An Intelligent Optimization Back-Analysis Method for Geomechanical Parameters in Underground Engineering Article Swipe
Jianhe Li
,
Weizhe Sun
,
Guoshao Su
,
Yan Zhang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/app12115761
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/app12115761
The geomechanical parameters in underground engineering are usually difficult to determine, which can pose great obstacles in underground engineering. A novel displacement back-analysis method is proposed to determine the geomechanical parameters in underground engineering. In this method, the problem of geomechanical parameter determination is converted into an optimization problem, regarding the geomechanical parameters as the optimization parameters, and the error between the calculated results and the field measurement information as the optimization objective function. The grasshopper optimization algorithm (GOA), which offers excellent global optimization performance, and the Gaussian process regression (GPR) machine learning, offering powerful fitting ability, are combined to address the time-consuming numerical calculations. Furthermore, the proposed method is combined with the 3D numerical calculation software FLAC3D to form the GOA-GPR-FLAC3D method, which can be used in the displacement back-analysis of geomechanical parameters in underground engineering. The results of a case study show that the proposed method can greatly improve computational efficiency while ensuring high precision compared with the GOA. When applied to the Tai’an Pumped Storage Power Station, this method can obtain more accurate results compared with the GOA under the same evaluation times and is more suitable for the back-analysis of rock parameters in underground engineering.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app12115761
- https://www.mdpi.com/2076-3417/12/11/5761/pdf?version=1654656887
- OA Status
- gold
- Cited By
- 7
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4281873286
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4281873286Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app12115761Digital Object Identifier
- Title
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An Intelligent Optimization Back-Analysis Method for Geomechanical Parameters in Underground EngineeringWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-06-06Full publication date if available
- Authors
-
Jianhe Li, Weizhe Sun, Guoshao Su, Yan ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/app12115761Publisher landing page
- PDF URL
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https://www.mdpi.com/2076-3417/12/11/5761/pdf?version=1654656887Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2076-3417/12/11/5761/pdf?version=1654656887Direct OA link when available
- Concepts
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Computer science, Kriging, Displacement (psychology), Geotechnical engineering, Geology, Machine learning, Psychology, PsychotherapistTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 4, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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34Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.of | 39, 131, 139, 193 |
| abstract_inverted_index.to | 9, 26, 99, 118, 163 |
| abstract_inverted_index.GOA | 180 |
| abstract_inverted_index.The | 0, 74, 137 |
| abstract_inverted_index.and | 57, 64, 85, 186 |
| abstract_inverted_index.are | 6, 97 |
| abstract_inverted_index.can | 12, 124, 148, 172 |
| abstract_inverted_index.for | 190 |
| abstract_inverted_index.the | 28, 37, 50, 54, 58, 61, 65, 70, 86, 101, 106, 112, 120, 128, 145, 159, 164, 179, 182, 191 |
| abstract_inverted_index.GOA. | 160 |
| abstract_inverted_index.When | 161 |
| abstract_inverted_index.case | 141 |
| abstract_inverted_index.form | 119 |
| abstract_inverted_index.high | 155 |
| abstract_inverted_index.into | 45 |
| abstract_inverted_index.more | 174, 188 |
| abstract_inverted_index.pose | 13 |
| abstract_inverted_index.rock | 194 |
| abstract_inverted_index.same | 183 |
| abstract_inverted_index.show | 143 |
