng, and Wu, Kun

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

Cloud fraction significantly affects the short- and long-wave radiation. Its realistic representation in general circulation models (GCMs) still poses great challenges in modeling the atmosphere. Here, we present a neural network-based diagnostic scheme that uses the grid-mean temperature, pressure, liquid and ice water mixing ratios, and relative humidity to simulate the sub-grid cloud fraction. The scheme, trained using CloudSat data with explicit consideration of grid sizes, realistically simulates the observed cloud fraction with a correlation coefficient (r) > 0.9 for liquid-, mixed-, and ice-phase clouds. The scheme also captures the observed non-monotonic relationship between cloud fraction and relative humidity and is computationally efficient, and robust for GCMs with a variety of horizontal and vertical resolutions. For illustrative purposes, we conducted comparative analyses of the 2006-2019 climatological-mean cloud fractions among CloudSat, and simulations from the new scheme and the Xu-Randall scheme (optimized the same way as the new scheme). The network-based scheme improves not only the spatial distribution of the total cloud fraction but also the cloud vertical structure (r > 0.99). For example, the biases of too-many high-level clouds over the tropics and too-many low-level clouds over regions around 60{\deg}S and 60{\deg}N in the Xu-Randall scheme are significantly reduced. These improvements are also found to be insensitive to the spatio-temporal variability of large-scale meteorology conditions, implying that the scheme can be used in different climate regimes.

Published
2023
Full Text
View/download PDF

2. An Adaptive System Identification Framework for Early Detection of Themoacoustic Oscillation in Gas Turbine Combustor

Author

Sun, Jiahao, Gu, Xiwen, Yang, Shixi, Gu, Tingwei, Zang, Peng, IFToMM, Series Editor, Ceccarelli, Marco, Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Agrawal, Sunil K., Advisory Editor, Ball, Andrew D., editor, Ouyang, Huajiang, editor, Sinha, Jyoti K., editor, and Wang, Zuolu, editor

Published
2024
Full Text
View/download PDF

3. A Digital-Twin Assisted Performance Prediction Model for Industrial Gas Turbines

Author

Huang, Qinni, Gu, Xiwen, Shao, Jianwei, Yang, Shixi, IFToMM, Series Editor, Ceccarelli, Marco, Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Agrawal, Sunil K., Advisory Editor, Ball, Andrew D., editor, Ouyang, Huajiang, editor, Sinha, Jyoti K., editor, and Wang, Zuolu, editor

Published
2024
Full Text
View/download PDF

12. A Novel Transfer Learning Method for Robot Bearing Fault Diagnosis Based on Deep Convolutional Residual Wasserstein Adversarial Network

Author

Pan, Bing, Xiong, Xin, Hu, Hailiang, He, Jun, Yang, Shixi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Huayong, editor, Liu, Honghai, editor, Zou, Jun, editor, Yin, Zhouping, editor, Liu, Lianqing, editor, Yang, Geng, editor, Ouyang, Xiaoping, editor, and Wang, Zhiyong, editor

Published
2023
Full Text
View/download PDF

13. Research on Vibration Characteristics of Last Stage Blade Based on Blade Tip-Timing Technology

Author

Hu, Xinyu, Zhuang, Daming, He, Jun, Huang, Haizhou, Yang, Shixi, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Zhang, Hao, editor, Feng, Guojin, editor, Wang, Hongjun, editor, Gu, Fengshou, editor, and Sinha, Jyoti K., editor

Published
2023
Full Text
View/download PDF

14. Research on the Influence of Crack Parameters on the Vibration Characteristics of Gas Turbine Compressor Blades

Author

Yu, Weiwen, Yang, Shixi, Chi, Hongwei, Peng, Zhisheng, He, Jun, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Zhang, Hao, editor, Feng, Guojin, editor, Wang, Hongjun, editor, Gu, Fengshou, editor, and Sinha, Jyoti K., editor

Published
2023
Full Text
View/download PDF

15. A Novel Method for Stacking Optimization of Aeroengine Multi-stage Rotors Based on 3D Deviation Prediction Model

Author

Kang, Jia, He, Jun, Peng, Zhisheng, Huang, Haizhou, Yang, Shixi, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Zhang, Hao, editor, Feng, Guojin, editor, Wang, Hongjun, editor, Gu, Fengshou, editor, and Sinha, Jyoti K., editor

Published
2023
Full Text
View/download PDF

16. Dynamic Behavior Analysis of a Rotor-Bearing-Squeeze Film Damper Coupling System with Bearing Outer Race Localized Defect

Author

Zhou, Chen, He, Jun, Yang, Shixi, Sui, Yongfeng, Xiong, Xin, Gu, Xiwen, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Rizzo, Piervincenzo, editor, and Milazzo, Alberto, editor

Published
2023
Full Text
View/download PDF

28. Exponentially Stabilizing Continuous-Time Controllers for multi-domain hybrid systems with application to 3D bipdeal walking

Author

Gan, Chunbiao, Yuan, Haihui, Yang, Shixi, and Ge, Yimin

Subjects
Computer Science - Systems and Control
Abstract

This paper presents a systematic approach to exponentially stabilize the periodic orbits of multi-domain hybrid systems arising from 3D bipedal walking. Firstly, the method of Poincare sections is extended to the hybrid systems with multiple domains. Then, based on the properties of the Poincare maps, a continuous piecewise feedback control strategy is presented, and three methods are furthermore given to design the controller parameters based on the developed theorems. By those design methods, the controller parameters in each continuous phase can be designed independently, which allows the strategy to be applied to hybrid systems with multiple domains. Finally, the proposed strategy is illustrated by a simulation example. To show that the proposed strategy is not limited to bipedal robots with left-right symmetry property which is assumed in some previous works, an underactuated 3D bipedal robot with asymmetric walking gait is considered., Comment: submitted to IEEE Transactions on Automatic Control

Published
2016

30. DDAGCN: an unsupervised cross-domain identification method for tie rod bolt loosening in a rod-fastening rotor system under different working conditions.

