Occurrence Of Major Accidents Research Articles

Design and implementation of an accelerating rate calorimeter based on Modelica modeling

The safety of self-reactive chemicals has garnered attention due to their immense destructive power. The use of an accelerating rate calorimeter allows for more accurate measurement and understanding of the kinetic parameters and reaction mechanisms of self-reactive chemicals, thereby reducing the occurrence of major accidents. In this study, a new accelerating rate calorimeter is designed and constructed by combining Modelica and a fuzzy Proportional-Integral-Derivative algorithm. The feasibility of the calorimeter data was verified by using two solutions with significantly different reaction rates: 20 % mass fraction di‑tert‑butyl peroxide/toluene and tert-butylperoxy-2-ethylhecanoate. Their thermal hazard characteristic parameters were compared with the literature data. In addition, the risk level of thermal runaway was determined using the Stoessel risk assessment method. These results demonstrate that the accelerating rate calorimeter based on Modelica modeling meets the accuracy of thermal hazard characteristic parameters. It is capable of performing risk assessments for runaway reactions of self-reactive chemicals.

Design of the Comprehensive Monitoring System of Ro-Ro Ship Power Plant Based on LabVIEW

In this paper, using power machinery monitoring technology, testing technology, signal analysis and processing technology, combined with the characteristics of the dual-engine and double-propeller arrangement, carrying, complex waters and variable operating conditions of the power unit of the ro-ro ship, a set of virtual instruments is designed for the power of the ro-ro ship. Device integrated monitoring system. The system has a complete set of comprehensive monitoring system, which can monitor the power output working status of the power unit of the ro-ro ship. Under different working conditions, the system can collect and analyse signals through sensors, and automatically obtain information such as combustion work in the cylinder, gearbox gear transmission and meshing, shaft trajectory dynamic vibration and shaft power, and is a monitoring platform for marine power plants. The development and intelligent cabin provide technical support. The system realizes the automatic monitoring of ships, effectively improves the safety and reliability of ship operations, and reduces and avoids the occurrence of major accidents. At the same time, it has also completed the integration and digitization of ship power plant monitoring, providing support for decision-making in the use, operation and control, maintenance, and management of equipment and systems, effectively improving the safety and reliability of ship operations, and further promoting the development of smart ships and smart engine rooms.

Incipient fault prediction for nonlinear stochastic distribution systems

AbstractIn order to avoid the occurrence of major accidents in the industrial production process, incipient fault prediction that can predict fault in advance has attracted more and more attentions. In this article, a generalized correntropy filtering‐based incipient fault prediction strategy is proposed, which is suitable for nonlinear stochastic distribution systems with simultaneous actuator and sensor faults and non‐Gaussian noise. Three filters are designed to predict the incipient fault of nonlinear stochastic distribution systems: the first one is used to predict the time when the incipient fault occurs, and the other two are used to estimate the evolution rate of sensor fault and actuator fault, respectively. When the residual signal exceeds the predetermined threshold, the fault is detected and the time of occurrence can be also estimated. Once the fault is detected, the designed filter can be used to estimate the evolution rate of the unknown fault. After estimating the time of fault appearance and its evolution rate, the change process of incipient fault can be predicted. Finally, an example of a chemical reaction process is given to illustrate the validity of the prediction scheme.

Multi-objective optimization for preventive maintenance of offshore safety critical equipment integrating dynamic risk and maintenance cost

Safety-critical equipment (SCE) are installed on offshore installations as important safety barriers to prevent the occurrence of major accident. In order to ensure the specified safety function of SCE, preventive maintenance (PM) is an indispensable activity. However, PM decision making is still a challenge as it is influenced by various factors such as the risk in association with SCE degradation, risk in association with PM, and maintenance-related cost. Especially, the relevant risks are inherently dynamic in nature and the effects of these influence factors are conflicting. Therefore, this study focuses on the optimization of PM interval for SCE integrating the dynamic characteristics of risk and the conflicting effects among the increased risks due to PM and SCE degradation as well as maintenance-related cost. A systematic multi-objective optimization framework is proposed for the PM interval optimization. Two dynamic risk models are established for the evaluation of dynamic risk profiles of SCE in the operational phase and PM phase respectively. In combination with the lifecycle maintenance-related cost model of SCE, the multi-objective optimization with three objective functions is conducted for the PM interval optimization. The proposed framework is applied in the case study on a typical SCE (pressure safety valve, PSV) to optimize the PM interval. The effectiveness and availability of this framework is verified. It is noted that the common industrial practice of conducting PM once a year is acceptable for PSV once the risks in both operational and PM phases are given equal importance weight. However, a larger PM interval is recommended when the lifecycle maintenance-related cost is included in the optimization goal and further validation procedures are conducted, i.e. statistical analysis of optimal candidates and reassessment of risk profile with the optimal candidates. The proposed multi-optimization framework provides a useful tool for the optimal PM interval determination for the SCE on offshore installations.

