Stress Analysis of Operating Gas Pipeline Installed by Horizontal Directional Drilling and Pullback Force Prediction During Installation

With the development of the natural gas industry, the demand for pipeline construction has also increased. In the context of advocating green construction, horizontal directional drilling (HDD), as one of the most widely utilized trenchless methods for pipeline installation, has received extensive attention in industry and academia in recent years. The safety of natural gas pipeline is very important in the process of construction and operation. It is necessary to conduct in-depth study on the safety of the pipeline installed by HDD method. In this dissertation, motivated by the following considerations, two aspects of HDD installation are studied. First, through the literature review, one issue that has not received much attention so far is the presence of stress problem during the operation condition. Thus, two chapters (Chapters 3 and 4) in this dissertation are related to the pipe stress analysis during the operation. Regarding this problem, two cases are considered according to the fluidity of drilling fluid. The more dangerous situation is determined by comparing the pipeline stress in the two working conditions. The stress of pipeline installed by HDD method and open-cut method is also compared, and it indicates that the stress of pipeline installed by HDD method is lower. Moreover, through the analysis of influence factors and stress sensitivity, the influence degree of different parameters on pipeline stress is obtained. Secondly, literature review indicates that the accurate prediction of pullback force in HDD construction is of great significance to construction safety and construction success. However, the accuracy of current analytical methods is not high. In the context of machine learning and big data, three new hybrid data-driven models are proposed in this dissertation (Chapter 5) for near real-time pullback force prediction, including radial basis function neural network with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN-RBFNN), support vector machine using whale optimization algorithm with CEEMDAN (CEEMDAN-WOA-SVM), and a hybrid model combines random forest (RF) and CEEMDAN. Three novel models have been verified in two projects in China. It is found that the prediction accuracy is dramatically improved compared with the original analytical models (or empirical models). In addition, through the feasibility analysis, the great potential of machine learning model in near real-time prediction is proved. At the end of this dissertation, in addition to summarizing the primary conclusions, three future research directions are also pointed out: (1) stress analysis of pipelines installed by HDD in more complex situations; (2) stress analysis of pipeline during HDD construction; (3) database establishment in HDD engineering

Stress analysis of operating gas pipeline installed by horizontal directional drilling and pullback force prediction during installation

With the development of the natural gas industry, the demand for pipeline construction has also increased. In the context of advocating green construction, horizontal directional drilling (HDD), as one of the most widely utilized trenchless methods for pipeline installation, has received extensive attention in industry and academia in recent years. The safety of natural gas pipeline is very important in the process of construction and operation. It is necessary to conduct in-depth study on the safety of the pipeline installed by HDD method. In this dissertation, motivated by the following considerations, two aspects of HDD are studied. First, through the literature review, one issue that has not received much attention so far is the presence of stress problem during the operation condition. Thus, two chapters (Chapters 3 and 4) in this dissertation are related to the pipe stress problem during the operation. Regarding this problem, two cases are considered according to the fluidity of drilling fluid. The more dangerous situation is determined by comparing the pipeline stress in the two working conditions. The stress of pipeline installed by HDD method and open-cut method is compared, and it indicates that the stress of pipeline installed by HDD method is lower. Moreover, through the analysis of influence factors and stress sensitivity, the influence degree of different parameters on pipeline stress is obtained. Secondly, literature review indicates that the accurate prediction of pullback force in HDD construction is of great significance to construction safety and construction success. However, the accuracy of current analytical methods is not high. In the context of machine learning and big data, three new hybrid data-driven models are proposed in this dissertation (Chapter 5) for near real-time pullback force prediction, including radial basis function neural network with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN-RBFNN), and support vector machine using whale optimization algorithm with CEEMDAN (CEEMDAN-WOA-SVM), and a hybrid model combines random forest (RF) and CEEMDAN. Three novel models have been verified in two projects across the Yangtze River in China. It is found that the prediction accuracy is dramatically improved compared with the original analytical models (or empirical models). In addition, through the feasibility analysis, the great potential of machine learning model in near real-time prediction is proved. At the end of this dissertation, in addition to summarizing the main conclusions obtained, three future research directions are also pointed out: (1) stress analysis of pipelines installed by HDD in more complex situations; (2) stress analysis of pipeline during HDD construction; (3) database establishment in HDD engineering

