Fishbone diagram and risk matrix analysis method and its application in safety assessment of natural gas spherical tank (2023)

A dam failures cause immeasurable losses, but more concrete face rockfill dams (CFRDs) are being built in areas where earthquakes occur frequently. If the risk level of CFRDs under seismic action can be identified promptly and corresponding measures taken in advance, dam failure risks can be mitigated to protect life and property. However, no study has been conducted on the seismic risk analysis of CFRDs. This study aimed to meet public security needs; hence, the risk matrix approach was used for analyzing the semi-quantitative risk of CFRDs under seismic action. Considering the seismic failure modes of dam deformation and dam slope instability, we also proposed a calculation technique of seismic failure possibility for high CFRDs. According to the worst-case scenario, the linear weighted sum method was used to assess the comprehensive seismic risk loss of CFRDs in terms of life loss,and economic loss, and socio-environmental impact. The risk levels of CFRDs under seismic action were accurately evaluated, and corresponding risk management measures were proposed according to the “As Low As Reasonably Practicable” principle. The results of this work fill the gap in the risk analysis of CFRDs under seismic action. Additionally, the results provide a theoretical basis and technical support for future seismic designs, seismic risk assessments, and risk decision-making for high CFRDs and similar projects in strong seismic areas.

An accident caused by train control system may not only bring expensive loss, but also result in severe destruction to surrounding environment. The purpose of this study is to study operational risk of Chinese Train Control System- Level 3 (CTCS-3). An integrated risk assessment method is developed by combining fishbone diagram (FD), Fuzzy Analytic Hierarchy Process (FAHP) with cloud model. Based on fishbone diagram, risk factors (RFs) of train control system are identified from two perspectives of hazard event, namely occurrence frequency and sequence severity. To further classify RFs quantitatively, a revised risk matrix based on FAHP is introduced to calculate the consequence and likelihood weights for each risk factor (RF), and then Risk Index (RI) is getting by making product of consequence and likelihood weights, which reflects relative influence degree on operational risk. Finally, in order to assess the comprehensive operational risk of CTCS, cloud model is used to logically calculate quantitative results, and the CTCS-3 in Wuhan-Guangzhou high-speed railway is empirically investigated to analyze its overall operational risk level. The result shows that its risk level is between medium and low, and more inclined to low, which means being acceptable but not ideal. Meanwhile, some specific suggestions and measures are proposed to eliminate or reduce RFs with higher frequency and worse consequence.

Various risk factors of urban gas pipelines will lead to leakage, significantly impacting the environment, assets, and life safety, thus making pipeline risk prevention and control crucial. However, existing methods cannot sufficiently model the uncertainty in the pipeline risk evaluation process. In addition, the calculation method of factor weights may lead to unrealistic results. In this study, variable weight theory and cloud theory are introduced. Then, a novel method of cloud-variable weight function is proposed to analyze the pipeline's risk level and critical risk factors by establishing a pipeline risk assessment index system. The proposed method fully considers the uncertainty in the evaluation process, resolves the contradiction of existing methods to model the fuzzy concepts accurately, optimizes the weight distribution, and obtains a more scientific and reasonable assessment result. A case study is conducted on a pipeline in Beijing City. The results illustrate that the proposed method is beneficial for helping pipeline operators determine the pipeline risk status and weak links in the pipeline system, thereby providing a basis for risk control and rehabilitation.

Recently, hazardous cargo accidents such as those at Beirut and Tianjin ports have raised serious concerns over how high-risk cargoes should be handled. While the role of human error in such accidents is widely known, knowledge of how the related factors interact is less developed. To that end, the present study analyzed 352 hazardous cargo accidents occurring at ports between 1960 and 2018. A novel research framework, the Human Factors Analysis and Classification System for Port Environment Hazardous Cargo Accidents (HFACS-PEHCA) was developed for the analysis. The findings revealed that violations, limited intellect, inappropriate supervision, and an inadequate safety culture were the most prominent factors involved in hazardous cargo accidents. Correlations between these factors were established and the probabilities of five accident causation paths were calculated. The most likely way for a hazardous cargo accident to occur was via the path “Deficient safety culture → Inappropriate supervision → Limited Intellect → Violations.” The study draws on these insights to propose safety procedures to mitigate the risk of accidents at ports dealing with hazardous cargo.

