Showing papers in "Journal of Loss Prevention in The Process Industries in 2012"
TL;DR: This paper identifies the state-of-the-art in leak detection and localization methods and evaluates the capabilities of these techniques in order to identify the advantages and disadvantages of using each leak detection solution.
Abstract: Gas leaks can cause major incidents resulting in both human injuries and financial losses. To avoid such situations, a considerable amount of effort has been devoted to the development of reliable techniques for detecting gas leakage. As knowing about the existence of a leak is not always enough to launch a corrective action, some of the leak detection techniques were designed to allow the possibility of locating the leak. The main purpose of this paper is to identify the state-of-the-art in leak detection and localization methods. Additionally we evaluate the capabilities of these techniques in order to identify the advantages and disadvantages of using each leak detection solution.
429 citations
TL;DR: In this article, a fuzzy logic is employed to derive fuzzy probabilities of basic events in fault tree and to estimate fuzzy probabilities ( likelihood ) of output event consequences, which can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process.
Abstract: Vast amounts of oil & gas (O&G) are consumed around the world everyday that are mainly transported and distributed through pipelines. Only in Canada, the total length of O&G pipelines is approximately 100,000 km, which is the third largest in the world. Integrity of these pipelines is of primary interest to O&G companies, consultants, governmental agencies, consumers and other stakeholder due to adverse consequences and heavy financial losses in case of system failure. Fault tree analysis (FTA) and event tree analysis (ETA) are two graphical techniques used to perform risk analysis, where FTA represents causes (likelihood) and ETA represents consequences of a failure event. ‘Bow-tie’ is an approach that integrates a fault tree (on the left side) and an event tree (on the right side) to represent causes, threat (hazards) and consequences in a common platform. Traditional ‘bow-tie’ approach is not able to characterize model uncertainty that arises due to assumption of independence among different risk events. In this paper, in order to deal with vagueness of the data, the fuzzy logic is employed to derive fuzzy probabilities ( likelihood ) of basic events in fault tree and to estimate fuzzy probabilities ( likelihood ) of output event consequences. The study also explores how interdependencies among various factors might influence analysis results and introduces fuzzy utility value (FUV) to perform risk assessment for natural gas pipelines using triple bottom line (TBL) sustainability criteria, namely, social, environmental and economical consequences. The present study aims to help owners of transmission and distribution pipeline companies in risk management and decision-making to consider multi-dimensional consequences that may arise from pipeline failures. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process. A simple example is used to demonstrate the proposed approach.
239 citations
TL;DR: In this article, the authors proposed the principles and factors that contribute to the resilience of a process, including Flexibility, Controllability, Early Detection, Minimization of Failure, Limitation of Effects, Administrative Controls/Procedures, and five main contributing factors, including Design, Detection Potential, Emergency Response Plan, Human Factor, and Safety Management.
Abstract: Although many efforts have focused on studying methods to prevent incidents in major hazard plants, mishaps still occur because of various technical and human failures and random natural events. It seems that unexpected disturbances not being absorbed by the system and leading to catastrophes are unavoidable even under good risk management; this seems to be true especially today with the more complex systems. Resilience, which is the ability to recover quickly after an upset, has been recognized as an important characteristic of a complex organization handling hazardous technical operations. In response to the need to further improve the safety of industrial processes or plants, there is a need to study the resilience of a process operation incase unexpected events occur. The aim of this work is to propose the principles and factors that contribute to the resilience of a process. Both are identified based on literature reviews and expert opinions. Six principles, including Flexibility, Controllability, Early Detection, Minimization of Failure, Limitation of Effects, Administrative Controls/Procedures, and five main contributing factors, including Design, Detection Potential, Emergency Response Plan, Human Factor, and Safety Management are identified in this work. An example has been used to demonstrate and support recognized contributing factors. These principles and contributing factors can be applied to evaluations of the resilience of a design or process operation.
182 citations
TL;DR: It is proved that the disturbing signals can be efficiently removed by the analysis of time and frequency domain, while the new characteristics of the accumulative value difference, mean value difference and peak value difference of signals in adjacent intervals can detect the leak effectively and decrease the false alarm rate significantly.
