Pipeline transportation is the most important transport mode for crude oil. When oil pipeline operates at low throughput or shutdown, congelation accident always happen as the temperature of oil in pipeline drops, which causes malignant accidents and significant financial losses. Study of the various factors affecting congelation failure is necessary. According to the statistics and analysis of congelation accident, direct and indirect reasons of affecting pipeline congelation failure were determined. Combining with fuzzy comprehensive assessment method, the related importance of factors on congelation accident was studied, and the grade of factors affecting failure congelation of pipeline was also identified. Aiming at the factors, some improvement measures were put forward. These can provide evidences for accident treatment, planned maintenance, security operation and scientific management.

In waxy crude oil transportation process, wax crystals start to precipitate as the oil temperature drops to wax appearance point, and then form a network structure gradually which attaches to the wall. The problem of wax deposition seriously affects the normal operation of pipeline. Based on the wax deposition tendency coefficient method, combined with experimental data, the parameters related to wax deposition tendency coefficient is fitted, and the wax deposition rate equation of crude oil is determined finally. The variation law of wax deposition rate along the pipeline is analyzed, and the influence of different seasons and different throughput the on wax deposition rate is discussed subsequently.

The exergy consumption during the transportation of heated oil includes four items: valid and invalid pressure exergy consumption, valid and invalid heat exergy consumption. These four parts are taken as the same loss in traditional evaluation systems of pipeline energy consumption, which somewhat hinders the further energy-conservation study. So establishing a scientific exergy consumption evaluation system is an important basis work of energy efficiency management. Based on the index system of energy efficiency for pipeline proposed by predecessors, the meaning of energy quality for exergy and the categories of exergy flow, the energy consumption index set of exergy transfer is set up in this article. Moreover, by computing exergy consumption index of exergy transfer for an oil pipeline in Daqing Oilfield, a part of representative indexes are selected by analyzing the obtained data with correlation coefficient method. Finally, the exergy consumption evaluation system is constructed.

Pipeline transportation is a substance conveying process that makes crude oil flowing from first station to ultimate station and at the same time takes a certain amount of driving energy for cost. Based on related theories of engineering fluid mechanics, mathematics analytic formula of driving exergy in oil pipeline transportation is deduced by micro-element analysis. We can get the conclusion that driving exergy loss has a positive correlation with diameter and throughput, and also a contrary trend with insulation thickness and outbound temperature by analyzing the influence on driving exergy loss from operation parameters in pipeline process,. This research can provide theoretical guidance for energy consumption classification, and further more, the technical support for energy consumption in pipeline system.

BACKGROUND To date, almost all of these studies have identified multiple risk factors but did not offer practical instruments for routine use in predicting death risk in human H7N9 infection cases. Such an instrument could be useful in identifying high-risk H7N9 patients who can benefit from reducing the risk of death. OBJECTIVE We aimed to create a clinical nomogram to predict the overall death (OD) risk of patients with H7N9 virus infection (VI). METHODS We reviewed specific factors and outcomes regarding patients with H7N9 VI to determine relationships and developed a nomogram to calculate individualized patient risk. This model was used to predict each individual patient’s probability of death based on results obtained from the multivariate binary logistic regression analysis. RESULTS We examined 227 patients with H7N9 VI enrolled in our study over a nearly 6-year period. Stepwise selection was applied to the data, which resulted in a final model with 7 independent predictors. The nomogram model was constructed for maximum predictive accuracy. The concordance index of this nomogram was 0.906 and 0.822 for the training and validation sets, respectively, which indicates adequate discriminatory power. The calibration curves for the OD showed optimal agreement between nomogram prediction and actual observation in the training and validation sets, respectively. A decision-curve analysis of the clinical benefit indicates that the prognostic model, including age ≥ 60 years , chronic disease, poor hand hygiene , time from illness onset to the first medical visit, incubation period of ≤ 5 days, peak C-reactive protein ≥120 mg/L, and increased initial neutrophil count factors, resulted in a higher net benefit across a wide range of decision threshold probabilities (i.e., an approximately 6 – 98% risk of death). With the cutoff threshold values of 30% and 20% predicted probabilities, nomogram models showed sensitivities of 85.7% and 80.9% and specificities of 78.3% and 73.1% when applied to the training and validation sets, respectively. CONCLUSIONS We established and validated a novel nomogram that can predict OD for patients with H7N9 VI. This practical prognostic model may help clinicians in decision making, clinical diagnosis, and treatment selection.