Distribution,risk evaluation,and source analysis of the heavy metals in the sediment deposition of the lower Shichuanhe River,Shaanxi,China

In this study, 30 sediment samples were collected from the lower reaches of the Shichuanhe River in Xi’an, Shaanxi Province, China, to test the distribution of heavy metal elements in this area and for an analysis of the pollution levels of this area, hope to provide guidance on agricultural production activities in this region. The results show that the heavy metal elements in this area are mainly concentrated at the Qinghe River and Shichuanhe River confluences. Furthermore, the element contents are higher than that of the background levels of the continental crust(UCC) and close to the background levels of the soil from Shaanxi Province;the two most enriched elements are Cd and As, with contents of 0.79 and 22.7 mg·kg-1, respectively, and their contents are 3.8 and 1.72 times higher than that of the background values. Herein, the heavy metal pollution assessment methods applied indicated that Cd and As are the two most abundant pollutant elements in the area’s soils. As has a peak geo-accumulation index value of 3, and the pollution level is high, while Cd exhibits high potential ecological risks due to its high toxicity(potential risk index of 143) and an active fraction of more than 64%.In addition, a principal component analysis and hierarchical cluster analysis study showed that there are two sources of the heavy metals in this area. The Zn, As, Ni, Cu, Pb,and Cr are mainly from natural sources, and the Cd likely comes from a discharge of untreated agricultural wastewater in the region. The Cd which poses a high potential risk and mainly results from human activities, needs to be further monitored.

Improved AHP–TOPSIS model for the comprehensive risk evaluation of oil and gas pipelines

A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process(AHP)and technique for order preference by similarity to an ideal solution(TOPSIS)is established to identify potential hazards in time.First,a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors:corrosion,external interference,material/construction,natural disasters,and function and operation.Next,the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method.Then,the TOPSIS of a multi-attribute decision-making theory is studied.The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines.The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS.Finally,the weight and the closeness coefficient are combined to determine the risk level of pipelines.Empirical research using a long-distance pipeline as an example is conducted,and adjustment factors are used to verify the model.Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible.The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive,rational,and scientific evaluation results.It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines.The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.

Seismic risk evaluation for a planning mountain tunnel using improved analytical hierarchy process based on extension theory

Seismic risk evaluation(SRE) in early stages(e.g., project planning and preliminary design)for a mountain tunnel located in seismic areas has the same importance as that in final stages(e.g.,performance-based design, structural analysis, and optimization). SRE for planning mountain tunnels bridges the gap between the planning on the macro level and the design/analysis on the micro level regarding the risk management of infrastructural systems. A transition from subjective or qualitative description to objective or quantitative quantification of seismic risk is aimed to improve the seismic behavior of the mountain tunnel and thus reduce the associated seismic risk. A new method of systematic SRE for the planning mountain tunnel was presented herein. The method employs extension theory(ET)and an ET-based improved analytical hierarchy process. Additionally, a new risk-classification criterion is proposed to classify and quantify the seismic risk for a planning mountain tunnel. This SRE method is applied to a mountain tunnel in southwest China, using the extension model based on matter element theory and dependent function operation.The reasonability and flexibility of the SRE method for application to the mountain tunnel are illustrated.According to different seismic risk levels and classification criteria, methods and measures for improving the seismic design are proposed, which can reduce the seismic risk and provide a frame of reference for elaborate seismic design.

Reliability Risk Evaluation Method for Complex Mechanical System Based on Optimal Bayesian Network

In order to reduce the calculation of the failure probability in the complex mechanical system reliability risk evaluation,and to implement importance analysis of system components effectively,the system fault tree was converted into five different Bayesian network models. The Bayesian network with the minimum conditional probability table specification and the highest computation efficiency was selected as the optimal network. The two heuristics were used to optimize the Bayesian network. The fault diagnosis and causal reasoning of the system were implemented by using the selected Bayesian network. The calculation methods of Fussel-Vesely( FV),risk reduction worth( RRW),Birnbaum measure( BM) and risk achievement worth( RAW) importances were presented. A certain engine was taken as an application example to illustrate the proposed method. The results show that not only the correlation of the relevant variables in the system can be accurately expressed and the calculation complexity can be reduced,but also the relatively weak link in the system can be located accurately.