Abstract: The leak of gas pipelines can be detected and located by the acoustic method. The technologies of recognizing and extracting wave characteristics are summarized in details in this paper, which is to distinguish leaking and disturbing signals from time and frequency domain. A high-pressure and long distance leak test loop is designed and established by similarity analysis with field transmission pipelines. The acoustic signals collected by sensors are de-noised by wavelet transform to eliminate the background noises, and time-frequency analysis is used to analyze the characteristics of frequency domain. The conclusion can be drawn that most acoustic signals are concentrated on the ranges of 0–100 Hz. The acoustic signal recognition and extraction methods are verified and compared with others and it proves that the disturbing signals can be efficiently removed by the analysis of time and frequency domain, while the new characteristics of the accumulative value difference, mean value difference and peak value difference of signals in adjacent intervals can detect the leak effectively and decrease the false alarm rate significantly. The formula for leak location is modified with consideration of the influences of temperature and pressure. The positioning accuracy can be significantly improved with relative error between 0.01% and 1.37%.
167 citations
TL;DR: In this paper, a game-theoretic approach is used to analyze the strategies selected by manufacturers to reduce life cycle environmental risk of materials and carbon emissions, through the application of the "tolerability of risk" concept.
Abstract: This paper provides an approach in the context of green supply chain management, using game theory to analyze the strategies selected by manufacturers to reduce life cycle environmental risk of materials and carbon emissions. Through the application of the ‘tolerability of risk’ concept, a basis for determining the extent of environmental risk and carbon emissions reduction has been established. Currently, scant attention is given to holistic supervision of the supply chain with respect to carbon emissions by governments, and thus the starting hypothesis here is that the default strategy that manufacturers will adopt is only to reduce carbon emissions, and thereby environmental risk, in so far as this is compatible with the aim of increasing revenue. Moreover, we further hypothesize that, once necessary governmental policy has been established in the supply chain management, the strategic choices of the manufacturers would be influenced by government penalties or incentives. A case example is provided to demonstrate the insight that indicates the application of game theory. The limitations of the game model and analysis are discussed, laying a foundation for further work.
151 citations
TL;DR: In this article, experimental tests were performed in a 5-L closed cylindrical vessel for explosions of hydrogen-methane mixtures in stoichiometric air, and different compositions of hydrogen molar content in the fuel were tested (from pure methane to pure hydrogen) at varying initial pressures.
Abstract: The effects of enriching natural gas with hydrogen on local flame extinction, combustion instabilities and power output have been widely studied for both stationary and mobile systems. On the contrary, the issues of explosion safety for hydrogen–methane mixtures are still under investigation. In this work, experimental tests were performed in a 5 L closed cylindrical vessel for explosions of hydrogen–methane mixtures in stoichiometric air. Different compositions of hydrogen–methane were tested (from pure methane to pure hydrogen) at varying initial pressures (1, 3 and 6 bar). Results have allowed the quantification of the combined effects of both mixture composition (i.e., hydrogen content in the fuel) and initial pressure on maximum pressure, maximum rate of pressure rise and burning velocity. The measured burning velocities were also correlated by means of a Le Chatelier’s Rule-like formula. Good predictions have been obtained (at any initial pressure), except for mixtures with hydrogen molar content in the fuel higher than 50%.
150 citations
TL;DR: In this article, a generic model based on Risk Influencing Factors has been developed and is adapted to use for specific failure scenarios, which is also useful in demonstrating the importance and effects of improving human and organizational aspects.
Abstract: Investigations of major accidents show that technical, human, operational, as well as organizational factors influence the accident sequences. In spite of these facts, quantitative risk analyses of offshore oil and gas production platforms have focused on technical safety systems. This paper describes an effort to develop further the quantitative risk analysis of the platform specific hydrocarbon release frequency by considering operational barriers in event trees and fault trees, as well as risk influencing factors that determine the basic event probabilities in the fault trees. A generic model based on Risk Influencing Factors has been developed and is adapted to use for specific failure scenarios. The full Bayesian Belief Network (BBN) model is presented, and two alternative implementations are outlined. Human error probabilities are discussed, importance measurement, as well as modelling of common cause and interactions. Use of the model is briefly outlined, but the possible applications are presented more thoroughly in a companion paper. It has been demonstrated that the model is capable of reflecting relative differences between alternative installations with different cultures and implementation of management systems. The model is also useful in demonstrating the importance and effects of improving human and organizational aspects.
145 citations
TL;DR: In this article, the authors proposed a methodology to characterize the uncertainties, aggregate knowledge and update prior knowledge or evidence, if new data become available for the bow-tie analysis, to minimize the overall uncertainty, fusing the knowledge of multiple experts and updating prior knowledge with new evidence.