An intelligent diagnosis model of accidents in nuclear power plant

This essay focus on the situation when the operator of the main control room can not handle the accident in time or make wrong judgment under accident condition in nuclear power plant, which may lead to the occurrence of major accidents or even more accidents concurrently. An intelligent fuzzy diagnosis model based on Grey Relational degree is constructed in this paper, by establishing accident-state correlation matrix and accident-state probability matrix, defining the vector of information weights for accident characteristic vector and monitoring result vector with linear transform, using Grey Relation to measure the relevance degree between monitoring result vector and accident characteristic vector, Searching for suspected accidents approaching to real solutions in iterative recursive algorithms, realizing automatic fuzzy diagnosis of multiple accidents. The results of simulation experiments of LOCA accidents indicate that the model and algorithm can diagnose various common accidents accurately and rapidly in complex nuclear power systems, providing strategy for operator’s diagnosis decision.

Safety evaluation of major hazard installations based on regional disaster system theory

Major accidents have catastrophic effects on humans and all of society. To prevent the occurrence of major accidents, it is essential to strengthen the management of major hazard installations. Generally, effective identification and reasonable evaluation of major hazard installations are the basic steps in safety management. At present, the evaluation methods for major hazard installations mainly focus on consequence analysis and probabilistic analysis without considering the vulnerability of hazard-affected bodies. Therefore, the proposed method will introduce regional disaster system theory and comprehensively analyze hazard-formative factors, the hazard-formative environment and hazard-affected bodies to achieve a more complete and effective assessment of major hazard installations. Hazard-formative factors are evaluated based on the rapid ranking method, hazard-formative environments are evaluated based on Bayesian networks, and hazard-affected bodies are evaluated based on the fuzzy comprehensive evaluation method. A tank group and a chemical industrial park are used to verify the feasibility and effectiveness of the new method.

보우-타이 기법을 활용한 위험관리 사례 연구

The main purpose of safety management is to reduce the frequency of accidents. If a company has steadily succeeded in reducing accidents with sustained efforts, the area that the company should be interested in is the occurrence of major accidents that have a very low frequency of accidents. This serious industrial accident is an event that should not happen forever unless the company wants to become bankrupt. Once it happens, it will have a disastrous impact on the business. In developed countries, especially In Europe, R&D projects have been promoted in order to prevent serious industrial accidents after they’d suffered from the Alexander Kielland accident in 1980 (Norway) and the Piper Alpha accident (UK) in 1988 As a result, barrier management has been adopted as the most effective approach to prevent major accidents. Shell has developed Bow-tie which is one of barrier managements, having made it gone up in the world. Bow-tie is currently legislated in many countries and is being used for risk management in various industries. In China, Malaysia and Singapore, companies using bow-tie technique continuously is being increased. In Korea, however, there have been no successful cases even though some companies have attempted it. In this research, bow-tie was applied to oil refinery company to effectively respond to complex emergency situation, and Barrier review to prevent serious accidents for R&D project of a steel company. Lastly, a serious accident that was conducted by the accident investigation committee at a petrochemical company was investigated again with Bow-tie. Through this research, it was confirmed that bow-tie is effective tool for risk management, so that I expect there will be an opportunity for Korean companies to recognize what efforts should be made to prevent serious industrial accidents.

