請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68267完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 詹魁元(Kuei-Yuan Chan) | |
| dc.contributor.author | Ying-Hua Chu | en |
| dc.contributor.author | 朱盈樺 | zh_TW |
| dc.date.accessioned | 2021-06-17T02:16:09Z | - |
| dc.date.available | 2018-01-04 | |
| dc.date.copyright | 2018-01-04 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-10-11 | |
| dc.identifier.citation | [1]L. Schwer. “Guide for Verification and Validation in Computational Solid Mechanics”.American Society of Mechanical Engineers, 60(10):1–15, 2006.
[2]R. Oliva. “Model Calibration as A Testing Strategy for System dynamics models”.European Journal of Operational Research, 151(3):552– 568, 2003. [3] X. Jiang and S. Mahadevan. “Wavelet Spectrum Analysis Approach to Model Validation of Dynamic Systems”. Mechanical Systems and Signal Processing, 25:575–590, 2011.[4] S. Stevenson, B. Fox-Kemper, M. Jochum, B. Rajagopalan, and S. Yeager. “ENSO Model Validation Using Wavelet Probability Analysis”. Journal of Climate, 23(20):5540–5547, 2010. [5] M. Tsatsanis and G. Giannakis. “Time-varying System Identification and Model Validation Using Wavelets”. IEEE Transactions on Signal Processing, 41(12):3512–3523, Dec 1993. [6] X. Jiang and S. Mahadevan. “Bayesian Wavelet Method for Multivariate ModelAssessment of Dynamic Systems”. Journal of Sound and Vibration, 312(4):694–712, 2008. [7] L. Wang. “Karhunen - Lo`eve Expansions and their Applications”. London School of Economics and Political Science (United Kingdom), 2008. [8] K. Phoon, H. Huang, and S. Quek. “Comparison between Karhunen - Lo`eve and Wavelet Expansions for Simulation of Gaussian Processes”. Computers and Structures, 82(13):985–991, 2004. [9] K. Phoon, S. Huang, and S. Quek. “Simulation of Second-order Processes UsingKarhunen - Lo`eve Expansion”. Computers and Structures, 80(12):1049–1060,2002. [10] K. Phoon, S. Huang, and S. Quek. “Implementation of Karhunen - Lo`eve Expansion for Simulation Using a Wavelet-Galerkin Scheme”. Probabilistic EngineeringMechanics, 17(3):293–303, 2002. [11] K. Phoon, H. Huang, and S. Quek. “Simulation of Strongly Non-Gaussian Processes Using Karhunen - Lo`eve Expansion”. Probabilistic Engineering Mechanics,20(2):188–198, 2005. [12] W. Betz, I. Papaioannou, and D. Straub. “Numerical Methods for the Discretizationof Random Fields by Means of the Karhunen - Lo`eve Expansion”. Computer methods in applied mechanics and engineering, 271:109–129, 2014. [13] J. Yang, D. Zhang, and J.-Y. Yang. “A Generalised K-L expansion Method which can deal with Small Sample Size and High-dimensional Problems”. Pattern Analysis and Applications, 6(1):47–54, 2003. [14] Z. Wang, Y. Fu, R.-J.Yang, B. Saeed, and W. Chen. “Model Validating Dynamic Engineering Models under Uncertainty”. Journal of Mechanical Design,138(11):111402, 2016. [15] S Ferson, L. William, and L Ginzburg. “Model Validation and Predictive Capability for the Thermal Challenge Problem”. Computer Methods in Applied Mechanics and Engineering, 197(29):2408–2430, 2008. [16] X. Zhimin, P. Hao, F. Yan, and R.-J Yang. “Validation Metric for Dynamic System Responses under Uncertainty”. SAE International Journal of Materials and Manufacturing, 8(2015-01-0453):309–314, 2015.[17] Z. Zhan, F. Yan, and R.-J Yang. “Enhanced Error Assessment of Response Time Histories ( EEARTH ) Metric and Calibration Process”. 2011. [18] M Kokkolaras, G Hulbert, P Papalambros, and R Yang. “Comparing Time Histories for Validation of Simulation Models”. Journal of Dynamic Systems, Measurement, and Control, 132(6):061401–0614010, 2010. [19] R. Ramesh and S Mahadevan. “Computational Methods for Model Reliability Assessment”. Reliability Engineering and System Safety, 93(8):1197–1207, 2008. [20] M. Mccarthy, H. Possingham, J. Day, and A. Tyre. “Testing the Accuracy of Population Viability Analysis”. Conservation Biology, 15(4):1030–1038, 2001. [21] M. Analla. “Model Validation Through the Linear Regression Fit to Actual Versus Predicted Values”. Agricultural Systems, 57(1):115–119, 1998. [22] M. Reynolds. “Procedures for Statistical Validation of Stochastic Simulation Models”. Forest science, 27(2):349–364, 1981. [23] A. Robinson and R. Froese. “Model Validation Using Equivalence Tests”. Ecological Modelling, 176(3):349–358, 2004. [24] D. Mayer. “Statistical validation”. Ecological modelling, 68(1-2):21–32, 1993. [25] 顏月珠. “無母數統計方法Nonparametric Statistics”. O'‡, 2006. [26] D. Montgomery and G. Runger. “Applied Statistics and Probability for Engineers”. Wiley, 2010. [27] M. Hollander and D. A. White. “Nonparametric Statistics Methods”. Wiley, 1999. [28] J.Y.Wong. “Theory Of Ground Vehicles”. Wiley, 1993. [29] R.W. Rivers. “Evidence in Tra c Crash Investigation and Reconstruction”. Thomas, 2006. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68267 | - |
