Chemical Process Safety

Quantification of spatial and temporal concentration profiles of vapor clouds resulting from accidental loss of containment of toxic and/or flammable substances is of great importance as correct prediction of spatial and temporal profiles can not only help in designing mitigation/prevention equipment such as gas detection alarms and shutdown procedures but also help decide on modifications that may help prevent any escalation of the event.The most commonly used models – SLAB (Ermak, 1990), HEGADAS (Colenbrander, 1980), DEGADIS (Spicer & Havens, 1989), HGSYSTEM (Witlox & McFarlane, 1994), PHAST (DNV, 2007), ALOHA (EPA & NOAA, 2007), SCIPUFF (Sykes, Parker, Henn, & Chowdhury, 2007), TRACE (SAFER Systems, 2009), etc. – for simulation of dense gas dispersion consider the dispersion over a flat featureless plain and are unable to consider the effect of presence of obstacles in the path of dispersing medium. In this context, computational fluid dynamics (CFD) has been recognized as a potent tool for realistic estimation of consequence of accidental loss of containment because of its ability to take into account the effect of complex terrain and obstacles present in the path of dispersing fluid.The key to a successful application of CFD in dispersion simulation lies in the accuracy with which the effect of turbulence generated due to the presence of obstacles is assessed. Hence a correct choice of the most appropriate turbulence model is crucial to a successful implementation of CFD in the modeling and simulation of dispersion of toxic and/or flammable substances.In this paper an attempt has been made to employ CFD in the assessment of heavy gas dispersion in presence of obstacles. For this purpose several turbulence models were studied for simulating the experiments conducted earlier by Health and Safety Executive, (HSE) U.K. at Thorney Island, USA (Lees, 2005). From the various experiments done at that time, the findings of Trial 26 have been used by us to see which turbulence model enables the best fit of the CFD simulation with the actual findings. It is found that the realizable k–ɛ model was the most apt and enabled the closest prediction of the actual findings in terms of spatial and temporal concentration profiles. It was also able to capture the phenomenon of gravity slumping associated with dense gas dispersion.► A new CFD-based method is presented for modeling dense gas dispersion in presence of obstacles. ► The novelty lies in the use of turbulence model and the manner of resolution of domain geometry. ► Excellent fit of theory with experimental findings.

The lack of formal integration between process design stages with risk and consequence estimation is a hurdle to designing inherently safe process plants. Conventional risk assessment methodologies are often not carried out concurrently with process design. Therefore, process designers lack the information about risk levels and consequence that may result from the process conditions being considered in a particular process route until the design is completed. Hence, effects of changes in process conditions on risk levels and consequence cannot be studied in a time effective manner during the design stages. Few studies have been identified on the possibility and viability of integrating risk estimation with process design. But viable framework and methodology for doing so has not yet been reported. This paper presents a feasible framework in which risk and consequences estimation can be part of design stages. A demonstrative tool named as integrated risk estimation tool (iRET) was developed by using process simulation software, HYSYS and spreadsheet, MS Excel as the platforms. iRET estimates risk due to explosions by using TNT equivalence method and the TNO correlation method. iRET has a potential to be extended to include all forms of risk such as fire, explosion, toxic gas releases and boiling liquid expanding vapour explosion (BLEVE). The paper also presents case studies to demonstrate the functionality and viability of using iRET in conjunction with process design. The results of these case studies have successfully shown that the risk due to explosion can be assessed during the initial design stage ensuring a safer plant. The framework and iRET there by presented here provide systematic methodology and technology to design inherently safer plants.

Fires are important responsible factors to cause catastrophic events in the process industries, whose consequences usually initiate domino effects. The artificial neural network has been shown to be one of the rapid methods to simulate processes in the risk analysis field. In the present work, experimental data points on jet fire shape ratios, defined by the 800 K isotherm, have been applied for ANN development. The mass flow rates and the nozzle diameters of these jet flames have been considered as input dataset; while, the jet flame lengths and widths have been collected as output dataset by the ANN models. A Bayesian Regularization algorithm has been chosen as the three-layer backpropagation training from Multi-layer perceptron algorithm. Then it has been compared with a Radial based functions algorithm, based on single hidden layer. The optimized number of neurons in the first and second hidden layers of the MLP algorithm, and in the single hidden layer of the RBF algorithm has been found to be twenty and fifteen, respectively. The best MSE validation performance of MLP and RBF networks has been found to be 0.00286 and 0.00426 at 100 and 20 epochs, respectively.

The auto mechanic industry in Sri Lanka is at a constant growth. Large scale organizations such as UNIMO, DIMO, and Toyota Lanka etc. tend to follow a specific occupational health and safety plan to minimizing risk and create a safe working environment for their employees. But as for small scale, auto mechanic workshops do not follow an occupational health and safety plan. They tend to use alternative safety precautions which are not reliable. There were five possible risks identified in small scale auto mechanic workshops. That can be summarized as hazardous substances, fire and explosions, risk during tire repair, the risk associated with the use of various tools, and work-related stress and the corresponding solutions of the identified risk are discussed in detail.

The domino effect accidents in process industries pose a severe threat to human life and the environment and have the potential to affect nearby facilities as well. Numerous techniques, such as the Bayesian network, have been used for modelling the domino effect. However, these techniques have inherent limitations. These include the inability to consider complex behaviour of process equipment in combined loading and the time dependency of equipment failure. In the current study, a Generalised Stochastic Petri-net model, called as DOMINO-GSPN, is developed to model domino effect accident likelihood and its propagation pattern. The proposed technique is capable of modelling time-dependent failure behaviour of the process component in combined loading. The results from the model are useful in monitoring process risk. A case study is used to demonstrate the application and effectiveness of the model. The results from the model are compared with the past study of a Bayesian network-based domino effect model. This comparative analysis highlights the unique feature of the model and its relevance as a domino effect risk assessment and management tool.

This paper addresses ontologies of intentional and unintentional processes. Specifically, a methodology for developing processes ontologies is described. Typically, domain ontologies are developed in an ad-hoc fashion, without the reasons and justifications of the class structure. To resolve this issue, we propose a methodology based on Formal Concept Analysis (FCA) as a way to assist the development of a domain ontology. FCA is an analysis technique for knowledge processing based on applied lattice and order theory. The methodology is illustrated with the development of an explosion ontology.

An improved, safe, and scalable isolation process for (substituted) pyridine and quinoline N-oxides in quantitative yields along with high purities using the m-CPBA−NH 3 (g) system is described. The safety was assessed by reaction calorimetry and differential scanning calorimetry studies for possible hazards during the conversion and isolation steps. Careful interpretation of the data substantiated the safety and scalability. The process flow is simplified to meet the industrial requirements of safety, cost-effectiveness, and utility minimization. The reaction was safely demonstrated at a 2.5 kg scale.

A failure of a Liquefied Natural Gas (LNG) tanker can occur due to collision or rupture in loading/unloading lines resulting in spillage of LNG on water. Upon release, a spreading liquid can form a pool with rapid vaporization leading to the formation of a flammable vapor cloud. Safety analysis for the protection of public and property involves the determination of consequences of such accidental releases. To address this complex pool spreading and vaporization phenomenon of LNG, an investigation is performed based on the experimental tests that were conducted by the Mary Kay O'Connor Process Safety Center (MKOPSC) in 2007. The 2007 tests are a part of medium-scale experiments carried out at the Brayton Fire Training Field (BFTF), College Station. The dataset represents a semi-continuous spill on water, where LNG is released on a confined area of water for a specified duration of time. The pool spreading and vaporization behavior are validated using empirical models, which involved determination of pool spreading parameters and vaporization rates with respect to time. Knowledge of the pool diameter, pool height and spreading rate are found to be important in calculating the vaporization rates of the liquid pool. The paper also presents a method to determine the vaporization mass flux of LNG using water temperature data that is recorded in the experiment. The vaporization rates are observed to be high initially and tend to decrease once the pool stopped spreading. The results of the analysis indicated that a vaporization mass flux that is varying with time is required for accurate determination of the vaporization rate. Based on the data analysis, sources of uncertainties in the experimental data were identified to arise from ice formation and vapor blocking.

One of the LNG accident scenarios is the collision of an LNG carrier on an iceberg during marine transportation. A collision can result in damages to the vessel and lead to the leakage of the contents on ice or an ice-water mixture. When cryogenic liquid comes in contact with ice, it undergoes rapid vaporization due to the difference in temperature between the ice and cryogenic liquid. This process is different from the heat transfer between water and cryogenic liquid as ice is a solid and thus heat transfer to the pool occurs primarily through conduction. In this paper, the heat transfer phenomenon between ice and cryogenic liquid was studied through a small-scale experiment and the resulting vaporization mass fluxes were reported. The experiment involved six spills with varying amount of liquid nitrogen on different ice temperature to determine its effect on vaporization mass flux. The vaporization mass fluxes were determined by direct measurement of the mass loss during the experiment. The results indicated that the vaporization mass flux was a function of release rate and ice temperature. When the release rate and ice temperature was high, the vaporization mass flux follows a decreasing trend. With further reduction in release rate and ice temperature, the vaporization mass flux was found to be independent with time. The one dimensional conduction model was validated against experimental results. The predicted temperatures and heat flux were found to be in good agreement with the experimental data.

A process model for turbulent pressurized circulating fl uidized-bed coal gasifi er is created using ASPEN PLUS
software. Both hydrodynamic and reaction kinetics parameter are taken into account, whose expressions for fl uidized
bed are adopted from the literature. Various reactor models available in ASPEN PLUS with calculator as
External Block are nested to solve hydrodynamics and kinetics. Multiple operational parameters for a pilot-plant
circulating fl uidized-bed coal gasifi er are used to demonstrate the effects on coal gasifi cation characteristics. This
paper presents detailed information regarding the simulation model, including robust analysis of the effect of stoichiometric
ratio, steam to coal ratio, gasifi cation temperature and gasifi cation agent temperature. It is observed
that, with the increase in the fl ow rate of air, the components hydrogen, carbon monoxide, carbon dioxide and
methane reduce, which causes the Lower Heating Value (LHV) of synthesis gas (Syn. Gas) to decrease by about
29.3%, while increment in the steam fl ow rate shows a minute increase in heating value of only 0.8%. Stoichiometric
ratio has a direct relationship to carbon conversion effi ciency and carbon dioxide production. Increasing the
steam to coal ratio boosts the production of hydrogen and carbon monoxide, and causes a drop in both carbon
dioxide concentration and the conversion effi ciency of carbon. High gasifying agent temperature is desired because
of high concentration of CO and H2, increasing carbon conversion and LHV. A high gasifying agent temperature
is the major factor that affects the coal gasifi cation to enhance H2 and CO production rapidly along with other
gasifi cation characteristics.

Aviation Turbine Kerosene (ATK) or jet fuel is stored in stainless steel tanks or in epoxy coated tanks to prevent contamination through reaction with the tank sheets. Epoxy coated tanks overtime may develop cracks and coating defects which exposes the jet fuel to the steel surface. This is not optimal and it is an aberration to global best practices. Coating defects are corrected after surface preparation through blasting, and grit blasting is one of the common methods. Grit blasting is a hot work that may generate sparks which can be ignited by jet fuel fumes. In the oil and gas industry, personnel are moved via choppers to and from oil platforms and rigs, and this requires ready availability of jet fuel in storage tanks on oil platforms. Jet fuel tank repairs and recertification on offshore facilities where flammable crude oil and gas vapours may be present, coupled with jet fuel fumes is a high risk operation. This study presents a detailed job safety analysis and risk assessment that identifies potential hazards and the necessary safeguards and controls needed to safely manage tank recertification on offshore facilities toward preventing explosion and accidents.

The fifth edition of the United Nations Global Assessment Report on Disaster Risk Reduction (GAR) is being issued four years after the adoption of the Sendai Framework for Disaster Risk Reduction 2015–2030 (Sendai Framework).

This edition of GAR is the first punctuation mark in the implementation of the Sendai Framework. It offers an update on progress made in implementing the outcome, goal, targets and priorities of the Sendai Framework and disaster-related Sustainable Development Goals. It provides an analysis of how risk science is changing, presents areas for additional endeavour, and explores aspects of understanding and managing systemic risk. It presents innovative research and practice for pursuing risk-informed sustainable development, and provides an introduction to the wider scope and nature of hazards and related risks to be considered.

Chapter 3 of the report on "risk" investigates how we currently monitor and model a range of hazards, including tsunamis, landslides, floods and fires. Other hazards are less familiar as they were not part of the Hyogo Framework for Action. However, they are part of the Sendai Framework and include: biological, nuclear/radiological, chemical/industrial, NATECH (natural hazards triggering technological disasters) and environmental hazards. Chapter 3 looks at our understanding of how these hazards interact with exposure and vulnerability.

Chapter 3.1.9 on "Natech" describes Natech events which are a recurring but often overlooked fature in many disaster situations. Besides providing examples of important Natech accidents that occurred in the past, the characteristics of Natech risk are discussed. Information on Natech risk drivers and instruments for effective Natech risk management are explained, together with how progress in Natech risk reduction can be measured.

An alarm management methodology can be proposed as a discrete event sequence recognition problem where time patterns are used to identify the process safe condition, especially in the start-up and shutdown stages. Industrial plants, particularly in the petrochemical, energy, and chemical sectors, require a combined approach of all the events that can result in a catastrophic accident. This document introduces a new layer of protection (super-alarm) for industrial processes based on a diagnostic stage. Alarms and actions of the standard operating procedure are considered discrete events involved in sequences, where the diagnostic stage corresponds to the recognition of a special situation when these sequences occur. This is meant to provide operators with pertinent information regarding the normal or abnormal situations induced by the flow of alarms. Chronicles Based Alarm Management (CBAM) is the methodology used to build the chronicles that will permit to generate the super-alarms furthermore, a case study of the petrochemical sector using CBAM is presented to build the chronicles of the normal startup, abnormal start-up, and normal shutdown scenarios. Finally, the scenario validation is performed for an abnormal start-up, showing how a super-alarm is generated.

