Boilover in liquid hydrocarbon tank fires

Boilover is a violent ejection of certain liquid hydrocarbons due to prolonged burning during a storage tank fire. It happens due to vaporization of the water sub-layer that commonly resides at the base of a storage tank, resulting in the ejection of hot fuel from the tank, enormous fire enlargement, formation of a fireball and an extensive ground fire. Boilover is a very dangerous accidental phenomenon, which can lead to serious injuries especially to emergency responders. The boilover can occur several hours after the fuel in a storage tank caught fire. The delayed boilover occurrence is an unknown strong parameter when managing the emergency response operations. Modelling and simulation of the boilover phenomenon will allow the prediction of the important characteristics features of such an event and enable corresponding safety measures to be prepared. Of particular importance is the time from ignition to the occurrence of boilover. In order to establish a tool for the prediction of the boilover events, it is essential to understand what happens within the fuel during a fire. Such understanding is important in order to recognize and determine the mechanisms for the hot zone formation and growth which are essentials, especially for predicting the onset time of boilover. Accordingly, boilover experiments and tests were planned and carried out at field scale by the Large Atmospheric Storage Tank FIRE (LASTFIRE) project with the intentions to evaluate the nature and consequences of a boilover, and to establish a common mechanism that would explain the boilover occurrence. Undertaking field scale experiments, however, is difficult to carry out so often due to high costs and high safety concerns. In order to obtain more detailed measurements and visual records of the behaviour of the liquids in the pool, a novel laboratory scale rig has been designed, built and commissioned at Loughborough University. The vessels used in the field scale tests and the laboratory scale rig were instrumented with a network of thermocouples, in order to monitor the distribution in temperature throughout the liquid and its variation with time. The temperature distribution variation as a function of time enabled the recognition of the phases of the evolution of the hot zone and hence the mechanism of boilover. The rig has allowed well defined and repeatable experiments to be performed and hence enable to study and assess boilover in a reproducible manner. In addition, visualisation of the fuel behaviour during the experiments could be obtained to better understand the formation and growth of hot zone, the boiling of water layer and hence the boilover occurrence. A number of small and larger scale experiments had been completed to obtain a wide spectrum of results, evaluating the effect of tank diameters, fuel depth, and water depth on the rate and extent of the boilover. The analysis of the results had elucidated further the processes of the hot zone formation and its growth, and hence mechanisms involved in the boilover occurrence. The important observation was that there are three stages observed in the mechanism of boilover incidence. At the start of the fire there is a stage when the hot zone is formed. This is followed by a period when the bottom of the hot zone moves downwards at a pseudo constant rate in which the distillation process (vaporisation of the fuel s lighter ends) is taking place. The final stage involved the heating up of the lowest fuel layer consisting of components with very high boiling points and occurrence of boilover. Based on the observations of the mechanisms involved in the hot zone formation and its growth, predictive calculations were developed which focus on the provision of an estimate on the time to boilover upon the establishment of a full surface fire and an estimate of the amount of fuel remaining in the tank prior to the occurrence of the boilover. A predictive tool was developed in order to provide predictions on the important parameters associated with a boilover event i.e. the time to boilover, the amount of fuel remaining in the tank prior to boilover and hence the quantity of fuel that would be ejected during boilover and the consequences of a boilover i.e. fire enlargement, fireball effects and the ground area affected by the expulsion of oil during a boilover event. The predictive tool developed is capable of providing good estimates of onset time to boilover and predicts consequences of the boilover. The tool predicting the time to boilover of the LASTFIRE field scale test and the laboratory scales tests was shown to produce predictions that correlated with the observed time to boilover. Apart from the time to boilover, the predictive calculation is also able to provide an estimate of fuel amount remained in the tank at the instance of boilover occurrence. Consequently, the tool is capable of predicting the quantity of burning fuel being ejected and hence the area affected by the extensive ground fire surrounding the tank. The predictive results are conservatives but yet show good agreement with observed time to boilover in real boilover incidents. Certain considerations in the development of safe and effective fire fighting strategies in handling fire scenario with a potential of boilover occurrence, can be assessed using the predictive tool developed

Scientific Model Development for Machinery Safety using Machine Reliability, Integrity and Availability

