scholarly journals EFFECT OF HEAT CURING METHODS ON THE TEMPERATURE HISTORY AND STRENGTH DEVELOPMENT OF SLAB CONCRETE FOR NUCLEAR POWER PLANT STRUCTURES IN COLD CLIMATES

2012 ◽  
Vol 44 (5) ◽  
pp. 523-534 ◽  
Author(s):  
Gun-Che Lee ◽  
Min-Cheol Han ◽  
Dae-Hyun Baek ◽  
Kyung-Taek Koh
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Temperature History ◽  
Strength Development ◽  
Cold Climates ◽  
Heat Curing ◽  
Curing Methods

scholarly journals Effects of Magnetite Aggregate and Steel Powder on Thermal Conductivity and Porosity in Concrete for Nuclear Power Plant

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Han-Seung Lee ◽  
Seung-Jun Kwon
Keyword(s):  
Thermal Conductivity ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Steel Powder ◽  
Radiation Shielding ◽  
Strength Development ◽  
Equivalent Thermal Conductivity ◽  
Low Thermal Conductivity ◽  
Thermally Conductive

Among many engineering advantages in concrete, low thermal conductivity is an attractive property. Concrete has been widely used for nuclear vessels and plant facilities for its excellent radiation shielding. The heat isolation through low thermal conductivity is actually positive for nuclear power plant concrete; however the property may cause adverse effect when fires and melt-down occur in nuclear vessel since cooling down from outer surface is almost impossible due to very low thermal conductivity. If concrete containing atomic reactor has higher thermal conductivity, the explosion risk of conductive may be partially reduced. This paper presents high thermally conductive concrete development. For the work, magnetite with varying replacements of normal aggregates and steel powder of 1.5% of volume are considered, and the equivalent thermal conductivity is evaluated. Only when the replacement ratio goes up to 30%, thermal conductivity increases rapidly to 2.5 times. Addition of steel powder is evaluated to be effective by 1.08~1.15 times. In order to evaluate the improvement of thermal conductivity, several models like ACI, DEMM, and MEM are studied, and their results are compared with test results. In the present work, the effects of steel powder and magnetite aggregate are studied not only for strength development but also for thermal behavior based on porosity.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

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