| abstract_inverted_index.that | 144 |
| abstract_inverted_index.this | 35, 170 |
| abstract_inverted_index.used | 126 |
| abstract_inverted_index.with | 111, 158, 178 |
| abstract_inverted_index.(GPR) | 90 |
| abstract_inverted_index.Power | 168 |
| abstract_inverted_index.error | 59 |
| abstract_inverted_index.field | 66 |
| abstract_inverted_index.great | 14 |
| abstract_inverted_index.novel | 20 |
| abstract_inverted_index.study | 142 |
| abstract_inverted_index.times | 185 |
| abstract_inverted_index.under | 181 |
| abstract_inverted_index.which | 11, 79, 123 |
| abstract_inverted_index.while | 153 |
| abstract_inverted_index.(GOA), | 78 |
| abstract_inverted_index.FLAC3D | 117 |
| abstract_inverted_index.Pumped | 166 |
| abstract_inverted_index.global | 82 |
| abstract_inverted_index.method | 23, 108, 147, 171 |
| abstract_inverted_index.obtain | 173 |
| abstract_inverted_index.offers | 80 |
| abstract_inverted_index.Storage | 167 |
| abstract_inverted_index.address | 100 |
| abstract_inverted_index.applied | 162 |
| abstract_inverted_index.between | 60 |
| abstract_inverted_index.fitting | 95 |
| abstract_inverted_index.greatly | 149 |
| abstract_inverted_index.improve | 150 |
| abstract_inverted_index.machine | 91 |
| abstract_inverted_index.method, | 36, 122 |
| abstract_inverted_index.problem | 38 |
| abstract_inverted_index.process | 88 |
| abstract_inverted_index.results | 63, 138, 176 |
| abstract_inverted_index.usually | 7 |
| abstract_inverted_index.Gaussian | 87 |
| abstract_inverted_index.Station, | 169 |
| abstract_inverted_index.Tai’an | 165 |
| abstract_inverted_index.ability, | 96 |
| abstract_inverted_index.accurate | 175 |
| abstract_inverted_index.combined | 98, 110 |
| abstract_inverted_index.compared | 157, 177 |
| abstract_inverted_index.ensuring | 154 |
| abstract_inverted_index.offering | 93 |
| abstract_inverted_index.powerful | 94 |
| abstract_inverted_index.problem, | 48 |
| abstract_inverted_index.proposed | 25, 107, 146 |
| abstract_inverted_index.software | 116 |
| abstract_inverted_index.suitable | 189 |
| abstract_inverted_index.algorithm | 77 |
| abstract_inverted_index.converted | 44 |
| abstract_inverted_index.determine | 27 |
| abstract_inverted_index.difficult | 8 |
| abstract_inverted_index.excellent | 81 |
| abstract_inverted_index.function. | 73 |
| abstract_inverted_index.learning, | 92 |
| abstract_inverted_index.numerical | 103, 114 |
| abstract_inverted_index.objective | 72 |
| abstract_inverted_index.obstacles | 15 |
| abstract_inverted_index.parameter | 41 |
| abstract_inverted_index.precision | 156 |
| abstract_inverted_index.regarding | 49 |
| abstract_inverted_index.calculated | 62 |
| abstract_inverted_index.determine, | 10 |
| abstract_inverted_index.efficiency | 152 |
| abstract_inverted_index.evaluation | 184 |
| abstract_inverted_index.parameters | 2, 30, 52, 133, 195 |
| abstract_inverted_index.regression | 89 |
| abstract_inverted_index.calculation | 115 |
| abstract_inverted_index.engineering | 5 |
| abstract_inverted_index.grasshopper | 75 |
| abstract_inverted_index.information | 68 |
| abstract_inverted_index.measurement | 67 |
| abstract_inverted_index.parameters, | 56 |
| abstract_inverted_index.underground | 4, 17, 32, 135, 197 |
| abstract_inverted_index.Furthermore, | 105 |
| abstract_inverted_index.displacement | 21, 129 |
| abstract_inverted_index.engineering. | 18, 33, 136, 198 |
| abstract_inverted_index.optimization | 47, 55, 71, 76, 83 |
| abstract_inverted_index.performance, | 84 |
| abstract_inverted_index.back-analysis | 22, 130, 192 |
| abstract_inverted_index.calculations. | 104 |
| abstract_inverted_index.computational | 151 |
| abstract_inverted_index.determination | 42 |
| abstract_inverted_index.geomechanical | 1, 29, 40, 51, 132 |
| abstract_inverted_index.GOA-GPR-FLAC3D | 121 |
| abstract_inverted_index.time-consuming | 102 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5039750959 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I150807315 |
| citation_normalized_percentile.value | 0.79808829 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |