Shuya Hou
Academic and research departments
Information and process systems engineering, School of Chemistry and Chemical Engineering.About
My research project
Risk assessment and emergency response study of multiple pool fires domino accidentsChemical tank farms, which are inherently hazardous and often have multiple tanks are clustered together, confront increased risks of accident propagation and consequential domino accidents due to their layout. Pool fires are one of the most common types of accidents in chemical tanks farms, and multiple pool fires (MPFs) is considered to have occurred when two or more fires occur simultaneously and may interact with each other. When MPFs occur simultaneously, their interaction exacerbates the severity of outcomes compared to single pool fires (SPF).
The main research objectives of this dissertation are as follows:
- Development of a CFD Numerical Simulation Model: a CFD numerical simulation model for the prediction of radiative heat transfer will be developed. This model aims to predict flame geometry and thermal radiation under the synergistic effect of MPFs, employing a comparative analysis of different turbulence models.
- Formulation of a Meta-Model: a meta-model for expedited prediction of the consequences of MPF accidents will be established, leveraging the developed numerical simulation model. This approach will facilitate the calculation such consequences under diverse conditions, enhancing the precision and efficiency of predictions.
- Creation of an MPF Domino Accident Emergency Response Model: an MPF domino accident emergency response model will be formulated to adeptly guide resource allocation, particularly in scenarios of constrained emergency response resources post-accident.
Supervisors
Chemical tank farms, which are inherently hazardous and often have multiple tanks are clustered together, confront increased risks of accident propagation and consequential domino accidents due to their layout. Pool fires are one of the most common types of accidents in chemical tanks farms, and multiple pool fires (MPFs) is considered to have occurred when two or more fires occur simultaneously and may interact with each other. When MPFs occur simultaneously, their interaction exacerbates the severity of outcomes compared to single pool fires (SPF).
The main research objectives of this dissertation are as follows:
- Development of a CFD Numerical Simulation Model: a CFD numerical simulation model for the prediction of radiative heat transfer will be developed. This model aims to predict flame geometry and thermal radiation under the synergistic effect of MPFs, employing a comparative analysis of different turbulence models.
- Formulation of a Meta-Model: a meta-model for expedited prediction of the consequences of MPF accidents will be established, leveraging the developed numerical simulation model. This approach will facilitate the calculation such consequences under diverse conditions, enhancing the precision and efficiency of predictions.
- Creation of an MPF Domino Accident Emergency Response Model: an MPF domino accident emergency response model will be formulated to adeptly guide resource allocation, particularly in scenarios of constrained emergency response resources post-accident.
ResearchResearch interests
machine learning; pool fire; quantitative risk analysis of domino accidents; deflagration-to-detonation transition
Research interests
machine learning; pool fire; quantitative risk analysis of domino accidents; deflagration-to-detonation transition
Publications
Fires spreading at limited distances one to the other can cause changes in burning rates and flame shapes due to synergistic effects. These may result in more severe consequences and in the generation of specific and more intense escalation vectors, causing a higher probability of domino scenarios. In this study, a specific approach was developed to consider synergistic effects of double pool fires in a quantitative risk assessment (QRA) framework aiming at the assessment of domino accident scenarios. The double pool fire synergy (DPFS) model developed was validated against experimental results obtained using different fuels. A comprehensive framework was developed to address the quantitative risk assessment of escalation leading to domino scenarios, combining the DPFS model, escalation probability estimation for domino accident, and Bayesian network analysis. Three case studies were carried out to analyze the impact of synergistic effects on escalation probability. The results show that synergistic effect of simultaneous multiple pool fires significantly increase the intensity of the escalation vector, and the escalation probability increases up to three orders of magnitude. Furthermore, the inclusion of synergistic effect in the analysis of posterior probability improves the accuracy of identifying the critical units in domino scenarios, contributing to a better selection of the emergency response targets.
On June 13, 2020, an LPG tanker leaked, followed by a vapor cloud explosion on the highway section near Liangshan Village, Wenling City, China. The accident killed 20 people and injured more than 170, causing severe damage to the surrounding area and significant impact to the society. This work studied the large vapor cloud explosion of the LPG transportation accident in terms of the dynamic phenomena of explosion, building damage level, and mechanism of DDT. The accident analysis indicates that blast shock wave front and reaction front were moving together at a speed higher than the speed of sound; the explosion overpressure of the accident is consistent with the calculation using the detonation approach of TNO multi-energy method; the blockage level and flame acceleration distance caused by the shrubs, and the quantity of release LPG provide enough conditions for DDT occurrence. Therefore, it is believed that DDT has occurred in this accident. The findings of this work also contribute to providing scientific recommendations on preventing DDT accidents, including redesign the vegetation at incident-prone section of the highway to eliminate the condition of DDT occurrence, and optimize the transportation route to avoid highly populated areas.
