New machinery produced by the Ya. M. Sverdlov Ural hydraulic equipment factory

1971 ◽  
Vol 7 (8) ◽  
pp. 657-659
Author(s):  
B. A. Vakhrameev
Keyword(s):  
Hydraulic Equipment ◽  
Equipment Factory

scholarly journals A Study of Moist Air Condensation Characteristics in a Transonic Flow System

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 4052
Author(s):  
Jie Wang ◽  
Hongfang Gu
Keyword(s):  
Mach Number ◽  
Relative Humidity ◽  
Transonic Flow ◽  
Flow System ◽  
Plane Surface ◽  
Droplet Growth ◽  
Moist Air ◽  
Dry Air ◽  
Hydraulic Equipment ◽  
Non Equilibrium

When water vapor in moist air reaches supersaturation in a transonic flow system, non-equilibrium condensation forms a large number of droplets which may adversely affect the operation of some thermal-hydraulic equipment. For a better understanding of this non-equilibrium condensing phenomenon, a numerical model is applied to analyze moist air condensation in a transonic flow system by using the theory of nucleation and droplet growth. The Benson model is adopted to correct the liquid-plane surface tension equation for realistic results. The results show that the distributions of pressure, temperature and Mach number in moist air are significantly different from those in dry air. The dry air model exaggerates the Mach number by 19% and reduces both the pressure and the temperature by 34% at the nozzle exit as compared with the moist air model. At a Laval nozzle, for example, the nucleation rate, droplet number and condensation rate increase significantly with increasing relative humidity. The results also reveal the fact that the number of condensate droplets increases rapidly when moist air reaches 60% relative humidity. These findings provide a fundamental approach to account for the effect of condensate droplet formation on moist gas in a transonic flow system.

RATIONALIZATION OF THE UNIT FOR DIAGNOSING THE FLOW RATE OF HYDRAULIC EQUIPMENT FOR MOBILE MACHINES

2020 ◽  
Author(s):  
A.N. Sirotenko ◽  
◽  
S.A. Partko
Keyword(s):  
Flow Rate ◽  
Strength Analysis ◽  
Sensor Design ◽  
Flow Meter ◽  
Threaded Connection ◽  
Hydraulic Equipment ◽  
Mobile Machine

The article presents a strength analysis of the flowmeter design used in the diagnostics nodes of mobile machine hydraulic units. The connection of the flow meter housing with the bracket has been simplified and adapted for a more robust sensor design, taking into account the strength and tightness of the threaded connection. The tightness of the applied sealing method is confirmed by the analysis of the stressstrain state of the connection parts and confirmed practically.

scholarly journals Hybrid Artificial Intelligence Methods for Predicting Air Demand in Dam Bottom Outlet

2021 ◽  
Author(s):  
Aliakbar Narimani ◽  
Moghimi ◽  
Amir Mosavi
Keyword(s):  
Artificial Intelligence ◽  
Economic Value ◽  
Air Entrainment ◽  
Operating Conditions ◽  
Successful Operation ◽  
Volume Rate ◽  
Hydraulic Equipment ◽  
Bottom Outlets ◽  
Hybrid Artificial Intelligence ◽  
Bottom Outlet

In large infrastructures such as dams, which have a relatively high economic value, ensuring the proper operation of the associated hydraulic facilities in different operating conditions is of utmost importance. To ensure the correct and successful operation of the dam's hydraulic equipment and prevent possible damages, including gates and downstream tunnel, to build laboratory models and perform some tests are essential (the advancement of the smart sensors based on artificial intelligence is essential). One of the causes of damage to dam bottom outlets is cavitation in downstream and between the gates, which can impact on dam facilities, and air aeration can be a solution to improve it. In the present study, six dams in different provinces in Iran has been chosen to evaluate the air entrainment in the downstream tunnel experimentally. Three artificial neural networks (ANN) based machine learning (ML) algorithms are used to model and predict the air aeration in the bottom outlet. The proposed models are trained with genetic algorithms (GA), particle swarm optimization (PSO), i.e., ANN-GA, ANN-PSO, and ANFIS-PSO. Two hydrodynamic variables, namely volume rate and opening percentage of the gate, are used as inputs into all bottom outlet models. The results showed that the most optimal model is ANFIS-PSO to predict the dependent value compared with ANN-GA and ANN-PSO. The importance of the volume rate and opening percentage of the dams' gate parameters is more effective for suitable air aeration.

Análise de transitórios hidráulicos decorrentes da operação otimizada de estações elevatórias

2020 ◽  
pp. 17-26
Author(s):  
Gustavo Meirelles ◽  
◽  
Aloysio Saliba ◽  
Jorge Tarqui ◽  
Edna Viana ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Water Distribution ◽  
Particle Swarm ◽  
Water Distribution Network ◽  
Pressure Variation ◽  
Swarm Optimization ◽  
Transient Model ◽  
Demand Pattern ◽  
Steady State Model ◽  
Hydraulic Equipment

Neste trabalho são avaliados os transitórios hidráulicos decorrentes da operação otimizada de uma estação elevatória de uma rede de distribuição de água e os procedimentos operacionais que podem reduzir este problema para assegurar a confiabilidade do sistema. A operação otimizada é obtida utilizando o algoritmo Particle Swarm Optimization (PSO) e simulações em regime permanente, considerando que as bombas estarão operando com sua velocidade de rotação nominal ou desligadas. Em seguida, as manobras de arranque e paragem definidas são utilizadas num modelo em regime transitório para avaliar as variações de pressão decorrentes da operação otimizada. Os resultados obtidos demonstram que as variações de pressão não são elevadas, mas que, a longo prazo, podem ser significativos na redução da vida útil dos equipamentos hidráulicos. Além disso, observou-se que a variação da demanda num modelo transitório pode causar erros significativos, sendo necessária uma modelação cautelosa neste aspeto. In this work, the hydraulic transients resulting from the optimized operation of a pumping station in a water distribution network are studied and operational procedures to reduce this problem and ensure the reliability of the system are evaluated. An optimal pumping scheduling is obtained using the Particle Swarm Optimization (PSO) and a steady state model considering pumps operating only at their nominal rotational speed or switched off. Then, the pumps schedules are used in a transient model to evaluate the pressure surges of the optimized operation. The results showed that the pressure variation is not high but can be relevant in the reduction of service life of the hydraulic equipment. In addition, it was observed that the demand pattern in the transient model can cause significant errors, and its modeling has to be carefully handled.

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