Designing a reliable leak bio-detection system for natural gas pipelines

Batzias, F.A.; Siontorou, Christina G.; Spanidis, P.-M.P.

doi:10.1016/j.jhazmat.2010.09.115

Cited by 58 publications

(19 citation statements)

References 176 publications

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“…Pipelines are one of the most convenient and effective ways to transport enormous amounts of hazardous materials, especially natural gas (NG) [1,2]. In addition, NG consumptions and subsequently the pipeline systems are ever increasing worldwide [3,4].…”

Section: Introductionmentioning

confidence: 99%

Dynamic safety assessment of natural gas stations using Bayesian network

Zarei

Azadeh

Khakzad

et al. 2017

Journal of Hazardous Materials

210

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Pipelines are one of the most popular and effective ways of transporting hazardous materials, especially natural gas. However, the rapid development of gas pipelines and stations in urban areas has introduced a serious threat to public safety and assets. Although different methods have been developed for risk analysis of gas transportation systems, a comprehensive methodology for risk analysis is still lacking, especially in natural gas stations. The present work is aimed at developing a dynamic and comprehensive quantitative risk analysis (DCQRA) approach for accident scenario and risk modeling of natural gas stations. In this approach, a FMEA is used for hazard analysis while a Bow-tie diagram and Bayesian network are employed to model the worst-case accident scenario and to assess the risks. The results have indicated that the failure of the regulator system was the worst-case accident scenario with the human error as the most contributing factor. Thus, in risk management plan of natural gas stations, priority should be given to the most probable root events and main contribution factors, which have identified in the present study, in order to reduce the occurrence probability of the accident scenarios and thus alleviate the risks.

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Section: Introductionmentioning

confidence: 99%

Dynamic safety assessment of natural gas stations using Bayesian network

Zarei

Azadeh

Khakzad

et al. 2017

Journal of Hazardous Materials

210

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“…These researches can be categorized into two main groups: leakage detection location and calculation its amount. In the case of leakage detection, some methods and studies for gas pipeline leak detection have been developed in recent studies [8][9][10][11][12].…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Correlations for estimating natural gas leakage from above-ground and buried urban distribution pipelines

Ebrahimi‐Moghadam

Farzaneh–Gord

Deymi–Dashtebayaz

2016

Journal of Natural Gas Science and Engineering

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“…When a beam of IR radiation containing a range of wavelengths is incident upon a material, the material absorbs certain wavelengths [16]. Even if the strength of the radiation is insufficient to cause an electronic energy transition [17], it can still cause vibrational and rotational transitions.…”

Section: Principlesmentioning

confidence: 99%

Development of an Optical Gas Leak Sensor for Detecting Ethylene, Dimethyl Ether and Methane

Tan

Pei

Zhu³

et al. 2013

Sensors

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In this paper, we present an approach to develop an optical gas leak sensor that can be used to measure ethylene, dimethyl ether, and methane. The sensor is designed based on the principles of IR absorption spectrum detection, and comprises two crossed elliptical surfaces with a folded reflection-type optical path. We first analyze the optical path and the use of this structure to design a miniature gas sensor. The proposed sensor includes two detectors (one to acquire the reference signal and the other for the response signal), the light source, and the filter, all of which are integrated in a miniature gold-plated chamber. We also designed a signal detection device to extract the sensor signal and a microprocessor to calculate and control the entire process. The produced sensor prototype had an accuracy of ±0.05%. Experiments which simulate the transportation of hazardous chemicals demonstrated that the developed sensor exhibited a good dynamic response and adequately met technical requirements.

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Designing a reliable leak bio-detection system for natural gas pipelines

Cited by 58 publications

References 176 publications

Dynamic safety assessment of natural gas stations using Bayesian network

Dynamic safety assessment of natural gas stations using Bayesian network

Correlations for estimating natural gas leakage from above-ground and buried urban distribution pipelines

Development of an Optical Gas Leak Sensor for Detecting Ethylene, Dimethyl Ether and Methane

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