This paper presents a tank farm safety assessment method based on the structure entropy weight method and cloud model. This method considers the natural fuzziness of safety and fluctuation in the safety level, which can not only provide the assessment index weights combined subjectively and objectively but also consider the fuzziness of the safety level boundary. Finally, this method can be used to obtain a scientific safety level to prevent accidents. In addition, taking the tank farms of four petroleum and petrochemical companies as examples, this safety assessment method is verified to be an effective tool for safety management.

The work presented in this paper used a quantitative analysis of relevant risks through the development of fault tree analysis and risk analysis methods to aid real time risk prediction and safety evaluation of leak in a storage tank. Criticality of risk elements and their attributes can be used with real time data to predict potential failures likely to occur. As an example, a risk matrix was used to rank risk of events that could lead to a leak in a storage tank and to make decisions on risks to be allowed based on past statistical data. An intelligent system that recognizes increasing level(s) and draws awareness to the possibility of additional increase before unsafe levels are attained was used to analyse and make critical decisions. After a visual depiction of relationships between hazards and controls had been actualized, dynamic risk modelling was used to quantify the effect controls can potentially have on hazards by applying historical and real-time data into a probabilistic model. The output of a dynamic risk model is near real-time quantitative predictions of risk likelihood. Results from the risk matrix analysis method mixed with RTD and FTA were analyzed, evaluated, and compared.

Journal of Cleaner Production, Volume 174, 2018, pp. 96-113

This paper presents a new approach for robust load-flow in radial and meshed electric power systems. In the presented method, with an acceptable level of accuracy, and even exact, the ability of radial basis function (RBF) artificial neural networks (ANNs) for nonlinear mapping is exploited to solve nonlinear equation set of load flow analysis that can be applied to a wide range of nonlinear equation sets. Unlike Newton Raphson (NR) method, the proposed method does not need to calculate partial derivatives and inverse Jacobian matrix and so has less computation time. Moreover, it is suitable for the radial and ill-conditioned networks that have higher values of R/X ratio. The method includes all types of buses, i.e. PQ, PV and Slack buses. The proposed method is a general method which is applicable to all types of power system networks, including radial, meshed, and open-loop. The proposed method is applied to different power and distribution test systems and compared with the other load-flow methods and the results validate its authenticity, robustness, efficiency and accuracy.

Journal of Cleaner Production, Volume 174, 2018, pp. 139-149

China has modified its pollution control policy system with such price tools as the pollution charge (PC) policy and the payment for initial emission allowance (PIEA) policy. The aim of PC policy is to compensate for the environment damage caused by pollutants, while PIEA is in charge of the initial emission allowance (IEA) within the emission trading system (ETS). However, since the implementation of PIEA, it has been criticized as redundant because of the similar pricing scheme with the PC. In addition, the existing PIEA pricing approaches have ignored interactions with other policies, such as PC and total emission control (TEC) policies. In this research, we established an optimal control-based model with chemical oxygen demand (COD) and ammoniacal nitrogen (NH₃-N), two independent pollutants variables, to simulate the water pollutants' PIEA price. Simulation results indicated that emission quantity and optimal social benefit in the PC–PIEA combination scenario was equal to the situation in the PIEA scenario. Under this design, PC compensated for the emission damage, and PIEA paid for the scarcity rent, while PIEA does not duplicate the PC policy. In addition, the PIEA policy has a complex effect on pollutant emission. Because PIEA policy increases the enterprises' discharging cost, most regions' COD emissions are less than the baseline, excepting Beijing, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, and Guangdong, in which emission quantities are greater than the baseline. The NH₃-N emission shows an opposite trend. The simulation result is that excluding Inner Mongolia, Hubei, Hunan, Tibet, Gansu, Qinghai, Ningxia, and Xinjiang, the NH₃-N emissions in the rest of regions are increased. TEC policy has a significant effect on pollutant emissions and the PIEA price. The COD emission quantity with TEC is lower than that without the TEC policy, therefore, the TEC policy will be effective for pollutant emission control. The pollutant beyond the restricted target will be charged a payment for IEA at a higher price than without the TEC policy.

