Summary In deep well drilling, rock breaking has some problems, such as low rock breaking efficiency, serious thermal wear of cutters, short service life, and high cost. It is noticed that the application of CO2 drilling fluid in the oil and gas underbalanced drilling is an efficient approach to achieve the reduction of CO2 emissions. Thus, based on the rock-breaking advantages of CO2 jetting, a new rock-breaking method of combing high-pressure CO2 jet and polycrystalline diamond cutter (PDC) is proposed in our study. The cooling mechanism and influencing during rock breaking by using the high-pressure CO2 jet-PDC are conducted. With the test system during composite rock breaking of the high-pressure CO2 jet-PDC, the composite rock-breaking experiment of the high-pressure CO2 jet-PDC was carried out. In the experiment, the comparison of the CO2 jet, N2 jet, water jet, and without a jet was conducted and analyzed. And based on the numerical simulation analysis, the intense cooling mechanism was expounded. In the process during composite rock breaking of the high-pressure CO2 jet-PDC, the intense cooling mechanism was mainly attributed to three main reasons: the thermal effect of the jet flow, the expansion endothermic effect of the jetted flow, and the phase transformation cooling effect of the CO2 jet. The effects of rock samples, jet temperatures, jet flow pressures, and rock temperatures on the cutting temperature were experimentally explored, and finally, the intense cooling rules of composite rock breaking were obtained. The experimental results showed that the CO2 jet had a stronger cooling effect on granite than that of the sandstone. In a certain range, jet pressure was positively correlated with the cutting temperature, whereas jet temperature and heating time were negatively correlated with cutting temperature. The study provides the theoretical support for the CO2 application as a drilling medium in underbalanced drilling.
BACKGROUND: Melanoma is a tumor caused by melanocytes with a high degree of malignancy, easy local recurrence, distant metastasis, and poor prognosis. It is also difficult to be detected by inexperienced dermatologist due to their similar appearances, such as color, shape, and contour. OBJECTIVE: To develop and test a new computer-aided diagnosis scheme to detect melanoma skin cancer. METHODS: In this new scheme, the unsupervised clustering based on deep metric learning is first conducted to make images with high similarity together and the corresponding model weights are utilized as teacher-model for the next stage. Second, benefit from the knowledge distillation, the attention transfer is adopted to make the classification model enable to learn the similarity features and information of categories simultaneously which improve the diagnosis accuracy than the common classification method. RESULTS: In validation sets, 8 categories were included, and 2443 samples were calculated. The highest accuracy of the new scheme is 0.7253, which is 5% points higher than the baseline (0.6794). Specifically, the F1-Score of three malignant lesions BCC (Basal cell carcinoma), SCC (Squamous cell carcinomas), and MEL (Melanoma) increase from 0.65 to 0.73, 0.28 to 0.37, and 0.54 to 0.58, respectively. In two test sets of HAN including 3844 samples and BCN including 6375 samples, the highest accuracies are 0.68 and 0.53 for HAM and BCN datasets, respectively, which are higher than the baseline (0.649 and 0.516). Additionally, F1 scores of BCC, SCC, MEL are 0.49, 0.2, 0.45 in HAM dataset and 0.6, 0.14, 0.55 in BCN dataset, respectively, which are also higher than F1 scores the results of baseline. CONCLUSIONS: This study demonstrates that the similarity clustering method enables to extract the related feature information to gather similar images together. Moreover, based on the attention transfer, the proposed classification framework can improve total accuracy and F1-score of skin lesion diagnosis.
In an offshore operational environment, complex loads such as the hook load, stand load and wind load play a crucial role in the structural strength and reliability of the offshore derrick. Previous studies have mainly focused on the effect of a specific load on the strength of the derrick by using commercial software. Therefore, the influencing mechanism of each complex load on the strength and reliability of the offshore derrick is urgently necessary to explore. Not only is the strength numerical model of the JJ315/45-K typical derrick established and conducted via APDL (ANSYS Parametric Design Language), but also the stress–strength reliability simulation is explored and plotted using Python code and APDL. Furthermore, the influence and contribution of each load to the strength and reliability is determined. With the increase in hook load, the positions of maximum reliability risk appear in section II-1. With the increase in stand load or back wind load, the positions of maximum reliability risk appear in the bottom section. In addition, with the decrease in the columns’ height, the stress proportion of the hook load decreases by 73.5%, the stress proportion of the stand load increases by 22.6%, and the stress proportion of the back wind load changes slightly. When the wind speed is less than 20 m/s, the hook load mainly affects the minimum reliability index of the derrick. Moreover, when the wind speed is more than 20 m/s, the back wind load mainly affects the minimum reliability index of the derrick. This study provides a thorough explanation of the strength distribution law and the reliability of derricks under complex loads.
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