Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm
Nuclear magnetic resonance (NMR) technology provides an innovative method employed in detecting the porous structures in frozen rock and soil masses. On the basis of NMR relaxation theory, fuzzy random characteristics of the NMR T2 spectrum and pore structure are deeply analyzed in accordance with t...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/5999874 |
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| author | Yao Ya-feng Lin Jian Ge Jian Peng Shi-long Yin Jian-chao Ouyang Li-na |
| author_facet | Yao Ya-feng Lin Jian Ge Jian Peng Shi-long Yin Jian-chao Ouyang Li-na |
| author_sort | Yao Ya-feng |
| collection | DOAJ |
| description | Nuclear magnetic resonance (NMR) technology provides an innovative method employed in detecting the porous structures in frozen rock and soil masses. On the basis of NMR relaxation theory, fuzzy random characteristics of the NMR T2 spectrum and pore structure are deeply analyzed in accordance with the complex and uncertain distribution characteristics of the underground rock and soil structure. By studying the fuzzy random characteristics of the NMR T2 spectrum, the fuzzy random conversion coefficient and conversion method of the T2 spectrum and pore size distribution are generated. Based on the niche principle, the traditional genetic algorithm is updated by the fuzzy random method, and the improved niche genetic algorithm is proposed. Then, the fuzzy random inversion of the conversion coefficient is undertaken by using the improved algorithm. It in turn makes the conversion curve of the T2 spectrum and pore size distribution align with the mercury injection test curve in diverse pore apertures. Compared with the previous least square fitting method, it provides a more accurate approach in characterizing complicated pore structures in frozen rock and soil masses. In addition, the improved niche genetic algorithm effectively overcomes the shortcomings of the traditional genetic algorithm, such as low effectiveness, slow convergence, and weak controllability, which provides an effective way for parameter inversion in the section of frozen geotechnical engineering. Finally, based on the T2 spectrum test of frozen sandstone, the fuzzy random characterization of frozen sandstone pore distribution is carried out by using this transformation method. The results illustrate that the conversion coefficient obtained through the improved algorithm indirectly considers the different surface relaxation rates of different pore sizes and effectively reduces the diffusion coupling effects, and the pore characteristics achieved are more applicable in engineering practices than previous methods. |
| format | Article |
| id | doaj-art-c808e3ab516b4e2fbdf526aaecfca75e |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
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| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-c808e3ab516b4e2fbdf526aaecfca75e2025-02-03T07:23:58ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422021-01-01202110.1155/2021/59998745999874Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic AlgorithmYao Ya-feng0Lin Jian1Ge Jian2Peng Shi-long3Yin Jian-chao4Ouyang Li-na5School of Architectural Engineering, Nantong Vocational University, Nantong 226001, ChinaAnhui Key Laboratory of Building Structure and Underground Engineering, Anhui Jianzhu University, Hefei 210037, ChinaSchool NZIHT, Western Institute of Technology at Taranaki, New Plymouth 4032, New ZealandAnhui Key Laboratory of Building Structure and Underground Engineering, Anhui Jianzhu University, Hefei 210037, ChinaAnhui Key Laboratory of Building Structure and Underground Engineering, Anhui Jianzhu University, Hefei 210037, ChinaAnhui Key Laboratory of Building Structure and Underground Engineering, Anhui Jianzhu University, Hefei 210037, ChinaNuclear magnetic resonance (NMR) technology provides an innovative method employed in detecting the porous structures in frozen rock and soil masses. On the basis of NMR relaxation theory, fuzzy random characteristics of the NMR T2 spectrum and pore structure are deeply analyzed in accordance with the complex and uncertain distribution characteristics of the underground rock and soil structure. By studying the fuzzy random characteristics of the NMR T2 spectrum, the fuzzy random conversion coefficient and conversion method of the T2 spectrum and pore size distribution are generated. Based on the niche principle, the traditional genetic algorithm is updated by the fuzzy random method, and the improved niche genetic algorithm is proposed. Then, the fuzzy random inversion of the conversion coefficient is undertaken by using the improved algorithm. It in turn makes the conversion curve of the T2 spectrum and pore size distribution align with the mercury injection test curve in diverse pore apertures. Compared with the previous least square fitting method, it provides a more accurate approach in characterizing complicated pore structures in frozen rock and soil masses. In addition, the improved niche genetic algorithm effectively overcomes the shortcomings of the traditional genetic algorithm, such as low effectiveness, slow convergence, and weak controllability, which provides an effective way for parameter inversion in the section of frozen geotechnical engineering. Finally, based on the T2 spectrum test of frozen sandstone, the fuzzy random characterization of frozen sandstone pore distribution is carried out by using this transformation method. The results illustrate that the conversion coefficient obtained through the improved algorithm indirectly considers the different surface relaxation rates of different pore sizes and effectively reduces the diffusion coupling effects, and the pore characteristics achieved are more applicable in engineering practices than previous methods.http://dx.doi.org/10.1155/2021/5999874 |
| spellingShingle | Yao Ya-feng Lin Jian Ge Jian Peng Shi-long Yin Jian-chao Ouyang Li-na Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm Advances in Materials Science and Engineering |
| title | Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm |
| title_full | Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm |
| title_fullStr | Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm |
| title_full_unstemmed | Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm |
| title_short | Fuzzy Random Characterization of Pore Structure in Frozen Sandstone: Applying Improved Niche Genetic Algorithm |
| title_sort | fuzzy random characterization of pore structure in frozen sandstone applying improved niche genetic algorithm |
| url | http://dx.doi.org/10.1155/2021/5999874 |
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