scholarly journals Analysis of Stiffened Penstock External Pressure Stability Based on Immune Algorithm and Neural Network

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Wensheng Dong ◽  
Xuemei Liu ◽  
Yunhua Li
Keyword(s):  
Neural Network ◽  
Bearing Capacity ◽  
Wall Thickness ◽  
External Pressure ◽  
Hydroelectric Power Station ◽  
Thin Wall ◽  
Hydroelectric Power ◽  
Stability Calculation ◽  
Critical External Pressure ◽  
Pressure Stability

The critical external pressure stability calculation of stiffened penstock in the hydroelectric power station is very important work for penstock design. At present, different assumptions and boundary simplification are adopted by different calculation methods which sometimes cause huge differences too. In this paper, we present an immune based artificial neural network model via the model and stability theory of elastic ring, we study effects of some factors (such as pipe diameter, pipe wall thickness, sectional size of stiffening ring, and spacing between stiffening rings) on penstock critical external pressure during huge thin-wall procedure of penstock. The results reveal that the variation of diameter and wall thickness can lead to sharp variation of penstock external pressure bearing capacity and then give the change interval of it. This paper presents an optimizing design method to optimize sectional size and spacing of stiffening rings and to determine penstock bearing capacity coordinate with the bearing capacity of stiffening rings and penstock external pressure stability coordinate with its strength safety. As a practical example, the simulation results illustrate that the method presented in this paper is available and can efficiently overcome inherent defects of BP neural network.

Design of cylindrical steel liquid tanks with stepped walls using One-foot method

2021 ◽  
Vol 7 (4) ◽  
pp. 162
Author(s):  
Özer Zeybek
Keyword(s):  
Wall Thickness ◽  
Calculation Method ◽  
External Pressure ◽  
Thin Wall ◽  
Buckling Mode ◽  
Equivalent Thickness ◽  
Steel Tanks ◽  
Uniform Wall ◽  
Hand Calculation ◽  
Cylindrical Steel

Cylindrical steel tanks are used in most countries to store bulk volumes of both solid and liquid products such as water, oil, gasoline and grain. Such steel tanks are prone to buckling when subjected to external pressure either due to vacuum or due to wind. These types of shell structures are generally controlled by elastic buckling failure because of the thin wall thickness. Cylindrical shells are commonly constructed with stepwise variable wall thickness due to economic reasons. The thickness of the tank shell wall is designed to increase from top to bottom because the stress resultants on the tank wall gradually increase towards the base of the tank. For open-top tanks, a primary stiffening ring is required at or near the top to maintain roundness under all loads. Stress resultants in a primary stiffening ring were previously identified by the Author for uniform wall thick tanks. In this new study, the applicability of this hand calculation method in stepped wall tanks has been investigated. Pursuant to this goal, a specified tank shell was designed considering One-foot method. Then, the stepped wall tank was transformed into an equivalent 1-course tank for hand calculation. Using the previously developed hand calculation method by Author, a test for the in-plane bending moment in the ring was conducted to achieve an acceptable value for stepped wall tanks. The analysis results show that the previously proposed method for uniform wall thick tanks may also be used for stepped wall tanks considering an equivalent thickness. On the other hand, using Linear Buckling Analysis (LBA), the buckling mode was obtained for two different stepped wall tanks in the study.

scholarly journals Generation of prognostic interval estimates of water inflows to hydroelectric reservoirs using multiparametric neural network

2021 ◽  
Vol 289 ◽  
pp. 01003
Author(s):  
Vladislav Berdnikov
Keyword(s):  
Neural Network ◽  
Subject Area ◽  
Hydroelectric Power Station ◽  
Hydroelectric Power ◽  
Practical Application ◽  
Power Station ◽  
Interval Estimates ◽  
Hydroelectric Reservoirs ◽  
Advantages And Disadvantages ◽  
The Neural Network

The article discusses the practical application of the neural network for hydropower and water management systems. Various models of neural networks are understood, their advantages and disadvantages for a particular subject area. Method and operation of multiparametric neural network are described using practical examples, in particular, formation of interval estimates in reservoir of hydroelectric power station.

scholarly journals Displacement Back Analysis for a High Slope of the Dagangshan Hydroelectric Power Station Based on BP Neural Network and Particle Swarm Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Zhengzhao Liang ◽  
Bin Gong ◽  
Chunan Tang ◽  
Yongbin Zhang ◽  
Tianhui Ma
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Back Analysis ◽  
Hydroelectric Power Station ◽  
Mechanical Parameters ◽  
Hydroelectric Power ◽  
Power Station ◽  
Bp Neural Network Model