Acoustic Prediction and Risk Evaluation of Shallow Gas in Deep-Water Areas

Shallow gas is a potential risk in deep-water drilling that must not be ignored,as it may cause major safety problems,such as well kicks and blowouts.Thus,the pre-drilling prediction of shallow gas is important.For this reason,this paper conducted deep-water shallow gas acoustic simulation experiments based on the characteristics of deep-water shallow soil properties and the theory of sound wave speed propagation.The results indicate that the propagation speed of sound waves in shallow gas increases with an in-crease in pressure and decreases with increasing porosity.Pressure and sound wave speed are basically functions of the power expo-nent.Combined with the theory of sound wave propagation in a saturated medium,this paper establishes a multivariate functional relationship between sound wave speed and formation pressure and porosity.The numerical simulation method is adopted to simulate shal-low gas eruptions under different pressure conditions.Shallow gas pressure coefficients that fall within the ranges of 1.0-1.1,1.1-1.2,and exceeding 1.2 are defined as low-,medium-,and high-risk,respectively,based on actual operations.This risk assessment me-thod has been successfully applied to more than 20 deep-water wells in the South China Sea,with a prediction accuracy of over 90%.

Credit risk evaluation using adaptive Lq penalty SVM with Gauss kernel

In order to improve the performance of support vector machine (SVM) applications in the field of credit risk evaluation, an adaptive Lq SVM model with Gauss kernel (ALqG-SVM) is proposed to evaluate credit risks. The non-adaptive penalty of the object function is extended to (0, 2] to increase classification accuracy. To further improve the generalization performance of the proposed model, the Gauss kernel is introduced, thus the non-linear classification problem can be linearly separated in higher dimensional feature space. Two UCI credit datasets and a real life credit dataset from a US major commercial bank are used to check the efficiency of this model. Compared with other popular methods, satisfactory results are obtained through a novel method in the area of credit risk evaluation. So the new model is an excellent choice.

Researches on Risk Evaluation of Green Agro-product Closed Supply Chain

Closed supply chain is a superior form of management model of chain supply and an effective means of improving the modernization of agro-product circulation. Based on the research results of the current literatures on supply chain risk and agro-product supply chain, related subjects of the agro-product closed supply chain involving production, management and consumption are studied and analyzed and the primary risking factors in the supply chain system are classified as environmental risk, system risk, information risk, management risk and quality risk. Risk of agro-product closed supply chain is evaluated by using the method of fuzzy comprehensive evaluation and the values are acquired. The result shows that risk of agro-product closed supply chain is moderate with relatively high risk, which basically accords with the present actual situations. It can be seen from the index weights of various levels that the key first-level indices influencing the risks are system risk, information risk, quality and safety risk and the key second-level are the coordinating and controlling ability of core enterprises, the implementation of information traceability and the construction of quality safety system. Therefore, risk of agro-product closed supply chain should be reduced by taking prevention and controlling measures mainly from these aspects.

Authorization Management Framework Based on Joint Trust-Risk Evaluation

Authorization management is important precondition and foundation for coordinating and resource sharing in open networks. Recently, authorization based on trust is widely used whereby access rights to shared resource are granted on the basis of their trust relation in distributed environment. Nevertheless, dynamic change of the status of credential and chain of trust induces to uncertainty of trust relation. Considering uncertainty of authorization and analyzing deficiency of authorization model only based on trust, we proposes joint trust-risk evaluation and build the model based on fuzzy set theory, and make use of the membership grade of fuzzy set to express joint trust-risk relation. Finally, derivation principle and constraint principle of joint trust-risk relationships are presented. The authorization management model is defined based on joint trust-risk evaluation, proof of compliance and separation of duty are analyzed. The proposed model depicts not only trust relationship between principals, but also security problem of authorization.