Research on Parallel Control Technology of Three-phase Inverter Based on Multiple Proportional Resonance Controller

The parallel operation of multiple inverters can increase the fault tolerance of the system and prevent the occurrence of major accidents. At the same time, it also has strong flexibility, which can reduce the volume and weight of the system and increase the capacity of the system, which is very attractive in the application of uninterruptible power supply. In the inverter parallel system, the circulation will be generated between the inverters due to the existence of the path. Circulation can cause current distortion, reduce system performance, and even damage equipment in severe cases. In order to effectively suppress the generation of circulation, this paper proposes a multiple proportional resonance control strategy for the parallel three-phase inverter system, that is, the voltage outer loop is controlled by PI+PR, and the current inner loop is controlled by PR. Two three-phase inverter parallel systems are built in MATLAB/Simulink simulation environment to compare and analyze the control effect of uncontrolled, traditional PI control and multiple PR control. The simulation results show that the proposed control method has a good suppression effect on the circulation generated in the inverter parallel system, even under the condition of unbalanced load.

Research and Practice on Compound Talents Training Model of Safety Management—A Case Study from Xi'an University of Science and Technology

The current frequent occurrence of major accidents shows the urgent need of the society for compound talents in safety management. At present, the training of safety engineering talents in colleges and universities is more prominent in the safety knowledge and skills of students in their professional fields. Therefore, by analyzing the problems existing in the training of safety engineering professionals in engineering colleges and universities, the necessity of cultivating safety management talents has been discussed. According to the questionnaire, we can understand the social needs of safety management talents and analyze the knowledge structure of safety management talents. It also introduces the attempts of Xi'an University of Science and Technology(XUST) in the training of safety management compound talents. Through exploring the training method of safety management compound talents, it provides a reference for improving students' comprehensive practical ability and innovative ability in safety technology and management.

Design of Combustible Gas Automatic Detection and Alarm System

With the social development, gas has been widely applied to various aspects of social life. However, the combustible gas has brought us great convenience, but also there is a considerable risk. Based on this, we designed a kind of "prevention" as the characteristics of the combustible gas automatic detection and alarm systems. The system is the choice of technology is mature and low-cost entry-level 52 series microcontroller as the control center, the whole system is divided into classification sensor detection, alarm distinguishes between sound and light alarm, force control bodies of three parts. The system will detect concentrations of flammable gases, scientific classification, for different grades of police intelligence, the appropriate device driver to send a loud sound and light alarm signal. When you reach the highest level but no one to lift the danger, the system will automatically cut off the gas supply to open the ventilation exhaust and other devices to prevent the occurrence of major accidents, to achieve "prevention first, combining prevention and control" of the human and automatic alarm control system. The automatic alarm control system available in the field of gas alarm has been widely used, it has certain extensibility, compatibility, and stability.

Wind power cabin high temperature hot spot remote intelligent monitoring and early warning system

With the increasing energy crisis, the development and utilization of wind energy, which is a substitute for traditional energy sources and has renewable and cleanliness, has gradually attracted the attention of people all over the world. While the wind power industry is growing rapidly and the unit capacity of the unit is gradually increasing, the operational safety of wind power equipment is receiving more and more attention. If the wind turbine component fails, the small one will result in downtime maintenance, and the other will cause the machine to be destroyed. Because the wind farm is built in remote areas or offshore areas far away from the city, the traffic is inconvenient, and the wind turbines are at high altitude, so it is very difficult to maintain the unit. Once a fault or fire occurs, it is difficult to rescue in time. Let it develop its accident. In view of the high cost of detection, the failure of detecting faults, and the high proportion of missed faults, the on-line monitoring of the operating status of wind power equipment, the real-time diagnosis of early warning faults, and the maintenance of equipment are also important. The online monitoring system is applied to the health monitoring of wind power equipment, which not only can alert the equipment to potential failures, avoid the occurrence of major accidents, but also can determine the fault type and severity of the equipment based on the integration of existing analytical methods. Save on operational maintenance and repair costs. At a deeper level, mining and analyzing the monitoring data can also complete the estimation of the equipment’s continuous running time before the major accident, promptly remind the staff and provide reasonable rescue plans and solutions.

