Failure Database Research Articles

Determining the reliability function of the thermal power system in power plant 'Nikola Tesla, Block B1' using the Weibull distribution

The assessment of thermal power system reliability represents a key step towards maintaining the stability and efficiency of the system. Through the application of mathematical models, risk analysis, and maintenance strategies, it is possible to optimise system performance and reduce the risk of failures. This paper presents an assessment of the reliability of the thermal energy system in fossil fuel power plant ‘Nikola Tesla, Block B1’, based on a twelve-year failure database. By implementing the theory of reliability, based on statistics and theory of possibility, and using the simple and complex two-parameter Weibull distribution, the theoretical functions of the failure rate are determined. A significant advantage of such a study is the opportunity of an early and in-depth understanding of the logic and mechanisms of system risk behaviour, and a more precise assessment of its functioning throughout future exploitation.

Presence of Atrial Fibrillation (AF) is a poor prognostic marker in patients with Heart Failure with reduced Ejection Fraction (HFrEF) and Left Bundle Branch Block (LBBB)

Abstract Background Observational data indicate that between 20-30% of patients with HFrEF have LBBB. While numerous independent variables are implicated in the overall prognosis of these patients, this group of patients respond poorly to medical therapy. Presence of AF further impairs the functioning of the left ventricle by several mechanisms e.g., left atrial dilatation, decreased left ventricular filling, irregular cycle length, functional mitral regurgitation etc. Literature is sparse on the cumulative effect of AF in this group of patients. Purpose To assess the effect of AF on left ventricular ejection fraction (LVEF) and mortality in patients presenting with HFrEF and LBBB Methods Single centre, retrospective, observational study over 33 months (Jan 2021 – Sept 2023). Patients with HFrEF and LBBB (as defined by the European Society of Cardiology, 2021) identified from the heart failure database. Results (Table) N=80 Whole cohort: age 74.8 +/- 13.6 years (median:79, range 39-96); 57/80 (67.5%) males. Hypertension [41/80 (51.3%)] was most common comorbidity. Majority were on 3 drugs (23/80, 28.8%) of guideline directed medical therapy (GDMT) with ~1 in 4 patients [19/80 (23.8%)] on all 4 drugs. 32/80 (40.0%) were in AF, remainder in sinus rhythm (SR). Mean baseline LVEF: 21.8 +/- 8.4. Mean LVEF continued to be ≤35% (paired echocardiograms available in 50.0% patients) inspite of GDMT. The QRS duration continued to prolong on follow-up. Patients in AF were statistically significantly older, were less often on all 4 GDMT drugs (particularly sodium glucose transporter 2 inhibitors - SGLT2i’s), and were less likely to survive than those in SR. No difference in comorbid conditions or QRS prolongation on follow-up were seen between patients with AF versus SR. There was trend towards a larger increase in mean LVEF in patients with SR than AF. Conclusions In our experience, patients with HFrEF and LBBB continue to have a high mortality (45.0% at ~ 3 years) inspite of GDMT. AF is seen in a high percentage of patients (40.0%) in this cohort, worsening the prognosis further, with mortality nearly 3 times higher than those in SR. Aggressive management of patients with HFrEF and LBBB with, where indicated, early cardiac resynchronisation therapy (CRT) and more so, of those with AF (with +/- atrioventricular node ablation or left atrial ablation) should be considered at an early stage after diagnosis.Table

Using Neural Networks to Develop a Database of Failures and Emergencies at Hydroelectric Power Stations

Using Neural Networks to Develop a Database of Failures and Emergencies at Hydroelectric Power Stations

Failure analysis and preventative measures on cracking of tube-to-tubesheet joints of the large-scale heat exchanger

A large-scale heat exchanger in an EO/EG plant suffered a severe leakage failure after 3 years of service, and numerous fractures and cracks were found in the tube-to-tubesheet joints. A series of failure investigations, including macroscopic and microscopic inspection, physicochemical analysis, metallographic examination, and stress analysis, have been used to clarify the causes of cracking of tube-to-tubesheet joints. The macroscopic inspection revealed that the cracking of the joints occurred on the tube inlet side, and the fracture exhibited circumferential cracking. Scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS) presented that the fracture is a mixture of transgranular and intergranular cracking (predominantly intergranular), and the surface of the fracture is covered by corrosion products with chlorine, oxygen, and copper content. Furthermore, the stress analysis concluded that the joints were subjected to residual stresses, tensile stresses, and thermal stresses. Therefore, the cracking of the tube-to-tubesheet joints was caused by stress corrosion cracking (SCC), which originated from crevice corrosion and intergranular corrosion. Then, the corrosion mechanism involved in this failure was discussed in detail, and corresponding preventive measures were proposed. Achievements in this paper may supplement the failure database of tube-to-tubesheet joints in large-scale heat exchangers and reduce similar failures through engineering practices.

