ReMuSSE: A Redundant Mutant Identification Technique Based on Selective Symbolic Execution

2021 ◽  
pp. 1-14
Author(s):  
Chang-ai Sun ◽  
An Fu ◽  
Xinling Guo ◽  
Tsong Yueh Chen
2018 ◽  
Vol 1 (2) ◽  
pp. 9-14
Author(s):  
Marisol Cervantes-Bobadilla ◽  
Ricardo Fabricio Escobar Jiménez ◽  
José Francisco Gómez Aguilar ◽  
Tomas Emmanuel Higareda Pliego ◽  
Alberto Armando Alvares Gallegos

In this research, an alkaline water electrolysis process is modelled. The electrochemical electrolysis is carried out in an electrolyzer composed of 12 series-connected steel cells with a solution 30% wt of potassium hydroxide. The electrolysis process model was developed using a nonlinear identification technique based on the Hammerstein structure. This structure consists of a nonlinear static block and a linear dynamic block. In this work, the nonlinear static function is modelled by a polynomial approximation equation, and the linear dynamic is modelled using the ARX structure. To control the current feed to the electrolyzer an unconstraint predictive controller was implemented, once the unconstrained MPC was simulated, some restrictions are proposed to design a constrained MPC (CMPC). The CMPC aim is to reduce the electrolyzer's energy consumption (power supply current). Simulation results showed the advantages of using the CMPC since the energy (current) overshoots are avoided.


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Zhenbang Chen ◽  
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Tianqi Zhang ◽  
Kenli Li ◽  
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Author(s):  
Shady Issa ◽  
Miguel Viegas ◽  
Pedro Raminhas ◽  
Nuno Machado ◽  
Miguel Matos ◽  
...  
Keyword(s):  

Author(s):  
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Yongjuan Liang ◽  
Zhunyi Xie ◽  
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