scholarly journals Driving Risk Assessment in Work Zones Using Cloud Model

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Chi Zhang ◽  
Hong Zhang ◽  
Xiongying Ma ◽  
Min Zhang ◽  
Shiwei Wang

Work zones are prone to traffic accidents. They are considered as dangerous parts of expressways not only for drivers but also for highway construction workers, as they face a higher risk of traffic accidents in work zones. In order to identify the driving risks and to provide guidance to detect traffic risks in work zone, a comprehensive risk assessment method based on cloud model is developed to examine the driving risks in work zones. The proposed model relies on three parameters to determine the driving risks in work zones, namely, coefficient of variation of speed, deceleration, and minimum safety distance. VISSIM simulation software is used as a tool to construct the work zone driving conditions and the reverse cloud model is used to divide the concept and concept jump. The maximum activation intensity is considered as the base factor to determine the core risk level. Other activation intensities are used as a basis to optimize the edge level effect and generate a comprehensive function. The reconstruction area in Anhui Province is used as a case study to assess the driving risks in three expressway work zones. The results revealed that the risk scores of the three work zones 1, 2, and 3 are 48.48, 62.49, and 34.33, respectively. The results obtained by the developed driving risk assessment model are in good agreement with the experimental results. Hence, the model proposed in this paper can accurately assess the driving risks in work zones using a more scientific and intuitive approach, which provides an excellent tool to design safe expressway work zones.

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Han Wu ◽  
Sen Liu ◽  
Denghui Liu ◽  
Junwu Wang

The health, safety, and environment (HSE) risk assessment of major sewage transport tunnel projects (MSTTPs) is of great significance to guarantee sewage treatment, ecological environment protection, and sustainable development. To accurately evaluate the HSE risk of MSTTPs at the construction stage and effectively deal with their randomness and ambiguity, a risk assessment model based on the structural entropy weight method (SEWM) and the cloud model is put forward in this paper. First, an index system for MSTTPs was constructed via a literature review and expert interviews, and the rough sets method was used to filter the indicators. Then, weights were calculated by the SEWM, which is able to consider both subjective and objective factors of the weight calculation. Finally, to clarify the randomness and ambiguity in the evaluation, the HSE risk level was determined by the cloud similarity. The model was applied to the Donghu Deep Tunnel Project in Wuhan, China, and the results demonstrated that its HSE risk level was medium, which was acceptable. The index related to construction safety had the largest weight. A humid environment, improper power utilization, and sludge and mud pollution were found to be the most influential risk indicators. The risk level could be intuitively and qualitatively judged by the figure evaluation cloud, providing a vivid and rapid evaluation tool for the emergency decision-making of project managers, and the risk level could be quantitatively judged by the calculation of cloud similarity. Moreover, through the comparison with gray correlation degree, set pair analysis, and fuzzy comprehensive evaluation method evaluation results, we prove the scientificity and effectiveness of the proposed model. The research results provide a valuable reference for the project management of MSTTPs at the construction stage.


Author(s):  
Lian Chen ◽  
Shenglu Zhou ◽  
Qiong Yang ◽  
Qingrong Li ◽  
Dongxu Xing ◽  
...  

This study detailed a complete research from Lead (Pb) content level to ecological and health risk to direct- and primary-sources apportionment arising from wheat and rice grains, in the Lihe River Watershed of the Taihu region, East China. Ecological and health risk assessment were based on the pollution index and US Environmental Protection Agency (EPA) health risk assessment model. A three-stage quantitative analysis program based on Pb isotope analysis to determine the relative contributions of primary sources involving (1) direct-source apportionment in grains with a two-end-member model, (2) apportionment of soil and dustfall sources using the IsoSource model, and (3) the integration of results of (1) and (2) was notedly first proposed. The results indicated that mean contents of Pb in wheat and rice grains were 0.54 and 0.45 mg/kg and both the bio-concentration factors (BCF) were <<1; the ecological risk pollution indices were 1.35 for wheat grains and 1.11 for rice grains; hazard quotient (HQ) values for adult and child indicating health risks through ingestion of grains were all <1; Coal-fired industrial sources account for up to 60% of Pb in the grains. This study provides insights into the management of grain Pb pollution and a new method for its source apportionment.


Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 420
Author(s):  
Zening Wu ◽  
Yuhai Cui ◽  
Yuan Guo

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.


Author(s):  
Xiaochuan Wang ◽  
Huixian Wang

At present, the situation of coal mine safety production is still grim. The key to solve the problem is to analyze the risk of management activities in the process of coal mine safety production. This paper takes the management activities in the process of coal mine safety production as the research object. Firstly, according to the coal mine safety production standardization management system, the safety production management activities are carried out layer by layer. Then, the Failure Mode and Effect Analysis (FMEA) is used to identify the human errors that lead to the failure of management activities at all levels of coal mine. Furthermore, the Fuzzy Set Theory is used to determine the evaluation results of experts on the risk level of coal mine safety production management activities. Combined with Bayesian network (BN), the risk assessment model of coal mine safety production management activities is established. Through the model, the risk probability of coal mine enterprise management activities is accurately calculated. According to the evaluation results, the risk of management activities in coal mine safety production is analyzed.


Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Yan Wang ◽  
Jie Su ◽  
Sulei Zhang ◽  
Siyao Guo ◽  
Peng Zhang ◽  
...  

In view of the shortcomings in the risk assessment of deep-buried tunnels, a dynamic risk assessment method based on a Bayesian network is proposed. According to case statistics, a total of 12 specific risk rating factors are obtained and divided into three types: objective factors, subjective factors, and monitoring factors. The grading criteria of the risk rating factors are determined, and a dynamic risk rating system is established. A Bayesian network based on this system is constructed by expert knowledge and historical data. The nodes in the Bayesian network are in one-to-one correspondence with the three types of influencing factors, and the probability distribution is determined. Posterior probabilistic and sensitivity analyses are carried out, and the results show that the main influencing factors obtained by the two methods are basically the same. The constructed dynamic risk assessment model is most affected by the objective factor rating and monitoring factor rating, followed by the subjective factor rating. The dynamic risk rating is mainly affected by the surrounding rock level among the objective factors, construction management among the subjective factors, and arch crown convergence and side wall displacement among the monitoring factors. The dynamic risk assessment method based on the Bayesian network is applied to the No. 3 inclined shaft of the Humaling tunnel. According to the adjustment of the monitoring data and geological conditions, the dynamic risk rating probability of level I greatly decreased from 81.7% to 33.8%, the probability of level II significantly increased from 12.3% to 34.0%, and the probability of level III increased from 5.95% to 32.2%, which indicates that the risk level has risen sharply. The results show that this method can effectively predict the risk level during tunnel construction.


Author(s):  
SHENPING HU ◽  
XUDONG LI ◽  
QUANGEN FANG ◽  
ZAILI YANG

Risks associated with a vessel traffic system at sea are analyzed according to the elements in this system and a new method is developed to ensure safe ship operation. Based on Bayes' point estimation and probability influence diagram to estimate the traffic accidents related to vessel traffic, an analysis model is established for the quantitative risk assessment (QRA) of the vessel traffic system at sea. After the analysis on occurrence likelihood of the accidents related to ship traffic, a structure on the basis of Bayesian networks is developed to obtain the QRA of their relative risks. QRA is also put forward after analyzing the features and situations of the vessel traffic system and identifying the corresponding hazards including characteristics of those hazards. The risk distributions of ship traffic are described and results are presented on QRA in relation to various features by using this risk assessment model. This method, verified in the cases of QRA, turns out to be feasible by the use of identified posterior probability.


Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 452-452
Author(s):  
Sabine Eichinger ◽  
Georg Heinze ◽  
Paul Alexander Kyrle