Detection of congestive heart failure based on Gramian angular field and two-dimensional symbolic phase permutation entropy

Congestive heart failure (CHF) is a serious threat to human health. Electrocardiogram (ECG) signals have been proven to be useful in the detection of CHF. However, the low amplitude and short duration of the ECG signals, as well as the superimposed noise during the real-time acquisition of the signal, seriously affect the CHF detection. To improve the detection rate of CHF, this paper proposes a congestive heart failure detection method based on Gramian angular field (GAF) and two-dimensional symbolic phase permutation entropy (SPPE2D). The significant advantage of this method is that it reduces the sensitivity to noise, and good performance can be obtained without denoising using raw ECG signals. We segment the original ECG signals into 2 s non-overlapping segments and convert them into images using the GAF method. Then, the SPPE2D algorithm is proposed to measure the complexity between normal sinus rhythm (NSR) and CHF, and analyze the anti-noise performance of the algorithm. Finally, the SPPE2D features of GAF images are computed and input into a support vector machine (SVM) for CHF detection. Classification accuracy on the Massachusetts Institute of Technology − Beth Israel Hospital Normal Sinus Rhythm Database and Beth Israel Deaconess Medical Center Congestive Heart Failure Database is 99.59%, sensitivity is 99.42%, specificity is 99.80%, and F1-score is 99.62%. The accuracy of detecting CHF reach more than 97.75% in the other five CHF databases. The experimental results show that the method based on GAF and SPPE2D can effectively detect CHF by images of ECG signals and has good robustness. CHF can be detected using the 2 s sample lengths of ECG signals recording with high sensitivity, giving clinicians ample time to treat patients with CHF.

Prediction of ‘effective’ corrosion rates by in-situ internal pressure creep testing in LBE for Ti-stabilised DIN 1.4970 (15-15Ti) austenitic stainless steel cladding tubes

ABSTRACT In this paper, a new high-temperature methodology for determining the ‘effective’ corrosion rates of internal pressure-tested cladding tubes, based on the reduced creep failure times under exposure, is presented. The methodology has been developed to estimate the combined damage accumulation of corrosion and creep and to establish temperature limits for the use of 1515Ti claddings in high-temperature Lead-Bismuth-Eutectic (LBE). The results are compared to static corrosion rates determined from earlier test campaigns in stagnant LBE. All tests are conducted on 24% cold worked 1515Ti cladding tubes that are the SCK CEN reference material for the MYRRHA design efforts. The virgin material creep model that is the basis for the corrosion rate estimation, has been fitted on an extended creep failure database and a life-fraction rule is applied to accommodate for the life reduction caused by the sought ‘constant’ effective corrosion rate.

P1100 A multivariate time-dependent proportional hazard model to predict development of intestinal failure from Crohn’s Disease

Abstract Background Intestinal Failure (IF) is a rare but severe complication of Crohn’s disease (CD). Advancement in therapy has not eliminated incident IF from CD (CDIF), and risk factors for developing IF from CD are not well characterised. The Copenhagen Intestinal Failure Database contains one of the largest, comprehensively described adult CDIF cohort1 from 1973 to 2018, which can be linked with a Danish nationwide CD cohort2 to explore healthcare utilisation patterns associated with developing IF from onset of CD. Methods CDIF patients from Copenhagen Intestinal Failure Database and a nationwide CD cohort without IF were followed from CD diagnosis until IF, death, or censoring on 31/12/2018. Hospital contacts, surgeries, medication use and employment status were extracted from multiple Danish population-based registries. Unplanned hospitalisation or emergency department attendance (inpatient-contact), CD-related abdominal surgery, and stopping work for 6 months or more (in working-age CD patients, excluding full-time study and parental leave) were considered time-dependent covariates and tested for significance (p<0.05) in univariate proportional hazard models. Significant covariates were then modelled together with additional non-time-dependent clinical and demographic variables in multivariate proportional hazard models. Backward variable selection was performed to derive a final predictive model. Results 175 CDIF and 22845 CD patients from whom data was available were followed for 2283.1 and 293536.5 patient-years, respectively. Univariate time-dependent proportional hazard models showed that every instance of unplanned IBD inpatient contact, CD-related abdominal surgery, and stopping work was significantly associated with increased hazard of developing IF, with a hazard ratio of 4.91 (95% CI 3.54-6.80, p<0.001), 29.79 (95% CI 9.70-91.48, p<0.001) and 1.61 (95% CI 1.15-2.26, p=0.005). In multivariate analysis, earlier decade of IBD onset, unplanned IBD inpatient contacts, length of stay of the inpatient contact, CD-related abdominal surgery, complicated surgery, number of previous admissions and surgeries and previous median-long term unemployment increased the rate of developing IF (Table), whereas age and comorbidity level at CD onset, non-IBD inpatient contacts, type of surgery, biologics use, and current employment status were not found to be significantly associated with IF development. Conclusion This is the first study to demonstrate significantly increased risks of developing IF from CD from increased healthcare utilisation patterns.

