scholarly journals The Tamunier gold deposit in the Northern Ural: Physicochemical formative conditions, ore and fluid sources, genesis

LITOSFERA ◽  
2019 ◽  
pp. 139-147
Author(s):  
D. A. Zamiatina ◽  
V. V. Murzin
Keyword(s):  
Genetic Model ◽  
Isotope Geochemistry ◽  
Geological Structure ◽  
Sulphide Ores ◽  
Formation Mode ◽  
Proposed Model ◽  
Volcano Plutonic Belt ◽  
Plutonic Belt ◽  
Fluid Formation

Research subject.This research study was aimed at investigating metasomatic minerals and ores in the Tamunier Deposit, which is located in the Northern Urals, at the Eastern side of the Tagil megazone within the Auerbach volcano-plutonic belt.Materials and methods.Well core samples were investigated using a complex of research methods, including optical and electron microscopy, X-ray spectral microanalysis, mineral geothermometry, thermobarogeochemistry (microthermometry, gas chromatography, determination of the salt composition of fluid inclusions in minerals) and isotope geochemistry (isotopes C, O, S, Sr, Pb).Results.A genetic model describing the formation of the Tamunier deposit was developed using the data obtained on its geological structure, mineral composition of metasomatites and ores, fluid formation mode, sources of ore matter and ore-bearing fluid. In the proposed model, the magmatogenic sodium chloride fluid carrying ore components and S is separated from the Auerbach complex at the depth of intrusion. Penetrating to the surface, this fluid interacts with the rocks of volcanic-sedimentary strata, thereby extracting a number of components, including CO2, S and Sr.Conclusion.Despite the presence of sulphide mineralization of hydrothermal-sedimentary genesis in the volcanogenic-sedimentary rock mass, the data obtained has allowed us to refer the gold-sulphide ores under study to magmatogenic-hydrothermal formations. The estimated P-T conditions (t= 100–370ºС andP= 0.4–0.6 kbar) and the shallow depth of the Tamunier field have shown its correspondence to the sub-epithermal level in the model of the porphyry-epithermal ore-magmatic system.

Stable isotope geochemistry of travertines from northern Urumieh-Dokhtar volcano-plutonic belt, Iran

2017 ◽  
Vol 34 (3) ◽  
pp. 869-881
Author(s):  
Alireza Zarasvandi ◽  
Reihaneh Roshanak ◽  
Reinhard Gratzer ◽  
Houshang Pourkaseb ◽  
Farid Moore
Keyword(s):  
Stable Isotope ◽  
Isotope Geochemistry ◽  
Stable Isotope Geochemistry ◽  
Volcano Plutonic Belt ◽  
Plutonic Belt

Modeling of Dynamic Loads on the Polished Rod of Pumping Unit in Case of Mulfunction of Rod Pump Operating

2014 ◽  
Vol 10 ◽  
pp. 95-101
Author(s):  
A.S. Topolnikov
Keyword(s):  
Multiphase Flow ◽  
Satisfactory Agreement ◽  
Model Simulation ◽  
Theoretical Modeling ◽  
Dynamic Loads ◽  
Plunger Pump ◽  
Proposed Model ◽  
Pumping Unit ◽  
Polished Rod

The paper presents the results of theoretical modeling of joined movement of pump rods and plunger pump and multiphase flow in a well for determination of dynamic loads on the polished rod of pumping unit. The specificity of the proposed model is the possibility of taking into account for complications in rod pump operating, such as leakage in valve steam, presence of gas and emulsion, incorrect fitting of plunger inside the cylinder pump. The satisfactory agreement of results of the model simulation with filed measurements are obtained.

scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

scholarly journals Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 930
Author(s):  
Fahimeh Hadavimoghaddam ◽  
Mehdi Ostadhassan ◽  
Ehsan Heidaryan ◽  
Mohammad Ali Sadri ◽  
Inna Chapanova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Viscosity Data ◽  
Oil Viscosity ◽  
Pvt Data ◽  
Proposed Model ◽  
Wide Range ◽  
Engineering Problems ◽  
Functional Forms ◽  
Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

scholarly journals The coalescent process in models with selection, recombination and geographic subdivision

1991 ◽  
Vol 57 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Norman Kaplan ◽  
Richard R. Hudson ◽  
Masaru Iizuka
Keyword(s):  
Genetic Variation ◽  
Population Genetic ◽  
Genetic Model ◽  
Sequence Data ◽  
Balancing Selection ◽  
Similar Model ◽  
Proposed Model ◽  
Coalescent Approach ◽  
Neutral Mutations ◽  
Better Than

