Impact assessment of traffic-induced vibration on natural gas transmission pipeline

Bajcar, Tom; Cimerman, Franc; Širok, Brane; Ameršek, M.

doi:10.1016/j.jlp.2012.07.021

Cited by 16 publications

(8 citation statements)

References 9 publications

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“…Bajcar et al studied the effects of traffic‐induced vibrations on natural gas pipelines. Dynamic stresses from traffic vibrations affect the loading of natural gas pipeline materials and may have some impact on natural gas loads and pose some safety threat to the surrounding environment 22 . Liang et al investigated the mechanical behavior of common polyethylene natural gas pipelines when ground is overload.…”

Section: Research Statusmentioning

confidence: 99%

A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

Zeng

Shao

Bian

et al. 2022

Energy Science & Engineering

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Natural gas load forecasting provides decision-making support for natural gas dispatch and management, pipeline network construction, pricing, and sustainable energy development. To explain the uncertainty and volatility in natural gas load forecasting, this study predicts the natural gas load volatility. As the natural gas load volatility has the time-series features, along with long-term memory, volatility aggregation, asymmetry, and nonnormality, this study proposes a natural gas load volatility prediction model by combining generalized autoregressive conditional heteroscedasticity (GARCH) family models, XGBoost algorithm, and long short-term memory (LSTM) network. The model first takes the GARCH family models parameters of sliding estimation and meteorological factors as the influencing factors of volatility, and then it screens these influencing factors through the extreme gradient boosting (XGBoost) algorithm. Finally, the selected important features are input into the LSTM network to predict the volatility, and the 90% confidence interval of the volatility is calculated. Compared with a variety of single and combined models, the model proposed in this study has an average reduction of 45.404% in the evaluation index of mean squared error. The experimental results show that the model proposed in this study has a good performance and accuracy in predicting the volatility of natural gas load.

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Section: Research Statusmentioning

confidence: 99%

A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

Zeng

Shao

Bian

et al. 2022

Energy Science & Engineering

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“…In this part, the vibration isolation performance of the composite subgrade structure subjected to different vibration intensities was investigated. The vibration of different intensities was achieved by a load hammer falling from different heights (5,10,15,20, and 25 cm). The thickness of the XPS plates was 5 cm, which was determined in the previous section.…”

Section: The Effect Of Vibration Intensity On the Vibration Isolationmentioning

confidence: 99%

Study on the Vibration Isolation Performance of Composite Subgrade Structure in Seasonal Frozen Regions

Han¹,

Wei²,

Wang³

2020

Preprint

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Silty clay modified by fly ash and crumb rubber is a kind of sustainable subgrade filler which has good anti-freeze-thaw resistance stability but wake vibration isolation performance. The objective of this study was to improve the vibration isolation of the modified soil and investigate the vibration isolation effect of the composite subgrade structure of XPS plates and the modified soil by indoor impact test. First, the vibration isolation performance of silty clay, modified soil and composite subgrade structure was respectively evaluated. Second, the effect of XPS plate’s thickness and vibration intensity on the vibration performance of the composite subgrade structure were evaluated. Third, the vibration isolation performance of the test groups under the condition of freeze-thaw cycles was assessed. The results show that the vibration isolation performance of subgrade can be effectively improved by setting XPS plates. The composite subgrade structure has certain vibration isolation effect, especially in vertical direction. Considering vibration isolation performance and costs, 5cm is the optimum XPS plates thickness. The composite subgrade structure has great vibration isolation performance under the condition of freeze-thaw cycles, so it is suitable to be applied in road subgrade in seasonal frozen regions.

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“…Transportation, construction, or earthquakes can induce the propagation of low frequency elastic waves near structures [ 1 ]. The structural vibration and machine noise generated by low frequency elastic wave can not only destroy civil infrastructure, but also reduce the comfort level of residents [ 2 , 3 ]. Among all the negative impacts caused by low frequency elastic waves, the damage to human society and environment induced by seismic waves is the most destructive.…”

Section: Introductionmentioning

confidence: 99%

A Ternary Seismic Metamaterial for Low Frequency Vibration Attenuation

Chen

Lei

2022

Materials

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Structural vibration induced by low frequency elastic waves presents a great threat to infrastructure such as buildings, bridges, and nuclear structures. In order to reduce the damage of low frequency structural vibration, researchers proposed the structure of seismic metamaterial, which can be used to block the propagation of low frequency elastic wave by adjusting the frequency range of elastic wave propagation. In this study, based on the concept of phononic crystal, a ternary seismic metamaterial is proposed to attenuate low frequency vibration by generating band gaps. The proposed metamaterial structure is periodically arranged by cube units, which consist of rubber coating, steel scatter, and soft matrix (like soil). The finite element analysis shows that the proposed metamaterial structure has a low frequency band gap with 8.5 Hz bandwidth in the range of 0–20 Hz, which demonstrates that the metamaterial can block the elastic waves propagation in a fairly wide frequency range within 0–20 Hz. The frequency response analysis demonstrates that the proposed metamaterial can effectively attenuate the low frequency vibration. A simplified equivalent mass–spring model is further proposed to analyze the band gap range which agrees well with the finite element results. This model provides a more convenient method to calculate the band gap range. Combining the proposed equivalent mass–spring model with finite element analysis, the effect of material parameters and geometric parameters on the band gap characteristic is investigated. This study can provide new insights for low frequency vibration attenuation.

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Impact assessment of traffic-induced vibration on natural gas transmission pipeline

Cited by 16 publications

References 9 publications

A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

Study on the Vibration Isolation Performance of Composite Subgrade Structure in Seasonal Frozen Regions

A Ternary Seismic Metamaterial for Low Frequency Vibration Attenuation

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