Abstract: Bow-tie analysis is a fairly new concept in risk assessment that can describe the relationships among different risk control parameters, such as causes, hazards and consequences to mitigate the likelihood of occurrence of unwanted events in an industrial system. It also facilitates the performance of quantitative risk analysis for an unwanted event providing a detailed investigation starting from basic causes to final consequences. The credibility of quantitative evaluation of the bow-tie is still a major concern since uncertainty, due to limited or missing data, often restricts the performance of analysis. The utilization of expert knowledge often provides an alternative for such a situation. However, it comes at the cost of possible uncertainties related to incompleteness (partial ignorance), imprecision (subjectivity), and lack of consensus (if multiple expert judgments are used). Further, if the bow-tie analysis is not flexible enough to incorporate new knowledge or evidence, it may undermine the purpose of risk assessment. Fuzzy set and evidence theory are capable of characterizing the uncertainty associated with expert knowledge. To minimize the overall uncertainty, fusing the knowledge of multiple experts and updating prior knowledge with new evidence are equally important in addition to addressing the uncertainties in the knowledge. This paper proposes a methodology to characterize the uncertainties, aggregate knowledge and update prior knowledge or evidence, if new data become available for the bow-tie analysis. A case study comprising a bow-tie for a typical offshore process facility has also been developed to describe the utility of this methodology in an industrial environment.
104 citations
TL;DR: Wang et al. as mentioned in this paper investigated 1632 hazardous chemical accidents (HCAs) occurring in China (2006-2010) and found that the yearly number of HCAs is almost constant with a slightly increasing number of fixed facility HCAs.
Abstract: Utilizing data from official sources, 1632 hazardous chemical accidents (HCAs) occurring in China (2006–2010) were investigated for statistical characteristics. The following results were obtained: (1) Time volatility: The yearly number of HCAs is shown to be almost constant (with a slightly increasing number of fixed facility HCAs); fixed facility and transportation HCAs do not always follow similar patterns at month and hour-level. (2) Location distribution: There are provincial classifications of HCA materials involved in certain types of industries and the potential for HCAs is highly concentrated in urban areas. (3) Fixed facility type versus transportation type: Explosions represent almost half (48.4%) of fixed facility HCAs followed by releases (41.5%) and fires (10.1%); whereas for transportation HCAs, releases account for 79.6%, then explosions (15.1%) and fires (5.3%). As for domino effects, releases were often the cause of subsequent explosions or fires. (4) Injury versus death: In contrast with other industrial accidents, HCAs result in more severe casualties. For explosion and release HCAs in China, the ratio of death to major injury is quite high, with the exception of fire HCAs. (5) Cause: Concerning immediate causes, human factors account for the majority of HCAs followed by equipment deficiency; environment is also a causative factor. Internal corporate management failures and lack of external government supervision (particularly HCAs occurring in illegal corporations) are both root causes in China. (6)Corporate proneness: Majority of HCAs occur in private corporations; as corporations grow, the occurrence of HCAs are shown to decline steadily then level off, following which they are forecasted to increase again in the “aging stages”, all of which can be explained by Corporate Lifecycles Theory.
100 citations
TL;DR: In this paper, the authors investigated the effect of ventilation on spontaneous heating of coal in an isothermal oven and found that there is an optimum ventilation flow to produce the maximum rate of temperature rise at the critical ambient temperature when the coal sample particle size was increased.
Abstract: Ventilation plays an important role in the spontaneous heating of coal in an underground coal mine If the ventilation rate is too high, heat is carried away by convection If the ventilation rate is too low, the reaction rate becomes oxygen-limited The effect of ventilation on the spontaneous heating of coal was investigated in an isothermal oven in this study Experiments were conducted on three US coal samples with ventilation rates ranging from 100 to 500 cm 3 /min Experiments under ventilation were conducted to determine the critical ambient temperature, which is the minimum oven temperature required for a coal sample to achieve thermal runaway Spontaneous heating tests were then conducted at various ventilation rates at the critical ambient temperature and the results were compared with spontaneous heating tests without ventilation It was found that there is an optimum ventilation flow to produce the maximum rate of temperature rise at the critical ambient temperature When the coal sample particle size was increased, a higher critical ambient temperature was required The results in this study have application in the prevention of spontaneous combustion in underground coal mines
89 citations
TL;DR: In this paper, it was shown that complete transformation of bulk powders consisting of nm-particles into dust clouds consisting of well-dispersed primary particles is extremely difficult to accomplish, due to very strong inter-particle cohesion forces.