The right bank high slope of the Dagangshan Hydroelectric Power Station is located in complicated geological conditions with deep fractures and unloading cracks. How to obtain the mechanical parameters and then evaluate the safety of the slope are the key problems. This paper presented a displacement back analysis for the slope using an artificial neural network model (ANN) and particle swarm optimization model (PSO). A numerical model was established to simulate the displacement increment results, acquiring training data for the artificial neural network model. The backpropagation ANN model was used to establish a mapping function between the mechanical parameters and the monitoring displacements. The PSO model was applied to initialize the weights and thresholds of the backpropagation (BP) network model and determine suitable values of the mechanical parameters. Then the elastic moduli of the rock masses were obtained according to the monitoring displacement data at different excavation stages, and the BP neural network model was proved to be valid by comparing the measured displacements, the displacements predicted by the BP neural network model, and the numerical simulation using the back-analyzed parameters. The proposed model is useful for rock mechanical parameters determination and instability investigation of rock slopes.

Research on Horizontal Bearing Capacity of Precast Thin-Wall Steel and Spun Concrete Composite Pile

2014 ◽  
Vol 590 ◽  
pp. 336-340
Author(s):  
Xin Quan Wang ◽  
Shi Min Zhang ◽  
Juan Liao ◽  
Ying Sheng Huang ◽  
Hong Liu
Keyword(s):  
Bearing Capacity ◽  
Wall Thickness ◽  
Composite Foundation ◽  
Steel Pipe ◽  
Bending Test ◽  
Thin Wall ◽  
Analysis Model ◽  
Composite Pile ◽  
Spun Concrete ◽  
Outside Diameter

Precast thin-wall steel and spun concrete composite pile (TSC pile) is a new type of steel-concrete composite foundation pile whose performance is between steel pile and concrete pile. 3D numerical analysis model of TSC pile was established by FEM software in this paper. By compared with the laboratory bending test results, the model’s reliability was verified, and then the bearing capacity of TSC pile under horizontal load was calculated, moreover, influences of different cross section parameters (diameter, wall thickness, steel pipe thickness, pile’s length) on the horizontal bearing capacity of TSC pile were studied. The results show that: with the increase of pile’s outside diameter, wall thickness of steel pipe, wall thickness of concrete pipe and length of pile, the horizontal bearing capacity of TSC pile is increased. The outside diameter has a biggest impact on the horizontal bearing capacity of TSC pile, then pile’s length, steel pipe’s wall thickness, and the influences of concrete pipe’s wall thickness are the least.

Corrosion Condition Research and Bearing Capacity Analysis of a Space Truss Base on Corrosive Environments

2010 ◽  
Vol 163-167 ◽  
pp. 838-841
Author(s):  
Xu Yan ◽  
Tie Ying Li ◽  
Ning Yang
Keyword(s):  
Carbon Steel ◽  
Finite Elements ◽  
Bearing Capacity ◽  
Wall Thickness ◽  
Capacity Analysis ◽  
Thin Wall ◽  
Finite Elements Analysis ◽  
Corrosion Condition ◽  
Space Truss ◽  
Corrosive Environments

A certain natatorium is selected as the object for the corrosion researches on common carbon steel which has been used in the corrosive environments for 20 years. Bearing and deformation capacities are calculated to simulate corrosion by elastic and elasto-plastic finite elements analysis with ANSYS. The result is shown that corrosion condition should be considerable to the space truss with thin wall thickness in the severely corrosive environments.

Influences of Cross Section Parameters on Bending Resistance of TSC Pile

2014 ◽  
Vol 580-583 ◽  
pp. 464-468
Author(s):  
Xin Quan Wang ◽  
Shi Min Zhang ◽  
Juan Liao ◽  
Ying Sheng Huang
Keyword(s):  
Bearing Capacity ◽  
Cross Section ◽  
Wall Thickness ◽  
Thin Wall ◽  
Bending Resistance ◽  
Composite Pile ◽  
Spun Concrete ◽  
Set Up ◽  
Pile Model ◽  
Outside Diameter

