Showing papers in "Journal of Loss Prevention in The Process Industries in 2016"
Abstract: Pipeline faults like leakage and blockage always create problem for engineers. Detection of exact fault quantity and its location is necessary for smooth functioning of a plant or industry and safety of the environment. In this paper brief discussion is made on various pipeline fault detection methods viz. Vibration analysis, Pulse echo methodology, Acoustic techniques, Negative pressure wave based leak detection system, Support Vector Machine (SVM) based pipeline leakage detection, Interferometric fibre sensor based leak detection, Filter Diagonalization Method (FDM), etc. In this paper merit and demerits of all methods are discussed. It is found that these methods have been applied for specific fluids like oil, gas and water, for different layout patterns like straight and zigzag, for various lengths of pipeline like short and long and also depending on various operating conditions. Therefore, a comparison among all methods has been done based on their applicability. Among all fault detection methods, Acoustic reflectometry is found most suitable because of its proficiency to identify blockages and leakage in pipe as small as 1% of its diameter. Moreover this method is economical and applicable for straight, zigzag and long, short length pipes for low, medium and high density fluid.
244 citations
TL;DR: A review of existing knowledge on the genesis and flame acceleration of explosions from methane-air mixtures is presented in this paper, which leads the readers to understand the considerations which must be accounted for in order to obviate and/or mitigate any accidental explosion originating from methane air systems.
Abstract: This review examines existing knowledge on the genesis and flame acceleration of explosions from methane–air mixtures. Explosion phases including deflagration and detonation and the transition from deflagration to detonation have been discussed. The influence of various obstacles and geometries on explosions in an underground mine and duct have been examined. The discussion, presented here, leads the readers to understand the considerations which must be accounted for in order to obviate and/or mitigate any accidental explosion originating from methane–air systems.
154 citations
TL;DR: Based on measurements of explosion parameters of dust samples collected on the explosion site and on-site investigations and interviews, it was concluded that a series of consecutive explosions was initiated in one of the external dust filters as discussed by the authors.
Abstract: On August 2, 2014 a catastrophic dust explosion occurred in a large industrial plant for polishing various aluminium-alloy parts in Kunshan, China. The explosion occurred during manual polishing of the surfaces of aluminium-alloy wheel hubs for the car industry. 75 people lost their lives immediately and another 185 were injured. Subsequently, 71 of the seriously injured also died, which increased the total loss of lives to 146. The direct economic loss of was 351 million yuan. This is probably one of the most serious dust explosion catastrophes known apart from some very major coal dust explosion disasters in coal mines. Based on measurements of explosion parameters of dust samples collected on the explosion site and on-site investigations and interviews, it was concluded that a series of consecutive explosions was initiated in one of the external dust filters. Then it propagated into the main building via the dust extraction ducting and further onto the second floor. At the same time the propagating in-house dust flame was sucked into the ducts leading to seven other external dust filters, which also exploded. On the basis of investigations on site after the explosion and subsequent laboratory experiments and data analyses it was concluded that the explosion was most probably initiated by self-ignition of contaminated aluminium-alloy dust in the dust collecting barrel below the external bag filter unit in which the initial primary explosion took place. General ignorance of the potential risk of dust explosions in industries producing fine metal dusts as a low-mass waste by-product is the most probable basic root cause of this catastrophic accident. Therefore, avoiding accumulation of deposits of such dusts indoors by good regular housekeeping and other means is regarded the most effective and practical way of loss prevention due to metal dust explosions in such plants. In addition, explosion isolation between dust collecting systems and workshops appears to be another important measure towards minimizing the consequences of such explosions.
142 citations
TL;DR: A fuzzy approach enabling experts to use linguistic variables for evaluating two factors which are the parameters of matrix method is proposed to deal with shortcomings of a crisp risk score calculation and to decrease the inconsistency in decision making.
Abstract: Decision matrix risk-assessment (DMRA) technique is a systematic approach widely used in the Occupational Health and Safety (OHS) risk assessment. In a typical matrix method approach, a measure of risk value is obtained by evaluating two risk factors as the likelihood of a hazard and the severity of the hazard when it arises. In this paper, a fuzzy approach enabling experts to use linguistic variables for evaluating two factors which are the parameters of matrix method is proposed to deal with shortcomings of a crisp risk score calculation and to decrease the inconsistency in decision making. The parameters likelihood and severity related to the hazards in an aluminum plate manufacturing plant are weighted by using Fuzzy Analytic Hierarchy Process (FAHP), then the orders of priority of 23 various hazard groups are determined by using Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. As a follow-up study of the case application, the proposed risk assessment methodology is applied for hazard types in each department of the plant. Depending on the hazard control hierarchy, control measures are overtaken for the hazards that are placed at first of intra-department rankings.
133 citations
TL;DR: In the secondary literature, a difference is made between leading and lagging safety indicators as mentioned in this paper, and it can be expected that regulators of major hazard companies will ask to identify and implement both lagging and leading indicators, and anchor these indicators in a safety management system.