Abstract: Based on experience with powders of particle sizes down to the 1–0.1 μm range one might expect that dust clouds from combustible nm-particle powders would exhibit extreme ignition sensitivities (very low MIEs) and extreme explosion rates (very high K St -values). However, there are two basic physical reasons why this may not be the case. Firstly, complete transformation of bulk powders consisting of nm-particles into dust clouds consisting of well-dispersed primary particles is extremely difficult to accomplish, due to very strong inter-particle cohesion forces. Secondly, should perfect dispersion nevertheless be achieved, the extremely fast coagulation process in clouds of explosive mass concentrations would transform the primary nm-particles into much larger agglomerates within fractions of a second. Furthermore, for organic dusts and coal the basic mechanism of flame propagation in dust clouds suggests that increased cloud explosion rates would not be expected as the particle size decreases into the St -values than clouds of μm primary particles, in agreement with recent experimental evidence. In the case of the ignition sensitivity recently published evidence indicates that MIEs of clouds in air of some metal powders are significantly lower for nm particles than for μm particles. A possible reason for this is indicated in the paper.
TL;DR: In this article, the authors developed an accident modeling approach, SHIPP (System Hazard Identification, Prediction and Prevention), which identifies possible causal factors and potential consequences and provides quantitative results by combining fault and event tree analyses.
Abstract: The rapid growth in global demand for natural gas as a fuel has led to expansion of the production capacity of existing gas processing trains and the design of new process trains. The increasing complexity of high performance processing systems leads to more complex failure modes and new safety issues. To physical properties of liquefied natural gas (LNG) such as its cryogenic temperature and flammability and vapor dispersion characteristics, add additional concerns of potential safety issues. Therefore, continuous monitoring and implementation of appropriate actions are essential to prevent, control and mitigate unfavorable consequences of LNG production and use. The newly developed accident modeling approach, SHIPP (System Hazard Identification, Prediction and Prevention), is an important part of a comprehensive safety management system that helps to maintain and manage these safety issues. This approach is used to model accidents in gas processing facilities using safety barriers. It identifies possible causal factors and potential consequences and provides quantitative results by combining fault and event tree analyses. The predictive model employed in this approach helps to forecast the number of abnormal events in ensuing time intervals. In the current work, SHIPP has been validated using data from an LNG processing facility. Language: en
TL;DR: In this article, a failure modes and effects analysis (FMEA) method is developed using subjective information derived from domain experts to quantify the severity of personnel injury and environmental pollution, a risk index is introduced, and weight factors are determined by an analytic hierarchy process.
Abstract: Petrochemical facilities and plants require essential ongoing maintenance to ensure high levels of reliability and safety. A risk-based maintenance (RBM) strategy is a useful tool to design a cost-effective maintenance schedule; its objective is to reduce overall risk in the operating facility. In risk assessment of a failure scenario, consequences often have three key features: personnel safety effect, environmental threat and economic loss. In this paper, to quantify the severity of personnel injury and environmental pollution, a failure modes and effects analysis (FMEA) method is developed using subjective information derived from domain experts. On the basis of failure probability and consequence analysis, the risk is calculated and compared against the known acceptable risk criteria. To facilitate the comparison, a risk index is introduced, and weight factors are determined by an analytic hierarchy process. Finally, the appropriate maintenance tasks are scheduled under the risk constraints. A case study of a continuous catalytic reforming plant is used to illustrate the proposed approach. The results indicate that FMEA is helpful to identify critical facilities; the RBM strategy can increase the reliability of high-risk facilities, and corrective maintenance is the preferred approach for low-risk facilities to reduce maintenance expenditure.
TL;DR: In this article, a generic risk model has been developed and is adapted to use for specific failure scenarios, considering the operational barriers in event trees and fault trees, as well as risk influencing factors that determine the basic event probabilities in the fault trees.
Abstract: Operational safety is receiving more and more attention in the Norwegian offshore industry. Almost two thirds of all leaks on offshore installations in the period 2001–2005, according to the Risk Level Project by the Petroleum Safety Authority in Norway, resulted from manual operations and interventions, as well as shut-down and start-up. The intention with the Risk OMT (risk modelling – integration of organisational, human and technical factors) program has been to develop more representative models for calculation of leak frequencies as a function of the volume of manual operations and interventions. In the Risk OMT project a generic risk model has been developed and is adapted to use for specific failure scenarios. The model considers the operational barriers in event trees and fault trees, as well as risk influencing factors that determine the basic event probabilities in the fault trees. The full model, which applies Bayesian belief networks, is presented more thoroughly in a separate paper. This paper presents the evaluation of the model. The model has been evaluated through some case studies, and one important aspect is the evaluation of the importance of each risk influencing factor. In addition some risk-reducing measures have been proposed, and the paper presents how the effect of these measures has been evaluated by using the model. Finally, possible applications and recommendations for further work are discussed.
