The effect of vent ducts on the reduced explosion pressures of vented dust explosions

An investigation into the effects of vent ducts on reduced explosion pressures is described. Experiments were made using an 18.5m³ explosion vessel and a modified 20 1 sphere, with dusts having K_st values ranging from 144 bar ms⁻¹ to 630 bar ms⁻¹. The vent area/vessel volume ratio bursting pressure of the vent cover, and the length to diameter ratio of the vent duct have been varied. Straight vent ducts, and ducts containing sharp 45° and 90° bends have been used.A simple model to describe the effect of vent ducts on the reduced explosion pressure has been derived and compared with the experimental results. Agreement is shown to be satisfactory in nearly all cases. A comparison between the experimental results and guidance on the effect of vent ducts already available in the literature is discussed.     

Experimental study of the venting characteristics of dust explosion through a vent duct

To further understand the dynamic mechanism of dust explosion through a vent duct, we designed a small-scale cylindrical vessel connected with a vent duct and performed a dust explosion venting experiment under different opening pressures using corn starch as the explosive medium in this study. The results show that weakening effect of duct on venting is positively correlated with the opening pressure. The explosion pressure in the duct presents a three-peak-structure with time, successively caused by the membrane breaking shock wave, the secondary explosion in the tube, and the continuous combustion, and decreases gradually with the propagation distance. Meanwhile, the three pressure peaks are positively correlated with the opening pressure, while the time interval between them goes to contrary. The increase of opening pressure leads to the increase of secondary explosion intensity and reverse flow in the vessel, further accelerates the reaction rate in the vessel, and then shortens the duration of combustion in the vessel until the phenomenon of flame reignition in the vessel disappears.     

Does your facility have a dust problem: Methods for evaluating dust explosion hazards

The hazards of dust explosions prevailing in plants are dependent on a large variety of factors that include process parameters, such as pressure, temperature and flow characteristics, as well as equipment properties, such as geometry layout, the presence of moving elements, dust explosion characteristics and mitigating measures. A good dust explosion risk assessment is a thorough method involving the identification of all hazards, their probability of occurrence and the severity of potential consequences. The consequences of dust explosions are described as consequences for personnel and equipment, taking into account consequences of both primary and secondary events.While certain standards cover all the basic elements of explosion prevention and protection, systematic risk assessments and area classifications are obligatory in Europe, as required by EU ATEX and Seveso II directives. In the United States, NFPA 654 requires that the design of the fire and explosion safety provisions shall be based on a process hazard analysis of the facility, process, and the associated fire or explosion hazards. In this paper, we will demonstrate how applying such techniques as SCRAM (short-cut risk analysis method) can help identify potentially hazardous conditions and provide valuable assistance in reducing high-risk areas. The likelihood of a dust explosion is based on the ignition probability and the probability of flammable dust clouds arising. While all possible ignition sources are reviewed, the most important ones include open flames, mechanical sparks, hot surfaces, electric equipment, smoldering combustion (self-ignition) and electrostatic sparks and discharges. The probability of dust clouds arising is closely related to both process and dust dispersion properties.Factors determining the consequences of dust explosions include how frequently personnel are present, the equipment strength, implemented consequence-reducing measures and housekeeping, as risk assessment techniques demonstrate the importance of good housekeeping especially due to the enormous consequences of secondary dust explosions (despite their relatively low probability). The ignitibility and explosibility of the potential dust clouds also play a crucial role in determining the overall risk.Classes describe both the likelihood of dust explosions and their consequences, ranging from low probabilities and limited local damage, to high probability of occurrence and catastrophic damage. Acceptance criteria are determined based on the likelihood and consequence of the events. The risk assessment techniques also allow for choosing adequate risk reducing measures: both preventive and protective. Techniques for mitigating identified explosions risks include the following: bursting disks and quenching tubes, explosion suppression systems, explosion isolating systems, inerting techniques and temperature control. Advanced CFD tools (DESC) can be used to not only assess dust explosion hazards, but also provide valuable insight into protective measures, including suppression and venting.     

A new prediction method for dust explosion venting at high static activation pressures

Venting is an effective way to prevent harmful dust explosions, but the existing prediction methods are imprecise and are suitable only for applications with low activation pressures. A new method is proposed for predicting pressures based on an analysis of energy losses at high activation pressures and verified by aluminum dust explosion experiments. Compared with the experimental results, the results of the new model are relatively stable under working conditions with different activation pressures and venting areas. Based on the analysis of energy losses, the changes in the energy loss rate, temperature, and venting velocity during venting are found to be asynchronous. The thermal energy loss, which accounts for over 80 percent of the total, is expected to be larger than the kinetic energy loss. The thermal energy loss rate changes rapidly during venting, while the kinetic energy loss rate remains relatively stable. The new model is more accurate than the NFPA68 standard, which fails to consider the thermal energy loss. Neglecting the thermal energy loss may result in an underestimation of the pressure reduction; this error increases with decreasing activation pressure.     

