Uncertainty quantification of the inlet boundary conditions in a supercritical CO2 centrifugal compressor based on the non-intrusive polynomial chaos
Author
Abstract
Suggested Citation
DOI: 10.1016/j.energy.2024.133166
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Liang, Chengbin & Zheng, Qun & Lao, Xingsheng & Jiang, Yuting, 2024. "Enhancing robustness and accuracy of supercritical CO2 compressor performance prediction in closed Brayton cycles: A thermodynamic properties-based numerical method," Energy, Elsevier, vol. 305(C).
- Blatman, Géraud & Sudret, Bruno, 2010. "Efficient computation of global sensitivity indices using sparse polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1216-1229.
- Zhao, Quanbin & Xu, Jiayuan & Hou, Min & Chong, Daotong & Wang, Jinshi & Chen, Weixiong, 2024. "Dynamic characteristic analysis of SCO2 Brayton cycle under different turbine back pressure modes," Energy, Elsevier, vol. 293(C).
- Li, Yuzhe & Zhang, Enbo & Feng, Jiaqi & Zhang, Xu & Yue, Liangyuan & Bai, Bofeng, 2024. "Reduced-dimensional prediction method for the axial aerodynamic forces in the off-design operation of near-critical CO2 centrifugal compressors," Energy, Elsevier, vol. 302(C).
- Kriz, Daniel & Vlcek, Petr & Frybort, Otakar, 2024. "Numerical studies of sCO2 Brayton cycle," Energy, Elsevier, vol. 296(C).
- Romei, Alessandro & Gaetani, Paolo & Persico, Giacomo, 2022. "Computational fluid-dynamic investigation of a centrifugal compressor with inlet guide vanes for supercritical carbon dioxide power systems," Energy, Elsevier, vol. 255(C).
- Jeong, Yongju & Son, Seongmin & Cho, Seong Kuk & Baik, Seungjoon & Lee, Jeong Ik, 2020. "Evaluation of supercritical CO2 compressor off-design performance prediction methods," Energy, Elsevier, vol. 213(C).
- Tang, Xinzi & Wang, Zhe & Xiao, Peng & Peng, Ruitao & Liu, Xiongwei, 2020. "Uncertainty quantification based optimization of centrifugal compressor impeller for aerodynamic robustness under stochastic operational conditions," Energy, Elsevier, vol. 195(C).
- Sudret, Bruno, 2008. "Global sensitivity analysis using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 964-979.
- Xia, Zhiheng & Luo, Jiaqi & Liu, Feng, 2019. "Statistical evaluation of performance impact of flow variations for a transonic compressor rotor blade," Energy, Elsevier, vol. 189(C).
- D'Alessandro, Valerio & Montelpare, Sergio & Ricci, Renato & Zoppi, Andrea, 2017. "Numerical modeling of the flow over wind turbine airfoils by means of Spalart–Allmaras local correlation based transition model," Energy, Elsevier, vol. 130(C), pages 402-419.
- Shields, Michael D. & Zhang, Jiaxin, 2016. "The generalization of Latin hypercube sampling," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 96-108.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Cheng, Kai & Lu, Zhenzhou, 2018. "Sparse polynomial chaos expansion based on D-MORPH regression," Applied Mathematics and Computation, Elsevier, vol. 323(C), pages 17-30.
- Lambert, Romain S.C. & Lemke, Frank & Kucherenko, Sergei S. & Song, Shufang & Shah, Nilay, 2016. "Global sensitivity analysis using sparse high dimensional model representations generated by the group method of data handling," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 128(C), pages 42-54.
- Deman, G. & Konakli, K. & Sudret, B. & Kerrou, J. & Perrochet, P. & Benabderrahmane, H., 2016. "Using sparse polynomial chaos expansions for the global sensitivity analysis of groundwater lifetime expectancy in a multi-layered hydrogeological model," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 156-169.
- Brown, S. & Beck, J. & Mahgerefteh, H. & Fraga, E.S., 2013. "Global sensitivity analysis of the impact of impurities on CO2 pipeline failure," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 43-54.
- Pronzato, Luc, 2019. "Sensitivity analysis via Karhunen–Loève expansion of a random field model: Estimation of Sobol’ indices and experimental design," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 93-109.
- Touzani, Samir & Busby, Daniel, 2013. "Smoothing spline analysis of variance approach for global sensitivity analysis of computer codes," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 67-81.
- Zhang, Xufang & Pandey, Mahesh D., 2014. "An effective approximation for variance-based global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 164-174.
- Li, Jinxing & Liu, Tianyuan & Zhu, Guangya & Li, Yunzhu & Xie, Yonghui, 2023. "Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods," Energy, Elsevier, vol. 273(C).
- Chen, Xin & Molina-Cristóbal, Arturo & Guenov, Marin D. & Riaz, Atif, 2019. "Efficient method for variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 97-115.
- Oladyshkin, S. & Nowak, W., 2012. "Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 179-190.
- Wu, Zeping & Wang, Donghui & Okolo N, Patrick & Hu, Fan & Zhang, Weihua, 2016. "Global sensitivity analysis using a Gaussian Radial Basis Function metamodel," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 171-179.
- Deman, G. & Kerrou, J. & Benabderrahmane, H. & Perrochet, P., 2015. "Sensitivity analysis of groundwater lifetime expectancy to hydro-dispersive parameters: The case of ANDRA Meuse/Haute-Marne site," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 276-286.
- Xiang Peng & Xiaoqing Xu & Jiquan Li & Shaofei Jiang, 2021. "A Sampling-Based Sensitivity Analysis Method Considering the Uncertainties of Input Variables and Their Distribution Parameters," Mathematics, MDPI, vol. 9(10), pages 1-18, May.
- Wong, Chun Yui & Seshadri, Pranay & Parks, Geoffrey, 2021. "Extremum sensitivity analysis with polynomial Monte Carlo filtering," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
- Dubreuil, S. & Berveiller, M. & Petitjean, F. & Salaün, M., 2014. "Construction of bootstrap confidence intervals on sensitivity indices computed by polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 263-275.
- Novák, Lukáš & Valdebenito, Marcos & Faes, Matthias, 2025. "On fractional moment estimation from polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 254(PA).
- Shang, Yue & Nogal, Maria & Teixeira, Rui & Wolfert, A.R. (Rogier) M., 2024. "Extreme-oriented sensitivity analysis using sparse polynomial chaos expansion. Application to train–track–bridge systems," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
- Sudret, B. & Mai, C.V., 2015. "Computing derivative-based global sensitivity measures using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 241-250.
- Anstett-Collin, F. & Goffart, J. & Mara, T. & Denis-Vidal, L., 2015. "Sensitivity analysis of complex models: Coping with dynamic and static inputs," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 268-275.
- Cremona, Marzia A. & Liu, Binbin & Hu, Yang & Bruni, Stefano & Lewis, Roger, 2016. "Predicting railway wheel wear under uncertainty of wear coefficient, using universal kriging," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 49-59.
More about this item
Keywords
Inlet boundary condition uncertainties; Supercritical carbon dioxide centrifugal compressors; Non-intrusive polynomial chaos; Aerodynamic performance; Uncertainty quantification;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:310:y:2024:i:c:s0360544224029414. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.