TL;DR: In this paper, the Inherent Safety Key Performance Indicators (IS-KPIs) methodology was developed to provide both a flexible procedure for the identification of the hazards, and a sound consequence-based quantification of the safety performance.
Abstract: Effective support of inherent safety implementation in process design requires a quantitative metric for monitoring and communicating the expected safety performance of alternative design options. The Inherent Safety Key Performance Indicators (IS-KPIs) methodology was developed to provide both a flexible procedure for the identification of the hazards, and a sound consequence-based quantification of the safety performance. The integration of different hazard identification techniques yields the relevant accident scenarios for each unit in the plant. The calculation of credible damage distances by consolidate consequence simulation models provides a sound basis for the definition of the KPIs based on worst case effects. Specific indicators were devoted to hazards from external actions, as natural events and intentional malicious acts. The methodology was demonstrated by the comparison of alternative technological options for LNG regasification. The application evidenced the potential of the IS-KPI method in pinpointing the critical issues related to each alternative configuration.
TL;DR: A hierarchical framework is prepared to for asset integrity monitoring and assessment based on three major areas of asset integrity, namely: mechanical, personnel and process and uses a risk metric to classify asset integrity through the integration of leading and lagging indicators’ outcome.
Abstract: Asset integrity is a major concern of process facilities. Monitoring and assessing asset integrity is a challenging task due to the involvement of various dependent and independent parameters. Monitoring and assessing asset performance through indicators is one easily doable option. Lack of an appropriate set of indicators quantification technique and measurement cohesion limits the use of an indicator system. To overcome this, in the present paper a hierarchical framework is prepared to for asset integrity monitoring and assessment. The hierarchical structure is used to characterize the asset and relate it to an organization’s strategic goal. The hierarchical structure is based on three major areas of asset integrity, namely: mechanical, personnel and process. Further, it provides an opportunity to follow a bottom-up perspective for identifying multilevel level indicators. The proposed approach uses a risk metric to classify asset integrity through the integration of leading and lagging indicators’ outcome. The analytical hierarchy process is used to determine the weights, or for prioritization of each level indicator and for the aggregation of the indicators to classify risk. To test the proposed model, a benchmark study is conducted. The estimated asset integrity index value provides a tangible asset’s performance index. The system of indicators and their integration provide a comprehensive view of the process facility’s status and also reveal which sections of the facility need more attention.
TL;DR: In this paper, the authors present the results of a parametric sensitivity analysis of a widely used model for atmospheric dispersion of toxic gases, in order better to understand the influence of user-adjustable parameters on model outputs.
Abstract: We present the results of a parametric sensitivity analysis of a widely used model for atmospheric dispersion of toxic gases, in order better to understand the influence of user-adjustable parameters on model outputs. We have studied 60 min continuous release scenarios for three different products (nitric oxide, ammonia and chlorine), chosen to cover a range of physical characteristics and storage conditions. For each product, we have broken down base-case scenarios into a number of sub-scenarios corresponding to different release conditions which determine physical phenomena (flow rate, release angle, release elevation and atmospheric stability class). The use of statistical tools to analyze the results of a large number of model executions allows us to rank model parameters according to their influence on the variability of a number of model outputs (distances and concentrations), on a per-scenario and per-product basis. Analysis of the results allows us to verify our understanding of the modeling of cloud dispersion.
TL;DR: In this paper, an original design of foaming agent adding device was introduced, and its performance was investigated experimentally under different working flows and outlet pressures, and compared to the conventional jet adding device.
Abstract: In order to overcome the drawbacks of foam technology for controlling mine dust, an original design of foaming agent adding device was introduced, and its performance was investigated experimentally under different working flows and outlet pressures, and compared to the conventional jet adding device. The results show that the new design of the foaming agent adding device has a reasonable cavity negative pressure, does not produce cavitations, and has a lower inlet pressure demand with less pressure loss. Furthermore, it can add foaming agent at 0.5%–1.0% and regulate the proportions at this low ratio range continuously and stably, which significantly reduces the cost of controlling dust with foam. In addition, it decreases electric energy consumption and simplifies the foam system with no need for extra boosters. Besides, its effect on suppressing mine dust was investigated in the field via dust sample collections, and the results show that this new device is as effective at dust suppression as the conventional one. Therefore, it is believed that this study laid an important foundation for the widespread application of foam technology for dust control in underground coal mines.
