Benwei Hou

Prof. Dr. Benwei Hou

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

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

Representative Publications

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26 January 2020 in Sustainability
Verified
Journal Article
Open access
PDF file
ZHZhao Han
Zhao Han
DMDonghui Ma
Donghui Ma
BHBenwei Hou
Benwei Hou
WWWei Wang
Wei Wang
The malfunction of the water distribution system (WDS) following severe earthquakes have significant impacts on the post-earthquake rescue. Moreover, the restoration priority of earthquake-induced pipeline damages plays an important role in improving the post-earthquake serviceability of WDS and the “seismic resilience”. Thus, to enhance the seismic resilience of WDS, this study develops a dynamic cost-benefit method and introduces three existing methods to determine the restoration priority of pipeline damages based on a quantitative resilience evaluation framework. In this resilience evaluation framework, the restoration priority is firstly determined. Then the time-varying performance of post-earthquake WDS is modeled as a discrete event dynamic system. In this model, the system state changes after the reparation of pipeline damage, and the system performance is simulated by a hydraulic model to be consistent with the system state. In this study, this method is also tested and compared with other existing methods, and the results show that the system resilience corresponding to the restoration priority obtained by this method is close to that obtained by the global optimization method with a relative difference of less than 3%, whereas the calculation complexity is about 0.4% of the optimization model. It is concluded that this proposed method is valid.

28 August 2021 in Water
Verified
Journal Article
Open access
PDF file
BHBenwei Hou
Benwei Hou
XMXitao Ma
Xitao Ma
Kegong DiaoKegong Diao
Kegong Diao
ZZZilan Zhong
Zilan Zhong
SWShan Wu
Shan Wu
Seismic performance assessment of water distribution systems (WDSs) based on hydraulic simulation is essential for resilience evaluation of WDSs under earthquake disasters. The assessment is mainly to determine how the water supply will be affected due to pipe breaks caused by the earthquake, with the water supply loss estimated based on the loss of supply to nodes. Existing research works usually use the average or overall performance metric of all user nodes as the system performance indicator without considering user nodes’ individual performance and criticality. This paper proposes a framework to evaluate the importance of user nodes considering post-earthquake rescue service and the seismic performance of individual user nodes in the WDS, which supports the pipeline renovation plan to improve the performance of critical user nodes. The importance of user nodes is evaluated by a multi-index model, including the indices for daily service, post-earthquake rescue service, and network topology influence of user nodes. These indices evaluate the importance of user nodes in terms of their roles for daily water service, emergent rescue service, and water transmission to other nodes, respectively. Fragility model of pipelines evaluates the earthquake-induced damages of the WDS, and the seismic performance assessment of the WDS system is performed by the hydraulic model of the WDS with pipeline damages. The proposed framework is implemented in an actual WDS; the results show that the importance classification to user nodes by multi-index approach can identify the critical user nodes for post-earthquake rescue service, which traditional methods may ignore. The importance classification and seismic performance of individual user nodes make it feasible to check the seismic performance of critical user nodes and formulate a targeted pipeline renovation plan to focus limited resources on critical user nodes.

15 August 2022 in Structure and Infrastructure Engineering
Verified
Journal Article
Closed access
BHBenwei Hou
Benwei Hou
QXQianyi Xu
Qianyi Xu
ZZZilan Zhong
Zilan Zhong
JHJunyan Han
Junyan Han
HMHuiquan Miao
Huiquan Miao
XDXiuli Du
Xiuli Du
The reliability assessment of pipeline networks under nature disasters helps to improve the disaster prevention capability and overall resilience of pipeline networks. For the earthquake hazard, the seismic damage of pipelines in the network is usually correlated due to the spatial correlation of critical parameters, including characteristics of pipeline, soil properties and ground motions. This paper proposes a framework to evaluate the seismic reliability of pipeline network under spatially correlated parameters based on the quasi-Monte Carlo (QMC) simulation. The influence of spatial correlated random variables on the seismic reliability of pipeline network is investigated with explicit consideration of the correlated random variables including the peak ground velocity, the wall thickness and the yield stress of pipe segment. The framework has been implemented in seismic reliability evaluation of two pipeline networks. The result shows that the QMC method has better simulation accuracy than the standard MC method under same sampling numbers. The spatial correlations have different influences on the seismic connectivity reliability of pipeline networks with different topological redundancy and parallelism of connective paths from sources to user nodes. For the pipeline network with greater redundancy and parallelism, the model without considering the spatial correlations overestimates the network connectivity reliability.

12 June 2020 in Water
Verified
Journal Article
Open access
PDF file
SWShan Wu
Shan Wu
HHHongquan Han
Hongquan Han
BHBenwei Hou
Benwei Hou
Kegong DiaoKegong Diao
Kegong Diao
Short-term water demand forecasting plays an important role in smart management and real-time simulation of water distribution systems (WDSs). This paper proposes a hybrid model for the short-term forecasting in the horizon of one day with 15 min time steps, which improves the forecasting accuracy by adding an error correction module to the initial forecasting model. The initial forecasting model is firstly established based on the least square support vector machine (LSSVM), the errors time series obtained by comparing the observed values and the initial forecasted values is next transformed into chaotic time series, and then the error correction model is established by the LSSVM method to forecast errors at the next time step. The hybrid model is tested on three real-world district metering areas (DMAs) in Beijing, China, with different demand patterns. The results show that, with the help of the error correction module, the hybrid model reduced the mean absolute percentage error (MAPE) of forecasted demand from (5.64%, 4.06%, 5.84%) to (4.84%, 3.15%, 3.47%) for the three DMAs, compared with using LSSVM without error correction. Therefore, the proposed hybrid model provides a better solution for short-term water demand forecasting on the tested cases.

24 November 2025 in Reliability Engineering & System Safety
Verified
Journal Article
Closed access
BHBenwei Hou
Benwei Hou
RJRui Jia
Rui Jia
TMTianhe Ma
Tianhe Ma
MYMinghao Yuan
Minghao Yuan
CXChengshun Xu
Chengshun Xu

28 January 2025 in Reliability Engineering & System Safety
Verified
Journal Article
Closed access
BHBenwei Hou
Benwei Hou
PCPengxu Chen
Pengxu Chen
XZXudong Zhao
Xudong Zhao
ZCZhilong Chen
Zhilong Chen