Equipment Condition Monitoring and Diagnosis System Based on Evidence Weight

To ensure the safety and reliability of equipment and effectively prevent the occurrence of major accidents, a monitoring and diagnosis system of equipment condition is proposed in this paper. First, a perceptual model of four layers, which can collect the original data of equipment by sensors and analyze the real-time information with intelligent algorithms and display the decision making on the screen, is designed. Second, a method of condition monitoring and diagnosis based on evidence weight is proposed. The basic probability assignment of evidence is corrected by Mahalanobis distance and sensor weight. A threshold is introduced to select the appropriate fusion rule by comparing the relationship between threshold and conflict factor. In order to verify the effectiveness and practicability of the method, the improved fusion algorithm is applied to the monitoring and diagnosis of centrifugal pumps. Finally, a prototype system is implemented to illustrate the validity of the system in practice.

The radial basis function analysis of fire evacuation model based on RBF neural network

After the occurrence of major accidents, the people in the buildings should be evacuated to safe areas within the shortest time. It is the important part of safe evacuation and reduction of mass mortality accidents. Therefore, the research of fire evacuation problem has highly theoretical and practical values. In the fire evacuation scene, the individual attributes are affected by psychology and behavior among individuals. Based on radial basis function neural network, we used the principal component analysis to determine six main factors affecting evacuation time. These factors are taken as the input of neural network; the evacuation time as the output of neural network. The network was trained by 125 sets of survey data. The quadratic sum error of the model was similar to 0, thus better achieving simulation of actual situation.

The laser shock processing control system

This paper introduced control system for complex curved surface laser shock processing, which was a set of automatic and digital control system operation, and controlled by the industrial PC/PLC. And it completed the real-time online monitoring and information interaction feedback, belonging to the open distributed system, by the fact that the remote monitoring and control system status of processing effectively avoid the occurrence of major accidents. This system was laser shock processing core device (including laser, robot, auxiliary control, quality testing device and auxiliary system, etc.), that implemented each link of information interaction and systems work together. By the remote monitoring, control system status of processing effectively avoided the occurrence of major accidents. At the same time, the control system added process of laser shock processing test data record function. According to actual demand parameters database called the background, parameter optimization was processed effectively. In addition, the system also could realize laser shock processing model established in this paper, complex surface machining trajectory planning automatically and processing strategy. The system can realize the automatic production of the whole blade laser impact of aero engine, and it is already in the engineering application stage.

Efficiency prediction of control room operators based on human reliability analysis and dynamic decision-making style in the process industry

Process industries have a potential for the occurrence of major accidents. These accidents can have severe adverse effects on human health and the environment and they can cause extensive damage to equipment and buildings. During major process upsets, central control rooms are among the most stressful workplaces in the world. Therefore, Human Reliability Analysis and Dynamic Decision-Making Styles (DDMSs) play an important role in safety management in these industries. This study employs the intelligent Adaptive Neuro Fuzzy Inference System model associated with two questionnaires along with Cognitive Reliability Error Analysis Method to analyze the Human Reliability Influencing Factors (HRIFs) and DDMSs of the control room operators and to determine the efficiency of operators as well as their dominant and efficient decision-making styles. Nine influencing factors on human reliability and five DDMSs are evaluated and the correlation between the HRIFs is investigated. Efficiency of the operators, according to the HRIFs, is determined and they are ranked. Next, the most dominant and efficient of the DDMSs among the operators was identified. Finally, an intelligent algorithm for determining the efficiency of a control room's operators is developed. © 2015 American Institute of Chemical Engineers Process Saf Prog, 2015

The social bases of nuclear energy policies in Europe: Ideology, proximity, belief updating and attitudes to risk

AbstractThis article analyses the social bases underpinning the widely different trajectories of nuclear energy policies across Western European countries. Employing a set of surveys carried out in the last thirty years, it examines the conditional effects of ideology and geographical proximity to a nuclear power plant on attitudes toward nuclear energy, as well as the long‐ and short‐term dynamics of belief updating after the occurrence of major accidents. Results highlight how proximity can strengthen, weaken or have no effect on the ideological component of these attitudes. Moreover, the publics of most countries with experience in nuclear energy display the traits of Bayesian dynamics of belief updating, especially in the vicinity of a plant. The article also shows the fairly exceptional traits of French public opinion. In conclusion, the broad social constraints within which governments operate, across time and space, shed light on the different policy trajectories of European countries.