Abstract: Indicators for process safety can provide insight into safety levels of a process or of a company, but it is clear that the 'silver bullet' has not yet been identified. In secondary literature a difference is made between leading and lagging safety indicators. Primary literature questions this distinction, as well as the quantification of safety indicators. Safety Indicators for management and organisation have an ambiguous relationship with latent errors and conditions, being mentioned over and over in retrospective safety analyses of major accidents. Indicators for occupational safety do not necessarily have a relationship with process safety. In addition, it can be expected that regulators of major hazard companies will ask to identify and implement both lagging and leading indicators, and anchor these indicators in a safety management system. Therefore, the subject ‘safety indicators’ will remain in the spotlight, at least in the time to come.
114 citations
TL;DR: In this article, the authors proposed a risk assessment methodology for dynamic systems based on Bayesian network, which represents the dependencies among variables graphically and captures the changes of variables over time by the dynamic bayesian network.
Abstract: The oil/gas, chemical, petrochemical, food, power, papermaking and other process industries consist of numerous equipment and unit operations, thousands of control loops, and exhibit dynamic behavior. Chemical process plants are subjected to different types of process risks in daily operations, which include risks due to reactivity, toxicity and mechanical hazards, fire and explosion risks etc. Failure to manage or minimize hazards can result in serious incidents. Therefore, it is very important to identify hazards, perform risk assessments, and take proper initiatives to minimize/remove hazards and risks; else a catastrophic accident may result. Dynamic characteristics such as stochastic processes, operator response times, inspection and testing time intervals, ageing of equipment/components, season changes, sequential dependencies of equipment/components and timing of safety system operation also have great influence on the dynamic processes. Conventional risk assessment methodologies generally used in oil/gas and petrochemical plants have limited capacity in quantifying these time dependent characteristics. Therefore, it is important to develop a method that can address time-dependent effects in risk calculation and provide precise estimation. This study proposes a risk assessment methodology for dynamic systems based on Bayesian network, which represents the dependencies among variables graphically and captures the changes of variables over time by the dynamic Bayesian network. This study proposes to develop dynamic fault tree for a chemical process system/sub-system. Then a procedure to map the developed dynamic fault tree to map into the Bayesian network and the dynamic Bayesian network is provided to demonstrate the dynamic operational risk assessment methodology. A case study on a level control system is provided to illustrate the methodology's ability in capturing dynamic operational changes in process due to sequential dependency of one equipment/component on others.
106 citations
TL;DR: In this paper, a nonlinear statistical fault detection using kernel principal component analysis (KPCA)-based generalized likelihood ratio test (GLRT) is proposed, which is used to detect single as well as multiple sensor faults.
Abstract: Fault detection is often utilized for proper operation of chemical processes. In this paper, a nonlinear statistical fault detection using kernel principal component analysis (KPCA)-based generalized likelihood ratio test (GLRT) is proposed. The objective of this work is to extend our previous work (Harrou et al. (2013) to achieve further improvements and widen the applicability of the developed method in practice by using the KPCA method. The KPCA presented here is derived from the nonlinear case of principal component analysis (PCA) algorithm and it is investigated here as modeling algorithm in the task of fault detection. The fault detection problem is addressed so that the data are first modeled using the KPCA algorithm and then the faults are detected using GLRT. The detection stage is related to the evaluation of detection indices, which are signals that reveal the fault presence. Those indices are obtained from the analysis of the difference between the process measurements and their estimations using the KPCA technique. The fault detection performance is illustrated through two simulated examples, one using synthetic data and the other using simulated continuously stirred tank reactor (CSTR) data. The results demonstrate the effectiveness of the KPCA-based GLRT method over the conventional KPCA method through its two charts T2 and Q for detection of single as well as multiple sensor faults.
98 citations
TL;DR: In this paper, a kernel principal component analysis (KPCA)-based generalized likelihood ratio test (GLRT) was proposed for fault detection of chemical systems using input-output models.
Abstract: Fault detection is essential for proper and safe operation of various chemical processes, and it has recently become even more important than ever before. In this paper, we extended our previous work (Mansouri et al. (2016)), which addresses the problem of fault detection of chemical systems using kernel principal component analysis (KPCA)-based generalized likelihood ratio test (GLRT), to widen its applicability for processes represented by input-output models. Specifically, hypothesis testing fault detection technique that are based on linear and nonlinear partial least squares (PLS) models are developed. For nonlinear PLS models, a kernel PLS (KPLS) modeling framework is utilized. KPLS has been widely used to model various nonlinear processes, such as distillation columns and reactors. Thus, in the current work, a KPLS-based GLRT fault detection method is developed, in which KPLS is used as a modeling framework and the KPLS model generated residuals are evaluated using a GLRT statistic. The fault detection performance of the developed KPLS-based GLRT method is illustrated through a simulated example representing a continuously stirred tank reactor (CSTR). The simulation results show that the KPLS-based GLRT method outperforms its linear PLS-based version, and that both of the aforementioned techniques provide clear advantages over the conventional linear and nonlinear PLS based statistics, i.e., T 2 and Q .