Journal of Cleaner Production, Volume 174, 2018, pp. 324-332

Solid leather waste can be considered as a composite material highly structured whose organization is intimately connected with the collagen fibers. Any process aimed at destroying such structure is economically and energetically disadvantageous. A more cost-effective approach therefore would be to reuse the solid leather waste avoiding the wrecking stage: Principle of Minimal Wrecking. The maximum efficiency of the method can be achieved if waste separation is so subtle that each waste becomes a homogeneous system, ie raw material for a new production: Principle of Maximum Separation. These general principles have been applied to handle to solid leather waste from a bovine leather industry manufacturing soles and uppers where the separation process has been refined up to post-tanning dyeing stage. The collagen fibers of leather waste were classified on the basis of length and their compatibility with cellulose was morphologically monitored via electronic microscopy and quantitatively analyzed via physical tests. The degree of compatibility was such that no chemical pretreatment of the material was required. Thereby several ternary systems consisting of mixed newspapers, newspapers and leather waste of long fibers at different composition, were prepared for simple mixing. For each formulation a paperboard type was manufactured whose mechanical performance was tested according to ISO recommendations. The system of composition 70% mixed newspapers, 15% newspapers and 15% leather waste with long collagen fibers, exhibited the best performances and the paperboard quality was comparable to one of boxes and packaging commercially used. In addition, release tests proved the complete absence of Cr(VI) in the material. Transforming solid leather waste into new raw material increases the life cycle of the material and drastically reduces its environmental impact.

Journal of Cleaner Production, Volume 174, 2018, pp. 315-323

Due to the uncertainties resulted from environmental changes, the importance of green development has been paid increasingly attention in the world. However, our knowledge of the green development level of nine cities in the Pearl River Delta (PRD), China, was still limited. Therefore, this study, based on the analysis on the connotation of green development, employed multi-level evaluation method and entropy method to develop the urban green development evaluation index system from five aspects, including enhancement of living environment, treatment and utilization of pollutant, improvement of ecological efficiency, optimization of economic growth and development of innovative potential. This evaluation index system was further applied to evaluate the green development level of nine cities within PRD. Results showed that significant difference in green development level occurred among cities within PRD. Green development level in Shenzhen, Zhuhai, Guangzhou was relatively higher than that in other cities, with the advantages in improvement of ecological efficiency and optimization of economic growth. Green development level in Zhongshan, Dongguan, Huizhou, Foshan averaged in PRD, while Jiangmen and Zhaoqing had a delayed green development level because of their irrational economic structures and extensive growth patterns though these two cities possessed good ecological environment endowments. In the future, it is necessary for PRD to formulate specific and targeted policies and measures to further upgrade energy structure, transform industrial structure, improve public transportation, enhance forestry carbon sink, and eventually construct low-carbon circular industrial system and development pattern.

Engineering Structures, Volume 212, 2020, Article 110514

The improved fish-bone (IFB) model for seismic analysis of older and contemporary reinforced concrete frames is proposed by introducing a new procedure for the estimation of parameters of structural elements of the fish-bone model. The procedure makes it possible to approximately account for the importance of structural elements on the seismic response of a frame building and the effect of potential redistribution of demands between structural elements of the frame building. Firstly, the IFB model is described. Follows demonstration of its capability by simulating the response history of storey shears, storey drifts and storey accelerations of selected pseudo-dynamically tested frames. Finally, it is shown that the IFB models can provide pushover curves, the corresponding damage states and fragility functions based on response history analysis which are very similar to those obtained by the conventional multi-degree-of-freedom models. The capability of the IFB model with respect to conventional fish-bone model is also demonstrated by the pushover analysis. It can be observed that the IFB model significantly improves the simulation of the older reinforced concrete frames, which do not fulfil the strong column – weak beam concept, and the frames for which the columns or beams of one storey of a frame building differ significantly from each other. Additional research is needed to extend the capabilities of simplified structural models to plan irregular frame building.

Automation in Construction, Volume 37, 2014, pp. 98-109

Improvements to sustainability are generally measurable based on their environmental, economic, and socio-cultural effects. This study applied this concept by developing and empirically testing a risk-based method for assessing renewable energy policy. An integrated theoretical framework is proposed for analyzing group decision-making regarding renewable energy (RE) policy selection. The proposed graphical matrix approach combined with Monte Carlo simulation compares alternative RE schemes by identifying and measuring critical performance indicators with acceptable reliability. The mathematical model reliably prioritizes alternatives using majority voting to address uncertainty in multi-criteria decision making process. A case study using historical data from previous RE development projects to confirm the feasibility of this approach. Compared to the conventional deterministic method, the stochastic graphical matrix approach provides more reliable estimation accuracy, decision quality, and efficiency in selection of sustainable renewable energy. The systematic approach provides policy makers information for use in evaluation by synthesizing the judgments of a panel of experts.