TL;DR: In this article, the authors apply thermal runaway criteria to the esterification of acetic anhydride and methanol catalysed by sulphuric acid in isoperibolic conditions.
Abstract: Loss of temperature control is one of the major reasons that can lead to runaway reaction. This occurrence is commonly named thermal runway. The aim of this paper is the application of thermal runaway criteria in order to predict the onset of runaway phenomena and define the range of stability related to operating conditions in the reactor, with specific reference to the esterification of acetic anhydride and methanol catalysed by sulphuric acid tested in isoperibolic conditions. The isoperibolic calorimeter has also been used to obtain thermodynamic, kinetic and physical chemistry data necessary to develop a model for the reaction. Some runaway criteria applied in this work require a model for the process, so a model for the analyzed system been developed. Because of the modest reaction enthalpy and low activation energy this reacting system provide a severe test to the runaway criteria. In this work, various runaway criteria have been applied to the experimental and simulated data and the results obtained have been compared.
TL;DR: In this paper, the authors present a systematic hazards identification methodology for liquid hydrocarbon fuel storage tanks, by applying a checklist technique on the accident causes and the relevant protection measures, in the framework of the SEVESO Directive series.
Abstract: This paper presents a systematic hazards identification methodology for liquid hydrocarbon fuel storage tanks, by applying a checklist technique on the accident causes and the relevant protection measures, in the framework of the SEVESO Directive series A forum discussion with Greek industrial safety experts has been also organised by the authors in order to locate any lack of the methodology Results are presented and discussed, and it is concluded that the present hazards assessment methodology helps to identify the major contributors to risk, to improve safety measures and to assist the analysis in these aspects
TL;DR: The current trends of future-oriented prevention management in the chemical-using industry are presented and two concepts leading to the next generation of managing prevention within chemical industrial areas are explained and discussed.
Abstract: This paper presents the current trends of future-oriented prevention management in the chemical-using industry. Two concepts leading to the next generation of managing prevention within chemical industrial areas are explained and discussed. The first concept concerns integrated design-based safety and security; the second concerns the collaboration of several chemical plants to increase sustainable development of their activities and their environment.
TL;DR: A framework which makes use of both qualitative and quantitative techniques to optimize RAM and cost decisions in a process plant and a resource optimization model based on multi-stage decision making (MSDM) has been proposed.
Abstract: The research implications of reliability, availability and maintainability (RAM) aspects of engineering systems in recent years have increased substantially due to rising operation and maintenance costs. To strike a balance between the two the paper presents a framework which makes use of both qualitative and quantitative techniques to optimize RAM and cost decisions in a process plant. In the quantitative analysis, the imprecise and vague information regarding the system failure behavior is quantified by using the principles of fuzzy mathematics in terms of fuzzy and crisp values. Further, to manage the system reliability for best economic performance a resource optimization model based on multi-stage decision making (MSDM) has been proposed. The model makes use of crisp output values of unit's reliability along with relevant system information (number of components, manpower, cost ranges). In the qualitative analysis the in-depth analysis of the system is carried out using Root Cause analysis (RCA) and Failure Mode & Effects Analysis (FMEA). The ambiguities associated with the traditional FMEA are handled using Fuzzy Decision Making System (FDMS) and Grey Relation Analysis (GRA). The suggested framework has been illustrated with the help of a case.
TL;DR: In this paper, the authors focused on dust explosions of coarse and fine flocculent (or fibrous) samples of wood and polyethylene and found that a general trend was observed of enhanced explosion likelihood and consequence severity with a decrease in material diameter.
