Risk Analysis of Passalora sequoiae Invasion to China with Imported Coniferous Wood

According to international standard plant quarantine measures and principle risk analysis(ISPM No.11),a risk assessment was carried out for Passalora sequoiae through geographical distribution,possibility of colonization,probability of diffusion,economic importance and difficulty in risk management.Results show that P.sequoiae has a greater risk of introduction and diffusion,and it has distributed in parts of China.It is suggested that P.sequoiae should be added to the list of forest dangerous pests in China.Besides,porting departments should focus on the pathogen on imported host seedlings like Cryptomeria.

Risk analysis system of geo-hazard based on GIS technique

The socio-economic attribute of geo-hazard made us distinguish it from the traditional engineering geology study. It will get more social benefit from the analysis of the geo-hazard in the socio-economic attribute. The hazard and the vulnerability of the element controls the risk level of the regional geo-hazard. The risk analysis supported by GIS in geo-hazard study is one of the most important directions. Based on the author’s studies in recent years, a risk analysis system of regional geo-hazard (RiskAnly) has been developed on the basis of software MAPGIS. The paper introduces the train of system design, the structure and the workflow of RiskAnly. As a case study, the paper also deals with the risk zonation of the regional landslide hazard of China.

Risk analysis of extended reach wells in the Liuhua Oilfield,South China Sea,based on comprehensive fuzzy evaluation method

Drilling engineering has great uncertainty and it always involves huge investment and high risk. Risk analysis of extended reach drilling （ERD） is very important to prevent complex failures and to improve drilling efficiency. Nowadays there are few reports on how to analyze quantitatively the drilling risk for extended reach wells （ERWs）. Based on the fuzzy set theory, a comprehensive fuzzy evaluation model for analyzing risks of ERD is proposed in this paper. Well B6ERW07 is a planned 8,000-meter ERW with a high ratio of horizontal displacement （HD） to vertical depth （VD） in the Liuhua Oilfield, the South China Sea, China. On the basis of the evaluation model developed in this study, the risk for drilling Well B6ERW07 was evaluated before drilling. The evaluation result shows that the success rate of drilling this well is predicted to be 51.9%, providing important rational and scientific information for the decisionmakers.

Fuzzy Risk Analysis of Harbour Engineering Investment by Hierarchy System Approach

The present risk analysis model of engineering investment is built by fuzzy hierarchy approach under the assumption of maximizing the revenues of the project during its whole life cycle of operation. It can reasonably be expressed by a system evaluation analysis. As a matter of fact, the system, aimed by its system goal can be modelled by a set of factors, constitutively structured by certain links between them, to form a factorial network chart, which represents the essentials of the system behaviours, the nodes of which represent the factors concerned. The weight distribution between factors located at the same level can be determined by the eigen-value problem of a 'pair comparison' relation matrix. The weight distribution of factors at each level is successively manipulated until the fuzzy synthetic risk assessment. As an example of risk analysis of engineering investment, a harbour construction project is presented for illustration.

A Bayesian Network Approach for Offshore Risk Analysis Through Linguistic Variables

This paper presents a new approach for offshore risk analysis that is capable of dealing with linguistic probabilities in Bayesian networks （ BNs）. In this paper, linguistic probabilities are used to describe occurrence likelihood of hazardous events that may cause possible accidents in offshore operations. In order to use fuzzy information, an f-weighted valuation function is proposed to transform linguistic judgements into crisp probability distributions which can be easily put into a BN to model causal relationships among risk factors. The use of linguistic variables makes it easier for human experts to express their knowledge, and the transformation of linguistic judgements into crisp probabilities can significantly save the cost of computation, modifying and maintaining a BN model. The flexibility of the method allows for multiple forms of information to be used to quantify model relationships, including formally assessed expert opinion when quantitative data are lacking, or when only qualitative or vague statements can be made. The model is a modular representation of uncertain knowledge caused due to randomness, vagueness and ignorance. This makes the risk analysis of offshore engineering systems more functional and easier in many assessment contexts. Specifically, the proposed f-weighted valuation function takes into account not only the dominating values, but also the a-level values that are ignored by conventional valuation methods. A case study of the collision risk between a Floating Production, Storage and Off-loading （FPSO） unit and the anthorised vessels due to human elements during operation is used to illustrate the application of the proposed model.

