Acceleration Characteristics of a Rock Slide Using the Particle Image Velocimetry Technique

Li, Le; Zhao, Cong; Huang, Runqiu; Guo, Fan

doi:10.1155/2016/2650871

Cited by 2 publications

(1 citation statement)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In actual geological engineering, such as large-scale rock landslides that occur during rainfall, which instabilities were mainly triggered by the strength degradation of the essential anti-sliding structure under water–rock interaction 28 . For such conditions, the method of applying a jack with progressive loading to facilitate slope failure cannot consider the degradation effect of water on the rock 29 , 30 (Fig. 1 a).…”

Section: Introductionmentioning

confidence: 99%

Experimental study on the reasonable proportions of rock-like materials for water-induced strength degradation in rock slope model test

Cui

Xue

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Water-induced strength deterioration of rock mass is a crucial factor for rock slope instability. To better show the degradation process of rock slope water–rock interaction, we used bentonite as a water-sensitive regulator to build a new rock-like material that matches the features of water-induced strength degradation based on the cement-gypsum bonded materials. Twenty-five schemes of the material mixture proportion were designed using the orthogonal design method considering four factors with five variable levels, and a variety of experiments were conducted to obtain physico-mechanical parameters. In addition, one group of rock-like material proportion was selected and applied to the large-scale physical model test. The experiment results reveal that: (1) The failure mode of this rock-like material is highly similar to that of natural rock masses, and the physico-mechanical parameters vary over a wide range; (2) The bentonite content has a significant influence on the density, elastic modulus, and tensile strength of rock-like materials; (3) It is feasible to obtain the regression equation based on the linear regression analysis to determine the proportion of rock-like material; (4) Through application, the new rock-like material can effectively simulate or reveal the startup mechanism and instability characteristics of rock slopes under water-induced degradation. These studies can serve as a guide for the fabrication of rock-like material in the other model tests.

show abstract

Section: Introductionmentioning

confidence: 99%

Experimental study on the reasonable proportions of rock-like materials for water-induced strength degradation in rock slope model test

Cui

Xue

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

Estimating Acceleration from a Single Uniform Linear Motion-Blurred Image using Homomorphic Mapping and Machine Learning

Cortés-Osorio,

Gómez-Mendoza,

Riaño-Rojas

2024

Ing.

View full text Add to dashboard Cite

Context: Vision-based measurement (VBM) systems are becoming popular as an affordable and suitable alternative for scientific and engineering applications. When cameras are used as instruments, motion blur usually emerges as a recurrent and undesirable image degradation, which in fact contains kinematic information that is usually dismissed. Method: This paper introduces an alternative approach to measure relative acceleration from a real invariant uniformly accelerated linear motion-blurred image. This is done by using homomorphic mapping to extract the characteristic Point Spread Function (PSF) of the blurred image, as well as machine learning regression. A total of 125 uniformly accelerated motion-blurred pictures were taken in a light- and distance-controlled environment, at five different accelerations ranging between 0,64 and 2,4 m/s2. This study evaluated 19 variants such as tree ensembles, Gaussian processes (GPR), and linear, support vector machine (SVM), and tree regression. Results: The best RMSE result corresponds to GPR (Matern 5/2), with 0,2547 m/s2 and a prediction speed of 530 observations per second (obs/s). Additionally, some novel deep learning methods were used to obtain the best RMSE value (0,4639 m/s2 for Inception ResNet v2, with a prediction speed of 11 obs/s. Conclusions: The proposed method (homomorphic mapping and machine learning) is a valid alternative for calculating acceleration from invariant motion blur in real-time applications when additive noise is not dominant, even surpassing the deep learning techniques evaluated.

show abstract

Acceleration Characteristics of a Rock Slide Using the Particle Image Velocimetry Technique

Cited by 2 publications

References 29 publications

Experimental study on the reasonable proportions of rock-like materials for water-induced strength degradation in rock slope model test

Experimental study on the reasonable proportions of rock-like materials for water-induced strength degradation in rock slope model test

Estimating Acceleration from a Single Uniform Linear Motion-Blurred Image using Homomorphic Mapping and Machine Learning

Contact Info

Product

Resources

About