Chaoning Lin

Dr. Chaoning Lin

Delft University of Technology
orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 August 2019 in Neural Computing and Applications
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Journal Article
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CLChaoning Lin
Chaoning Lin
Tongchun LiTongchun Li
Tongchun Li
Siyu ChenSiyu Chen
Siyu Chen
XLXiaoqing Liu
Xiaoqing Liu
CLChuan Lin
Chuan Lin
SLSiling Liang
Siling Liang

1 December 2020 in Measurement
Verified
Journal Article
Closed access
Siyu ChenSiyu Chen
Siyu Chen
CGChongshi Gu
Chongshi Gu
CLChaoning Lin
Chaoning Lin
YWYao Wang
Yao Wang
Mohammad Amin Hariri-ArdebiliMohammad Amin Hariri-Ardebili
Mohammad Amin Hariri-Ardebili

11 January 2020 in Engineering with Computers
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Journal Article
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Siyu ChenSiyu Chen
Siyu Chen
Chong-Shi GuChong-Shi Gu
Chong-Shi Gu
CLChaoning Lin
Chaoning Lin
KZKang Zhang
Kang Zhang
YZYantao Zhu
Yantao Zhu

1 January 2021 in Journal of Water Resources Planning and Management
Verified
Journal Article
Closed access
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Wei GeWei Ge
Wei Ge
XWXiuwei Wang
Xiuwei Wang
ZLZongkun Li
Zongkun Li
HZHexiang Zhang
Hexiang Zhang
XGXinyan Guo
Xinyan Guo
Pieter Van GelderPieter Van Gelder
Pieter Van Gelder
Both hydrodynamic factors and social factors have large impacts on the loss of life caused by dam failure. Relatively large uncertainty intervals of the influencing factors lead to changes in the potential loss of life. Based on an analysis of the formation mechanism of loss of life, the influencing factors were identified. Combined with interval theory, a method for calculating loss of life and determining the impacts of the influencing factors on loss of life was proposed. The intervals of the exposure rate of the population at risk and the mortality of the exposed population, which are impacted by the major influencing factors such as the flood severity, warning time, understanding of dam failure, and building vulnerability, were recommended. Furthermore, a range of correction coefficients caused by the minor influencing factors, such as the dam failure time, rescue ability, and age distribution, was analyzed. The proposed method was validated by analyzing the losses of life in 21 flooded regions after 10 dam failure events and 2 flash river floods, in which the intervals of the estimated results all contained the actual loss of life. In addition, the ratios of the upper bounds to the corresponding lower bounds of the intervals were all less than 10, which is in accordance with the characteristic that the results of different existing methods vary within an order of magnitude. This is the first work that pays careful attention to the uncertainty intervals of loss of life estimates, and the proposed method effectively determined the severity of the potential loss of life caused by dam failure.

1 March 2021 in Applied Mathematical Modelling
Verified
Journal Article
Closed access
Siyu ChenSiyu Chen
Siyu Chen
CGChongshi Gu
Chongshi Gu
CLChaoning Lin
Chaoning Lin
MHMohammad Amin Hariri-Ardebili
Mohammad Amin Hariri-Ardebili

1 October 2020 in Advances in Engineering Software
Verified
Journal Article
Closed access
CLChaoning Lin
Chaoning Lin
TLTongchun Li
Tongchun Li
Siyu ChenSiyu Chen
Siyu Chen
CLChuan Lin
Chuan Lin
XLXiaoqing Liu
Xiaoqing Liu
TSTaozhen Sheng
Taozhen Sheng