A Risk-Effectiveness Design Method for Flare Height of Natural Gas Pipeline System

Abstract

The objective of this research is to develop a risk-effectiveness design method for flare height of natural gas pipeline system. The advantage of the proposed design method over the traditional methods is the impacts of population density to flare risk are considered and more economic flare height could be obtained under lower risk levels. The conventional design methods obtain the same flare height for both high and low population density area. A risk-effectiveness model is established by combing the risk cost and the flare construction cost. The optimal flare height is the minimum value calculated by the first derivative of the model. An application is given to show the model's usability under different population densities. The flare height of 19.4m, 21.7 m, 24.3m, and 28.6m are obtained by the method for four different regions with the population densities of 5.2×10−5, 1×10−4, 3×10−4 and 7×10−4 person/m3. The increased flare height implies the increase of the risk levels accompanying with the increase of the population density. A comparison with the design results gained by the API RP 521 method is made to prove the effectiveness of the proposed method. Under the condition that the compensation per person is 40 times of the construction fees per meter, the flare heights get by the proposed method are 69.7%, 78.0%, 87.4% and 102.9% of the API design heights with the population densities of 5.2×10−5, 1×10−4, 3×10−4 and 7×10−4 person/m3. The results show that a lower flare height would be obtained by the proposed method with the population densities lower than 7×10−4 person/m3, and a direct construction saving could be gained under this circumstance, which proved the economy of the proposed method. The main novelty lies in the risk-effectiveness model which combines the loss of human injuries and the cost of flare construction to obtain the optimal design results for different regions. Compared with the traditional method, the proposed method can not only reflect the impact of the population density to flare risks, but is also more economical under certain circumstance. This makes it possible to gain more benefits for flare operators under low risk levels.