93 citations
TL;DR: In this article, the authors analyzed 7,000 incidents at U.S. onshore hazardous liquid pipeline systems with an emphasis on natural hazards and found that 5.5% of all and 6.2% of the significant incidents were triggered by natural hazards, which resulted in a total hazardous substance release of 317,700 bbl.
Abstract: Incidents at U.S. onshore hazardous liquid pipeline systems were analyzed with an emphasis on natural hazards. Incidents triggered by natural hazards (natechs) were identified by keyword-based data mining and expert review supplemented by various data sources. The analysis covered about 7000 incidents in 1986–2012, 3800 of which were regarded as significant based on their consequences. 5.5% of all and 6.2% of the significant incidents were found to be natechs that resulted in a total hazardous substance release of 317,700 bbl. Although there is no trend in the long-term yearly occurrence of significant natechs, importance is found to be increasing due to the overall decreasing trend of the incidents. Meteorological hazards triggered 36% of the significant natechs, followed by geological and climatic hazards with 26% and 24%. While they occurred less frequently, hydrological hazards caused the highest amount of release which is about 102,000 bbl. The total economic cost of significant natechs was 597 million USD, corresponding to about 18% of all incident costs in the same period. More than 50% of this cost was due to meteorological hazards, mainly tropical cyclones. Natech vulnerabilities of the system parts vary notably with respect to natural hazard types. For some natural hazards damage is limited possibly due to implemented protection measures. The geographical distribution of the natechs indicated that they occurred more in some states, such as Texas, Oklahoma, and Louisiana. About 50% of the releases was to the ground, followed by water bodies with 28%. Significant consequences to human health were not observed although more than 20% of the incidents resulted in fires. In general, the study indicated that natural hazards are a non-negligible threat to the onshore hazardous liquid pipeline network in the U.S. It also highlighted problems such as underreporting of natural hazards as incident causes, data completeness, and explicit data limitations.
89 citations
TL;DR: In this article, a Bayesian belief network (BBN)-based probabilistic internal corrosion hazard assessment approach for oil & gas pipelines is presented. But, the model is limited to a single pipeline.
Abstract: A substantial amount of oil & gas products are transported and distributed via pipelines, which can stretch for thousands of kilometers. In British Columbia (BC), Canada, alone there are over 40,000 km of pipelines currently being operated. Because of the adverse environmental impact, public outrage and significant financial losses, the integrity of the pipelines is essential. More than 37 pipe failures per year occur in BC causing liquid spills and gas releases, damaging both property and environment. BC oil & gas commission (BCOGS) has indicated metal loss due to internal corrosion as one of the primary causes of these failures. Therefore, it is of a paramount importance to timely identify pipelines subjected to severe internal corrosion in order to improve corrosion mitigation and pipeline maintenance strategies, thus minimizing the likelihood of failure. To accomplish this task, this paper presents a Bayesian belief network (BBN)-based probabilistic internal corrosion hazard assessment approach for oil & gas pipelines. A cause-effect BBN model has been developed by considering various information, such as analytical corrosion models, expert knowledge and published literature. Multiple corrosion models and failure pressure models have been incorporated into a single flexible network to estimate corrosion defects and associated probability of failure (PoF). This paper also explores the influence of fluid composition and operating conditions on the corrosion rate and PoF. To demonstrate the application of the BBN model, a case study of the Northeastern BC oil & gas pipeline infrastructure is presented. Based on the pipeline's mechanical characteristics and operating conditions, spatial and probabilistic distributions of corrosion defect and PoF have been obtained and visualized with the aid of the Geographic Information System (GIS). The developed BBN model can identify vulnerable pipeline sections and rank them accordingly to enhance the informed decision-making process.
85 citations
TL;DR: In this paper, the authors developed a quantitative approach for the assessment of safety barrier performance in the prevention of fire escalation leading to domino accidents, which confirmed the important role of safety barriers performance in controlling the expected frequency of domino scenarios.
Abstract: The present study aimed at the development of a quantitative approach for the assessment of safety barrier performance in the prevention of fire escalation leading to domino accidents. In order to obtain a synthetic evaluation of the protection barriers performance, specific key performance indicators (KPIs) were defined, incorporating the results of probabilistic assessment of barrier performance. The results confirmed the important role of safety barriers performance in controlling the expected frequency of domino scenarios. The KPI analysis allowed determining the performance of different barrier types accounting for specific site factors. The results allowed a more detailed assessment of the expected frequency of secondary mitigated and unmitigated scenarios in the assessment of risk due to domino effect.
TL;DR: A novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity and a promising severity and location detectability and a low False Alarm Rate were achieved.
Abstract: Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.
