scholarly journals Assessment of Water Measurements in an Irrigation Canal System Based on Experimental Data and the CFD Model

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3102
Author(s):  
Hu Xu ◽  
Zhenhua Wang ◽  
Wenhao Li ◽  
Qiuliang Wang
Keyword(s):  
Water Depth ◽  
Average Error ◽  
Irrigation Canal ◽  
Hydrodynamic Models ◽  
Monitoring Point ◽  
Hydraulic Test ◽  
Canal Systems ◽  
Important Means ◽  
Modified Formula ◽  
Selection Of

Due to their convenience, water measuring structures have become an important means of measuring water in irrigation canal systems However, relevant research on upstream and downstream water-depth monitoring point locations is scarce. Our study aims to determine the functional relationship between the locations of the water-depth monitoring points and the opening width of the sluice. We established 14 trunk-channel and branch-channel hydrodynamic models. The locations of the water-depth monitoring points for the upstream and downstream reaches and their hydraulic characteristics were assessed using a numerical simulation and hydraulic test. The results showed that the locations of the upstream and downstream water-depth monitoring points were, respectively, 16.26 and 15.51 times the width of the sluice. The average error between the calculated flow rate and the simulated value was 14.37%; the average error between the flow rates calculated by the modified and the simulated values was 3.36%. To further verify the accuracy of the modified discharge calculation formula, by comparing the measured values, we reduced the average error of the modified formula by 19.29% compared with the standard formula. This research provides new insights into optimizing water measurements in irrigation canal systems. The results provide an engineering basis for the site selection of water-depth monitoring points that is suitable to be widely applied in the field.

Utilizing Data-Driven Models to Predict Brittleness in Tuscaloosa Marine Shale: A Machine Learning Approach

2021 ◽  
Author(s):  
Jamal Ahmadov
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Brittleness Index ◽  
Estimation Methods ◽  
Gradient Boosting ◽  
Average Error ◽  
Support Vector ◽  
Marine Shale ◽  
Effective Manner ◽  
Selection Of

Abstract The Tuscaloosa Marine Shale (TMS) formation is a clay- and liquid-rich emerging shale play across central Louisiana and southwest Mississippi with recoverable resources of 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas. The formation poses numerous challenges due to its high average clay content (50 wt%) and rapidly changing mineralogy, making the selection of fracturing candidates a difficult task. While brittleness plays an important role in screening potential intervals for hydraulic fracturing, typical brittleness estimation methods require the use of geomechanical and mineralogical properties from costly laboratory tests. Machine Learning (ML) can be employed to generate synthetic brittleness logs and therefore, may serve as an inexpensive and fast alternative to the current techniques. In this paper, we propose the use of machine learning to predict the brittleness index of Tuscaloosa Marine Shale from conventional well logs. We trained ML models on a dataset containing conventional and brittleness index logs from 8 wells. The latter were estimated either from geomechanical logs or log-derived mineralogy. Moreover, to ensure mechanical data reliability, dynamic-to-static conversion ratios were applied to Young's modulus and Poisson's ratio. The predictor features included neutron porosity, density and compressional slowness logs to account for the petrophysical and mineralogical character of TMS. The brittleness index was predicted using algorithms such as Linear, Ridge and Lasso Regression, K-Nearest Neighbors, Support Vector Machine (SVM), Decision Tree, Random Forest, AdaBoost and Gradient Boosting. Models were shortlisted based on the Root Mean Square Error (RMSE) value and fine-tuned using the Grid Search method with a specific set of hyperparameters for each model. Overall, Gradient Boosting and Random Forest outperformed other algorithms and showed an average error reduction of 5 %, a normalized RMSE of 0.06 and a R-squared value of 0.89. The Gradient Boosting was chosen to evaluate the test set and successfully predicted the brittleness index with a normalized RMSE of 0.07 and R-squared value of 0.83. This paper presents the practical use of machine learning to evaluate brittleness in a cost and time effective manner and can further provide valuable insights into the optimization of completion in TMS. The proposed ML model can be used as a tool for initial screening of fracturing candidates and selection of fracturing intervals in other clay-rich and heterogeneous shale formations.

scholarly journals Dependences Of Reservoir Oil Properties On Surface Oil

2020 ◽  
Author(s):  
Sudad H Al-Obaidi ◽  
Galkin AP
Keyword(s):  
Hydrodynamic Models ◽  
Reservoir Properties ◽  
High Quality ◽  
Data Dependencies ◽  
Models Of Development ◽  
Production Wells ◽  
Exploration And Production ◽  
High Degree ◽  
Selection Of

Knowledge of the properties of reservoir oil is necessary when calculating reserves, creating projects development, creating hydrodynamic models of development objects. Reservoir oil properties are determined by downhole samples taken, as usual, from exploration and production wells. In some cases, it is impossible to create conditions for the selection of high-quality downhole samples at exploration and production wells. In such cases, we must use samples of surface oil to obtain information about the reservoir properties of this oil. In this work and as a result of the analysis of the accumulated data, dependencies with a high degree of correlation were obtained, which make it possible to quickly assess the expected parameters of reservoir oil, having only the density of surface oil.