Risk Analysis and Assessment of Overtopping Concerning Sea Dikes in the Case of Storm Surge

Risk analysis and assessment relating coastal structures has been one of the hot topics in the area of coastal protection recently. In this paper, from three aspects of joint return period of multiple loads, dike failure rate and dike continuous risk prevention respectively, three new risk analysis methods concerning overtopping of sea dikes are developed. It is worth noting that the factors of storm surge which leads to overtopping are also considered in the three methods. In order to verify and estimate the effectiveness and reliability of the newly developed methods, quantified mutual information is adopted. By means of case testing, it can be found that different prior variables might be selected dividedly, according to the requirement of special engineering application or the dominance of loads. Based on the selection of prior variables, the correlating risk analysis method can be successfully applied to practical engineering.

Risk Analysis on Groundwater Resources Carrying Capacity Based on Blind Number Theory

Blind numbers of evaluation indices about groundwater resources carrying capacity are defined from the concomitancy of randomness, fuzziness, grey property and unascertainment of groundwater system. Based on fuzzy theory, a comprehensive evaluation model on groundwater resources carrying capacity is constructed with blind information. Then a risk assessment model of surcharge about groundwater resources carrying capacity is established on blind reliability theory. The probable value ＂＊＂ matrix of fuzzy membership degree about carrying capacity corresponding to each judgment level can be obtained with the aid of blind algorithm as well as the subjective reliability ＂×＂ matrix. And then a graph of ＂groundwater carrying capacity v.s. accumulative reliability＂ can be gained Based on the graph, fuzzy membership degree of groundwater resources carrying capacity to each judgment level under different risk probability can be got. Thus, a comparatively reasonable judgment to groundwater resources carrying capacity might be obtained, with comprehensive analysis to the state of society, economy technology and ecology.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

Risk Analysis of Big Data Based on Cloud Computing for the Inspection and Testing of Toxic and Hazardous Substances in Meat Products

Large-scale data emerge in food safety inspection and testing industry with the development of Internet technology in China.This paper was aimed at designing toxic and hazardous substance big data risk analysis algorithm in food safety inspection and testing based on cloud computing^([1]).Cloud computing platform was set up to store the massive extensive data with geographical distribution,dynamic and high complexity from the Internet,and MapReduce^([2]) computational framework in cloud computing was applied to process and compute parallel data.The risk analysis results were obtained by analyzing 1000000 meat products testing data collected from the laboratory management information system based on web.The results show that food safety index IFS < 1,which proves that the food safety state is in good condition.

Study on risk analysis of supply chain enterprises

The sources of supply chain enterprise risk from different aspects including material flow, information flow, cash flow and partner relationship is analyzed. Measures for risk reduction have also been summarized from the aspects of risk sharing, information sharing, change of inventory control mode, and supply chain flexibility. Finally, problems in current research on supply chain risk management are pointed out and a discussion on future research trend is presented.

Risk Analysis of Sulfites Used as Food Additives in China

This study was to analyze the risk of sulfites in food consumed by the Chinese people and assess the health protection capability of maximum-permitted level （MPL） of sulfites in GB 2760-2011. Sulfites as food additives are overused or abused in many food categories. When the MPL in GB 2760-2011 was used as sulfites content in food, the intake of sulfites in most surveyed populations was lower than the acceptable daily intake （ADI）. Excess intake of sulfites was found in all the surveyed groups when a high percentile of sulfites in food was intaken. Moreover, children aged 1-6 years are at a high risk to intake excess sulfites. The primary cause for the excess intake of sulfites in Chinese people is the overuse and abuse of sulfites by the food industry. The current MPL of sulfites in GB 2760-2011 protects the health of most populations.

Seismic risk analysis of coastal area of Pakistan

Estimation of seismic hazard for the fast developing coastal area of Pakistan is carried out using deterministic and probabilistic approaches. On the basis of seismotectonics and geology, eleven faults are recognized in five seismic provinces as potential hazard sources. Maximum magnitude potential for each of these sources is calculated. Peak ground acceleration (PGA) values at the seven coastal cities due to the maximum credible earthquake on the relevant source are also obtained. Cities of Gwadar and Ormara with acceleration values of 0.21g and 0.25g respectively fall in the high seismic risk area. Cities of Turbat and Karachi lie in low seismic risk area with acceleration values of less than 0.1g. The Probabilistic PGA maps with contour interval of 0.05g for 50 and 100 years return period with 90% probability of non-exceedance are also compiled.