Maintenance-related major accidents: Classification of causes and case study

The potential for major accidents is inherent in most industries that handle or store hazardous substances, for e.g. the hydrocarbon and chemical process industries. Several major accidents have been experienced over the past three decades. Flixborough Disaster (1974), Seveso Disaster (1976), Alexander Kielland Disaster (1980), Bhopal Gas Tragedy (1984), Sandoz Chemical Spill (1986), Piper Alpha Disaster (1988), Philips 66 Disaster (1989), Esso Longford Gas Explosion (1998), Texas City Refinery Explosion (2005), and most recently the Macondo Blowout (2010) are a few examples of accidents with devastating consequences.Causes are being exposed over time, but in recent years maintenance influence tends to be given less attention. However, given that some major accidents are maintenance-related, we intend to concentrate on classifying them to give a better insight into the underlying and contributing causes.High degree of technological and organizational complexity are attributes of these industries, and in order to control the risk, it is common to deploy multiple and independent safety barriers whose integrity cannot be maintained without adequate level of maintenance. However, maintenance may have a negative effect on barrier performance if the execution is incorrect, insufficient, delayed, or excessive. Maintenance can also be the triggering event.The objectives of this article are: (1) To investigate how maintenance impacts the occurrence of major accidents, and (2) To develop classification schemes for causes of maintenance-related major accidents.The paper builds primarily on model-based and empirical approaches, the latter being applied to reports on accident investigation and analysis. Based on this, the Work and Accident Process (WAP) classification scheme was proposed in the paper.

Dynamics of low-viscosity oils retained by rigid and flexible barriers

Oil spills are of major environmental concern in coastal regions. Experience shows that even the best efforts have not prevented the occasional occurrence of major accidents on the sea. As long as massive oil spills are probable, special techniques and equipment will remain essential for facilitating spill cleanup in coastal regions. Mechanical oil barriers, or “booms”, are used to contain or divert oil spills on water and are key tools in oil spill response. Recently, an anti-pollution boom, called the Cavalli system, was designed with the intention of preventing the spread of spilled oil by trapping it inside a flexible floating reservoir and improving the pumping operation by decreasing the reservoir surface, consequently increasing the oil layer thickness. The main aim of the present study is to investigate the response of barriers of different types (rigid/flexible) in oil slick containment and to evaluate the capability of a trapping reservoir, i.e., the Cavalli system, as a particular case. For this purpose, both experimental and numerical approaches were pursued. Two-dimensional experiments with rigid and flexible barriers containing a low-viscosity oil were conducted in a laboratory flume. To enhance the understanding of the mechanisms associated with oil containment, numerical simulations were also carried out. The slick shape evolution and dynamics, failure initiation, and rate of oil loss under different conditions were examined and analyzed. An empirical relationship was suggested in order to assess the maximum permissible oil–water relative velocity as a function of barrier draft and oil characteristics. Equations were also proposed to predict the slick length and headwave thickness as a function of contained oil volume.

Availability of Community Level Information on Industrial Risks in the EU

In this paper, European Commission policy issues in industrial risk management are discussed, especially with regard to the new Directive on the control of major accident hazards involving dangerous substances (Seveso II Directive). In all new risk management related elements of this Directive, such as Safety Reports, Safety Management Systems or Land Use Planning, particular emphasis is given to efficient flows of relevant information among the operators of a site that falls under the Directive (Seveso Plant), the national Competent Authority, the European Commission and the general public. Two types of information can be distinguished: data describing the risk potential of Seveso Plants and data describing the full spectrum of accident causation and evolution at such plants. The first type of risk related information is available prior to a major accident (information on risk sources), while the second one is available only posterior to such events (accident data). The Commission's efforts to implement the Directive resulted not only in the establishment of a EU wide major accidents database (MARS, in operation since the days of the predecessor legislation, Seveso I), but also the current aim of establishing a Seveso Plants information system (SPIRS). In this paper, on the basis of experience with these two systems, developments with regard to the implementation of the Seveso I Directive in the EU Member States during the last 15 years are described, and trends in the number of Seveso Plants and number of major accidents that occurred at such plants are discussed. It is shown that the rate of occurrence of major accidents is approximately constant, and, since the number of risk sources has increased, the number of accidents per unit of activity therefore has decreased. Also, due to a different classification scheme, a significant increase in the number of Seveso Plants from Seveso I to Seveso II can be expected.