SummaryA population genetic model with a single locus at which balancing selection acts and many linked loci at which neutral mutations can occur is analysed using the coalescent approach. The model incorporates geographic subdivision with migration, as well as mutation, recombination, and genetic drift of neutral variation. It is found that geographic subdivision can affect genetic variation even with high rates of migration, providing that selection is strong enough to maintain different allele frequencies at the selected locus. Published sequence data from the alcohol dehydrogenase locus of Drosophila melanogaster are found to fit the proposed model slightly better than a similar model without subdivision.

scholarly journals Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Proceedings ◽  
2020 ◽  
Vol 33 (1) ◽  
pp. 30
Author(s):  
Masrour Makaremi ◽  
Camille Lacaule ◽  
Ali Mohammad-Djafari
Keyword(s):  
Cross Validation ◽  
Cervical Vertebra ◽  
Artificial Intelligent ◽  
X Ray ◽  
Treatment Timing ◽  
Proposed Model ◽  
Clustering And Classification ◽  
The Right ◽  
Biological Image

Many environmental and genetic conditions may modify jaws growth. In orthodontics, the right treatment timing is crucial. This timing is a function of the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM is important. In orthodontics, the lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features to do it. Nowadays, Machine Learning (ML) and Artificial Intelligent (AI) tools are used for many medical and biological image processing, clustering and classification. This paper reports on the development of a Deep Learning (DL) method to determine directly from the images the degree of maturation of CVM classified in six degrees. Using 300 such images for training and 200 for evaluating and 100 for testing, we could obtain a 90% accuracy. The proposed model and method are validated by cross validation. The implemented software is ready for use by orthodontists.

Analytical Solution of Hydrostatic Pocket Tilting

2016 ◽  
Vol 821 ◽  
pp. 113-119 ◽  
Author(s):  
Eduard Stach ◽  
Jiří Falta ◽  
Matěj Sulitka
Keyword(s):  
Computational Models ◽  
Load Capacity ◽  
Navier Stokes ◽  
Navier Stokes Equation ◽  
Detailed Model ◽  
Limit Values ◽  
Inertia Effects ◽  
Proposed Model ◽  
Machine Tool Structure

Tilting (parallelism error) of guiding surfaces may cause reduction of load capacity of hydrostatic (HS) guideways and bearings in machine tools (MT). Using coupled finite element (FE) computational models of MT structures, it is nowadays possible to determine the extent of guiding surfaces deformation caused by thermal effects, gravitational force, cutting forces and inertia effects. Assessment of maximum allowable tilt has so far been based merely on experience. The paper presents a detailed model developed for description of the effect of HS bearing tilt on the load capacity characteristics of HS guideways. The model allows an evaluation of the tilt influence on the change of the characteristics as well as determination of the limit values of allowable tilt in interaction with compliant machine tool structure. The proposed model is based on the model of flow over the land of the HS pocket under extended Navier-Stokes equation. The model is verified using an experimental test rig.

scholarly journals A holistic approach for the optimization of offshore wind farm layouts considering cable layouts

2019 ◽  
Vol 122 ◽  
pp. 04005
Author(s):  
Ilayda Ulku ◽  
Cigdem Alabas-Uslu
Keyword(s):  
Total Energy ◽  
Wind Farm ◽  
Holistic Approach ◽  
Offshore Wind ◽  
Total Power ◽  
Holistic Model ◽  
Electrical Cable ◽  
Proposed Model ◽  
Wake Effects

A wind farm, mainly, is composed of a set of turbines, one or more transmitters and a set of electrical cable connections between turbines and transmitters. Determination of turbine locations within the farm to maximize total power generation is called turbine location (TL) problem. Relative turbine positions affect the amount of overall energy because of wake effects. Determination of cable connections among turbines and transmitters to collect produced energy by turbines at transmitters is called cable layout (CL) problem. While TL problem is directly effective on the total energy production in the farm, CL problem indirectly affects the total energy due to the power losses. In the literature, TL and CL problems are solved sequentially where the layout found by solving of TL is used as an input of CL problem. To minimize wake effects in TL problem, distances between turbine pairs should be increased, however, as the distances are increased the cable cost increases in CL problem. A new mathematical model is developed to deal with simultaneously solving of TL and CL problems. A set of test instances are used to show the performance of the proposed model. The experiments show the practical use of the proposed holistic model.

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