scholarly journals Method to Realize the Tilt Monitoring and Instability Prediction of Hazardous Rock on Slopes

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zheng He ◽  
Mowen Xie ◽  
Zhengjun Huang ◽  
Guang Lu ◽  
Bo Yan ◽  
...  
Keyword(s):  
Tilt Angle ◽  
Failure Time ◽  
Prediction Method ◽  
Correlation Equation ◽  
Physical Model Test ◽  
Sensitive Material ◽  
Monitoring Method ◽  
Accelerated Evolution ◽  
Separation Degree

Hazardous rock refers to an unstable rock block that is cut by weak structural planes and gradually separates from the slope. Hazardous rock generally collapses rapidly, and at present, it is challenging to effectively identify the separation degree of the rock and accurately predict its sudden failure. In this study, focusing on a hazardous rock with tilt behavior, a microelectromechanical system (MEMS) acceleration sensor is used in combination with the calculation principle of the included angle of the space vector to establish a microtilt angle monitoring method. A physical model test is designed, in which a thermally sensitive material (with heat-sensitive strength) is adopted as the weak structural plane of the hazardous block, and the change in the tilt angle during the process of block instability is monitored at a sampling frequency of 1000 Hz. The test results show that the accelerated evolution of the tilt angle is a precursor to hazardous rock failure. In the rapid acceleration stage, the reciprocal of the tilt angle rate is approximately linear with time, and a correlation equation is obtained. Assuming that the change rate of the tilt angle is approximately infinite, the failure time of hazardous rock can be predicted using the correlation equation. In addition, the effectiveness of the instability prediction method based on microtilt angle monitoring is verified by analyzing the long-term monitoring data of hazardous rock.

Prediction of Long-Term Compression Strength for Quasi-Isotropic CFRP Laminates

2014 ◽  
Vol 1016 ◽  
pp. 119-124
Author(s):  
Jun Kang ◽  
Zhi Dong Guan ◽  
Zhun Liu ◽  
Xing Li ◽  
Jun Wu Mu ◽  
...  
Keyword(s):  
Composite Laminates ◽  
Failure Time ◽  
Prediction Method ◽  
Temperature Shift ◽  
Mechanical Analysis ◽  
Critical Parameters ◽  
Term Strength ◽  
Cfrp Laminates ◽  
Isotropic Composite

Long-term strength prediction method is developed based on three theories: accelerated testing methodology (ATM), strain invariant failure theory (SIFT) and progressive damage analysis (PDA). It can predict the strength and damage at a given failure time. Net resin 5228A was experimented by dynamic mechanical analysis and static tensile loading under various temperatures to determine the time-temperature shift factors and master curve of Young’s modulus. Unidirectional laminates of CCF300/5228A were tested under different temperatures to calculate the SIFT/ATM critical parameters. Long-term strength of quasi-isotropic composite laminates (QIL) was predicted. Good agreement between numerical results and experiments is observed, which demonstrates the applicability of this method.

Evaluation of Leakage Probability of Non-Asbestos Fiber Sheet Gasket at Elevated Temperature Based on Percolation Theory

2010 ◽  
Author(s):  
Masahiro Hagihara ◽  
Hirokazu Tsuji ◽  
Atsushi Yamaguchi
Keyword(s):  
High Temperature ◽  
Percolation Theory ◽  
Life Prediction ◽  
Prediction Method ◽  
Acoustic Tomography ◽  
Leakage Path ◽  
Temperature Environment ◽  
Fiber Sheet ◽  
Bolted Flange

A long-term life prediction method for a compressed fiber sheet gasket under a high-temperature environment is studied. Non-asbestos compressed fiber sheet gaskets are now being used as a substitute for asbestos in the bolted flange joint, for instance petrochemical factories. Consequently, there is a real need for a technology to predict the lifetime of non-asbestos compressed fiber sheet gaskets quantitatively. In this report, the facing surface of the gasket and flange is visualized with scanning acoustic tomography (SAT). Voids were observed on the facing surface of the gasket and increased with the increase in exposure time at high temperature. If a leakage path for inner fluids is created by the increasing number of voids, the leak occurs on the facing surface of the gasket. The probability of a leak due to voids and the lifetime of this gasket are predicted by applying the percolation theory, which describes the connectedness of clusters.