P1118 High Crohn’s Disease burden but disproportionally low use of biologics in Crohn’s Disease patients with Intestinal Failure: a longitudinal comparative study from 1973-2018

Abstract Background Patients with Crohn’s Disease (CD) complicated by Intestinal Failure (CDIF) are considered to be among those with the most severe form of CD. Their clinical course before IF onset has not been well characterised. We aimed to describe and compare CD-specific natural history, disease burden and treatment between CDIF patients and CD patients without IF over a 40-year period. Methods CDIF patients from Copenhagen Intestinal Failure Database (1973-2018) and a Danish nationwide CD cohort without IF (1977-2018) were followed from onset of CD until IF, death, or 31/12/2018. Hospital contacts, surgeries, prescription dispensation, employment and mortality data were extracted from multiple population-based registries. Groups were compared using logistic regression for proportions and Poisson regression for rates. Standard mortality ratio (SMR) was calculated against age, gender and year-matched Danish population references, and an adjusted mortality rate ratio between CDIF and CD patients was obtained from Cox models. Results 182 CDIF and 22845 CD patients were followed for 3035.7 and 293536.5 patient-years, respectively. At CD diagnosis, CDIF patients were younger (median age 24 years vs 35 years, p<0.0001), from earlier decades (71.5% vs 16.5% before 1991, p<0.0001), and had fewer comorbidities (6.9% vs 20.4%, p<0.0001). The 10-year cumulative incidence of IF declined from 2.7% in patients diagnosed with CD prior to 1980 to 0.2% in patients diagnosed after 2000, but the number of new CDIF patients has not declined over the decades (Table). A greater proportion CDIF patients received at least 1 course of steroids (70.8% versus 59.8%, p=0.02) and immunomodulators (59.3% vs 48.7%, p=0.03), had IBD-related hospital contacts (98.2% vs 55.2%, p<0.0001) and abdominal surgeries (94.9% vs 47.6%, p<0.0001), and stopped working for >6 months (65.8% vs 57.8% of working-age patients, p=0.05). However, in the biologics era (after 2000), CDIF patients were not treated with biologics more often (20.4% vs 21% had any biologics, p=ns). In those who were treated, CDIF patients had less cumulative time on biologics (3.9 years vs 11.2 years per 100 patient-years, p=0.001). CDIF and CD patients had a SMR of 3.7 (97.5% CI 2.79,4.72) and 1.7 (97.5% CI 1.61, 1.72), respectively. After adjusting for age, sex and co-morbidity, CDIF patients were at 3.42 times risk of dying compared to CD patients. Conclusion The incidence of CDIF has reduced in newly diagnosed CD patients, however the number of new CDIF patients has not yet declined due to increasing CD prevalence. Despite CDIF patients experiencing a significantly higher burden of CD before the onset of IF, they were not more likely to receive biologics. They also appear more refractory to biologics.

Divide and recombine approach for warranty database: estimating the reliability of an automobile component

The continuously updated database of failures and censored data of numerous products has become large, and on some covariates, information regarding the failure times is missing in the database. As the dataset is large and has missing information, the analysis tasks become complicated and a long time is required to execute the programming codes. In such situations, the divide and recombine (D&R) approach, which has a practical computational performance for big data analysis, can be applied. In this study, the D&R approach was applied to analyze the real field data of an automobile component with incomplete information on covariates using the Weibull regression model. Model parameters were estimated using the expectation maximization algorithm. The results of the data analysis and simulation demonstrated that the D&R approach is applicable for analyzing such datasets. Further, the percentiles and reliability functions of the distribution under different covariate conditions were estimated to evaluate the component performance of these covariates. The findings of this study have managerial implications regarding design decisions, safety, and reliability of automobile components.