Liquefied natural gas (LNG) is widely used, because it provides an easy and economic solution to the transport and storage of natural gas (NG), especially on long distances or when transport by pipeline is not viable. The LNG pool fire is one major process safety accident at the LNG facilities according to the report of the U.S. Government Accountability Office. Moreover, due to the high surface emissive power of LNG compared to other hydrocarbon fuels, LNG pool fires have a high potential in causing domino effects and cascading events in process industry. Previous studies developed Computational Fluid Dynamics (CFD) models of LNG pool fires, but the mass burning rate was fixed manually as a model input, not considering that the mass burning rate is determined by the fuel’s physical properties and heat input vaporizing the fuel. In this study, a model of LNG pool fire controlled by material physical properties was developed using fire dynamics simulator (FDS), and was validated against LNG pool fire experiments carried out by Mary Kay O’Connor Process Safety Center (MKOPSC). Statistical performance measurement shows that the model is superior to the semi-empirical approaches in predicting the mass burning rate of LNG pool fire under different pool sizes. A flame geometry analysis software was developed comparing different algorithms, and the centroid method was selected. The results show that the fire model (200 kW/m3 as flame contour) can accurately predict the flame geometry observed in the experimental runs. The influence of wind velocity and dike height on the mass burning rate was also investigated. The results show that the height of the concrete dike is negatively correlated with the mass burning rate of LNG pool fire. The effect of wind velocity on LNG mass burning rate is twofold. The forced convective boundary layer at lower wind velocity promotes LNG combustion and increases the mass burning rate, while higher wind velocities reduce the mass burning rate due to the reduction of the thermal radiation feedback. The findings in this study will contribute to an accurate risk assessment of LNG pool fire accidents in the process industry.
AnoverviewofSafetyEngineeringeducationinChinaisconducted.First,definition, researchspecialty, anddevelopmenthistoryofSafetyScienceandEngineeringare introduced.Second,ageographicaldistributionstudyindicatesthatuniversitiesofferingSafetyEngineering inmainlandChinaaremainly locatedinEastChina,Central NorthChina,andsomeprovincesinWestandSouthChina,whichisconsistentwith thelatestgrossdomesticproduct (GDP)andyear-endresidentpopulationdata.The analysisofevaluationinhighereducationfocusesonengineeringeducationaccreditation, first-class discipline construction, andChinaUniversity Subject Rankings. Third,SafetyEngineeringcurriculainChinamainlyincludegeneraleducationcourses andprofessionalcourses.Theformerisdividedintobasiceducationcoursesandsubjecteducationcourses, andthe latter isdividedintoprofessional corecoursesand professionalcharacteristiccourses.Theprofessionalcharacteristiccoursesofferedby variousuniversitiesaredifferentfromeachother,mainlyduetotheirresearchspecialties, suchas firesafety, chemical safety,miningsafety, constructionsafety, and nuclear safety. Finally, existingchallenges, includinga lackofengineeringpractice, lackof systematic course content, and lackof professional competitiveness, are discussed.
To mitigate the hazards of fragments during a runaway reaction explosion or a boiling liquid expanding vapor explosion (BLEVE), an accurate estimate of the maximum kinetic energy of the fragments and the trajectory is critical. On June 13, 2020, an LPG tanker truck slanted over and exploded on the highway interchange at Wenling, Zhejiang Province, China. A BLEVE occurred initially, with the cylindrical vessel rupturing into one end-cap and one rocket-like vessel. The 12-ton rocket-like projectile was thrown 364 m away, resulting in an LPG vapor cloud larger than 300 m, followed by several explosions ultimately. It provided a good opportunity to study the ‘rocket’ BLEVE process and to evaluate the potential trajectory model. Image analysis technique and 3D modeling using SketchUp were employed to reconstruct the spatial and temporal information in the accident, by comparing the Sketchup model with the accident video information processed by MATLAB. An accurate trajectory of the fragment was reconstructed, giving the projectile velocity to be 170–176 m/s and the averaged trajectory angle around 8°. The BLEVE process was further modeled using a two-phase flow discharge model together with a rocket propulsion model, and the predicted results fit well with those as estimated by the reconstructed model. The trajectory of the fragment was also modeled using the projectile velocity and trajectory angle, together with discussion on the effects of air drag resistance, which provided a good prediction and fit well with the trajectory in the SketchUp model.
Considering the hazard of wood fire is one of the major cataclysms in nature, an effective way to prevent the loss of wood fire should be studied, such as fire-resistant materials. In this work, a novel silica foam with controllable gelation time was developed and tested for its fire-retardant effect and mechanism on wood. The optimum formula is 0.4wt% compound foaming agent (SDS: SDBS: APG = 3:3:2), 0.1wt% foam stabilizer (CMC-Na), 30 vol.% sodium silicate solution and 40 vol.% acetic acid. The fire-retardant mechanism of silica foam on wood was investigated through X-ray photoelectron spectroscopy (XPS), X-Ray Diffraction (XRD), fourier transform infrared spectroscopy (FTIR), Thermo Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), and fire retardance analysis. XPS and XRD results indicate that the silica foam contributes to the formation of a thermal stable layer on the wood surface for fire retardancy, and the hydrophilic groups (C-O and C = O), especially the C-O functional group accounts for approximately 95% of the entire carbon-containing functional group in the silica foam, and amorphous silica in the silica foam can adsorb water physically or chemically, helping to provide a wetting effect for fire retardancy. FTIR result indicates that the Si–O-C and Si–C bonds formed between the silica foam and wood can promote the formation of a charred layer at high temperature, reinforcing the fire retardancy. TGA and fire retardance analysis results indicate that the silica foam can inhibit the pyrolysis reactions of wood, and the mass loss rate of the wood is reduced by 50% and 30%, respectively.