Stochastic Modelling of Vulnerability Life Cycle and Security Risk Evaluation

The objective of the present study is to propose a risk evaluation statistical model for a given vulnerability by examining the Vulnerability Life Cycle and the CVSS score. Having a better understanding of the behavior of vulnerability with respect to time will give us a great advantage. Such understanding will help us to avoid exploitations and introduce patches for a particular vulnerability before the attacker takes the advantage. Utilizing the proposed model one can identify the risk factor of a specific vulnerability being exploited as a function of time. Measuring of the risk factor of a given vulnerability will also help to improve the security level of software and to make appropriate decisions to patch the vulnerability before an exploitation takes place.

Research on Risk Evaluation Method for International Engineering Projects

Risk evaluation is one of the important elements of international engineering project management. The risk factors of international engineering projects are systematically analyzed from multiple dimension features of the projects. The muhilayer evaluation index system for the international engineering project risk assessment is proposed and constructed, which consists of 8 I-grade indexes and 24 II-grade indexes as policy risk, market risk, resource risk, and technical scheme risk, schedule risk, funding risk, personnel risk and management risk. And then the self-evaluation and benchmarking evaluation methods are applied to evaluate the international engineering project risk, and established the corresponding mathematical models. Finally, a project evaluation example is given to illustrate the applicability and effectiveness of the mathematical models.

Market Risk Evaluation on Single Futures Contract:SV-CVaR Model and Its Application on Cu00 Data

A new stochastic volatility（SV）method to estimate the conditional value at risk（CVaR）is put forward.Firstly,it makes use of SV model to forecast the volatility of return.Secondly,the Markov chain Monte Carlo（MCMC）simulation and Gibbs sampling have been used to estimate the parameters in the SV model.Thirdly,in this model,CVaR calculation is immediate.In this way,the SV-CVaR model overcomes the drawbacks of the generalized autoregressive conditional heteroscedasticity value at risk（GARCH-VaR）model.Empirical study suggests that this model is better than GARCH-VaR model in this field.

Clues from networks:quantifying relational risk for credit risk evaluation of SMEs

Owing to information asymmetry,evaluating the credit risk of small-and mediumsized enterprises(SMEs)is difficult.While previous studies evaluating the credit risk of SMEs have mostly focused on intrinsic risk generated by SMEs,our study considers both intrinsic and relational risks generated by neighbor firms’publicly available risk events.We propose a framework for quantifying relational risk based on publicly available risk events for SMEs’credit risk evaluation.Our proposed framework quantifies relational risk by weighting the impact of publicly available risk events of each firm in an interfirm network—considering the impact of interfirm network type,risk event type,and time dependence of risk events—and combines the relational risk score with financial and demographic features to evaluate SMEs credit risk.Our results reveal that relational risk score significantly improves both discrimination and granting performances of credit risk evaluation of SMEs,providing valuable managerial and practical implications for financial institutions.

Development of a Fuzzy Fire Risk Evaluation Model for Building Construction Sites in Hong Kong

Earlier research works on fire risk evaluation indicated that an objective,reliable,comprehensive,and practical fire risk evaluation model is essential for mitigating fire occurrence in building construction sites.Nevertheless,real empirical studies in this research area are quite limited.This journal paper gives an account of the second stage of a research study aiming at developing a fuzzy fire risk evaluation model for building construction sites in Hong Kong.The empirical research findings showed that the overall fire risk level of building construction sites is 3.6427,which can be interpreted as“moderate risk”.Also,the survey respondents perceived that“Restrictions for On-Site Personnel”is the most vital fire risk factor;with“Storage of Flammable Liquids or Dangerous Goods”being the second;and“Attitude of Main Contractor”the third.The proposed fuzzy fire risk evaluation model for building construction sites can be used to assess the overall fire risk level for a building construction site,and to identify improvement areas needed.Although the fuzzy fire risk evaluation model was developed domestically in Hong Kong,the research could be reproduced in other nations to develop similar models for international comparisons.Such an extension would provide a deeper understanding of the fire risk management on building construction sites.