Author

Zhou, Chen, He, Jun, Yang, Shixi, and Xiong, Xin

Subjects
CONVOLUTIONAL neural networks, MARGINAL distributions, FAULT diagnosis, DATA mining, ROTORS, IDENTIFICATION
Abstract

The cross-domain diagnosis of tie rod bolt loosening is essential for guaranteeing the healthy operation of rod-fastening rotor (RFR) systems. The unsupervised domain adaptation (UDA) method effectively alleviates the impact of domain discrepancy and has been applied for cross-domain diagnosis. Traditional UDA methods mainly focus on the marginal and conditional distributions with fixed weights to adapt the domain distribution discrepancy. However, the fixed distribution combination cannot satisfy the requirement of feature domain alignment under different working conditions, and the relative importance of the two distributions cannot be evaluated quantitatively. This paper proposes an improved dynamic distribution adaptive graph convolutional network (DDAGCN) for the cross-domain diagnosis of tie rod bolt loosening under different working conditions. This method can quantitatively evaluate the relative significance of each distribution in representing the distribution discrepancy. First, it combines the convolutional neural network and the graph convolutional network to extract the features in the graph structure by using the connection relationship between nodes, and realizes the full extraction of neighbourhood information of nodes. Then, the dynamic distribution adaptive alignment strategy is introduced to construct the dynamic linear combination of marginal and conditional distributions, so as to measure the distribution discrepancy between domains. Meanwhile, the domain adversarial module is combined to further reduce the domain gap and finally realize feature alignment. The extracted domain invariant features can effectively enhance the generalization ability and fault identification ability of the model. The case of the public bearing dataset verifies that the effectiveness and generalization ability of the proposed method for cross-domain fault diagnosis under different working conditions is superior to other compared methods. In addition, the identification ability of the proposed method for the degree of tie rod bolt loosening is verified by the self-made bolt loosening dataset of the RFR system. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

31. A hybrid modeling method of fatigue crack growth for gas turbine blades under combined high and low cycle fatigue loadings.

Author

Yang, Shixi, Huang, Qinni, Gu, Xiwen, Lan, Jibing, and Sui, Yongfeng

Abstract

Fatigue crack is one of the major faults of the gas turbine blades. Previous modeling studies on fatigue crack growth of blades mainly focus on a single numerical or analytical approach considering different sizes of cracks under various fatigue loadings. However, the actual crack propagation process is time-varying. The iteration and update of the model are necessary to evaluate the fatigue life of blades precisely. This paper proposes a hybrid modeling method to study blade crack growth under combined high and low cycle fatigue (CCF) loadings. The method emphasizes the combination and interaction between the finite element (FE) numerical simulation and the analytical calculation based on the fracture mechanics model. The current crack propagation length of the blade FE model is calculated from the crack growth rate obtained by the stress intensity factor (SIF) range according to Paris law. Then, a new SIF range is resolved from the FE model with the updated crack length. The proposed method is verified by the first-stage compressor blade from an in-service gas turbine. Results show that the crack growth is faster using the proposed hybrid modeling method than the traditional method. The update of the SIF range under CCF loadings cannot be ignored when predicting the fatigue life of the blade. Also, a sensitivity analysis is carried out. Suggestions are given on how to set the crack extension length at each stage during modeling, especially when the blade approaches failure. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

42. A Modulation Signal Bispectrum Enhanced Squared Envelope for the Detection and Diagnosis of Compound Epicyclic Gear Faults

Author

Xu, Yuandong, Feng, Guojin, Tang, Xiaoli, Yang, Shixi, Gu, Fengshou, Ball, Andrew D., Xu, Yuandong, Feng, Guojin, Tang, Xiaoli, Yang, Shixi, Gu, Fengshou, and Ball, Andrew D.

Abstract

Epicyclic gearboxes are prevalent in a variety of important engineering systems such as automotive, aerospace, wind turbines, civil equipment and industrial robots owing to the merits of compact structure and high power density. To ensure the productivities of such important systems, condition monitoring techniques are being actively studied to resolve the challenge of varying transmission paths and multiple modulations in vibration signals acquired from ring gear housing. This paper proposes a new Modulation Signal Bispectrum (MSB) Enhanced Squared Envelope method to analyse the vibration signals acquired by a special On-Rotor Sensing (ORS) transducer that is mounted on the shaft of an epicyclic gearbox. A vibration signal model of ORS measurements from epicyclic gearboxes is presented to show the multiple modulation influences. Moreover, inevitable noise influences are also investigated on the conventional squared envelope and the state-of-the-art spectral correlation analysis. On this base, MSB is introduced to suppress these influences for accurately extracting equally spaced harmonics in the squared envelope and is then integrated to isolate fault signatures, allowing effective fault detection and diagnosis of epicyclic gearboxes, which lead to novel contributions of an MSB Enhanced Squared Envelope (MSB-ESE) approach. An experimental study of compound epicyclic gear faults was conducted to demonstrate the superior performance of MSB-ESE along with the special ORS technique in detecting and diagnosing the compound faults on sun and planet gears.

Published
2023

46. DOA Estimation of Multiple Convolutively Mixed Sources Based on Principle Component Analysis

Author

Jiao, Weidong, Yang, Shixi, Chang, Yongping, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Leung, Chi Sing, editor, Lee, Minho, editor, and Chan, Jonathan H., editor

Published
2009
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results