Modified Generalized-Brillouin-Zone Theory with On-site Disorders

We study the characterization of the non-Hermitian skin effect (NHSE) in non-Hermitian systems with on-site disorder. We extend the application of generalized-Brillouin-zone (GBZ) theory to these systems. By proposing a modified GBZ theory, we give a faithfully description of the NHSE. For applications, we obtain a unified $\beta$ for system with long-range hopping, and explain the conventional-GBZ irrelevance of the magnetic suppression of the NHSE in the previous study.Comment: 7-pages, 3 figure

Light availability, soil phosphorus and different nitrogen forms negatively affect the functional diversity of subtropical forests

Understanding the relationship between functional diversity (FD) and species diversity changes and the effects of environmental factors on FD during succession is useful to improve forest management, conservation and restoration strategies. In this study, we measured 9 environmental factors related to light availability, soil water content and nutrients, and 19 leaf functional traits related to leaf light and nutrient utilization, growth and defense, water-use efficiency, and leaf respiration strategies in the dominant species during subtropical forest succession in southern China. Logarithmic function analysis and linear mixed model were used to explore the relationships between FD and species diversity and between FD and environmental factors. The results showed that FD and species diversity were not linearly correlated during succession. The light availability (represented by leaf area index), soil phosphorus, and different nitrogen forms were negatively related to the FD, suggesting these factors were the main environmental factors affecting FD during succession in the subtropical forest. By dividing FD into components corresponding to the diversity of different plant strategies, this study improves our understanding of the roles of light availability and soil nutrients in plant community functional structure, and provides useful information for forest conservation and restoration

Restoration of Mangrove Plantations and Colonisation by Native Species in Leizhou Bay, South China

To examine the natural colonization of native mangrove species into remediated exotic mangrove stands in Leizhou Bay, South China, we compared soil physical–chemical properties, community structure and recruitments of barren mangrove areas, native mangrove species plantations, and exotic mangrove species—Sonneratia apetala Buch.Ham—between plantations and natural forest. We found that severely degraded mangrove stands could not regenerate naturally without human intervention due to severely altered local environments, whereas some native species had been recruited into the 4–10 year S. apetala plantations. In the first 10 years, the exotic species S. apetala grew better than native species such as Rhizophora stylosa Griff and Kandelia candel (Linn.) Druce. The mangrove plantation gradually affected soil physical and chemical properties during its recovery. The exotic S. apetala was more competitive than native species and its plantation was able to restore soil organic matter in about 14 years. Thus, S. apetala can be considered as a pioneer species to improve degraded habitats to facilitate recolonization by native mangrove species. However, removal to control proliferation may be needed at late stages to facilitate growth of native species. To ensure sustainability of mangroves in South China, the existing mangrove wetlands must be managed as an ecosystem, with long-term scientific monitoring program in place

Restoration of Mangrove Plantations and Colonisation by Native Species in Leizhou Bay, South China

To examine the natural colonization of native mangrove species into remediated exotic mangrove stands in Leizhou Bay, South China, we compared soil physical–chemical properties, community structure and recruitments of barren mangrove areas, native mangrove species plantations, and exotic mangrove species—Sonneratia apetala Buch.Ham—between plantations and natural forest. We found that severely degraded mangrove stands could not regenerate naturally without human intervention due to severely altered local environments, whereas some native species had been recruited into the 4–10 year S. apetala plantations. In the first 10 years, the exotic species S. apetala grew better than native species such as Rhizophora stylosa Griff and Kandelia candel (Linn.) Druce. The mangrove plantation gradually affected soil physical and chemical properties during its recovery. The exotic S. apetala was more competitive than native species and its plantation was able to restore soil organic matter in about 14 years. Thus, S. apetala can be considered as a pioneer species to improve degraded habitats to facilitate recolonization by native mangrove species. However, removal to control proliferation may be needed at late stages to facilitate growth of native species. To ensure sustainability of mangroves in South China, the existing mangrove wetlands must be managed as an ecosystem, with long-term scientific monitoring program in place

Uncoupling protein-2 increases nitric oxide production and TNFAIP3 pathway activation in pancreatic islets

