“…Figure 1a shows the Yellow River mainstream, China. The study area is the Shisifenzi bend (111 • 2 53 E, 40 • 17 39 N) in the Inner Mongolia reach of the Yellow River, which is over a river length of 820 km [45], as shown in Figure 1b. This bend (Figure 1c) is a typical funnel bend characterized by a wide entrance and a narrow exit [46].…”
Section: Study Area and Monitoring Devicementioning
Acquisition of continuous drift ice characteristic parameters such as ice size, shape, concentration, and drift velocity are of great importance for understanding river freezing and thawing processes. This study acquired hourly oblique images captured by a shore-based camera in the winter of 2021–2022 on the Yellow River, China. The pixel point scale method for correcting oblique images is provided. The 61 lines were measured at the calibration site and the absolute error between the measured value and the calculated value was in the range of 0.009–0.850 m, with a mean error of 0.236 m. After the correction of oblique images, the true equivalent diameter of drift ice during the freezing period ranged from 0.52–13.10 m with a mean size of 3.36 m, which was larger than that of 2.30 m during the thawing period which ranged from 0.20–12.54 m. It was found that the size of drift ice increased with time during the freezing period and decreased with time during the thawing period. The fractal dimension and roundness were used to represent drift ice shape. The fractal dimension ranged from 1.0–1.3 and the roundness ranged from 0.1–1.0. A Gaussian distribution was used to estimate drift ice size and shape distributions. There is a nonlinear relationship between ice concentration and drift velocity, which can be well expressed by the logistic function. In the future, drift ice parameters for more years and hydrometeorological data for the same time need to be accumulated, which helps to analyze the freezing and thawing patterns of river ice.
“…Figure 1a shows the Yellow River mainstream, China. The study area is the Shisifenzi bend (111 • 2 53 E, 40 • 17 39 N) in the Inner Mongolia reach of the Yellow River, which is over a river length of 820 km [45], as shown in Figure 1b. This bend (Figure 1c) is a typical funnel bend characterized by a wide entrance and a narrow exit [46].…”
Section: Study Area and Monitoring Devicementioning
Acquisition of continuous drift ice characteristic parameters such as ice size, shape, concentration, and drift velocity are of great importance for understanding river freezing and thawing processes. This study acquired hourly oblique images captured by a shore-based camera in the winter of 2021–2022 on the Yellow River, China. The pixel point scale method for correcting oblique images is provided. The 61 lines were measured at the calibration site and the absolute error between the measured value and the calculated value was in the range of 0.009–0.850 m, with a mean error of 0.236 m. After the correction of oblique images, the true equivalent diameter of drift ice during the freezing period ranged from 0.52–13.10 m with a mean size of 3.36 m, which was larger than that of 2.30 m during the thawing period which ranged from 0.20–12.54 m. It was found that the size of drift ice increased with time during the freezing period and decreased with time during the thawing period. The fractal dimension and roundness were used to represent drift ice shape. The fractal dimension ranged from 1.0–1.3 and the roundness ranged from 0.1–1.0. A Gaussian distribution was used to estimate drift ice size and shape distributions. There is a nonlinear relationship between ice concentration and drift velocity, which can be well expressed by the logistic function. In the future, drift ice parameters for more years and hydrometeorological data for the same time need to be accumulated, which helps to analyze the freezing and thawing patterns of river ice.
Introduction. The article deals with a problem relevant to the territory of our country – the calculation of the bearing capacity of ice crossings and winter roads. This problem is becoming more and more urgent in connection with the development of the northern territories, an increase in the carrying capacity of road transport and the volume of cargo traffic. At the same time, the construction of permanent roads and bridge crossings requires very large capital expenditures, which are not yet available for the Russian Federation.Methods and materials. A critical analysis of methods for determining by calculation the bearing capacity of ice cover at crossings (the maximum permissible load on the axle of a single car or road train) was carried out.The recommendations of normative and methodological documents on this issue are considered. The presented analysis of domestic and foreign publications made it possible to evaluate mathematical models of different levels of complexity and detail, with a different set of factors influencing the final result.Results. As a result of the research, a summary table, which contains formulas for calculating the bearing capacity of the ice cover, the parameters that are taken into account in these formulas, as well as the values of the bearing capacity calculated using these formulas for two temperatures: 0 °C and minus 20 °C has been compiled.Conclusions. According to the results of the analysis, it can be seen that the largest number of parameters is taken into account in M.M. Kazansky-R.A. Shulman; Q. Wang; ODM 218.4.030-2016 Methodological recommendations for assessing the carrying capacity of ice crossings’ dependencies. At the same time, the value of the bearing capacity, calculated according to the 11th formulas, varies by 2-3 or more times presented. Consequently, the presented mathematical models for predicting the carrying capacity of ice crossings require experimental verification on real objects by dragging the control cargo (with some refinement of this method).
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