Validation of the Chinese system for cardiac operative risk evaluation (SinoSCORE):the experience from Guangdong Cardiovascular Institute

Objective To validate of the Chinese system for cardiac operative risk evaluation (SinoSCORE) in Cantonese surgery patients. Methods Data from Guangdong Cardiovascular Institute in the period January 2004 through December 2008 were analyzed on 2462 Cantonese heart surgery patients. First,compared risk factors of this series and database of SinoSCORE,and then calculated

A prospective evaluation of preoperative risk evaluation system for geriatric orthopedic patients

Objective To evaluate the correlation and efficacy of Preoperative Risk Evaluation System for Geriatric Orhopedic Patients (PRESGOP),Acute Physiology and Chronic Health Evaluation (APACHE) and Physiological and Operative Score for

Risk evaluation for the task transfer of an aircraft maintenance program based on a multielement connection number

This paper proposes a framework for evaluating the efficacy and suitability of maintenance programs with a focus on quantitative risk assessment in the domain of aircraft maintenance task transfer. The analysis is anchored in the principles of Maintenance Steering Group-3 (MSG-3) logic decision paradigms. The paper advances a holistic risk assessment index architecture tailored for the task transfer of maintenance programs. Utilizing the analytic network process (ANP), the study quantifies the weight interrelationships among diverse variables, incorporating expert-elicited subjective weighting. A multielement connection number-based evaluative model is employed to characterize decision-specific data, thereby facilitating the quantification of task transfer-associated risk through the appraisal of set-pair potentials. Moreover, the paper conducts a temporal risk trend analysis founded on partial connection numbers of varying orders. This analytical construct serves to streamline the process of risk assessment pertinent to maintenance program task transfer. The empirical component of this research, exemplified through a case study of the Boeing 737NG aircraft maintenance program, corroborates the methodological robustness and pragmatic applicability of the proposed framework in the quantification and analysis of mission transfer risk.

Risk Evaluation of Ammonia Leakage based on Modified Probability Calculation Formulas

Due to its flammable,explosive,and corrosive characteristics,fire,and explosion accidents caused by ammonia leakage occur from time to time.In this work,the concentration distribution of the model was calculated according to the existing formula of probabilistic risk assessment.Using the revised formulas,the leakage of the ammonia room was quantitatively analyzed,and different state parameters were analyzed to find out the dangerous leakage points of the ammonia refrigeration system.The results of the calculation are that the existence of obstacles in the space will increase the probability of leakage risk.And the greater the leakage time to the lower flammability limit accounts for the total leakage time,the greater the risk probability.Dangerous leakage in ammonia systems mainly occurs in storage tanks and condensers.The data show that the dynamic mass flow of ammonia leakage decreases with time,and the leakage diameter increases with the increase of leakage pressure.At the same time,the leakage mass increases gradually with the leakage aperture near circular.

Multiple Failure Modes of Compressor Station Incorporated into Risk Evaluation of Electricity-gas Integrated Energy Systems

Multiple failure modes of gas compressor stations have not been modeled into risk evaluation of electricity-gas integrated energy system(EGIES).This paper presents a method to incorporate multiple failure modes of compressor stations with bypass systems in the EGIES risk evaluation.Three outage models representing multi-states and multi-failure-modes of com-pressor stations and a bi-level Monte Carlo sampling algorithm for the models are developed.A novel network model of EGIES considering compressor stations with multiple failure modes is presented.An EGIES with a modified RBTS and an 11-node gas system is used to demonstrate the effectiveness of the proposed method and models.Results indicate that compressor stations have both positive and negative significant impacts on the risk of EGIES.Bypass systems for compressor stations can effectively offset the negative impacts.Ignoring compressor stations and their station failures in the risk evaluation of EGIES may result in an inaccurate estimation of the system risk levels and even lead to a misleading conclusion in system planning.Index Terms-Compressor station,electricity-gas integrated energy system,multiple failure modes,risk evaluation.

SSO Risk Evaluation for a Grid-connected PMSG-based Wind Farm Based on Sequential Monte Carlo Simulation

In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.