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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50577
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor卿建業
dc.contributor.authorYi-Kuang Panen
dc.contributor.author潘怡光zh_TW
dc.date.accessioned2021-06-15T12:47:02Z-
dc.date.available2017-07-26
dc.date.copyright2016-07-26
dc.date.issued2016
dc.date.submitted2016-07-22
dc.identifier.citationG.E.P Box and G. Jenkins. Time series analysis: Forecasting and control. Holden Day, 1970.
Phoon, K. K. (1995). Reliability-based design of foundations for transmission linestructures, Ph.D. Dissertation, Cornell University, Ithaca, NY.
Ahmed, A. and Soubra, A.-H. (2012). Probabilistic analysis of strip footings resting on a spatially random soil using subset simulation approach. Georisk, 6(3), 188-201.
Ahmed, A. and Soubra, A.-H. (2014). Probabilistic analysis at the serviceability limit state of two neighboring strip footings resting on a spatially random soil. Structural Safety, 49, 2-9.
Al-Bittar, T. and Soubra, A.-H. (2014). Probabilistic analysis of strip footings resting on spatially varying soils and subjected to vertical or inclined loads. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 140(4), 04013043.
Ching, J., Hu, Y.G., Yang, Z.Y., Shiao, J.Q., Chen, J.C., and Li, Y.S. (2011). Reliability-based design for allowable bearing capacity of footings on rock masses by considering angle of distortion. International Journal of Rock Mechanics and Mining Sciences, 48, 728-740.
Ching, J. and Phoon, K.K. (2013a). Mobilized shear strength of spatially variable soils under simple stress states. Structural Safety, 41, 20-28.
Ching, J. and Phoon, K.K. (2013b). Probability distribution for mobilized shear strengths of spatially variable soils under uniform stress states, Georisk, 7(3), 209-224.
Ching, J., Phoon, K.K., and Kao, P.H. (2014). Mean and variance of the mobilized shear strengths for spatially variable soils under uniform stress states. ASCE Journal of Engineering Mechanics, 140(3), 487-501.
Fenton, G.A. and Griffiths, D.V. (2002). Probabilistic foundation settlement on spatially random soil. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 128(5), 381-390.
Fenton, G.A. and Griffiths, D.V. (2005). Three-dimensional probabilistic foundation settlement. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 131(2), 232-239.
Griffiths, D.V. and Fenton, G.A. (2009). Probabilistic settlement analysis by stochastic and random finite-element methods. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 135(11), 1629-1637.
Griffiths, D.V., Paiboon, J., Huang, J., and Fenton, G.A. (2012). Homogenization of geomaterials containing voids by random fields and finite elements. International Journal of Solids and Structures, 49, 2006-2014.
Houy, L., Breysse, D., and Denis, A. (2005). Influence of soil heterogeneity on load redistribution and settlement of a hyperstatic three-support frame. Geotechnique, 55(2), 163-170.
Jha, S.K. and Ching, J. (2013). Simulating spatial averages of stationary random field using Fourier series method. ASCE Journal of Engineering Mechanics, 139(5), 594-605.
Jimenez, R. and Sitar, N. (2009). The importance of distribution types on finite element analyses of foundation settlement. Computers and Geotechnics, 36, 474-483.
Nour, A., Slimani, A., and Laouami, N. (2002). Foundation settlement statistics via finite element analysis. Computers and Geotechnics, 29, 641-672.
Paiboon, J., Griffiths, D.V., Huang, J., and Fenton, G.A. (2013). Numerical analysis of effective elastic properties of geomaterials containing voids using 3D random fields and finite elements. International Journal of Solids and Structures, 50, 3233-3241.
Paice, G.M., Griffiths, D.V., and Fenton, G.A. (1996). Finite element modeling of settlements on spatially random soil. ASCE Journal of Geotechnical Engineering, 122(9), 777-779.
Rungbanaphana, P., Honjo, Y., and Yoshida, I. (2010). Settlement prediction by spatial-temporal random process using Asaoka’s method. Georisk, 4(4), 174-185.
Vanmarcke, E.H. (1977). Probabilistic modeling of soil profiles. ASCE Journal of Geotechnical Engineering Division, 103(11), 1227-1246.
Vanmarcke, E.H. (1984). Random Fields: Analysis and Synthesis, MIT Press, Cambridge, Mass.
G.A. Fenton and E.H. Vanmarcke. (1990). Simulation of random fields via local average subdivision. Journal of Geotechnical Engineering Mechanics, 116(8):1733--1749.
