A comparative study of radiation models on propane jet fires based on experimental and computational studies

Radiation as a consequence of jet fires is one of the significant parameters in process industry events. In the present work, the open field vertical propane jet fire was studied via experimental and computational fluid dynamics (CFD). The predicted values of radiation were verified at three locations in the horizontal direction from the jet fire. In the simulation section, four radiation models of Monte Carlo (MC), P-1, Discrete Transfer (DT), and Rosseland were applied to find the fine model for simulating the jet fire. Shear Stress Transport (SST) and Eddy Dissipation Concept (EDC) models are employed for combustion and turbulence, respectively. The estimated data by the simulation demonstrated that the MC radiation is better than the other models with an average error of 5% for predicted incident radiation from the jet flame axis. Also, the P-1 radiation model had an above 65% error at around the jet fire, but due to the error of less than 15% estimated by MC and DT models, these radiation models could simulate the jet flame radiation. The simulation outcomes proved that the Rosseland radiation model is not applicable owing to a lack of accurate temperature prediction.

Analysis of deep learning neural network combined with experiments to develop predictive models for a propane vertical jet fire

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.

Theoretical and experimental studies on hazard analysis of LPG/LNG release: a review

The purpose of this study is to analyze the failure and associated hazards of liquefied petroleum gas (LPG) and natural gas (NG) vessels during handling, storage, and transport. The leakage of LPG and NG from the vessels creates major hazards with the loss of containment. In case of fire, an extensive damage to the property (such as building and plants) and the population also occurs. This review is focused on several areas where the work done in the literature is scarce and missing, such as the failure modes of LPG or NG vessels during storage and transport and the estimation of the amount of the leakage and ignition time during these situations. This paper describes the different possible events such as jet fire, fireball, and vapor cloud explosion (VCE) and their mechanisms and the blast effects on the population or the environment. In this paper, all the experimental studies on pool fire, jet fire, boiling liquid expanding vapor explosion, and VCE associated with LPG/LNG have been analyzed. Moreover, modeling approaches and their corresponding equations, computational fluid dynamic approaches, and software used have also been reviewed.

Analysis of domino effect in pipelines

Parallel pipelines are frequently installed over long distances, due to the difficulty in creating or maintaining the required corridor. This implies that a release in one pipeline can seriously affect another one. The main risks associated with this domino effect are erosion by fluid-sand jets and the thermal action of jet fires. In this paper a survey has been performed on the accidents that have occurred, and the diverse associated domino sequences are analyzed. The probability of occurrence of domino effect is a function of the location of the hole, the jet direction and solid angle, the diameter of both pipelines and the distance between them. A mathematical model has been developed to estimate this probability. The model shows how the probability of domino effect decreases with the distance and diameter of the source pipe, and increases with the diameter of the target pipe. Its frequency can be estimated from this probability and from the frequency of the initiating pipe failure plus, in the case of jet fire impingement, the probability of ignition. The frequency of the target pipe failure thus calculated, always higher than its individual frequency, allows a more realistic risk analysis.

Convective heat transfer around vertical jet fires: an experimental study

The convection heat transfer phenomenon in vertical jet fires was experimentally analyzed. In these experiments, turbulent propane flames were generated in subsonic as well as sonic regimes. The experimental data demonstrated that the rate of convection heat transfer increases by increasing the length of the flame. Assuming the solid flame model, the convection heat transfer coefficient was calculated. Two equations in terms of adimensional numbers were developed. It was found out that the Nusselt number attains greater values for higher values of the Rayleigh and Reynolds numbers. On the other hand, the Froude number was analyzed only for the subsonic flames where the Nusselt number grows by this number and the diameter of the orifice.

Axial temperature distribution in vertical jet fires

The behaviour of vertical commercial propane jet fires (flame lengths of up to 8m) was studied experimentally. The temperatures along the jet fire centreline were measured using a set of thermocouples and the flame contour was determined from infra-red (IR) images. The results show that temperature increases from the bottom of the flame, reaches a maximum value and decreases again at the top zone. A second-degree polynomial expression describes fairly well the variation of temperature as a function of the position on the flame centreline. The temperature along the centreline was found to increase for Q values lower than 7MW and to decrease at higher values.