TL;DR: In this paper, the authors developed a novel methodology using Bayesian Network (BN) to conduct the dynamic safety analysis for the offloading process of an LNG carrier and investigated different risk factors associated with LNG offloading procedures in order to predict the probability of undesirable accidents.
Abstract: The growing demand for natural gas has pushed oil and gas exploration to more isolated and previously untapped regions around the world where construction of LNG processing plants is not always a viable option. The development of FLNG will allow floating plants to be positioned in remote offshore areas and subsequently produce, liquefy, store and offload LNG in the one position. The offloading process from an FLNG platform to a gas tanker can be a high risk operation. It consists of LNG being transferred, in hostile environments, through loading arms or flexible cryogenic hoses into a carrier which then transports the LNG to onshore facilities. During the carrier's offloading process at onshore terminals, it again involves risk that may result in an accident such as collision, leakage and/or grounding. It is therefore critical to assess and monitor all risks associated with the offloading operation. This study is aimed at developing a novel methodology using Bayesian Network (BN) to conduct the dynamic safety analysis for the offloading process of an LNG carrier. It investigates different risk factors associated with LNG offloading procedures in order to predict the probability of undesirable accidents. Dynamic failure assessment using Bayesian theory can estimate the likelihood of the occurrence of an event. It can also estimate the failure probability of the safety system and thereby develop a dynamic failure assessment tool for the offloading process at a particular FLNG plant. The main objectives of this paper are: to understand the LNG offloading process, to identify hazardous events during offloading operation, and to perform failure analysis (modelling) of critical accidents and/or events. Most importantly, it is to evaluate and compare risks. A sensitivity analysis has been performed to validate the risk models and to study the behaviour of the most influential factors. The results have indicated that collision is the most probable accident to occur during the offloading process of an LNG carrier at berth, which may have catastrophic consequences.
TL;DR: In this article, a new kind of compound material composed of compound foaming agent (CFA) and high water absorbency gel (HWAG) for controlling the spontaneous combustion of coal in coal mine was researched and developed.
Abstract: A new kind of compound material—foamed gel composed of compound foaming agent (CFA) and high water absorbency gel (HWAG) and formed by physical and mechanical stirring—for controlling the spontaneous combustion of coal in coal mine was researched and developed. It makes use of the all-around properties of foam and gel to control the spontaneous combustion of coal in coal mine. The composition, preparation, and controlling mechanisms of foamed gel were analyzed. To optimize the characterizations of the foamed gel, the optimal CFA concerning foaming ability and mixed ratios of single foaming agents, mass concentration, and salt-resistance performance as well as the optimal HWAG concerning optimal synthesis parameters, Fourier transform infrared spectroscopy, thermogravimetric property, and foam stability were analyzed. Meanwhile, characterizations including microstructure and controlling spontaneous combustion of coal of foamed gel were studied. The results were best when the mass fraction of compound of modification alkyl polyglucoside (APG) and sodium dodecyl sulfate (SDS) is 0.9%, the mixed ratio of APG versus SDS is 4:1, the mass fraction of HWAG is 0.4%, and methylenebis acrylamide concentration, ammonium persulfate concentration, and mass fraction ratio of soluble starch:acrylic acid of HWAG synthesis are 0.05%, 0.5%, and 1:10, respectively. This is the ideal foamed gel. The success preparation of foamed gel and the microstructures differences between CFA and foamed gel are confirmd by the microstructures analysis results of CFA and foamed gel simultaneously. Moreover, foamed gel can effectively seal air leakages, prolong moisturizing time of coal, markedly enhance cooling effect on coal of moisture, and efficaciously reduce the rate of coal oxidation reaction and the heating rate to control the spontaneous combustion of coal in coal mine.
TL;DR: In this paper, the authors examined the impact of the ignition energy and vessel geometry on the magnitude of the pressure rise and flame propagation velocity in a cylindrically shaped explosion chamber constructed at The University of Newcastle, Australia.
Abstract: The fires and explosions caused by flammable hydrocarbon air mixtures are a major safety concern in the chemical and processing industries. The thermo-physical and chemical properties of the flammable fuels in a hybrid form appear to have a significant impact on the combustion process. This usually occurs due to substantial changes in the flammability concentration regimes. The aim of this study is to investigate the fire and explosive properties of hybrid fuels in the chemical and process industries. In addition, it examines the impact of the ignition energy and vessel geometry on the magnitude of the pressure rise and flame propagation velocity. The experimental work was conducted on a cylindrically shaped explosion chamber constructed as part of this study at The University of Newcastle, Australia. The chamber was made of mild steel and was 30 m in length and 0.5 in diameter. It included a series of high resolution pressure transducers, a pyrometer, as well as a high speed video camera. Methane and coal dust were used as fuels and chemical igniters with a known energy were used to ignite the fuels. The results obtained from this study showed that both the ignition energy and the diluted combustible fuel dust have significant impacts on the Over Pressure Rise (OPR) in an explosion chamber. The significant findings included that the OPR doubled when 30 g m −3 of coal dust was added to a 6% methane/air mixture, and it increased by 60% when 10 kJ was used instead of a 1 kJ ignition source. The initial ignition energy was observed to considerably enhance the speed of both the pressure wave and the flame front, where the pressure wave speed doubled when using a 5 kJ instead of a 1 kJ ignition source. However, the pressure wave speed increased by five times when a 10 kJ was used instead of a 1 kJ ignition source. Additionally, the maximum flame front velocity observed for the ignition source with 5 kJ energy was twice the flame front velocity for the 1 kJ ignition source. Finally, it was observed that the time needed for the initial methane ignition was reduced by about 50% when using a 10 kJ instead of a 1 kJ ignition source.
