Automatic transformation between water level meter measurement data and altitude on the large-scale physical model

2019 ◽  
Vol 70 ◽  
pp. 101638
Author(s):  
Hong Chen ◽  
Hongwu Tang ◽  
Limo Tang ◽  
Yanjun Wu
Keyword(s):  
Water Level ◽  
Physical Model ◽  
Large Scale ◽  
Measurement Data ◽  
Level Meter

Mobile Water Level Meter System

2012 ◽  
Vol 468-471 ◽  
pp. 1508-1511
Author(s):  
Guang Xiang Xu ◽  
Yan Yan Zhang ◽  
Wu Gao
Keyword(s):  
Water Level ◽  
Physical Model ◽  
Pressure Measurement ◽  
Arbitrary Point ◽  
Zero Point ◽  
Measurement Instruments ◽  
Mobile Water ◽  
Level Measurement ◽  
Closed Tube ◽  
Level Meter

By applying the principle of the closed tube, pressure measurement and ultrasonic water level measurement instruments, a kind of mobile and unfixed zero point water level meter system was introduced and designed in this paper to overcome the deficiency of its difficulty in measuring the arbitrary point water level by the currently fixed water level meters. The mobile water level meter system can measure arbitrary point water level precisely and rapidly in a certain range. Experiment testing has already shown the feasibility of the developed water level meter system with the characteristics of light and handy, easy fabrication and learning and can thus be widely used in the study of hydraulic model and physical model experiments.

Soil/Tire Interaction Analysis Using FEM and FVM

2005 ◽  
Vol 33 (1) ◽  
pp. 38-62 ◽  
Author(s):  
S. Oida ◽  
E. Seta ◽  
H. Heguri ◽  
K. Kato
Keyword(s):  
Large Scale ◽  
Interaction Analysis ◽  
Yield Criterion ◽  
Surrounding Medium ◽  
Flow Analysis ◽  
Measurement Data ◽  
Traction Force ◽  
Elastoplastic Material ◽  
The Road ◽  
Soil Flow

Abstract Vehicles, such as an agricultural tractor, construction vehicle, mobile machinery, and 4-wheel drive vehicle, are often operated on unpaved ground. In many cases, the ground is deformable; therefore, the deformation should be taken into consideration in order to assess the off-the-road performance of a tire. Recent progress in computational mechanics enabled us to simulate the large scale coupling problem, in which the deformation of tire structure and of surrounding medium can be interactively considered. Using this technology, hydroplaning phenomena and tire traction on snow have been predicted. In this paper, the simulation methodology of tire/soil coupling problems is developed for pneumatic tires of arbitrary tread patterns. The Finite Element Method (FEM) and the Finite Volume Method (FVM) are used for structural and for soil-flow analysis, respectively. The soil is modeled as an elastoplastic material with a specified yield criterion and a nonlinear elasticity. The material constants are referred to measurement data, so that the cone penetration resistance and the shear resistance are represented. Finally, the traction force of the tire in a cultivated field is predicted, and a good correlation with experiments is obtained.

Underwater high-precision ultrasonic water level measurement method for hydraulic physical model

2020 ◽  
Vol 28 (9) ◽  
pp. 2027-2034
Author(s):  
Yue-jie SHU ◽  
◽  
Jun WU ◽  
Yuan-hang ZHOU ◽  
Yu-feng MA ◽  
...  
Keyword(s):  
Water Level ◽  
Physical Model ◽  
High Precision ◽  
Measurement Method ◽  
Level Measurement

scholarly journals Inverse Infiltration Modeling of Dike Covers Made of Dredged Material Using PEST and AMALGAM

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 41
Author(s):  
Tim Jurisch ◽  
Stefan Cantré ◽  
Fokke Saathoff
Keyword(s):  
Large Scale ◽  
Measurement Data ◽  
Fine Grained ◽  
Dredged Materials ◽  
Measurement Results ◽  
Large Scale Field ◽  
Eigenvalue Ratio ◽  
Ill Posed ◽  
Materials Used ◽  
Installation Technology

A variety of studies recently proved the applicability of different dried, fine-grained dredged materials as replacement material for erosion-resistant sea dike covers. In Rostock, Germany, a large-scale field experiment was conducted, in which different dredged materials were tested with regard to installation technology, stability, turf development, infiltration, and erosion resistance. The infiltration experiments to study the development of a seepage line in the dike body showed unexpected measurement results. Due to the high complexity of the problem, standard geo-hydraulic models proved to be unable to analyze these results. Therefore, different methods of inverse infiltration modeling were applied, such as the parameter estimation tool (PEST) and the AMALGAM algorithm. In the paper, the two approaches are compared and discussed. A sensitivity analysis proved the presumption of a non-linear model behavior for the infiltration problem and the Eigenvalue ratio indicates that the dike infiltration is an ill-posed problem. Although this complicates the inverse modeling (e.g., termination in local minima), parameter sets close to an optimum were found with both the PEST and the AMALGAM algorithms. Together with the field measurement data, this information supports the rating of the effective material properties of the applied dredged materials used as dike cover material.

scholarly journals Analysis of Pore Water Pressure and Piping of Hydraulic Well

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 502
Author(s):  
Jinman Kim ◽  
Heuisoo Han ◽  
Yoonhwa Jin
Keyword(s):  
Numerical Analysis ◽  
Water Level ◽  
Pore Water ◽  
Large Scale ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Hydraulic Gradient ◽  
Water Levels ◽  
Seepage Velocity ◽  
Seepage Analysis