Law of variation for low density polyethylene dust explosion with different inert gases

To reveal the effects of different inert gases on explosion characteristics during low density polyethylene (LDPE) dust explosion and optimize the explosion-proof process, eight N₂ (CO₂)/air mixed inerting conditions were experimentally studied. Typical inerting conditions with 12 L cylindrical explosive tank were used to study the characteristics on the flame propagation. The thermogravimetric analysis with related theories were used to further explain the mechanism and quantities in low density polyethylene (LDPE) dust explosion with different inert gases. The results showed that the reduction of O₂ concentration could effectively delay the progress of flame growth process and weaken the effect of dust combustion reaction. The flame growth process of condition (N₂/air (18% O₂)) was 2.05 times slower than that of the non-inert condition. The explosion strength was obviously reduced, and the characteristic parameters such as explosion pressure and flame propagation speed were also affected by the decrease of O₂ concentration. For LDPE powder, the smaller the median diameter, the greater the explosion intensity and the lower the limiting oxygen content (LOC). The LOC with CO₂ was usually higher than that with N₂ and the effect of CO₂ was significantly better than N₂ in inerting.     

A quantitative risk assessment tool for the external safety of industrial plants with a dust explosion hazard

A quantitative risk assessment (QRA) tool has been developed by TNO for the external safety of industrial plants with a dust explosion hazard. As a first step an industrial plant is divided into groups of modules, defined by their size, shape, and constructional properties. Then the relevant explosion scenarios are determined, together with their frequency of occurrence. These include scenarios in which one module participates, as well as domino scenarios. The frequency is partly based on casuistry.

A typical burning velocity is determined depending on the ignition type, the dust properties and the local conditions for flame acceleration. The resulting pressure development is predicted with the ‘thin flame model’. Module failure occurs when the explosion load exceeds thresholds, which are derived from single degree of freedom (SDOF) calculations for various types of modules. A model has been developed to predict the process of pressure venting after module failure and the related motion of launched module parts.

The blast effects of the primary explosion are based on results from calculations with BLAST3D. The blast and flame effects of the secondary external explosion due to venting are calculated using existing models. The throw of fragments and debris is quantified with a recently developed model. This model is based on trajectory calculations and gives the impact densities, velocities, and angles as output. Furthermore the outflow of bulk material is taken into account. The consequences for external objects and human beings are calculated using existing models. Finally the risk contours and the Societal risk (FN curve) are calculated, which can be compared to regulations.     

Prediction of gas explosion pressures: A machine learning algorithm based on KPCA and an optimized LSSVM

A gas explosion, as a common accident in public life and industry, poses a great threat to the safety of life and property. The determination and prediction of gas explosion pressures are greatly important for safety issues and emergency rescue after an accident occurs. Compared with traditional empirical and numerical models, machine learning models are definitely a superior approach. However, the application of machine learning in gas explosion pressure prediction has not reached its full potential. In this study, a hybrid gas explosion pressure prediction model based on kernel principal component analysis (KPCA), a least square support vector machine (LSSVM), and a gray wolf optimization (GWO) algorithm is proposed. A dataset consisting of 12 influencing factors of gas explosion pressures and 317 groups of data is constructed for developing and evaluating the KPCA-GWO-LSSVM model. The results show that the correlations among the 12 influencing factors are eliminated and dimensioned down by the KPCA method, and 5 composite indicators are obtained. The proposed KPCA-GWO-LSSVM hybrid model performs well in predicting gas explosion pressures, with coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) values of 0.928, 26.234, and 12.494, respectively, for the training set; and 0.826, 25.951, and 13.964, respectively, for the test set. The proposed model outperforms the LSSVM, GWO-LSSVM, KPCA-LSSVM, beetle antennae search improved BP neural network (BAS-BPNN) models and reported empirical models. In addition, the sensitivity of influencing factors to the model is evaluated based on the constructed database, and the geometric parameters X1 and X2 of the confined structure are the most critical variables for gas explosion pressure prediction. The findings of this study can help expand the application of machine learning in gas explosion prediction and can truly benefit the treatment of gas explosion accidents.     

A new shock tube configuration for studying dust-lifting during the initiation of a coal dust explosion

The traditional defence against propagating coal dust explosions is the application of dry stone dust. This proven and effective safety measure is strictly regulated based on extensive international experience. While new products, such as foamed stone dust, offer significant practical benefits, no benchmark tests currently exist to certify their dust lifting performance in comparison to dry stone dust. This paper reviews the coal dust explosion mechanism, and argues that benchmark testing should focus on dust lifting during the initial development of the explosion, prior to arrival of the flame. In a practical context, this requires the generation of shock waves with Mach numbers ranging from 1.05 to 1.4, and test times of the order of 10's to 100's of milliseconds. These proposed test times are significantly longer than previous laboratory studies, however, for certification purposes, it is argued that the dust lifting behaviour should be examined over the full timescales of an actual explosion scenario. These conditions can be accurately targeted using a shock tube at length scales of approximately 50 m. It is further proposed that useful test time can be maximised if an appropriately sized orifice plate is fitted to the tube exit, an arrangement which also offers practical advantages for testing. The paper demonstrates this operating capability with proof-of-concept experiments using The University of Queensland's X3 impulse facility.