With the development of society, the demand for mineral resources is gradually increasing, and the current situation of decreasing total resources dictates the inevitable interaction between open-pit combing underground extraction (OPUG) in time and space. In this research, we took the Anjialing coal mine in Shanxi Province of China as a case study, and tested the physical and mechanical properties of coal rocks in the laboratory. The similarity criterion was used to build a similar experimental model for the deformation evolution of the slope of the open-pit mine section; the digital scattering method was used to test the influence of the underground mining process parameters on the deformation evolution of the open-pit slope. The results showed that there was an obvious distribution of “three zones” above the mining goaf, namely, a collapse zone, fracture zone, and slow subsidence zone. When the mining face was continuously advanced towards the bottom of the open pit, the supporting stress of the mining face transferred to the side of the open-pit slope. Additionally, large displacement and stress concentration were observed on the slope near the stoping line, which caused the slope body to move along the uppermost part of the slope first, and thereafter along the lower part. Various techniques for slope stability control are discussed, including the optimization of spatial and temporal relationships between open-pit and underground mining, the optimization of mining plans, and the use of monitoring and early warning systems. The results can provide a guide for slope stability control of similar open-pit mines in the process of mining coal resources.
In order to study the influence range of vibroflotation device (VD) on the formation during vibroflotation pile densification, based on the physical model test of vibroflotation pile, the relationship curve of the main key construction control parameters during vibroflotation densification was established. The analysis showed that: under the test conditions, the main influence range of the VD on the surrounding soil pressure and acceleration was about 1r in the horizontal direction (r = VD radius), and about ± 2r in the vertical direction. The influence on pore water pressure in surrounding soil was about 2r in horizontal direction and ± 3r in vertical direction. In the process of densification, the pore pressure concentration in the soil around the VD had a certain delay compared with the increase of current intensity, which was manifested as the delayed accumulation effect of pore water pressure in the vibroflotation densification. The peak acceleration was 1r ahead of the peak current intensity, which showed the effect of vibroflotation pre-densification. The research conclusions could provide useful reference for the design and construction of vibroflotation piles.
The association between acute-phase blood pressure (BP) and outcomes in watershed infarction (WI) remains unclear. This study aimed to investigate the relationships between BP and BP changes with neurological functional decline (NFD) and functional outcome at 90 days. We included patients with WI from a prospective, observational, single-center study (Effect of Cardiac Function on Short-Term Functional Prognosis in Patients with Acute Ischemic Stroke, SPARK). We recorded data of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on the day of admission, as well as on day 2 and day 3. In logistic regression models, both the baseline BP and BP changes were assessed. Among the 207 patients with WI, 147 (71%) had concurrent cortical and internal infarcts. After adjusting for relevant factors, higher baseline SBP (OR:1.17; 95% CI:1.01-1.37) and DBP (OR:1.04; 95% CI:1.01-1.09) were associated with an increased risk of NFD. However, the restricted cubic spline (RCS) curve indicated that this association was statistically significant only when SBP was >180 mmHg or DBP was >100 mmHg. Additionally, an elevation in DBP of ≥4 mmHg on day 3 was associated with a reduced risk (OR:0.28; 95% CI: 0.08-0.97), whereas an elevation of DBP ≥10 mmHg was not. Neither baseline BP nor BP changes were associated with functional outcome. In patients with WI, the risk of NFD increases when baseline SBP >180 mmHg or DBP >100 mmHg. However, raising DBP by ≥4 mmHg but <10 mmHg on day 3 is associated with a reduced risk of NFD. BP may not be associated with functional outcome. https://www.chictr.org.cn/, ChiCTR2300067696.
Abstract The methodology of artificial intelligence (AI), particularly artificial neural network (ANN), would be in favor of nuclear energy system development. These ANN simulators may provide more efficient means than the traditional nuclear design codes, especially for the design of the key parameters, such as core geometry and layout, material composition. In this paper, a neutronics calculation code SARAX and the corresponding multilayer perceptron (MLP) surrogate model were used as simulators for core parameters optimization of a reference lead based fast reactor. The pellet radius, enrichments and active height are the interested core parameters, and core burnup and power distribution are the target characteristics in the study. The training of structure and weight parameters in MLP network are based on about 5000 calculations of SARAX code. Test results of neural network show a good agreement between MLP surrogate model and SARAX code. The feasibility of the MLP surrogate model to be used in core parameters optimization was also discussed. Results showed that, the core surrogate model based on MLP could be quickly constructed and regulated, and be a more efficient simulators in a innovate reactor optimization. The above work is completed in Sinan Platform, a multidisciplinary intelligent design platform developed by China Nuclear Power Technology Research Institute Co. Ltd.
Nuclear power plants have a large number of safety or non-safety related mechanical equipment. Knowing when and where these equipment failure or near failure is one of the key problems in nuclear safety and nuclear health management and maintenance, that is to predict the remaining useful life for specific equipment. A prediction model labeled as Weibull time to event recurrent neural network (WTTE-RNN) is proposed to effectively obtain the prediction and estimation of time to event (such as customer churn, patient survival, machine failure). The model is effective even under some missing-spots in the training data (i.e. deleted data). The purpose of this research is to study the main challenges faced by the application of WTTE-RNN to the nuclear equipment, and identify feasible optimization directions. The results may lay a foundation for the WTTE-RNN application to the remaining useful life.
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