Ching, J. Tong, X.W., and Hu, Y.G. (2016). Effective Young's modulus for a spatially variable soil mass subjected to a simple stress state. Georisk, 10(1), 11-26.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50577-
dc.description.abstract由於土壤是天然材料,其形成受自然環境影響甚巨,材料性質較為複雜,但在大地工程問題中為了簡化分析,經常假設土體為均質。本研究探討具空間變異性土壤之楊氏模數,若此土壤須以一均質土壤來模擬時,該如何決定此均質土壤的楊氏模數?為了回答此問題,本研究以隨機有限元素法模擬具空間變異性土壤的受力變形狀況,對3D簡單土體模型施以軸向位移,以所得應力反推土壤的整體楊氏模數,定義此整體楊氏模數為代表此具空間變異性土壤之有效楊氏模數。
本研究試圖以簡單的數學平均來估計有效楊氏模數,發現在3D簡單土體模型問題中,有效楊氏模數可以適當的空間平均來估計其值以及統計性質(平均值、變異係數),對於等向性案例,可用幾何平均來估計,對於層狀案例,水平方向可用算術平均,垂直方向可用調和平均來估計,對於柱狀案例,水平方向可用幾何平均,垂直方向可用算術平均來估計;而簡化的彈簧串並聯模式則適用於各種不同方向性的隨機場案例,以及應力應變分布不均的基本土體模型案例。
Fenton and Griffiths (2002, 2005)曾研究過相關問題,他們發現在淺基礎問題中,若其下為等向性空間變異的土壤,則此基礎所感受到土壤的有效楊氏模數的統計性質,可用基礎下方土壤楊氏模數幾何平均的統計性質來估計;本研究在3D基本土體模型問題的主要結論與Fenton and Griffiths一致,且更為強大,我們發現不只是有效楊氏模數的統計性質,它的數值亦可以適當的空間平均來估計,然而,當我們回到淺基礎問題時,卻發現依然僅有統計性質可被估計,對於基本土體模型的結論不適用於淺基礎,我們猜測可能是淺基礎問題應力應變分布不均,再次以應力應變分布不均的基本土體模型問題來驗證,但發現此猜測錯誤,對於兩種問題差異的部分,仍需更進一步的研究。
zh_TW
dc.description.abstractIn order to simplify the geotechnical problems, engineers usually assumed the soil to be homogeneous. However, the soil was formed naturally with complicated processes, it should not be homogeneous. If we have to use a value to represent its property, how to determine this value? This study focus on the Young’s modulus. We use random finite element analysis to simulate a soil mass with spatially variable Young’s modulus subjected to displacement-controlled 1D compression and back-calculate the overall Young’s modulus by the stress responses. Define the overall Young’s modulus as the effective Young’s modulus(Eeff).
We investigate whether the effective Young’s modulus can be strongly correlated to any spatial average. For the 3D elementary soil mass problems, we find that the numerical vales and statistics of effective Young’s modulus can be approximated by appropriate spatial averages. For isotropic cases, Eeff can be approximated by geometric mean. For layer cases, Eeff can be approximated by arithmetic mean (Ea) when loading direction is parallel to the layers and can be approximated by harmonic mean (Eg) when loading direction is perpendicular to the layers. For column cases, Eeff can be approximated by harmonic mean(Eh) when loading direction is parallel to the columns and can be approximated by geometric mean when loading direction is perpendicular to the columns. And the unified spatial average model can approximate Eeff in every case above without switch among Ea, Eg and Eh.
Fenton and Griffiths (2002, 2005) studied probabilistic foundation settlement, and they found that for foundations on soils with isotropic SOFs, Eeff can be modeled as Eg of the E random field over a prescribed domain under the footing. For elementary soil mass problems, we have the consistent and more stronger results. We find that not only the statistics but also the numerical values of Eeff can be approximated by appropriate apatial averages. However, when we go back to foundation problems, we find only the statistics of Eeff can be approximated by apatial averages. The reason why the results of elementary soil mass can’t be applied on the foundation problems needs more investigation.
en
dc.description.provenanceMade available in DSpace on 2021-06-15T12:47:02Z (GMT). No. of bitstreams: 1
ntu-105-R03521111-1.pdf: 11940095 bytes, checksum: 7492e685a485747d0b1bb975cadb31b8 (MD5)
Previous issue date: 2016
en
dc.description.tableofcontents目錄
誌謝 I
中文摘要 II
Abstract III
符號表 V
目錄 VI
圖目錄 VIII
表目錄 X
第一章 緒論 1
1.1 研究背景 1
1.2 研究目的與方法簡述 2
1.3 本文內容 3
第二章 文獻回顧 4
2.1 隨機場 4
2.1.1 土壤的空間變異性 4
2.1.2 隨機場模型 6
2.1.3 建立隨機場 7
2.1.4 空間平均及平均效應 8
2.2相關研究 10
2.2.1 具空間變異性土體的淺基礎問題 11
2.2.2 二維基本土體模型問題 12
第三章 研究方法 14
3.1 楊氏模數隨機場 16
3.2有限元素分析(ABAQUS)模型 18
3.2.1 基本土體模型 18
3.2.2 方形基腳模型 20
3.3 隨機場的空間平均 23
3.3.1 基本空間平均:算術(Ea)、幾何(Eg)、調和(Eh) 23
3.3.2 串並聯模型(Et,P-S) 26
第四章 結果分析與比較 29
4.1 基本土體模型 29
4.1.1 等向性案例(δx = δy = δz = δ) 29
4.1.2 層狀土案例(δx = δy = ∞,δz = δ) 33
4.1.3 柱狀土案例(δx = δy = δ,δz = ∞) 36
4.1.4 串並聯模型在各案例的結果 38
4.2 方形基腳模型 39
4.2.1 等向性案例(δx = δy = δz = δ) 39
4.2.2 層狀土案例(δx = δy = ∞,δz = δ) 43
4.3 軟芯基本土體模型 44
第五章 結論與建議 47
5.1 結論 47
5.2 未來方向與建議 48
參考文獻 50
附錄 三維基本土體模型 53
附錄 基腳模型 70
dc.language.isozh-TW
dc.title以三維基本土體模型探討具空間變異性土體的有效楊氏模數zh_TW
dc.titleEffective Young’s modulus for a three-dimensional spatially variable elementary soil massen
dc.typeThesis
dc.date.schoolyear104-2
dc.description.degree碩士
dc.contributor.oralexamcommittee劉家男,林志平
dc.subject.keyword隨機場,關聯性長度,空間變異性,有限元素分析,彈性模數,zh_TW
dc.subject.keywordrandom field,scale of fluctuation,spatial variability,finite element analysis,elastic modulus,en
dc.relation.page73
dc.identifier.doi10.6342/NTU201601247
dc.rights.note有償授權
dc.date.accepted2016-07-25
dc.contributor.author-college工學院zh_TW
dc.contributor.author-dept土木工程學研究所zh_TW
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