CN114861489B - rPCK代理模型辅助的结构动参数辨识方法 - Google Patents
rPCK代理模型辅助的结构动参数辨识方法 Download PDFInfo
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- CN114861489B CN114861489B CN202210402995.9A CN202210402995A CN114861489B CN 114861489 B CN114861489 B CN 114861489B CN 202210402995 A CN202210402995 A CN 202210402995A CN 114861489 B CN114861489 B CN 114861489B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
- G06F17/13—Differential equations
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
Description
参数 | 单位 | 基于rPCK的结构动参数估计值 |
Ec | GPa | 1.36 |
ρc | Kg/m3 | 2239.07 |
Ef | GPa | 26.87 |
ρf | Kg/m3 | 2438.14 |
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CN202210402995.9A CN114861489B (zh) | 2022-04-18 | 2022-04-18 | rPCK代理模型辅助的结构动参数辨识方法 |
US18/135,218 US20230334198A1 (en) | 2022-04-18 | 2023-04-17 | STRUCTURAL DYNAMIC PARAMETER IDENTIFICATION METHOD AIDED BY rPCK SURROGATE MODEL |
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CN202210402995.9A CN114861489B (zh) | 2022-04-18 | 2022-04-18 | rPCK代理模型辅助的结构动参数辨识方法 |
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CN114861489B true CN114861489B (zh) | 2023-09-19 |
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112528517A (zh) * | 2020-12-24 | 2021-03-19 | 哈尔滨工业大学 | 基于两阶段收敛准则的钢箱梁疲劳可靠度分析方法 |
CN113033054A (zh) * | 2021-03-29 | 2021-06-25 | 河海大学 | 一种基于pce_bo的结构性能参数快速反演方法 |
WO2021253532A1 (zh) * | 2020-06-19 | 2021-12-23 | 浙江大学 | 一种高维随机场条件下的新型复合材料结构优化设计方法 |
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2022
- 2022-04-18 CN CN202210402995.9A patent/CN114861489B/zh active Active
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2023
- 2023-04-17 US US18/135,218 patent/US20230334198A1/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2021253532A1 (zh) * | 2020-06-19 | 2021-12-23 | 浙江大学 | 一种高维随机场条件下的新型复合材料结构优化设计方法 |
CN112528517A (zh) * | 2020-12-24 | 2021-03-19 | 哈尔滨工业大学 | 基于两阶段收敛准则的钢箱梁疲劳可靠度分析方法 |
CN113033054A (zh) * | 2021-03-29 | 2021-06-25 | 河海大学 | 一种基于pce_bo的结构性能参数快速反演方法 |
Non-Patent Citations (4)
Title |
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Bayesian inversion using adaptive Polynomial Chaos Kriging within Subset Simulation;Rossat, D (Rossat, D.) 等;《JOURNAL OF COMPUTATIONAL PHYSICS》;全文 * |
复合材料梁弹性参数不确定性量化及试验验证;吴邵庆;范刚;李彦斌;姜东;费庆国;;东南大学学报(自然科学版)(第06期);全文 * |
大坝安全诊断的混沌优化神经网络模型;曹茂森 等;《岩土力学》;全文 * |
面向高维数据的聚类算法设计和张量低秩表示研究;卓林琳;《中国博士学位论文全文数据库信息科技辑》;全文 * |
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US20230334198A1 (en) | 2023-10-19 |
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