TL;DR: In this article, the authors discuss the changes in approaches to handle chemical accidents from various perspectives and present a case in which the relevant agencies succeeded in responding relatively efficiently to a major chemical accident because of these changes.
Abstract: This study addresses the systematic changes in laws, regulations, business cultures, and accident responses of organizations on a national level for chemical safety management after a large chemical release accident The hydrogen fluoride leakage accident in Gu-mi City, in which 5 workers were killed and 18 were injured, has led the government to construct more practical plans and guidelines for managing and responding to chemical disasters The governmental reorganization against chemical accidents such as Joint inter-agency The Chemical Emergency Preparedness Center, which is a specialized agency focused on responding to chemical disasters, has also contributed to the technology used in responses to chemical accidents, and as a result, it has become possible to cope with disasters more efficiently through cooperation among relevant agencies Regarding relevant laws and regulations, the government has launched and clarified various acts and programs for the handling, management, and assessment of chemical substances and chemical-related accidents Moreover, private enterprises have been also making efforts to systematically manage safety issues and expand high-level safety culture In this paper, we discuss the changes in approaches to handle chemical accidents from various perspectives and present a case in which the relevant agencies succeeded in responding relatively efficiently to a major chemical accident because of these changes
TL;DR: In this article, the authors present an analysis and simulation of an accident involving a liquefied petroleum gas (LPG) truck tanker in Kannur, Kerala, India, where a crack in the bottom pipe caused leakage of LPG for about 20min forming a large vapor cloud, which got ignited, creating a fireball and a boiling liquid expanding vapor explosion (BLEVE) situation in the LPG tank with subsequent fire and explosion.
Abstract: This paper presents an analysis and simulation of an accident involving a liquefied petroleum gas (LPG) truck tanker in Kannur, Kerala, India. During the accident, a truck tanker hit a divider and overturned. A crack in the bottom pipe caused leakage of LPG for about 20 min forming a large vapor cloud, which got ignited, creating a fireball and a boiling liquid expanding vapor explosion (BLEVE) situation in the LPG tank with subsequent fire and explosion. Many fatalities and injuries were reported along with burning of trees, houses, shops, vehicles, etc. In the present study, ALOHA (Area Locations of Hazardous Atmospheres) and PHAST (Process Hazard Analysis Software Tool) software have been used to model and simulate the accident scenario. Modeling and simulation results of the fireball, jet flame radiation and explosion overpressure agree well with the actual loss reported from the site. The effects of the fireball scenario were more significant in comparison to that of the jet fire scenario.
TL;DR: In this article, the minimum explosion concentration (MEC), over pressure rise (OPR), deflagration index for gas and dust hybrid mixtures (K st ) and explosive region of hybrid fuel mixtures present in Ventilation Air Methane (VAM) were investigated.
Abstract: Deflagration explosions of coal dust clouds and flammable gases are a major safety concern in coal mining industry. Accidental fire and explosion caused by coal dust cloud can impose substantial losses and damages to people and properties in underground coal mines. Hybrid mixtures of methane and coal dust have the potential to reduce the minimum activation energy of a combustion reaction. In this study the Minimum Explosion Concentration (MEC), Over Pressure Rise (OPR), deflagration index for gas and dust hybrid mixtures (K st ) and explosive region of hybrid fuel mixtures present in Ventilation Air Methane (VAM) were investigated. Experiments were carried out according to the ASTM E1226-12 guideline utilising a 20 L spherical shape apparatus specifically designed for this purpose. Results obtained from this study have shown that the presence of methane significantly affects explosion characteristics of coal dust clouds. Dilute concentrations of methane, 0.75–1.25%, resulted in coal dust clouds OPR increasing from 0.3 bar to 2.2 bar and boosting the K st value from 10 bar m s −1 to 25 bar m s −1 . The explosion characteristics were also affected by the ignitors’ energy; for instance, for a coal dust cloud concentration of 50 g m −3 the OPR recorded was 0.09 bar when a 1 kJ chemical ignitor was used, while, 0.75 bar (OPR) was recorded when a 10 kJ chemical ignitor was used. For the first time, new explosion regions were identified for diluted methane-coal dust cloud mixtures when using 1, 5 and 10 kJ ignitors. Finally, the Le-Chatelier mixing rule was modified to predict the lower explosion limit of methane-coal dust cloud hybrid mixtures considering the energy of the ignitors.
