Although the use of polyethylene (PE) pipelines has become increasingly widespread in recent years, few studies have addressed their seismic design and ability to withstand blast waves. In order to establish their seismic capacity, the dynamic response of buried pipelines subjected to blast waves must be explored in depth. Here, we studied the dynamic response of PE pipes situated near an explosive source. Time histories of dynamic strains were measured by conventional strain gauges after simple waterproof treatment, and pipe and ground vibration velocity curves were obtained. Based on the experimental data, the attenuation law of the peak strains under the conditions of different charge masses and blast center distances was analyzed, and the spectrum characteristics of strain, velocity of the pipe, and ground velocity were studied. The results revealed that a large hoop strain on the PE pipes was produced due to the local impact near the explosive source. We found that peak hoop strain (PHS) or peak axial strain (PAS) had a power attenuation relationship with the scaled distance, and this relationship could also be derived by dimensional analysis. The average frequency of strains had the same attenuation form as the charge mass, which was between 10 Hz and 50 Hz. Additionally, the vibration of the pipe showed a low frequency. We also determined that the attenuation of the average frequency of pipe and ground vibration velocity was closely related to the charge mass and the scaled distance. Pipe peak vibration velocity (PPVV), ground peak particle velocity (GPPV), and the peak dynamic strain of pipe were highly positively correlated, which verifies the feasibility of using GPPV to characterize pipeline vibration and strain level. Thus, a blasting criterion of 10% minimum request strength (MRS) for PE pipe was proposed, which means that the additional PHS or PAS of the dangerous point must be less than 10% MRS, and we also propose limiting the safety distance–charge mass for blasts near buried PE pipelines by the criterion. Some results in this paper can serve as the basis for future in-depth theoretical research.

Precise and efficient air quality prediction plays a vital role in safeguarding public health and informing policy-making. Fine particulate matter, specifically PM_2.5 and PM₁₀, serves as a crucial indicator for assessing and managing air pollution levels. In this paper, a daily pollution concentration prediction model combining successive variational mode decomposition (SVMD) and a bidirectional long short-term memory (BiLSTM) neural network is proposed. Firstly, SVMD is used as an unsupervised feature-learning method to divide data into intrinsic mode functions (IMFs) and to extract frequency features and improve short-term trend prediction. Secondly, the BiLSTM network is introduced for supervised learning to capture small changes in the air pollutant sequence and perform prediction of the decomposed sequence. Furthermore, the Bayesian optimization (BO) algorithm is employed to identify the optimal key parameters of the BiLSTM model. Lastly, the predicted values are reconstructed to generate the final prediction results for the daily PM_2.5 and PM₁₀ datasets. The prediction performance of the proposed model is validated using the daily PM_2.5 and PM₁₀ datasets collected from the China Environmental Monitoring Center in Tianshui, Gansu, and Wuhan, Hubei. The results show that SVMD can smooth the original series more effectively than other decomposition methods, and that the BO-BiLSTM method is better than other LSTM-based models, thereby proving that the proposed model has excellent feasibility and accuracy.

In order to ensure the safe operation of buried polyethylene pipelines adjacent to blasting excavations, controlling the effects of blasting vibration loads on the pipelines is a key concern. Model tests on buried polyethylene pipelines under blasting loads were designed and implemented, the vibration velocity and dynamic strain response of the pipelines were obtained using a TC-4850 blast vibrometer and a UT-3408 dynamic strain tester, and the distribution characteristics of blast vibration velocity and dynamic strain were analyzed based on the experimental data. The results show that the blast load has the greatest effect on the circumferential strain of the polyethylene pipe, and the dynamic strain response is greatest at the section of the pipe nearest to the blast source. Pipe peak vibration velocity (PPVV), ground peak particle velocity (GPPV), and the peak dynamic strain of the pipe were highly positively correlated, which verifies the feasibility of using GPPV to characterize pipeline vibration and strain level. According to the failure criteria and relevant codes, combined with the analysis of experimental results, the safety threshold of additional circumferential stress on the pipeline is 1.52 MPa, and the safety control vibration speed of the ground surface is 21.6 cm/s.