scholarly journals Theoretical justification of the possibility of selection perspective individuals in variety populations of self-pollinators on the example of soybean

2021 ◽  
Vol 186 (2) ◽  
pp. 31-40
Author(s):  
V.M. Lukomets ◽  
◽  
S.V. Zelentsov ◽  
E.V. Moshnenko ◽  
◽  
...  
Keyword(s):  
F1 Hybrids ◽  
Individual Selection ◽  
Breeding Methods ◽  
Morphometric Traits ◽  
Phenotypic Differences ◽  
Soybean Cultivars ◽  
Oil Crops ◽  
Experimental Base ◽  
Modified Formula ◽  
Selection Of

Breeding practice shows that soybean cultivars developed by synthetic breeding methods are submitted for the state variety testing in the F10–F11 generation. But the newly bred cultivars are not completely homozygous. The studies were related to the determination of the frequencies of formation of atypical and suitable for selection promising individuals in soybean cultivars developed by synthetic breeding methods. The studies were carried out in 2019–2020 at the central experimental base of V.S. Pustovoit All-Russian Research Institute of Oil Crops, Krasnodar. In the experiments, we used cultivars of our own breeding: Selena, Puma, Vita, Irbis, Bars, Barguzin and Sayana with a total age of 11–15 years from the year F1 hybrids were obtained. To confirm the practical possibility of isolating individuals differing from the phenotypic varietal norm in varietal populations, a complete examination of the crops of all studied soybean cultivars was carried out. In the fields of all cultivars, individuals were identified that differed from the varietal norm phenotypically. Mostly, the isolated individuals were distinguished by an increased plant height, a more powerful habit, an increased number of beans per plant, and resistance to lodging. The facts of the detection of atypical individuals with improved morphological traits in soybean cultivars of different ages confirm the possibility of individual selection of plants in varietal populations based on morphometric traits. The statistical dynamics of a decrease in heterozygous individuals in increasing generations in a hybrid self-pollinating population in terms of the number of paired genes, by which the parental forms can hypothetically differ, were calculated using the modified formula of S. Borojević (1984). It was found that the frequency of formation of phenotypically different individuals in varietal populations of soybeans depends on the total age of the cultivar. The frequency of the formation of morphologically different individuals decreases with an increase in the number of generations of the cultivar. Individual selection of individuals with positive phenotypic differences from the varietal norm can be recommended as an additional source of promising and practically homozygous starting material for accelerated analytical breeding of soybean.

scholarly journals Framework for Offline Flood Inundation Forecasts for Two-Dimensional Hydrodynamic Models

Geosciences ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 346 ◽  
Author(s):  
Punit Bhola ◽  
Jorge Leandro ◽  
Markus Disse
Keyword(s):  
Real Time ◽  
Warning System ◽  
Flood Inundation ◽  
Hydrological Models ◽  
Hydrodynamic Models ◽  
Database Queries ◽  
Inundation Maps ◽  
Online Maps ◽  
The City ◽  
Selection Of

The paper presents a new methodology for hydrodynamic-based flood forecast that focuses on scenario generation and database queries to select appropriate flood inundation maps in real-time. In operational flood forecasting, only discharges are forecasted at specific gauges using hydrological models. Hydrodynamic models, which are required to produce inundation maps, are computationally expensive, hence not feasible for real-time inundation forecasting. In this study, we have used a substantial number of pre-calculated inundation maps that are stored in a database and a methodology to extract the most likely maps in real-time. The method uses real-time discharge forecast at upstream gauge as an input and compares it with the pre-recorded scenarios. The results show satisfactory agreements between offline inundation maps that are retrieved from a pre-recorded database and online maps, which are hindcasted using historical events. Furthermore, this allows an efficient early warning system, thanks to the fast run-time of the proposed offline selection of inundation maps. The framework is validated in the city of Kulmbach in Germany.

The Purpose of the Lex Calpurnia de repetundis

1987 ◽  
Vol 77 ◽  
pp. 1-12 ◽  
Author(s):  
J. S. Richardson
Keyword(s):  
Roman Republic ◽  
Standard Procedure ◽  
Second Century ◽  
Criminal Cases ◽  
History Of ◽  
Important Means ◽  
Administrative History ◽  
Selection Of

In 149 B.C. the tribune L. Calpurnius Piso proposed a law which was to have momentous consequences for the legal, political and administrative history of the Roman republic. It was his lex de rebus repetundis which first established the practice of trial before a quaestio perpetua, a jury, drawn from a panel of jurors who had always to be available, which became the standard procedure for criminal cases in the late republic. For over fifty years, from the first tribunate of C. Gracchus in 123 to the passing of the Lex Aurelia in 70, such courts were to provide a political storm-centre as various political figures attempted for their own ends to alter the criteria for the selection of the iudices who manned the juries. Moreover, from the late second century B.C. down to at least the second century A.D., the process de repetundis formed the most important means that was available to Rome's provincial subjects of bringing an action against a provincial governor for maladministration.

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