TL;DR: In this article, the authors present an experimental study to investigate the occurrence of a kick based on the changes in mass flow rate, pressure, density, and conductivity of the fluid in the downhole.
Abstract: Kick or influx poses a serious risk to the safety of the wellbore. Early detection of fluid influx from formation is crucial to minimize the possibility of a blowout occurrence. There is a high probability of delay in kick detection, when using an exclusively surface-based kick detection system. Down-hole monitoring techniques have a potential to detect a kick at its early stage. Down-hole monitoring would be particularly beneficial when the influx occurs as a result of a lost circulation scenario. This paper presents an experimental study to investigate the occurrence of a kick based on the changes in mass flow rate, pressure, density, and conductivity of the fluid in the down-hole. Pressure sensor, a Coriolis flow and density meter, and a conductivity sensor are employed to observe deteriorating well conditions in the down-hole. These observations can assess the occurrence of a kick and associated blowout risk. Monitoring of multiple down-hole parameters has the potential to improve the accuracy of interpretation related to kick occurrence, reduce the number of false alarms, and provide a broad picture of down-hole conditions. Moreover, the most sensitive parameters that get affected by the kick are identified. A methodology to detect the kick without false alarms is also reported.
TL;DR: In this paper, the influence of equivalence ratio, initial temperature and initial pressure on the maximum pressure rise rate and deflagration index of premixture is examined, and the performance of this correlation is examined and it is demonstrated to provide accurate prediction.
Abstract: The maximum pressure rise rate during gas explosions in enclosures and the deflagration index are important explosion characteristics of premixture. They can be used to quantify the potential severity of an explosion. However, there are large discrepancies in the deflagration index measured by different researchers for the same methane/air or hydrogen/air mixture. In this study, outwardly propagating spherical flames in a closed vessel are simulated by considering detailed chemistry as well as temperature-dependent thermal and transport properties. From simulation, the maximum pressure rise rate and deflagration index of methane, hydrogen and their mixtures are obtained. The influence of equivalence ratio, initial temperature and initial pressure on the maximum pressure rise rate and deflagration index is examined. It is found that the deflagration index has not been accurately measured in previous experiments, and that experiments conducted in cylindrical vessels have under-predicted greatly the deflagration index. For hydrogen/methane mixtures with hydrogen blending level above 70%, the deflagration index is observed to increase exponentially with hydrogen blending level. Moreover, the deflagration index is found to be greatly affected by initial pressure; while the initial temperature has little influence on deflagration index. Finally, based on theoretical analysis we propose a correlation to calculate the maximum pressure rise rate and deflagration index of methane at a broad range of initial pressure. The performance of this correlation is examined and it is demonstrated to provide accurate prediction.
TL;DR: In this article, a review and analysis of the frequency and consequences of failure of onshore pipelines transporting oil, refined products and natural gas is presented, and a desirable risk range is proposed.
Abstract: This paper reviews and analyses frequency and consequences of failure of onshore pipelines transporting oil, refined products and natural gas. Generally accepted risk levels are indicated and a desirable risk range is proposed. Pipeline failure statistics from the United States (US), Canada, Europe and Brazil are compared. Failure rates for internal and external corrosion, human action and natural forces are analyzed and the expected failure rate for each failure mechanism is indicated. The effects of relevant construction and environmental factors on the failure frequency are studied and mean trends are obtained. Furthermore, the sizes of the holes indicated at different databases are compared and a typical distribution of failure sizes is proposed for each mode of failure. Finally, the frequency of ignition after a loss of containment is studied for gas and liquid pipelines. Historical data on consequences of the accidental loss of containment of onshore pipelines is reviewed. Property damage and environmental reparation costs are evaluated directly from pipeline failure data. Straightforward regression models are proposed to quantify these types of consequence taking into account the released fluid and the characteristics of the environment. Societal impact is evaluated by combining simple fire models, heat versus mortality correlations and population density. Finally, values for the desired risk level are evaluated by three methods: i) a risk value representing the good engineering practice; ii) the risk associated to the most relevant codes and regulations concerning pipeline risk assessment and/or construction and operation; iii) an analytically derived optimal risk level. The risk values obtained by the three methodologies are similar and a desirable risk range is proposed.
TL;DR: In this paper, a quantitative assessment of resilience safety culture of a petrochemical plant using a questionnaire and was based on the two approaches of principal components analysis (PCA) and numerical taxonomy (NT).