DEVELOPING ALGORITHM FOR DIGITAL TWIN OF WELDED JOINT IN SHELL STRUCTURE (PART 1)

Most of oil and gas equipment is welded shell-type structures. Their operation may cause accidents of different complexity. Despite the fact that such structures go through technical diagnostics and life cycle analysis, the current accident statistics does not suggest any improvements. Nowadays there is a rapidly-developing line of research that focuses on creating so-called digital twins. These are numerical models that are based on real mechanical characteristics, dimensions and changes that may occur during the operation of the facility. These models allow using diagnostic data for assessing the remaining service life. While mechanical engineering deals with mass-produced products and has a large database of equipment failures, shell-type oil and gas facilities are mostly specific and their reliability database can barely be useful for predicting their performance. A number of studies on digital twins suggest heterogeneity in physical, mechanical and geometric properties pattern of shell-type structures. Some attempts to cover these properties in numerical models proved that it is actually possible to predict the areas where damage would occur most frequently and cause breakdown. However, in order to keep improving the quality of the modelling system, it is necessary to consider the properties of welded joints.This article deals with analyzing welded joints properties which are essential for developing an algorithm for a digital twin of a welded cylindrical shell. The study revises welded joints of pipe billets made of 09G2S steel. The equipment used meets all the standards concerning welded joints. Properties are distributed unevenly across the welded joint, the weld-affected area and the base metal. These areas are exposed to intensive sound waves within the human hearing range. As a result, they generate secondary acoustic emission signals. When intercepted and analyzed, the signals indicate local heterogeneity. Therefore, welded joints produced by joining weldless billet pipes were inspected by secondary acoustic emission analysis and the Expert-19 device. The test allows analyzing the acoustic properties of a sound wave that went through the welded joint. Before the experiment, it was determined how the measured properties correlate with the distance between the Leeb (D-type) sensor and the microphone that detected the sound wave and specified its characteristics for the numerical analysis. The analysis involved a special computer program. The sound-wave propagation was analyzed along the axes of the shell, its circumference and across the width. Since the properties of the welded shells were measured both before and after the welding, the data on distinctive changes all along the structures’ surface has been obtained for the first time. Also the test has for the first time determined the peculiar features of integral parameter distribution within the entire shell. Response level of acoustic-wave propagation to the heterogeneity has been illustrated in terms of both quality and quantity.

Optimal maintenance strategy of wind turbine subassemblies to improve the overall availability

Improving wind turbine performance, operation, and efficiency requires evolving Operation and Maintenance (O&M) methods. Different models are required for O&M choices. These models offer a broad variety of scenarios and variables to reduce energy costs and enhance wind farm profitability. In this regard, this paper proposes a detailed approach for maintenance decisions to pick an optimum maintenance strategy (MST) for different subassemblies of wind turbines based on failure analysis. This approach is predicated mostly on a vast field database of failures and repairs of several subassemblies of wind turbines. The maintenance model is comprised of many stages, including the data preparation stage, the availability optimization stage, and the optimum MST selection step. Consequently, this model aids in determining the appropriate MST for all subassemblies of wind turbines to achieve the necessary degree of availability.

Mean arterial pressure and mortality in patients with heart failure: a retrospective analysis of Zigong heart failure database.

It is commonly observed that a higher target of mean arterial pressure (MAP) is in previous studies. This study assessed the association of MAP with short-term mortality in heart failure (HF) patients. A retrospective cohort study was conducted by using data from Hospitalized patients with heart failure: integrating electronic healthcare records and external outcome database (v1.2 ). The characteristic of patients was described by 3 groups of MAP: below 80 mmHg, 80-100 mmHg, and above 100 mmHg. Univariate and multivariate logistic regression analyses were used to assess the relevance between MAP and all-cause mortality within 28 days and 6 months. For assessing the effect of multiple variables on patient survival time, 28-day and 6-month, Kaplan-Meier survival analysis and Forest plot were performed. The overall cohort comprised 2008 patients divided by MAP into 3 groups, each group had 344 (17.1%), 938 (46.7%), and 726 (36.2%) patients. Patients in MAP < 80 mmHg group had higher mortality than MAP 80-100 mmHg and MAP ≥ 100 mmHg in 28 days(3.8% versus 1.6% versus 1.2%) and in 6 months (4.9% versus 2.5% versus 2.3%). Univariate analysis showed that MAP as a continuous variate was associated with 28-day (OR was 0.98, 95% CIs: 0.96-0.99, P = 0.011) and 6-month mortality (OR was 0.98, 95% CIs: 0.97-1, P = 0.021) in HF patients. Model 4 put into multivariate logistic regression analyses showed MAP 80-100 mmHg (OR was 0.13, 95% CIs: 0.02-0.8, P = 0.027) stably associated with 28-day and 6-month mortality after adjusted covariable. Kaplan-Meier survival curves revealed a higher survival rate in the MAP ≥ 80 mmHg group than in the MAP < 80 mmHg group. The forest plot showed the stable effect of MAP ≥ 80 mmHg compared with MAP < 80 mmHg, the interaction analysis had no statistical significance effect between the two groups of MAP and multi-variable. It is indicated that MAP was independently associated with 28-day, 6-month all-cause mortality of HF patients, and compared with MAP < 80 mmHg, MAP ≥ 80 mmHg had a lower risk of 28-day, 6-month all-cause mortality of patients with HF.