Introduction: Machines are equipment that increases productivity and efficiency in a workplace. Machine Reliability, Integrity, and Availability are the most critical factors to ensure machinery safety in a workplace. Methods: Throughout this study, a series of reviews of previous literature are described in relation to the elements of reliability, integrity and availability. This study examines the methods used to investigate levels of each element as well as the results of performing the analysis. Each review is chosen from the aspect of the safety feature that can be interpreted from the research study. A scientific model that utilizes an improved Bottom-up Approach is proposed to further improve the worker's safety and enhance the productivity of an industry. Results: Research shows that the chosen reviews have positive and negative change towards the level of machinery safety and a more substantial approach is needed to further strengthen the issue. The proposed model combines the effort of employee and various management organization as a team. The model is validated using Bias- Variance Trade off method that analyses the proposed model in a 27MW power plant with a selection of employee and management. Conclusion:  Model validation proves that the proposed model is an effective method to increase the machinery reliability, integrity and availability in a workplace. The scientific methodology provided will help management as a team to avert mechanical accidents from occurring at an initial stage

Scientific model development for machinery safety using machine reliability, integrity and availability.

Machines are equipment that increases productivity and efficiency in a workplace. Machine Reliability, Integrity, and Availability are the most critical factors to ensure machinery safety in a workplace. Throughout this study, a series of reviews of previous literature are described in relation to the elements of reliability, integrity and availability. This study examines the methods used to investigate levels of each element as well as the results of performing the analysis. Each review is chosen from the aspect of the safety feature that can be interpreted from the research study. A scientific model that utilizes an improved Bottom-up Approach is proposed to further improve the worker's safety and enhance the productivity of an industry. Research shows that the chosen reviews have positive and negative change towards the level of machinery safety and a more substantial approach is needed to further strengthen the issue. The proposed model combines the effort of employee and various management organization as a team. The model is validated using Bias- Variance Trade off method that analyses the proposed model in a 27MW power plant with a selection of employee and management. Model validation proves that the proposed model is an effective method to increase the machinery reliability, integrity and availability in a workplace. The scientific methodology provided will help management as a team to avert mechanical accidents from occurring at an initial stage

A holistic team approach (HTA) model to curb machinery accidents in power plants.

Machinery accidents have been an important aspect that needs proper attention in all work places in recent years especially power plants. A large number of accident cases have been reported from the year 2018 to 2022. Accident report from DOSH (Department of Safety and Health Malaysia) indicates that a significant number of machinery accident cases occur in power plants while PERKESO (Social Security Organisation Malaysia)has investigated and tabulated accidents based on area of workplace and injury. Research shows that most statistical studies do not comprise of a preventive model to curb machinery accidents, which involves employees and management. A model that comprises of Machinery or Area of work (M) and the type of injury (I) is identified and summed in a form of a scientific equation which results in the possible accident type (α) which is the accident occurred. A Holistic Team Approach (HTA) model is designed that involves a team for each element M and I which comprises of engineers, technicians and operators working in the same area of equipment and a management representative. Each team is assigned to specific accidents according to the M and I element and classified as α-combinations. Teams are sent for incident investigation where preventive actions and reporting are discussed. A decision analysis is performed based on the model that emphasizes two Process Safety Management (PSM) elements which are accident investigation and employee participation. The HTA model is able to reduce machinery accidents by involving the elements of machinery and injury types, which is applicable to workplaces worldwide

Fabrication and characterization of polyvinylidene fluoride composite nanofiber membrane for water flux property

This research is about the investigation of the pure water flux property of composite polyvinylidene fluoride (PVDF) nanofibers. Electrospinning technique was used to prepare the composite electrospun nanofibers. PVDF was dissolved in N,N-dimethylformamide (DMF) solvent and blended together with activated carbon (AC) and polyvinylpyrrolidone (PVP). The nanofibers were characterized to determine the morphologies, wettability property, and its tensile strength. The fabricated nanofibers diameter was found in the range between 20 to 180 nm. The presence of AC deteriorates the mechanical properties of the nanofibers as the size of AC is larger than the external diameter of the nanofibers. The results of contact angle confirmed that the fabricated nanofiber exhibit less hydrophobic in the presence of PVP and AC. The less hydrophobi