Abstract: Over the last decades, some major accidents have occurred in highly reliable industries such as petrochemical plants. Probably, sophisticated safety management systems and a high level safety culture have contributed to decreasing the number of usual accidents, but these classical approaches may not have been sufficient to prevent the occurrence of extraordinary incidents and accidents. Consequently, there is a need for new approaches like resilience engineering to promote the safety of these systems. In this light, and to use safety culture more efficiently in ultra-safe systems, a new concept as “resilience safety culture” has been proposed. However, due to the paucity of studies and their qualitative nature, there is now more interest in using numerical methods to quantitatively evaluate the resilience safety culture of a system. This research, however, aimed at a quantitative assessment of resilience safety culture of a petrochemical plant using a questionnaire and was based on the two approaches of principal components analysis (PCA) and numerical taxonomy (NT). Accordingly, a questionnaire including 59 questions about several aspects of the safety culture and resilience engineering was designed and distributed to 354 randomly selected employees of 12 units in a petrochemical plant. The results of exploratory factor analysis of the data extracted thirteen factors which represent the resilience safety culture. The analysis also led to the determination of the score of resilience safety culture and its weakness in the petrochemical units. Implementing the proposed approach would enable the policy makers and managers in petrochemical industries to identify current weaknesses and challenges regarding the resilience safety culture in their system.
TL;DR: In this article, the authors applied ergonomic principles and methods (interviews, direct observation and focus groups) to describe common Environmental Defense Centers (EDC) system operations, and to identify constraints and conflicting procedural practices.
Abstract: The Environmental Defense Centers (EDCs) of Brazil provide response services following oil spill accidents. EDCs near affected areas rapidly organize and execute emergency response activities in order to minimize the environmental and economic impacts of spills. The current research applied ergonomic principles and methods (interviews, direct observation and focus groups) to describe common EDC system operations, and to identify constraints and conflicting procedural practices. Results of ergonomic field studies were modeled and analyzed using the Functional Resonance Analysis Method (FRAM), which can show how functional variability in planning, preparedness, execution, resources, economic and human factors affect the quality of emergency response activities. The FRAM analyses provide guidance for improving the resilience of oil spill emergency response systems.
TL;DR: In this paper, the authors presented a framework for the quantitative risk assessment of LNG-fueled vessels with respect to potential leakage using event tree analysis (ETA) and computational fluid dynamics (CFD) simulation.
Abstract: Liquefied natural gas (LNG) is used as fuel in various kinds of vessels, e.g., passenger ship, ferry, cargo vessel and platform supply vessel (PSV). It is an eco-friendly bunker fuel with many advantages, like decreasing the emissions of SOX and particulate materials (PM) and meeting the international maritime organization (IMO) MARPOL Annex VI requirements on NOX emissions, and economic benefits compared to heavy fuel oil (HFO). However, the leakage of LNG-fuel is a threat for the safety of LNG-fueled vessels, due to its inflammable and explosive characteristics. This paper illustrates a framework for the quantitative risk assessment of LNG-fueled vessels with respect to potential leakage. For illustration purposes, reference is made to a typical LNG-fueled ship, as a representative case. Event tree analysis (ETA) and computational fluid dynamics (CFD) simulation are integrated for the investigation of the hazard, the analysis of the consequences, and the quantification the risk of the LNG leakage. The results of the study are used to provide risk control options (RCOs), in terms of optimal risk mitigation for LNG-fueled vessels.
TL;DR: Two distinct formalisms to analyze failure scenarios and systems' availability are identified: generalized stochastic Petri nets (GSPN) and Fault tree driven Markov processes (FTDMP).
Abstract: Failure scenarios analysis constitutes one of the cornerstones of risk assessment and availability analysis. After a detailed review of available methods, this paper identified two distinct formalisms to analyze failure scenarios and systems' availability: generalized stochastic Petri nets (GSPN) and Fault tree driven Markov processes (FTDMP). The FTDMP formalism is a combination of the Markov process and the fault tree. This aims to overcome fault tree limitations while maintaining the use of deductive logic. The GSPN is a Petri net with probabilistic analysis using Monte Carlo simulation. The effectiveness of both methods is studied through an emergency flare system including a knockout drum. It is observed that GSPN provides a robust and reliable mechanism for accident scenario analysis. It provides additional information such as events' frequencies at operating and failing modes and expected occurrence timing and durations resulting from different complex sequences. Even for multi-state variables which could be used to design a safety management system. Although FTDMP is a powerful formalism, it provides limited information.
TL;DR: In this article, the authors made possible by NPRP grant No 6667-2-280 from the Qatar National Research Fund (a member of Qatar Foundation), which was used to support the work of the authors.
Abstract: This paper was made possible by NPRP grant No 6-667-2-280 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
TL;DR: In this article, the effect of initial temperature on the explosion pressure, P ex, of various liquid fuels (isooctane, toluene and methanol) and their blends, with three different fuel-fuel ratios, was investigated by performing experiments in a 20-l sphere at different concentrations of vaporized fuel in air.