Abstract: The research presented in this paper is focused on dust explosions of coarse and fine flocculent (or fibrous) samples of wood and polyethylene. Hybrid mixtures of fibrous polyethylene and admixed ethylene were also studied. Experimentation was conducted by following standardized test procedures and using standardized apparatus for determination of maximum explosion pressure, size-normalized maximum rate of pressure rise, minimum explosible concentration, minimum ignition energy, and minimum ignition temperature. A general trend was observed of enhanced explosion likelihood and consequence severity with a decrease in material diameter, as well as enhanced consequence severity with admixture of a flammable gas to the combustion atmosphere. The same phenomena are well-established for dusts composed of spherical particles; this highlights the importance of inherently safer design and the principle of moderation in avoiding the generation of fine sizes of flocculent dusts and hybrid mixtures of such materials with flammable gases. In addition to presenting experimental findings, the paper describes phenomenological modelling efforts for the flocculent polyethylene using four geometric equivalence models: radial equivalence, volumetric equivalence, surface area equivalence, and specific surface area equivalence. The surface area equivalence model was found to yield the best estimates of maximum rate of pressure rise for the flocculent polyethylene samples investigated experimentally.
TL;DR: In this article, the effects of particle characteristics on the mechanisms of flame propagation during organic dust explosions were analyzed in a half-closed small chamber and a high-speed video camera was used to record the flame propagation process.
Abstract: To reveal the effects of particle characteristics on the mechanisms of flame propagation during organic dust explosions clearly, three long chain monobasic alcohols which are solids at room temperature and have similar physical–chemical properties were chosen to carry out experiments in a half-closed small chamber. A high-speed video camera was used to record the flame propagation process and to obtain the direct light emission photographs. Flame temperature was detected by a fine thermocouple. Based on the experimental results above, analysis was conducted on flame propagation characteristics and temperature profiles of organic particle cloud. As a result, it was found that the particle materials, especially volatility, strongly affected the flame propagation behavior. Particle concentration also affects the combustion zone propagation process significantly. With increasing the particle concentration, the maximum temperature of the combustion zone increases at the lower concentration, reaches a maximum value, and then decreases at the higher concentration. The propagation velocity of the combustion zone has a linear relationship with the maximum temperature, which implies conductive heat transfer is dominant in the flame propagation process of the three different volatile dusts.
TL;DR: The Evidence Theory or Dempster–Shafer theory (DST) is proposed to deal with epistemic uncertainty in process plants, and the classical Fault Tree Analysis (FTA) is considered when input data are supplied by experts in an interval form.
Abstract: Process plants may be subjected to dangerous events. Different methodologies are nowadays employed to identify failure events, that can lead to severe accidents, and to assess the relative probability of occurrence. As for rare events reliability data are generally poor, leading to a partial or incomplete knowledge of the process, the classical probabilistic approach can not be successfully used. Such an uncertainty, called epistemic uncertainty, can be treated by means of different methodologies, alternative to the probabilistic one. In this work, the Evidence Theory or Dempster–Shafer theory (DST) is proposed to deal with this kind of uncertainty. In particular, the classical Fault Tree Analysis (FTA) is considered when input data are supplied by experts in an interval form. The practical problem of information acquisition from experts is discussed and two realistic scenarios are proposed. A methodology to propagate such an uncertainty through the fault tree up to the Top Event (TE) and to determine the belief measures is supplied. The analysis is illustrated by means of two simple series/parallel systems. An application to a real industrial safety system is finally performed and discussed.
TL;DR: A review of the main popular and typical methods used in mining industry to determine the mine gas explosibility are introduced and reviewed in this article, where case demonstrations for each method are also shown and can be used to instruct readers to understand how to apply them.
Abstract: Mine gas explosions present a serious safety threat in the worldwide mining industry. Since the beginning of mining, many coal miners have been killed due to the explosions. Accordingly, on a regular basis, mine operators should get air samples from the underground atmosphere. At the same time, monitoring and tracking the explosibility of the air sample should be done as a timely matter to avoid any potential explosions. All these works can provide very important information to assist the mine operators to well understand the mine atmospheric status and its trends. In additional, when facing the coal spontaneous combustion, mine fire events, or other chemical reactions related mine accidents, determination of explosibility is a definitely significant work for the safety of miners and mine rescue personnel especially when planning and implementing any mine rescue strategies. For many years, mining engineers and researchers have developed a number of methods for assessing the explosibility of the air–gas-mixture. Their research results provide a baseline for judgments of the mine gas explosibility and in determining the extent of change. In this paper, main popular and typical methods used in mining industry to determine the mine gas explosibility are introduced and reviewed. Case demonstrations for each method are also shown and can be used to instruct readers to understand how to apply them. Finally, a brief discussion about the current methods is presented and some preliminary suggestions are also listed for the further improvements in the future research.
TL;DR: The goals of the BLHAZID methodology are to generate outcomes that contain a high coverage of hazards, describe detailed failure causality in process systems and express this knowledge in a structured form for effective reused in subsequent applications.
