scholarly journals Selection of earthquake ground motions for multiple objectives using genetic algorithms

2019 ◽  
Vol 187 ◽  
pp. 414-427 ◽  
Author(s):  
Panagiotis E. Mergos ◽  
Anastasios G. Sextos
Keyword(s):  
Genetic Algorithms ◽  
Ground Motions ◽  
Multiple Objectives ◽  
Earthquake Ground Motions ◽  
Selection Of

Selection of the Test Specimens for Seismic Tests of Air-Operated Valve Actuators for Nuclear Power Plants

2019 ◽  
Author(s):  
Nobuo Kojima ◽  
Yoshitaka Tsutsumi ◽  
Yoshinao Matsubara ◽  
Koji Nishino ◽  
Yasuyuki Ito ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Ground Motions ◽  
Test Results ◽  
Earthquake Ground Motions ◽  
Dynamic Function ◽  
Design Earthquake ◽  
Seismic Tests ◽  
Selection Of

Abstract The soundness for the function of air-operated valves in nuclear power plants during earthquake has been investigated via seismic test results and so forth. Since the seismic response acceleration has increased more and more with a recent reassessment of design earthquake ground motions conducted according to the revised Japanese nuclear safety regulation, it is necessary to evaluate the soundness for the function of various valves subject to large acceleration beyond design basis. The air-operated valves currently installed in the nuclear power plants in Japan play the important roles in the sever accident events. In this study, we classified them based on the valve type, manufactures and the previous test results. Furthermore, we proposed the strategy for evaluating the seismic-proof and the seismic test condition for examining the soundness of the dynamic function. Here, the dynamic function is defined as the function required under and after earthquakes.

scholarly journals Designing Strong Privacy Metrics Suites Using Evolutionary Optimization

2021 ◽  
Vol 24 (2) ◽  
pp. 1-35
Author(s):  
Isabel Wagner ◽  
Iryna Yevseyeva
Keyword(s):  
Optimization Problem ◽  
Evolutionary Optimization ◽  
Multiple Objectives ◽  
Shared Value ◽  
Vehicular Communications ◽  
Open Problems ◽  
Value Range ◽  
Genomic Privacy ◽  
Metaheuristic Optimization Algorithms ◽  
Selection Of

The ability to measure privacy accurately and consistently is key in the development of new privacy protections. However, recent studies have uncovered weaknesses in existing privacy metrics, as well as weaknesses caused by the use of only a single privacy metric. Metrics suites, or combinations of privacy metrics, are a promising mechanism to alleviate these weaknesses, if we can solve two open problems: which metrics should be combined and how. In this article, we tackle the first problem, i.e., the selection of metrics for strong metrics suites, by formulating it as a knapsack optimization problem with both single and multiple objectives. Because solving this problem exactly is difficult due to the large number of combinations and many qualities/objectives that need to be evaluated for each metrics suite, we apply 16 existing evolutionary and metaheuristic optimization algorithms. We solve the optimization problem for three privacy application domains: genomic privacy, graph privacy, and vehicular communications privacy. We find that the resulting metrics suites have better properties, i.e., higher monotonicity, diversity, evenness, and shared value range, than previously proposed metrics suites.

Selection of an Optimum Feed Profile Using genetic Algorithms

2004 ◽  
Vol 37 (3) ◽  
pp. 577-581
Author(s):  
K.O. Jones ◽  
S. Romil
Keyword(s):  
Genetic Algorithms ◽  
Selection Of
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