A Software Risk Analysis Model Using Bayesian Belief Network

The uncertainty during the period of software project development often brings huge risks to contractors and clients. If we can find an effective method to predict the cost and quality of software projects based on facts like the project character and two-side cooperating capability at the beginning of the project,we can reduce the risk. Bayesian Belief Network(BBN) is a good tool for analyzing uncertain consequences, but it is difficult to produce precise network structure and conditional probability table.In this paper,we built up network structure by Delphi method for conditional probability table learning,and learn update probability table and nodes’confidence levels continuously according to the application cases, which made the evaluation network have learning abilities, and evaluate the software development risk of organization more accurately.This paper also introduces EM algorithm, which will enhance the ability to produce hidden nodes caused by variant software projects.

Risk Analysis of Gas Hydrate Formation during Deepwater Gas Well Testing

During deep-water gas wells testing period, predicting the generating zone of hydrate precisely in the whole flow range (bore holes and surface flow lines) is the key prerequisite of guarantee for testing flow. The unusual deep-water environment and low gas density make it easy to meet the conditions of hydrate generation during deep-water gas wells testing period, such as low temperature and high pressure, especially under the testing conditions, for instance, near mud line, surface chock line, low gas generating rate and surface shut-in. Wherefore, in view of all the operational modes during testing period (clean-out, variable rate flow, downhole and surface shut-in), based on temperature field of the whole flow range and phase equilibrium condition of hydrate, predicting method of hydrate generation zone is published;by taking enthalpy as the object of study, temperature calculation model increases the accuracy of temperature prediction;by integration of bore holes and surface lines, predicting plate of hydrate generation in the whole flow range is published. During flow period, the generating condition of hydrate is affected by rate of flow, and the lower the rate of flow is, the wider the hydrate generation zone is;during the stage of shut-in and initial flow, if pressure of strings is higher and temperature is lower, risk of hydrate generation will be greater and hydrate generation zone will be larger, so relevant actions should be taken to restrain hydrate generation.

Numerical Simulation and Risk Analysis of Coastal Inundation in Land Reclamation Areas:A Case Study of the Pearl River Estuary

Coastal inundation results in many human casualties and significant economic losses.In this study,an inundation model with an unstructured mesh was developed using the ADvanced CIRCulation(ADCIRC)and Simulating WAves Nearshore(SWAN)models to simulate 43 inundation events from 1998 to 2018.A combined wind-pressure field derived from the assimilation windpressure model was used to drive the coupled ADCIRC-SWAN model.On the basis of the model results,a sensitivity study of the influence of land reclamation on coastal inundation was conducted.The results of the study showed that coastline changes caused by reclamation significantly influence the distribution of coastal inundation,particularly in areas where narrow waterways,bays,and peninsulas are newly formed.Combining the extreme inundation events calculated using the Gumbel and Weibull distributions,the 10-year,50-year,100-year,and 200-year return coastal inundations were obtained for the Pearl River Estuary in China.The risk of coastal inundation was analyzed according to the probability of the inundation depth exceeding 1 m.A hazard grade zoning map was drawn to guide disaster relief and mitigation in the reclamation area.

Dynamic Risk Analysis of Permanent Deformation of Sea Embankment

For evaluation of the permanent deformation of a sea embankment under stochastic earthquake excitation, a robust dynamic risk analytical method is presented based on conventional permanent deformation analysis and stochastic seismic response analysis. This method can predict not only the mean value of maximum permanent deformation but also the reliability corresponding to different deformation control standards. The earthquake motion is modelled as a stationary Gaussian filtered white noise random process. The predicted average maximum horizontal permanent displacement is in agreement with the conventional result, Further studied are the reliability of permanent deformation due to stochastic wave details at one seismic motion level and the risk of permanent deformation due to stochastic seismic strength, i. e., the maximum acceleration in a long period. Therefore, it is possible to make the optimal design in terms of safety and economy according to the importance of a sea embankment. It is suggested that the improved stochastic seismic model that can catch the behavior of the non-stationary random process For sea embankments should be further studied in future.

Probabilistic Approach to Risk Analysis of Chemical Spills at Sea

Risk analysis of chemical spills at sea and their consequences for sea environment are discussed. Mutual interactions between the process of the sea accident initiating events, the process of the sea environment threats, and the process of the sea environment degradation are investigated. To describe these three particular processes, the separate semi-Markov models are built. Furthermore, these models are jointed into one general model of these processes interactions. Moreover, some comments on the method for statistical identification of the considered models are proposed.