This paper shows the results of a field appliance study of the hydraulic well method to prevent embankment piping, which is proposed by the Japanese Matsuyama River National Highway Office. The large-scale embankment experiment and seepage analysis were conducted to examine the hydraulic well. The experimental procedure is focused on the pore water pressure. The water levels of the hydraulic well were compared with pore water pressure data, which were used to look over the seepage variations. Two different types of large-scale experiments were conducted according to the installation points of hydraulic wells. The seepage velocity results by the experiment were almost similar to those of the analyses. Further, the pore water pressure oriented from the water level variations in the hydraulic well showed similar patterns between the experiment and numerical analysis; however, deeper from the surface, the larger pore water pressure of the numerical analysis was calculated compared to the experimental values. In addition, the piping effect according to the water level and location of the hydraulic well was quantitatively examined for an embankment having a piping guide part. As a result of applying the hydraulic well to the point where piping occurred, the hydraulic well with a 1.0 m water level reduced the seepage velocity by up to 86%. This is because the difference in the water level between the riverside and the protected side is reduced, and it resulted in reducing the seepage pressure. As a result of the theoretical and numerical hydraulic gradient analysis according to the change in the water level of the hydraulic well, the hydraulic gradient decreased linearly according to the water level of the hydraulic well. From the results according to the location of the hydraulic well, installation of it at the point where piping occurred was found to be the most effective. A hydraulic well is a good device for preventing the piping of an embankment if it is installed at the piping point and the proper water level of the hydraulic well is applied.

scholarly journals Large-Scale Landslide Displacement Rate Prediction Based on Multi-Factor Support Vector Regression Machine

2021 ◽  
Vol 11 (4) ◽  
pp. 1381
Author(s):  
Xiuzhen Li ◽  
Shengwei Li
Keyword(s):  
Support Vector Regression ◽  
Water Level ◽  
Large Scale ◽  
Displacement Rate ◽  
Support Vector ◽  
Single Factor ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Depth Analysis ◽  
Three Factor

Forecasting the development of large-scale landslides is a contentious and complicated issue. In this study, we put forward the use of multi-factor support vector regression machines (SVRMs) for predicting the displacement rate of a large-scale landslide. The relative relationships between the main monitoring factors were analyzed based on the long-term monitoring data of the landslide and the grey correlation analysis theory. We found that the average correlation between landslide displacement and rainfall is 0.894, and the correlation between landslide displacement and reservoir water level is 0.338. Finally, based on an in-depth analysis of the basic characteristics, influencing factors, and development of landslides, three main factors (i.e., the displacement rate, reservoir water level, and rainfall) were selected to build single-factor, two-factor, and three-factor SVRM models. The key parameters of the models were determined using a grid-search method, and the models showed high accuracies. Moreover, the accuracy of the two-factor SVRM model (displacement rate and rainfall) is the highest with the smallest standard error (RMSE) of 0.00614; it is followed by the three-factor and single-factor SVRM models, the latter of which has the lowest prediction accuracy, with the largest RMSE of 0.01644.

A Streamflow and Water Level Forecasting Model for the Ganges, Brahmaputra, and Meghna Rivers with Requisite Simplicity

2018 ◽  
Vol 19 (1) ◽  
pp. 201-225 ◽  
Author(s):  
Wahid Palash ◽  
Yudan Jiang ◽  
Ali S. Akanda ◽  
David L. Small ◽  
Amin Nozari ◽  
...  
Keyword(s):  
Water Level ◽  
Lead Time ◽  
Large Scale ◽  
Predictive Ability ◽  
Large River ◽  
Modeling Framework ◽  
Forecasting Accuracy ◽  
Weather Model ◽  
And Performance ◽  
The Ganges

A forecasting lead time of 5–10 days is desired to increase the flood response and preparedness for large river basins. Large uncertainty in observed and forecasted rainfall appears to be a key bottleneck in providing reliable flood forecasting. Significant efforts continue to be devoted to developing mechanistic hydrological models and statistical and satellite-driven methods to increase the forecasting lead time without exploring the functional utility of these complicated methods. This paper examines the utility of a data-based modeling framework with requisite simplicity that identifies key variables and processes and develops ways to track their evolution and performance. Findings suggest that models with requisite simplicity—relying on flow persistence, aggregated upstream rainfall, and travel time—can provide reliable flood forecasts comparable to relatively more complicated methods for up to 10 days lead time for the Ganges, Brahmaputra, and upper Meghna (GBM) gauging locations inside Bangladesh. Forecasting accuracy improves further by including weather-model-generated forecasted rainfall into the forecasting scheme. The use of water level in the model provides equally good forecasting accuracy for these rivers. The findings of the study also suggest that large-scale rainfall patterns captured by the satellites or weather models and their “predictive ability” of future rainfall are useful in a data-driven model to obtain skillful flood forecasts up to 10 days for the GBM basins. Ease of operationalization and reliable forecasting accuracy of the proposed framework is of particular importance for large rivers, where access to upstream gauge-measured rainfall and flow data are limited, and detailed modeling approaches are operationally prohibitive and functionally ineffective.

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