Structural System Reliability Analysis Based on Improved Explicit Connectivity BNs

Qi’ang Wang,Ziyan Wu 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.3

The study proposes an improved Explicit Connectivity Bayesian Networks (ECBNs) for system reliability assessment. The framework combines Analytic Hierarchy Process (AHP) with the traditional ECBNs. AHP is adopted to consider probabilistic dependencies between system components. Judgment matrix is constructed and weight vector, which meets the requirement of a random consistency check, is extracted to describe a conditional probability information of BNs intermediate nodes. The framework is especially suitable for the system with rare damage filed data. In addition, considering the multiple failure modes for the system component, the multi-dimensional Performance Limit State (PLS) function is proposed to estimate the marginal probability for the BNs root nodes. PLSs are properly modeled as interdependent random variables instead of deterministic quantities. Failing to properly account for the dependencies between PLSs, the non-conservative failure probability results will be obtained. Finally, the system reliability can be calculated through the BNs Junction Tree forward inference algorithm, and the most vulnerable components in the system can be identified through backward diagnose inference. The improved ECBNs theory is first applied to the system reliability evaluation for a reinforced concrete bridge to verify its validity.

Multivariate Probabilistic Seismic Demand Model for the Bridge Multidimensional Fragility Analysis

Qi’ang Wang,Ziyan Wu,Shukui Liu 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.9

Seismic fragility analysis for bridges is an essential issue for risk assessment of transportation networks exposed to seismic hazards. Considering multiple Performance Limit States (PLSs) and seismic demand parameters, the study proposes a multidimensional fragility evaluation methodology for engineering structures, and the objective of the paper is to show that the uncertainty and dependence between seismic demand parameters should be considered for fragility analysis. Thus, a new Probabilistic Seismic Demand Model (PSDM) following multivariate logarithmic normal distribution is addressed. Taking PLS correlation into consideration, multidimensional PLS formula is constructed to identify the structural failure domain. A RC bridge is studied to show the proposed theory. To consider bridge column plastic deformation and bearing nonlinear characteristic, nonlinear dynamic analyses are carried out. The bridge multidimensional fragility curves are derived and compared with fragility curves for an individual component. Results indicate that uncertainty and dependence of demand parameters can be properly dealt with by the multivariate PSDM. The multidimensional fragility is higher than fragility of any individual component, and the bridge as a system is more fragile. The ignorance of multiple components contribution to the system will generate an overestimation for the whole structural performance, which is adverse to engineering structural safety.

certainty and Dependence Analysis of Performance Limit State for Structural Multidimensional Fragility Evaluation

Qi’ang Wang,Ziyan Wu,Lu Liu 대한토목학회 2017 KSCE Journal of Civil Engineering Vol.21 No.4

Considering uncertainty and dependence of performance limit states (PLSs), the study addresses a methodology to evaluate multidimensional fragility. The purpose is to identify the PLS uncertainty quantitatively. The dependence between each PLS parameters is also investigated. The limit state band is firstly proposed to describe the bi-dimensional case. Through interval estimation, the band area with a certain confidence level is determined. A reinforcement concrete bridge is used as example to illustrate the proposed approach for developing fragility curves. PLS threshold samples are obtained to formulate limit state function using incremental dynamic analysis. The study investigates the sensitivity of the method for fragility assessment when different confidence levels are considered. In addition, influence of correlation coefficient between PLSs is evaluated. Results show that a fragility interval is obtained with the introduction of limit state band. The interval length decreases as with the reduction of the confidence level. The probability of failure becomes smaller when the dependence between PLSs is ignored, which will result in overestimation of the structural seismic performance

Early Recognition of Pediatric Strokes in the Emergency Department: Epidemiology, Clinical Presentation, and Factors Impeding Stroke Diagnosis in Children

Si Qi Tan(Si Qi Tan),Wen Qi Cher(Wen Qi Cher),Shu-Ling Chong(Shu-Ling Chong),Angelina Su Yin Ang(Angelina Su Yin Ang ),Sashikumar Ganapathy(Sashikumar Ganapathy ),Derrick Wei Shih Chan(Derrick Wei Shi 대한소아신경학회 2022 대한소아신경학회지 Vol.31 No.1

Purpose: Strokes are challenging to diagnose in pediatric emergency departments (EDs) as level of suspicion is low and atypical presentations are common. We analyzed clinical features, epidemiology and factors of delayed identification in arterial ischemic strokes (AIS) and hemorrhagic strokes (HS). Methods: Single-center retrospective cohort study of children aged between 29 days and 18 years old diagnosed with stroke between July 2016 to June 2021. Results: Among 36 children, 11 (30.5%) had AIS, 25 (69.4%) had HS. Median age for AIS was 9 years (interquartile range [IQR], 2 to 9) and HS 9 years (IQR, 1 to 11.5) (P=0.715). Focal neurological deficit was seen in 72.7% of AIS and 20% of HS (P=0.006). Only 18.2% of AIS and 52.0% of HS presented within 6 hours of symptoms. Median time from symptom onset to ED presentation was 24 hours (IQR, 12 to 28) for AIS and 7 hours (IQR, 1.8 to 48) for HS (P=0.595). Most (85.6%) arrived by own transport. Median time from presentation to neuroimaging was 7 hours (IQR, 0.9 to 7) for AIS and 4.8 (IQR, 1.3 to 16.8) hours for HS (P=0.376). Eleven patients, 9/25 (36.0%) HS and 2/11 (18.2%) AIS, did not have stroke as differential diagnosis at ED (P=0.714). Common initial diagnoses were viral illness or headaches. On univariate analysis, age <1 (odds ratio [OR], 17.5; 95% confidence interval [CI], 1.2 to 250.4; P=0.035) and absence of focal neurological deficit (OR, 13.091; 95% CI, 1.5 to 117.9; P=0.022) were significant factors for delayed identification. Conclusion: Index of suspicion for pediatric strokes among caregivers and clinicians should be increased. Public awareness campaigns are recommended.

Towards high-accuracy data modelling, uncertainty quantification and correlation analysis for SHM measurements during typhoon events using an improved most likely heteroscedastic Gaussian process

Qi’ang Wang,Zhi-Jun Liu,Hao-Bo Wang,Zhanguo Ma,Yi-Qing Ni,Jian Jiang,Rui Sun,Hao-Wei Zhu 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.32 No.4

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof- sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

섬모상 매트에 의한 탁수이동차단에 관한 실험적 연구

유지앙화 ( Ji Ang Hua Yu ),이치타오 ( Qi Ta O Yi ),김영철 ( Young Chul Kim ) 한국물환경학회 2010 한국물환경학회지 Vol.26 No.1