Mutations in the uncoupling protein 2 (Ucp2) gene are linked to type-2 diabetes. Here, a potential mechanism by which lack of UCP2 is cytoprotective in pancreatic β-cells was investigated. Nitric oxide (NO) production was elevated in Ucp2−/− islets. Proliferation (cyclin D2, Ccnd2) and anti-apoptosis (Tnfaip3) genes had increased expression in Ucp2−/− islets, whereas the mRNA of pro-apoptosis genes (Jun, Myc) was reduced. TNFAIP3 cellular localization was detected in both α- and β-cells of Ucp2−/− islets but in neither α- nor β-cells of UCP2+/+ islets, where it was detected in pancreatic polypeptide-expressing cells. TNFAIP3 distribution was not markedly altered 14 days after streptozotocin treatment. Basal apoptosis was attenuated in Ucp2−/− β-cells, while the nuclear factor κB (NF-κB) pathway was transactivated after islet isolation. Ucp2+/+ and Ucp2−/− islets were treated with cytokines for 24 h. Cytokines did not increase NF-κB transactivation or apoptosis in Ucp2−/− islets and TNFAIP3 was more strongly induced in Ucp2−/− islets. Inhibition of NO production strongly reduced NF-κB activation and apoptosis. These data show that null expression of Ucp2 induces transactivation of NF-κB in isolated islets, possibly due to NO-dependent up-regulation of inhibitor of κB kinase β activity. NF-κB transactivation appears to result in altered expression of genes that enhance a pro-survival phenotype basally and when β-cells are exposed to cytokines. TNFAIP3 is of particular interest because of its ability to regulate NF-κB signaling pathways

Wastewater pipe defect rating model for pipe maintenance using natural language processing

IntroductionClosed-circuit video (CCTV) inspection has been the most popular technique for visually evaluating the interior status of pipelines in recent decades. Certified inspectors prepare the pipe repair document based on the CCTV inspection. The traditional manual method of assessing structural wastewater conditions from pipe repair documents takes a long time and is prone to human mistakes. The automatic identification of necessary texts has received little attention. Computer Vision based Machine Learning models failed to estimate structural damage because they are not entirely understood and have difficulty providing high data needs. Hence, they have problems providing physically consistent findings due to their high data needs. Currently, a very small curated annotated image and video data set with well-defined, precisely labeled categories to test Computer Vision based Machine Learning models.MethodsThis study provides a valuable method to determine the pipe defect rating of the pipe repair documents by developing an automated framework using Natural Language Processing (NLP) on very small, curated annotated images, video data, and more text data. The text used in this study is broken into grammatical units using NLP technologies. The next step in the analysis entails using words to find the frequency of pipe defects and then classify them into respective defect ratings for pipe maintenance.Results and discussionsThe proposed model achieved 95.0% accuracy, 94.9% recall, 95% specificity, 95.9% precision score, and 95.7% F1 score, showing the potential of the proposed model to be used in large-scale pipe repair documents for accurate and efficient pipeline failure detection to improve the quality of the pipeline

Determining the Optimal N Input to Improve Grain Yield and Quality in Winter Wheat With Reduced Apparent N Loss in the North China Plain

Excessive or improper nitrogen (N) application rates negatively affect crop production and thereby environmental quality, particularly for winter wheat production in the North China Plain. Therefore, it is very important to optimize N fertilizer input to balance grain yield, environmental risk, and benefits under irrigated conditions. Three long-term stationary field experiments including five N levels, from 0 to 300 kg ha-1 [0 (N0), 90 (N90), 180 (N180), 240 (N240), and 300 (N300) kg ha-1] were carried out to investigate the effects of N regime on wheat yield, photosynthesis, and N balance at different sites. The grain yield and protein content increased quadratically with N rate, and the maximum values were 8087 kg ha-1 and 13.9% at N application rates of 250 and 337 kg N ha-1, respectively. N application increased the photosynthetic fluorescence parameters (Pn, Gs, and Tr) and N metabolism enzyme activities (NR and GS) which then increased grain yield. The leaching of soil nitrate into the deeper soil layers ( > 100 cm) increased with higher N fertilization and experimental years. The partial factor productivity (PFPN) was decreased by N because the apparent N loss increased with N application rate. In order to balance grain yield, N use efficiency (NUE), and N loss, the recommended N rate should be 120–171 kg N ha-1, and the corresponding yields and apparent N loss were 7278–7787 ka ha-1 and 22–37 kg ha-1, respectively