Combined Effect of Dispersion Pressure and Concentration on Minimum Ignition Temperature of Corn Dust using Response Surface Methodology – Preliminary Investigation

Corn dust is a significantly energetic dust and widely used substance in food processing industries. It not only poses dust hazards like suffocation or lungs related issues to the exposed workers but also is highly combustible under a conducive environment. In this study, the minimum ignition temperature (MIT) of corn dust clouds was evaluated at varying combinations of dispersion pressure and concentration using a Godbert–Greenwald (G–G) furnace. A response surface was generated using design expert as a tool for the application of response surface methodology (RSM). The predicted R2 and adjusted R2 are reasonably in close agreement as the difference is less than 0.2. The predicted surface is found to be in good agreement with the experimental results. However, as this is a preliminary study, the model will be improved in future research

Raman Calibration Models for Chemical Species Determination in CO2-Loaded Aqueous MEA Solutions Using PLS and ANN Techniques

The improvement in energy efficiency is recognized as one of the significant parameters for achieving our net-zero emissions target by 2050. One exciting area for development is conventional carbon capture technologies. Current amine absorption-based systems for carbon capture operate at suboptimal conditions resulting in an efficiency loss, causing a high operational expenditure. Knowledge of qualitative and quantitative speciation of CO2-loaded alkanolamine systems and their interactions can improve the equipment design and define optimal operating conditions. This work investigates the potential of Raman spectroscopy as an in situ monitoring tool for determining chemical species concentration in the CO2-loaded aqueous monoethanolamine (MEA) solutions. Experimental information on chemical speciation and vapour-liquid equilibrium was collected at a range of process parameters. Then, partial least squares (PLS) regression and an artificial neural network (ANN) were applied separately to develop two Raman species calibration models where the Kent–Eisenberg model correlated the species concentrations. The data were paired and randomly distributed into calibration and test datasets. A quantitative analysis based on the coefficient of determination (R2) and root mean squared error (RMSE) was performed to select the optimal model parameters for the PLS and ANN approach. The R2 values of above 0.90 are observed for both cases indicating that both regression techniques can satisfactorily predict species concentration. ANN models are slightly more accurate than PLS. However, PLS (being a white box model) allows the analysis of spectral variables using a weight plot

Inherent safety for sustainable process design of process piping at the preliminary design stage

Risk assessment is an accepted approach used worldwide to improve the sustainability of either the existing process plant or the design of a new installation. In the current practices, risk assessment is normally performed once the design has been completed. A better approach is to perform risk assessment at the initial design stages with the application of inherent safety concept to achieve the sustainable cleaner chemical process. This paper consolidates a new technique to improve the safety level of process piping from potential fire risk using the inherent safety concept. Inherently safer process piping (ISPP) technique utilizes fundamental of fluid flow to predict the potential damage from a major fire accident. A relative ranking of process streams is used to identify the critical process streams that have higher chances of damage. Risk assessment is performed to check if the potential fire exceeds the acceptance criteria or not. If the risk is not in the acceptable range, inherent safety principle is used to reduce the risk to the acceptable limit. The ISPP technique is validated using a case study of methanol process plant. This technique could be used to facilitate design practitioners to incorporate inherent safety at the early design stage

Process equipment common attributes for inherently safer process design at preliminary design stage

Hazards associated with chemical processes can lead to accidents and require therefore proper management. An inherent safety strategy is a proactive approach to serve this purpose, one capable of minimizing hazards whilst offering sustainable process design. Current inherent safety techniques are limited to comparing process routes and selecting safer one using the process parameters, whereas process equipment characteristics are rarely scrutinized. Therefore, this paper consolidates a new technique that integrates the mutually shared attributes of process equipment, in order to offer inherently safer process design at the preliminary design stage. Inherent safety assessment for process equipment (ISAPE)consists of an indexing procedure, followed by risk assessment. The indexing procedure can highlight the critical process equipment, which can be further studied through risk assessment. When the risk is beyond acceptable threshold and must be minimized, inherent safety concepts are implemented, leading towards inherently safer process design. The complete ISAPE technique is exhibited through the case study of the acetone production process. In this case study, various ISD options have been applied to the critical process equipment, identified through the proposed indexing; the options have then been compared to select the best one. The method is easy to use, and as such, it is suitable to be put into practice by design engineers at the preliminary design stage