Long-Term Wind Power Prediction Based on Rough Set

2013 ◽  
Vol 329 ◽  
pp. 411-415 ◽  
Author(s):  
Shuang Gao ◽  
Lei Dong ◽  
Xiao Zhong Liao ◽  
Yang Gao
Keyword(s):  
Neural Network ◽  
Wind Power ◽  
Rough Set ◽  
Wind Farm ◽  
Rough Set Theory ◽  
Prediction Method ◽  
Key Factors ◽  
Power Prediction ◽  
Wind Power Prediction

In long-term wind power prediction, dealing with the relevant factors correctly is the key point to improve the prediction accuracy. This paper presents a prediction method with rough set analysis. The key factors that affect the wind power prediction are identified by rough set theory. The chaotic characteristics of wind speed time series are analyzed. The rough set neural network prediction model is built by adding the key factors as the additional inputs to the chaotic neural network model. Data of Fujin wind farm are used for this paper to verify the new method of long-term wind power prediction. The results show that rough set method is a useful tool in long-term prediction of wind power.

A Super-Long-Term Prediction Method of Earth Polar Motion Based on Spectrum Analysis

2021 ◽  
pp. 619-628
Author(s):  
Weitao Lu ◽  
Lue Chen ◽  
Zhijin Zhou ◽  
Songtao Han ◽  
Tianpeng Ren
Keyword(s):  
Spectrum Analysis ◽  
Polar Motion ◽  
Prediction Method ◽  
Term Prediction ◽  
Long Term Prediction

scholarly journals System load trend prediction method based on IF-EMD-LSTM

2019 ◽  
Vol 15 (8) ◽  
pp. 155014771986765 ◽  
Author(s):  
Jing Yu ◽  
Feng Ding ◽  
Chenghao Guo ◽  
Yabin Wang
Keyword(s):  
Information System ◽  
Short Term Memory ◽  
Prediction Method ◽  
Short Term ◽  
Trend Prediction ◽  
Term Memory ◽  
System Load ◽  
Mode Function ◽  
Abnormal Points

Accurately predicting the load change of the information system during operation has important guiding significance for ensuring that the system operation is not interrupted and resource scheduling is carried out in advance. For the information system monitoring time series data, this article proposes a load trend prediction method based on isolated forests-empirical modal decomposition-long-term (IF-EMD-LSTM). First, considering the problem of noise and abnormal points in the original data, the isolated forest algorithm is used to eliminate the abnormal points in the data. Second, in order to further improve the prediction accuracy, the empirical modal decomposition algorithm is used to decompose the input data into intrinsic mode function (IMF) components of different frequencies. Each intrinsic mode function (IMF) and residual is predicted using a separate long-term and short-term memory neural network, and the predicted values are reconstructed from each long-term and short-term memory model. Finally, experimental verification was carried out on Amazon’s public data set and compared with autoregressive integrated moving average and Prophet models. The experimental results show the superior performance of the proposed IF-EMD-LSTM prediction model in information system load trend prediction.

Unexpected conservation and global transmission of agrobacterial virulence plasmids

Science ◽  
2020 ◽  
Vol 368 (6495) ◽  
pp. eaba5256 ◽  
Author(s):  
Alexandra J. Weisberg ◽  
Edward W. Davis ◽  
Javier Tabima ◽  
Michael S. Belcher ◽  
Marilyn Miller ◽  
...  
Keyword(s):  
Host Species ◽  
Evolutionary History ◽  
Virulence Plasmids ◽  
Ri Plasmid ◽  
Accelerated Evolution ◽  
Transfer Genes ◽  
Global Spread

The accelerated evolution and spread of pathogens are threats to host species. Agrobacteria require an oncogenic Ti or Ri plasmid to transfer genes into plants and cause disease. We developed a strategy to characterize virulence plasmids and applied it to analyze hundreds of strains collected between 1927 and 2017, on six continents and from more than 50 host species. In consideration of prior evidence for prolific recombination, it was surprising that oncogenic plasmids are descended from a few conserved lineages. Characterization of a hierarchy of features that promote or constrain plasticity allowed inference of the evolutionary history across the plasmid lineages. We uncovered epidemiological patterns that highlight the importance of plasmid transmission in pathogen diversification as well as in long-term persistence and the global spread of disease.

Sign in / Sign up

Export Citation Format

Share Document