Precast thin-wall steel and spun concrete composite pile (TSC pile) is a kind of new type of steel-concrete composite pile whose bearing performance is between steel pile and concrete pile. This article adopted FEM software to set up 3D TSC pile model to analyze its performance. Through the comparison with actual pure bending bearing experiment results, the model’s reliability was verified and the results showed that the model was reliable. Then lots of bending bearing capacity contrast calculations were conducted by using different cross section parameters (outside diameter, concrete pipe’s wall thickness and steel pipe’s wall thickness), and the influences of these parameters on bending resistance of TSC pile were discussed. The results showed that: with the increase of outside diameter, concrete pipe’s wall thickness and steel pipe’s wall thickness, TSC pile’s ultimate flexural bearing capacity increased. The influences of different parameters were not the same, outside diameter was the most important parameter, then concrete pipe’s wall thickness, and the last one was steel pipe’s wall thickness.

scholarly journals The simulation model for a flood management by flood control facilities

2018 ◽  
Vol 245 ◽  
pp. 15002 ◽  
Author(s):  
Roman Davydov ◽  
Valery Antonov ◽  
Dmitry Molodtsov ◽  
Alexey Cheremisin ◽  
Vadim Korablev
Keyword(s):  
Mathematical Models ◽  
Flood Control ◽  
Flood Management ◽  
Hydroelectric Power Station ◽  
Hydroelectric Power ◽  
Operating Characteristics ◽  
Hydro Power ◽  
Operation Modes ◽  
Wide Range ◽  
Environmental Requirements

The rapid spread of storm floods over large areas requires flood management throughout the river basin by the creation an innovative system of flood control facilities of various functional purposes distributed in the area. The central part of the system is the hydro system with hydro power plant. In addition, the flood control facilities on the side tributaries with self-regulating reservoir are included in the system. To assess the effect of controlling extreme water discharges by flood control facilities, it is necessary to develop special mathematical models reflecting the specifics of their operation. Unified mathematical models of the operation modes of a hydro complex with hydroelectric power station and flood control facility are created. They are implemented in a computer program that provides the ability to determine the main parameters and operating characteristics of hydro systems when performing multivariate calculations in a wide range of initial data. This makes possible specifying the parameters and operation modes of each hydro system with the current economic and environmental requirements, to assess the energy-economic and environmental consequences in the operation of the system of flood control facilities distributed in the area. The article analyses the results of the extreme water discharge’s regulation by the hydro system on the main river and flood control facilities on the side tributaries, considering environmental requirements.

scholarly journals Ce-Bearing FeSi Alloy Inoculation of Electrically Melted, Low Sulphur Grey Cast Irons for Thin Wall Castings

Metals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1122
Author(s):  
Irina Varvara Balkan ◽  
Iulian Riposan
Keyword(s):  
Wall Thickness ◽  
Structural Characteristics ◽  
Cooling Curve ◽  
Thin Wall ◽  
Cast Irons ◽  
Iron Castings ◽  
Grey Cast ◽  
The Difference ◽  
Thermal Cooling ◽  
Fesi Alloy

Electrically melted and over-heated (>1500 °C) grey cast iron at less than 0.04%S, as commonly used, solidifies large amounts of carbides and/or undercooled graphite, especially in thin wall castings; this is necessary to achieve a stronger inoculation. The efficiency of Ce-bearing FeSi alloy is tested for lower ladle addition rates (0.15 and 0.25 wt.%), compared to the base and conventional inoculated iron (Ba,Ca-bearing FeSi alloy). The present work explores chill and associated structures in hypoeutectic grey iron (3.6–3.8%CE, 0.02%S, (%Mn) × (%S) = 0.013–0.016, Alres < 0.002%), in wedge castings W1, W2 and W3 (ASTM A 367, furan resin sand mould), at a lower cooling modulus (1.1–3.5 mm) that is typically used to control the quality of thin wall iron castings. Relatively clear and total chill well correlated with the standard thermal (cooling curve) analysis parameters and structural characteristics in wedge castings, at different wall thickness, displayed as the carbides/graphite ratio and presence of undercooled graphite morphologies. The difference in effects of the two inoculants addition is seen as the ability to decrease the amount of carbides and undercooled graphite, with Ce-bearing FeSi alloy outperforming the conventional inoculant, especially as the wall thickness decreased. It appears that Ce-bearing FeSi alloy could be a solution for low sulphur, electric melt, thin wall iron castings production.

Porous-concrete pipe drainage of the earth dam of the Riga Hydroelectric Power Station

1974 ◽  
Vol 8 (10) ◽  
pp. 914-916
Author(s):  
I. S. Ronzhin ◽  
A. D. Osipov ◽  
V. Kh. Gol'tsman ◽  
A. B. Yumatov
Keyword(s):  
Earth Dam ◽  
Hydroelectric Power Station ◽  
Hydroelectric Power ◽  
Power Station ◽  
Porous Concrete ◽  
The Earth ◽  
Concrete Pipe
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