Abstract: A novel hazard identification methodology applied to process systems is presented in this paper. This blended hazard identification (BLHAZID) methodology blends two different types of HAZID methods: the function-driven and component-driven approach. The BLHAZID method is based on a conceptual framework called the Functional Systems Framework, which describes structure–function–goal relationships in process systems.
The goals of the BLHAZID methodology are to generate outcomes that contain a high coverage of hazards, describe detailed failure causality in process systems and express this knowledge in a structured form for effective reused in subsequent applications, such as fault diagnosis, operator training, design reviews, fault and event tree construction and hazard updates to satisfy major hazard facility requirements.
Both the BLHAZID methodology and the Functional Systems Framework were developed with involvement and advice from two major industrial partners. An industrial case study of a benzene saturation unit is presented to illustrate how the BLHAZID methodology operates in practice.
TL;DR: In this paper, a critical comparison between two methodologies which could be applied for a near-miss event assessment: a matrix and an index-based method is proposed, and an application in a test case of a chemical plant is proposed: results obtained have proved useful in supporting safety management in an effective design of a NMS.
Abstract: A close relationship between near-miss events and major accidents has been demonstrated in major hazard facilities: a near-miss and an accident have often common causes. A near-miss could be defined as a hazardous condition where the event sequence could lead to an accident if it had not been interrupted. An effective Near-miss Management System (NMS) aims to quickly recognize signals from the operational fields in order to apply prevention strategies. As a standard reference model has not yet been developed, the NMS design represents a complex issue. The present paper proposes a critical comparison between two methodologies which could be applied for a near-miss event assessment: a matrix and an index based method. The purpose is to evaluate potentiality and pitfalls of their application as their global efficiency could influence the whole performance of the whole NMS design. An application in a test case of a chemical plant is proposed: results obtained have proved useful in supporting safety management in an effective design of a NMS.
TL;DR: In this article, the authors compared two training approaches, classic and creative, in improving health, safety and environment (HSE) supervisors' participation in a petrochemical complex where the safety supervisors had been encouraged to report incidents through the Green Card system.
Abstract: The increasing trend of deaths and injuries in industries has led their authorities to develop accident investigation plans. One of the underlying aspects of such plans is hazard identification and incidents reporting which can be met by an appropriate employees' participation. So far, several studies have confirmed the effect of training in participation improvement. So the main objective of the present study was to compare two training approaches, classic and creative, in improving health, safety and environment (HSE) supervisors' participation. The study was carried out in an Iranian petrochemical complex where the safety supervisors had been encouraged to report incidents through the Green Card system. Classic and creative training approaches were applied to increase supervisors' participation. To do so, the supervisors were divided into Case and Control groups. In order to determine the level of supervisors' participation, the mean of completed green cards by each person at six month intervals was used. In this way, the level of participation in the two groups was measured before, during and after the intervention. To analyze the results, Student's t-test, Longitudinal Data Analysis and Mixed Model were employed. The results showed that both during and after the intervention, the effect of the creative approach was more than that of the classic approach. After twelve months of intervention stop, the participation trend in both groups was downward. However, this decrease was only significant in the control group. To conclude, the creative approach emphasizing on the participatory training could be an effective approach in improving the safety and consequently the health of supervisors in industries. Language: en
TL;DR: In this article, a method for assessing the effectiveness in the steps of the learning cycle: the 1st loop with reporting, analysis, decision, implementation, follow-up, and the 2nd loop on an aggregated basis.
Abstract: This paper describes a method for assessing the effectiveness in the steps of the learning cycle: the 1st loop with reporting – analysis – decision – implementation – follow-up, and the 2nd loop on an aggregated basis. For each step, the dimensions considered the most relevant for the learning process (scope, quality, timing and information distribution) and for each dimension the most relevant aspects (e.g. completeness and detail) were defined. A method for a semi-quantitative assessment of the effectiveness of the learning cycle was developed using these dimensions and aspects and scales for rating. The method will give clear indications of areas for improvement when applied. The results of the method can also be used for correlation with other safety parameters, e.g. results from safety audits and safety climate inquiries. The method is intended to be used on a sample of the broad range of incidents normally seen in process industry companies. The method was tested on a two-year incident reporting material from six companies from various types of process industries. It was found that the method and the tools worked very well in practice. The results gave interesting insights into the effectiveness of learning from the incidents.