Tracking in chemical inventory and management are important for safety-health-environmental (SHE) management system as regulatory and challenging laboratory organizations. SHE compliance, minimization of hazardous waste, responses and preparedness for emergency, and all benefit by knowing what they are exist and located, which has responsibility. PTFI Quality Control Laboratory developed an application by web-based system for chemical inventory information and information management, including for report of compliance. Chemical inventory and information management are using to meet of regulation requirements. It system can obtain hazard identification (HAZID), chemical storage compatibility, flammable liquid, and hazardous materials emergency procedures to prevent they become problem issues. This paper explaining for an inventory programs proposed methodology used to entity relationship diagram (ERD) from relational database schema, and databases demonstrated to meet hazardous materials issues, and it will be useful for chemical coordinator to maintain and manage chemical inventory and management.

Among the process safety strategies, inherent safety, proposed by Kletz, has been widely accepted and applied for the preliminary design of chemical processes. Process optimization with safety aspect has usually focused on accident costs rather than risk. Additionally, the significance of inherent assessment for process optimization has been overlooked. Simultaneous optimization of risk with inherent safety and process economics can be more impactful in practical process designs. Therefore, a new methodology is consolidated in this paper, such that an external risk and process economics model is coupled with HYSYS to achieve an optimized process design. Here, process stream index (PSI) has been suggested to identify the critical process streams. For identified critical process streams, risk analysis and process economics are studied. Risk estimation and process economics parameters are studied in an external model by extracting information from HYSYS through VBA coding. For unacceptable risk, minimization guide word is used to improve the performance of critical streams. With inherent safety implementation, process economics is also found to be improved, as 3.2% less energy would be required without any significant change in ammonia product quantity. This approach would serve to deal safety with process attributes as multi-objective optimization method of process design.

The success of every company depends of each employee's understanding of the key business components. Employee training and development will unlock the companies' profitability and reliability. When people, processes and technology work together as a team developing practical solutions, companies can maximize profitability and assets in a sustainable manner. Training and development is an investment in future success-give yourself and your employees the keys to success It is strategically important that your team understands the fundamentals of process unit operations concepts. This is the difference between being in the best quartile of operational ability and being in the last quartile. There is vast difference in the operational ability of operating companies and most benchmarking studies have confirmed this gap in operational abilities. Whether you have a team of new or seasoned employees, an introduction or review of these concepts are very beneficial in closing the gap if you are not in the best quartile, or maintaining a leadership position. Most studies show that a continuous reinforcement of best practices in operational principles is the most effective way to obtain the desired results. Training and learning should be an on going continuous life long goal.

The progress of technology has caused operating of many processes and resulted in
more complexity of the chemical process industries and one of the main challenges for these
companies is to manage the existing assets in the comprehensive and complex infrastructure.
Thus, the safe operations of these systems are at least as important as their design. It should be
noted; despite of implementing safety programs in today’s industry, accidents still occur, and
OSHA believes that all of these accidents follow typical patterns that help analyzers to recognize
their root cause and take proper actions. On the other hand, the cost of maintenance is a
considerable part of the total life cycle in these industries. Research has shown that some critical
components account for most of the downtime in such operations. An improvement of
maintenance practices which focused on risk based approach for critical components can improve
the reliability and safety; at the same time can reduce maintenance costs. So, in order to reach a
comprehensive risk management plan for these processes, we aim to prepare a domestic risk
management model for chemical process based on Risk Based Maintenance (RBM) using FAHP
technique. The initial steps involve literature review to identify critical assets and equipment. The
subsequent interviews will be discussed these issues with experienced practitioners to identify
their failures. The Delphi group method has been selected for data collection. Through three
rounds of Delphi process experts helped to filter all the information to come up with a series of the
most important strategic actions to RBM assessment of t systems. All of the RBM criteria have
been localized by expert team and the risk number could be calculated according to these factors.
There are several tools to analysis the risks of them. But, the classic approach always comes with
great uncertainty. Thus, The FAHP model will be introduced as the most applicable approach for
modeling of the risk management to overcome such limitations. However, by applying this
technique, it will be anticipated that the safety of system improved, the environmental impacts
and maintenance costs reduced, the spare parts allocated where necessary, and finally lead to
prioritization of the process’s safety measures according to their risk levels.