Utilization of Transthoracic Echocardiography Is Associated with a Decreased 6-month Readmission Rate in Hospitalized Heart Failure: A Propensity Score-matched Analysis

Objective: Repeated hospitalization due to congestion is a characteristic of the whole course of heart failure. Echocardiography can be used to assess cardiac function and volume status. However, whether echocardiography can reduce the rehospitalization rate remains unclear. This study aimed to evaluate the impact of transthoracic echocardiography (TTE) use on readmission rates in hospitalized patients with heart failure. Methods: The study was based on the Zigong heart failure database, which contained information on 2,008 adult patients with heart failure admitted to the Zigong Fourth People’s Hospital (Sichuan Province, China) from December 2016 to June 2019. Patients were divided into 2 groups according to the usage of TTE on the day of hospital admission (TTE group (1,371 patients) and no TTE group (637 patients), respectively). The primary outcome was the 6-month readmission rate. The statistical approaches used included multivariate Cox regression, propensity score analysis, and an inverse probability weighting model to ensure the robustness of the findings. Results: A significant reduction in 6-month readmission rate was observed among the TTE group compared with the no TTE group (hazard ratio = 0.60, 95% confidence interval (CI) = 0.52–0.69, P &lt; 0.001). The frequencies of intravenous nitrates, diuretics, and inotropes during hospitalization were significantly higher in the TTE group compared with those in the no TTE group (10.9% vs. 8.3%, 88.5% vs. 86.2%, and 66.9% vs. 65.6%, respectively, all P &lt; 0.001). The proportion of patients returning to the emergency department within 6 months was significantly lower in the TTE group compared with the no TTE group (35.6% vs. 50.3%, P &lt; 0.001). Conclusions: Utilization of TEE on admission day was associated with a reduced 6-month readmission rate in hospitalized patients with heart failure.

Finding Scope for Implementing Correct Strategy for Maintenance of Medical Equipment Using Failure Database

Finding Scope for Implementing Correct Strategy for Maintenance of Medical Equipment Using Failure Database

A Data-Driven Model for Ice-Breaking Resistance of Structure Based on Non-Smooth Discrete Element Method and Artificial Neural Network Method

In this paper, a data-driven model based on the Non-smooth Discrete Element Method (NDEM) and Artificial Neural Network Method (ANN) is proposed for the computation of the ice-breaking resistance of the structure. The idea of so-called “meta-modelling”, which means establishing an Artificial Neural Network (ANN) model based on a pre-computed ice failure database to avoid the time-consuming direct resolving of the ice fracture process, was integrated in the non-smooth discrete element method (NDEM). The developed model was validated by simulating the ice-breaking process of the cone structure, and the computational results match well with the experimental ones in the literature. After that, the effects of various parameters on the ice-breaking resistance were analyzed by the developed model. It was found that the factors that have great influence on the resistance of cone structure in level ice condition are the cone angle, navigation velocity and ice thickness.

Analysis of a database of open pit mine slope failures to predict travel distance, setback distance, and geometric properties

In mining, open pits have slopes cut as steep as possible to ensure efficient mining yet not too steep to jeopardize safety. Building on existing contributions, the Texas A&amp;M University Mine Slope database (TAMU-MineSlope) was created to provide global-scale insights into the runout mechanics of open pit slope failures and offer the database to engineers for further study. The database includes 134 cases of open pit slope failures that occurred at 76 mines worldwide. Based on energy principles and an analysis of the TAMU-MineSlope data, an equation to predict the travel distance of the slope failure mass is presented in this paper. Furthermore, based on the case histories analysis, an equation to predict the setback distance is proposed. Finally, the TAMU-MineSlope database shows that the average width to height ratio of the failing slope mass is 2.7 and that, for this ratio, the 3D factor of safety (FS) can reach a value 15% higher than the 2D FS. The database has been released in the public domain.

Regional Multihazard Risk-Assessment Method for Overhead Transmission Line Structures Based on Failure Rate and a Bayesian Updating Scheme

In this study, a new method for multihazard risk assessment of an overhead transmission line grid located over a relatively large area is proposed. The main task of this method was to assess annual risk for overhead transmission lines using failure rates estimated from historical failure data and then modifying these estimated failure rates by reanalysis data and a Bayesian updating scheme. For this purpose, a comprehensive database of structural failures was collected for climatic, geologic, and man-made hazards to overhead transmission lines. Risk denotes the probability of exceeding the sum of direct losses due to repair costs of overhead transmission line components and indirect losses due to energy not supplied or unplanned power-off after outages. The performance of the proposed method was evaluated in a case study of a target area. The results showed that climatic hazards contributed the most to total losses in the study area. Furthermore, when using indirect losses to estimate the annual loss, the average annual loss may increase by up to about 45% relative to direct losses, depending on the type of hazard. This demonstrates the importance of investigating indirect losses from structural failures in the risk assessment of overhead transmission lines.

Quantitative risk assessment of static equipment in petroleum and natural gas processing station based on corrosion-thinning failure degree

Quantitative risk assessment method for station static equipment based on the degree of corrosion-thinning failure is proposed. The corrosion rate and failure consequences are divided into 5 severity grades. A corrosion-thinning risk assessment matrix is established. The method is based on the corrosion-thinning intrinsic safety of the petroleum and natural gas process station and avoids the risk evaluation error caused by the mismatch of the failure database. It can analyze the severity of corrosion thinning, which is the improvement of the existing risk assessment method for static equipment. The quantitative risk assessment is applied to DA treatment station in T Oilfield. Combined with the current status of operation and management of the station, it is determined that the risk level of corrosion and thinning failure is medium.

Smart Trip Prediction Model for Metro Traffic Control Using Data Mining Techniques

In the urban rail transportation industry, collecting various data, including the number of trips, the number of fleet breakdowns, the number of breakdowns of railway lines, etc., contributes significantly to future planning and optimization of resources and costs. We are faced with big data analysis due to the daily production of large volumes of data in the urban rail transport industry. This study aims to find a trip prediction model for Tehran Metro to do trip decision-making. This paper provides a brief introduction to knowledge discovery from failure databases and presents the data mining methodology. The relevancy of data mining for a trip prediction model will be depicted. In this sense, considering the relevance of data collected on the metro control center and intelligent trip prediction, this paper presents a functional architecture of a predictive trip model using data mining techniques. Data Mining will identify behavior patterns, allowing a more accurate early detection of faults in the daily operation. This research has investigated three situations, including delayed trips, incomplete trips, and canceled trips, using actual data recorded over the past four years, including non-programmed failures and their impact on trips. A model with more than 90% (90.48%) accuracy suggests a trip status forecast on this line. Also, the research has used Rapid Miner software and the Decision tree technique in data mining and its rules. Also, the kappa index of 0.792 is calculated for the validation model. Therefore, the proposed model enables the prediction of three types of incomplete traffic, delayed trips, and cancellation of trips due to emergency failure at the time of the operation of the Tehran Metro.

The Research On Statistical Identification of Critical Infrastructure Chain Failure Paths

Using literature studies, case studies, empirical induction and statistical identification, we proposed an analytical framework based on empirical induction to identify and analyze chain failure problems among interdependent critical infrastructures. A case database of critical infrastructure chain failures was established, and as the research emphasis the identification method of critical infrastructure chain failure paths was constructed and designed. The chain failure paths of the critical infrastructure and its sub-networks in China and other countries and regions were discussed. Logical relationships of critical infrastructure chain failures were extracted from the established database covering 229 critical infrastructure chain failure cases. Statistics, identification, and analysis of data were conducted to form a quantitative assessment and understanding of the vulnerability of interdependent critical infrastructure networks. Finally, identification methods and probabilistic statistical methods for chain failure paths of critical infrastructure were designed and applied to the case base of this paper. Using this approach, fatal and severe failure paths of critical infrastructure can be identified and the efficiency of the relevant authorities' inspection work will be improved under cost constraints.