Longfei Hou’s research while affiliated with Tsinghua University and other places

With the increased number and scale of gas pipelines, gas explosions in underground spaces adjacent to pipelines occur occasionally. A method was proposed in this study for evaluating the explosion risk in underground spaces adjacent to gas pipelines. The method was established on the basis of a full-scale independent underground space (IUS) explosion experiment and the whole-chain accident evolution model of “leak-diffused aggregation-ignition-explosion,” which consists of the possibility, consequence, and correction factors of an underground space explosion was proposed. Explosion possibility assessment included pipeline leakage, diffusion aggregation, and ignition probabilities. In particular, the diffusion aggregation probability assessment method, as the focus here for explosion possibility assessment, was proposed based on the method of micro-elements and behavior of gas diffusion in soil. A manhole explosion experiment was carried out for IUS explosion consequence assessment, including the extent and intensity of explosion flame, overpressure, and debris effects. The experiment also confirmed the conclusion that the explosion overpressure of the manhole was not sufficient to cause harm to people. Flame and fragmentation damage should be paid attention to, especially for an underground space with deep depth(hL ≥ 2 m), large volume, no hinge and light quality manhole cover. The risk assessment method proposed here was applied in H city, and 24,830 underground spaces with high explosion risk were assessed from 510,835 underground spaces. Over the past three years, more than 200 dangerous cases of natural gas leaks and accumulations have been identified.

This study involved the construction and explosion of a large-scale (80-meter-long) underdrain and detailed investigations of the damaging impacts of a gas explosion to provide an experimental foundation for similarity modeling and infrastructural designs. The experiment vividly recreated the scene and explosion damage of the “11.22” explosion accident in Qingdao, China, thus allowing for evaluations of the movements and destruction of the cover plates. The damage mechanism was determined by analyzing the overpressure curves inside and outside the underground canal. It was determined that the cover plates were first lifted by the precursor wave, which induced a maximum overpressure of 0.06 MPa and resulted in explosion venting. The pressure entered the deflagration stage at the end of the explosion. The combustion wave overpressure reached 3.115 MPa close to the initiation point, and had a significant influence on the projectile energy of the cover plates there. Overall, 64% of the cover plates were only affected by the precursor wave, while 36% of the cover plates were subjected to both the precursor wave and the combustion wave; these cover plates were severely damaged. The results of this study provide fundamental insights relevant to the prevention and control of underdrain gas explosions.

The leaked gas from urban pipelines can easily spread to adjacent underground spaces and cause dangerous explosion accidents, therefore it is crucial to accurately identify underground spaces with high explosion consequences quantitatively, which is the key link to carry out the underground space explosion risk assessment. This paper proposes a method to quantitatively estimate the consequences of the urban underground drainage explosions. The method is established based on a large-scale underground explosion experiment and consists of several damage indicators as well as correction factors. The effects of fragments after the gas explosion, overpressure, and ground vibration post-explosion on nearby residents, infrastructures, and buried pipelines are quantitatively investigated through experimental results and theoretical analysis. The social impact and rescue force distribution affected by the explosion are assessed. A case study was generated in urban area which showed that this method is practicable. The results presented here may provide sound theoretical guidance for urban pipeline risk assessment and explosion hazard control.

Gas leakage from buried gas pipelines in urban areas can lead to accidents involving fire and explosion when the gas gets concentrated into the adjacent underground spaces. Determining monitoring points for the gas leakage in the underground spaces can prevent the initiation of fire and explosion. In this regard, this study proposes an optimized distribution model which relies on risk prediction. It maps the fire and explosion risk in the underground spaces to the discrete target pipeline based on the effect predicted by the monitoring sensors. Moreover, the total risk in this system is calculated through the micro-element method to design an effective distribution optimization strategy. A case study is conducted to illustrate the effectiveness of the new approach and compare it with the risk-based distribution method and effective monitoring length method. The results show that determining the optimized distribution plan is difficult using the risk-based distribution method and effective monitoring length method because these methods may determine a large number of monitoring points or cannot determine the specific location of the monitoring point. The proposed optimization model enables to derive the relationship between the number of distribution points and the risk in the system. For the same number of monitoring points, the rate of risk control in the system of the proposed model is twice that of the conventional model. As the number of monitoring points decreases, the monitoring cost for the prevention of fire and explosion would be largely reduced.

Purpose The purpose of this paper is to present a new technique for monitoring gas leakage in underground pipelines to prevent dangerous explosions. Design/methodology/approach A novel system for monitoring methane concentration in underground spaces was developed by integrating the multi-channeled air sampling method with an infrared gas sensor. A pipe installation methodology (without excavation) was established and verified accordingly. Findings The proposed approach was proven successful in reducing the quantity of sensors needed for real-time monitoring of underground pipeline leakage by about 80 per cent. Furthermore, this system lowers total operational cost by as much as 60 per cent. Originality/value The results presented here represent a possible solution to reducing the public safety risks associated with explosions and fires caused by pipeline leakage in underground spaces. Its total cost is low and its monitoring efficiency is high.

It is crucial to monitor gas concentration in an explosive underground space with the utmost accuracy and in real time; unfortunately, this involves a large number of costly monitoring points. This article proposes a novel method for optimizing gas leak monitoring points in a flexible manner per real-time monitoring requirements. The method accounts for leakage diffusion radius, effective monitoring length, and other relevant influence factors. The probability distribution function is utilized to describe the leakage diffusion radius, which can be used to calculate the effective monitored length by taking the expectation of any section of the pipeline as the actual monitored length. The method was tested and the results were analyzed, then improved upon via the optimal effective monitored length distribution. The proposed method was applied to a 356-meter-long concrete road with 121 inspection wells to find that the minimum amount of monitoring points is 60 and the maximum effective monitored length is 274.7 m. If the effective monitored length was reduced by 0.12%, the amount of monitoring points could be decreased to 50. The theoretical optimization scheme is 229.1 m in effective monitored length and 19 monitoring points. The proposed method represents a novel approach to preventing pipeline leakage. It allows for real-time, low-cost monitoring of gas concentration in the surrounding underground space near the pipeline, as well as for optimizing the distribution of monitoring points.