Abstract Abstract 452 Background: Venous thrombosis is a chronic and potentially fatal disease (case fatality 5-9%). Predicting the likelihood of recurrence is important, as most recurrences can be prevented by antithrombotic therapy, albeit at the price of an increased bleeding risk during anticoagulation. Despite a substantial progress in identifying the determinants of the recurrence risk, predicting recurrence in an individual patient is often not feasible. Venous thromboembolism (VTE) is a multicausal disease and the combined effect of clinical and laboratory factors on the recurrence risk is unknown. It was the aim of our study to develop a simple risk model that improves prediction of the recurrence risk in patients with unprovoked VTE. Methods and Findings: In a prospective multicenter cohort study we followed 929 patients with a first VTE after completion of at least 3 months of anticoagulation. The median observation time was 43.3 months. Patients with VTE provoked by surgery, trauma, cancer, pregnancy or oral contraceptive intake were excluded as were those with a natural inhibitor deficiency or the lupus anticoagulant. The main outcome measure was symptomatic recurrent VTE, which occurred in 176 patients. The probability of recurrence (95% CI) after 2, 5 and 10 years was 13.8% (11.6% to16.5%), 24.6% (21.6% to 28.9%), and 31.8% (27.6% to 37.4%), respectively. To develop a simple and easy to apply risk assessment model, clinical and laboratory variables (age, sex, location of VTE, body mass index, factor V Leiden, prothrombin G20210A mutation, D-Dimer, in vitro thrombin generation) were preselected based on their established relevance for the recurrence risk, simple assessment, and reproducibility. All variables were analyzed in a Cox proportional hazards model, and those significantly associated with recurrence were used to compute risk scores. Only male sex [HR vs. female 1.90 (95% CI 1.31–2.75)], proximal deep vein thrombosis [HR vs. distal 2.08 (95% CI 1.16–3.74)], pulmonary embolism [HR vs. distal thrombosis 2.60 (95% CI 1.49– 4.53)] and elevated levels of D-Dimer [HR per doubling 1.27 (95% CI 1.08–1.51)] or peak thrombin [HR per 100 nM increase 1.38 (95% CI 1.17–1.63)] were related to a higher recurrence risk. We developed a nomogram (Fig. 1) based on sex, location of initial thrombosis, and D-Dimer that can be used to calculate risk scores and to estimate the cumulative probabilities of recurrence in an individual patient. The model has undergone extensive validation by a cross-validation process. The cohort was divided into test and validation samples thereby mimicking independent validation. This process was repeated 1000 times and the results were averaged to avoid dependence of the validation results on a particular partition of our cohort. Patients were assigned to different risk categories according to their risk score, which corresponded well with the recurrence rate as patients with lower scores had lower recurrence rates. Conclusion: By use of a simple scoring system the assessment of the recurrence risk in patients with a first unprovoked VTE can be improved in routine care. Patients with unprovoked VTE in whom the recurrence risk is low enough to consider a limited duration of anticoagulation, can be identified. Disclosures: No relevant conflicts of interest to declare.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
X. B. Gu ◽  
S. T. Wu ◽  
X. J. Ji ◽  
Y. H. Zhu

The debris flow is one of the geological hazards; its occurrence is complex, fuzzy, and random. And it is affected by many indices; a new multi-index assessment method is proposed to analyze the risk level of debris flow based on the entropy weight-normal cloud model in Banshanmen gully. The index weight is calculated by using the entropy weight method. Then, the certainty degree of each index belonging to the corresponding cloud is obtained by using the cloud model. The final risk level of debris flow is determined according to the synthetic certainty degree. The conclusions are drawn that the method is feasible and accurate rate of risk estimation for debris flow is very high, so a new method and thoughts for the risk assessment of debris flow can be provided in the future.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Kai Hu ◽  
Junwu Wang ◽  
Han Wu

Frequent extreme climate events and rapid global urbanization have amplified the occurrence of accidents such as waterlogging or the overflow of pollution in big cities. This has increased the application scenarios of large-sized deep drainage tunnel projects (LSDDTPs). The scientific and accurate evaluation of the construction safety risks of LSDDTP can effectively reduce the corresponding economic losses and casualties. In this paper, we employed the hierarchical holographic model to construct the safety risk list of LSDDTPs in terms of the risk source and construction unit. Based on social network analysis, we then screened key indicators and calculated the weights of all secondary indicators from the correlation between risk factors. We subsequently developed a construction safety risk assessment model of LSDDTPs based on the matter-element extension method. The Donghu Deep Tunnel Project in Wuhan, China, was selected as a case study for the proposed method. The results of empirical research demonstrated that eight indicators (e.g., failure to effectively detect the change of the surrounding environment of the tunnel project) were key factors affecting the construction safety risk of IV, which is within the acceptable risk level. Our proposed model outperformed other methods (the fuzzy comprehensive evaluation, analytic hierarchy process, entropy weight method, and comprehensive weight method) in terms of scientific validity and research advancements.


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