| dc.description.abstract | 模擬模型與實驗模型的驗證是模型建構的初期任務之一，在動態模型的動態行為驗證上，常遇到的困難有(1)動態系統性能輸出缺乏可評估的單一量化方式(2)現行模型驗證指標過度強調模型吻合而非一致性。(3)動態系統輸出與參數的耦合關係複雜。本研究著重在模型動態行為驗證上，使用Karhunen-Loeve轉換及重組動態資訊，藉以有效比對重要資訊，並運用無母數檢定方式建立驗證指標，再以檢定之p值建構指標座標圖，如此一來能夠完整說明模擬模型與實驗模型的雷同程度與吻合程度，提供修正模型的方向。本研究使用三個案例作為演示:一為複製文獻中數學案例，說明本研究方法的延伸性，二為使用簡易常見工程系統(彈簧阻尼系統)，說明研究方法的有效性，三為真實工程車輛案例，說明研究方法的運用性。本研究不只探討動態模型結果之資訊擷取，同時完整提供動態模型驗證手法及程序上的輔助。 | zh_TW |
| dc.description.abstract | Validation is a vital step in the early stages of modelling. However,challenges in dynamic model validation include: (1) Dynamic performances need to be properly quantified. (2) Current studies emphasize on more model fitness rather than similarity.(3) Dynamic performances and systematic parameters are highly coupled.This thesis focuses on the validation of dynamic models. By using Karhunen–Loève transform (K-L transform) and rearranging of dynamic data, important information can be compared effectively. Together with nonparametric tests, where by using p-value in statistical hypothesis testing to construct a reference coordinate system, it is capable to describe the similarity and the fitness between a computational model and an experimental model, and at the same time, calibrate the model. This method is demonstrated using three cases: a mathematical case from literature to show its extensibility, a simple engineering case – a mass-spring-damper system to show its effectiveness, and a real case of vehicle to show its adaptivity. This thesis not only explores into the acquirement of dynamic modelling output data, but also provides a complete method of dynamic modelling validation and facilitation of the process. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T02:16:09Z (GMT). No. of bitstreams: 1 ntu-106-R04522601-1.pdf: 6597248 bytes, checksum: 7124603eec3e7215064563e936ed6008 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 摘要-i
Abstract-iii 圖目錄-ix 表目錄-x 符號列表-xi 第一章緒論-1 1.1前言-1 1.2研究動機與目的-4 1.2.1研究動機-4 1.2.2研究目的-5 1.3論文架構-6 第二章文獻回顧-8 2.1動態模型驗證-9 2.1.1動態模型輸出數據分析-9 2.1.2模型比對與指標建立-13 2.2小結-15 第三章指標建立-16 3.1無母數檢定概述-16 3.1.1統計學及假設檢定概念-16 3.1.2有母數統計及無母數統計-19 3.2模型比對指標建立-22 3.2.1雷同度-23 3.2.2吻合度-25 3.2.3指標座標圖建立-26 3.3小結-28 第四章研究方法-29 4.1真實系統、模擬、實驗三者關聯-29 4.2動態模型分析-32 4.2.1方法流程-32 4.2.2動態行為量化-33 4.2.3模型結果比對-37 4.3研究方法小結-39 第五章案例探討-40 5.1數學模型案例-40 5.1.1數學模型建構-41 5.1.2單一數學模型分析-42 5.1.3大小樣本數與多個數學模型分析-45 5.1.4結果與討論-47 5.2彈簧阻尼系統案例-48 5.2.1彈簧阻尼系統模型-48 5.2.2大小樣本數與模型參數調整分析-50 5.2.3結果與討論-54 5.3實際車輛案例-55 5.3.1車輛摩擬與實驗架構-55 5.3.2單一車輛模型分析-57 5.3.3車輛模型參數調整分析-58 5.3.4結果與討論-60 第六章結論-61 6.1研究貢獻-61 6.2未來工作-62 附錄A統計表-63 參考文獻-66 | |
| dc.language.iso | zh-TW | |
| dc.subject | K-L轉換 | zh_TW |
| dc.subject | 動態模型分析 | zh_TW |
| dc.subject | 模型驗證指標 | zh_TW |
| dc.subject | 吻合度 | zh_TW |
| dc.subject | 雷同度 | zh_TW |
| dc.subject | 無母數檢定 | zh_TW |
| dc.subject | 模型驗證 | zh_TW |
| dc.subject | Nonparametric test | en |
| dc.subject | Dynamic simulation analysis | en |
| dc.subject | Model validation | en |
| dc.subject | Similarity metric | en |
| dc.subject | Fitness metric | en |
| dc.subject | K-L transform | en |
| dc.title | 使用吻合與雷同指標以驗證工程系統之動態行為 | zh_TW |
| dc.title | Model Validation on Engineering System with Dynamic Performances Using Statistical Similarity and Fitness Metrics | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 劉霆(Tyng Liu),吳文方(Wen-Fang Wu) | |
| dc.subject.keyword | 模型驗證,無母數檢定,K-L轉換,雷同度,吻合度,模型驗證指標,動態模型分析, | zh_TW |
| dc.subject.keyword | Model validation,Nonparametric test,K-L transform,Fitness metric,Similarity metric,Dynamic simulation analysis, | en |
| dc.relation.page | 69 | |
| dc.identifier.doi | 10.6342/NTU201704219 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-10-12 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| 顯示於系所單位： | 機械工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-106-1.pdf 未授權公開取用 | 6.44 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。