Abstract: In this work, the effect of initial temperature on the explosion pressure, P ex , of various liquid fuels (isooctane, toluene and methanol) and their blends (isooctane-toluene and methanol-toluene, with three different fuel-fuel ratios) was investigated by performing experiments in a 20-l sphere at different concentrations of vaporized fuel in air. The initial temperature was varied from 333 K to 413 K. Results show that, as the fuel-air equivalence ratio, Φ, is increased, a transition occurs from a “thermodynamics-driven” explosion regime to a “radiant heat losses-driven” explosion regime. The maximum pressure, P max , is found in the former regime (Φ ex with increasing initial temperature. This trend has been explained by thermodynamics. In the latter regime (Φ > 3), P ex increases with increasing initial temperature. This trend has been addressed to the decrease in emissivity (and, thus, radiant heat losses) with the increase in temperature.
TL;DR: In this article, the effect of obstacles on the flame velocity was investigated by inserting different number of obstacles (3, 6, 9 and 12) and adjusting spacing of obstacles(175mm, 350mm, 525mm, and 700mm) in a long circular duct with lengths of 40m and inner diameter of 350mm.
Abstract: Effect of concentration and obstacles on methane-air mixture deflagration to detonation transition (DDT) was investigated in a long circular duct with lengths of 40 m and inner diameter of 350 mm. Five different concentrations 6%, 8%, 10%, 12% and 14% (in this paper, concentration specifically refers to volume concentration unless otherwise specified) were selected for the various investigations. Experimental results show that flame reaches the maximum velocity when mixtures are near the stoichiometric concentration without obstacles while deflagration to detonation transition (DDT) may occur when obstacles are arranged in the duct. Four kinds of obstacles with blockage ratio of 0.3, 0.45, 0.6 and 0.75 are used in the experiment. The effect of obstacles on the flame velocity was investigate by inserting different number of obstacles (3, 6, 9 and 12) and adjusting spacing of obstacles (175 mm, 350 mm, 525 mm and 700 mm). The blockage ratio of obstacles as well as their spacing and number has great effects on the flame velocity of the mixtures. A high number of obstacles in the duct can increase flame turbulence and lead to flame acceleration. At a mixture volume concentration of 8%, flame propagates faster with an increase in obstacle spacing and DDT could happen. The larger the obstacle blockage ratio, the stronger the interaction of the unburned mixture with a shock wave, which is more beneficial to the acceleration of the flame, while more heat is dissipated with an increase of the obstacle blockage ratio and this is not good for flame acceleration and propagation, so final flame acceleration is determined by the two competing factors.
TL;DR: In this article, an experimental study of jet fire was performed to understand the flame geometry of jet fires, and the results showed that the horizontal extent of visible flame length is affected by the wind flowing in the downwind direction of a jet fire, whereas, flame length parameter is independent of the threshold intensity value.
Abstract: An experimental study of jet fires is performed to understand the flame geometry of jet fires. Horizontal jet fire experiments are performed by varying the mass flow rate of fuel through a 19 mm nozzle. The exit velocities varied from 25 to 210 m/s, flame lengths from 1 to 6 m and Froude Numbers from 2 × 103 to 2 × 105. The experimental measurement includes the flame detection using standard CCD camera to capture the details of flame morphology. The frames obtained from CCD camera are reconstructed using image visualization technique to obtain the flame morphology like flame length and lift-off length. The modeling includes comparison of experimentally determined jet flames with empirical correlations. The flame length is well validated with three empirical correlations. The lift-off length is found to be under-predicted by all the models. With extended analysis on image processing, it is observed that lift-off length is sensitive to the threshold intensity value chosen for image processing, whereas, flame length parameter is independent of the threshold intensity value. The deviation between experimental and predicted values is also attributed to soot formation which affects the lift-off lengths and the heat radiated by jet fires. The flame area obtained from image visualization methods are compared to flame area obtained from empirical models. The effect of air entrainment is also studied on flame geometry. It is observed that the horizontal extent of visible flame length is affected by the wind flowing in the downwind direction of jet fire. The vertical extent of the jet fires is found to reduce with wind flowing in the crosswind direction.
TL;DR: In this article, the enhancement of inherent safety review and its implementation in the chemical process development and design is discussed, and the proposed accident-based ISDR is supported with detail review criteria for each phase of process design.
Abstract: This paper discusses the enhancement of inherent safety review and its implementation in the chemical process development and design. The aim is to update and improve the existing inherently safer design review (ISDR) practices during design of chemical process plant by exploiting major accident cases from the U.S. Chemical Safety Board (CSB) and Failure Knowledge Database (FKD). Although the basic guidelines to conduct ISDR during design phase are available, however they are too general and incomplete. The review criteria and their best timing for application are still missing. This paper attempts to develop the accident-based ISDR for chemical process plant design. The proposed accident-based ISDR is supported with detail review criteria for each phase of process design. The timing of ISDR application is corresponding to the common design tasks and decisions made in the design project. Therefore, timely design review could be done at the specific design task and the findings help designer to make a correct decision making.