scholarly journals Modelagem para o acoplamento do transporte de umidade, calor e cloreto de sódio em estruturas de concreto

2021 ◽  
Vol 21 (4) ◽  
pp. 143-156
Author(s):  
Rhayssa Maryell Marra Ribas ◽  
Gerson Henrique dos Santos ◽  
Viviane Okita
Keyword(s):  

Resumo A durabilidade dos materiais está diretamente ligada a sua capacidade de resistir aos agentes de deterioração. Nesse contexto, as estruturas de concreto podem estar sujeitas aos efeitos da umidade e do sal, reduzindo consideravelmente o seu tempo de vida útil. Os sais que entram pelos poros do concreto podem atacar sua armadura, bem como se concentrar em alguns pontos e cristalizar, gerando trincas e fissuras e reduzindo, deste modo, a sua resistência. Nesse sentido, este trabalho apresenta um modelo matemático para o transporte acoplado de calor, umidade e sal em meios porosos. As equações governantes foram discretizadas por meio do método dos volumes finitos resolvidas simultaneamente a partir do algoritmo MultiTriDiagonal Matrix Algorithm (MTDMA). A verificação do modelo foi realizada a partir da comparação de estudos de casos obtidos na literatura, mostrando uma boa concordância entre os resultados.

Author(s):  
Dinghui Wu ◽  
Juan Zhang ◽  
Bo Wang ◽  
Tinglong Pan

Traditional static threshold–based state analysis methods can be applied to specific signal-to-noise ratio situations but may present poor performance in the presence of large sizes and complexity of power system. In this article, an improved maximum eigenvalue sample covariance matrix algorithm is proposed, where a Marchenko–Pastur law–based dynamic threshold is introduced by taking all the eigenvalues exceeding the supremum into account for different signal-to-noise ratio situations, to improve the calculation efficiency and widen the application fields of existing methods. The comparison analysis based on IEEE 39-Bus system shows that the proposed algorithm outperforms the existing solutions in terms of calculation speed, anti-interference ability, and universality to different signal-to-noise ratio situations.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jie Zhao

With the continuous development of multimedia social networks, online public opinion information is becoming more and more popular. The rule extraction matrix algorithm can effectively improve the probability of information data to be tested. The network information data abnormality detection is realized through the probability calculation, and the prior probability is calculated, to realize the detection of abnormally high network data. Practical results show that the rule-extracting matrix algorithm can effectively control the false positive rate of sample data, the detection accuracy is improved, and it has efficient detection performance.


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