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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86712
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor何昊哲(Hao-Che ho)
dc.contributor.authorHsin-Yu Chenen
dc.contributor.author陳昕妤zh_TW
dc.date.accessioned2023-03-20T00:12:52Z-
dc.date.copyright2022-08-04
dc.date.issued2022
dc.date.submitted2022-07-29
dc.identifier.citation王如意、易任. (1979). 應用水文學. 國立編譯館. 連惠邦. (2017). 土砂災害與防治. 五南圖書出版股份有限公司. Admiraal, D. M., Stansbury, J. S., & Haberman, C. J. (2004). Case study: Particle velocimetry in a model of lake Ogallala. Journal of Hydraulic Engineering, 130(7), 599-607. Adrian, R. J. (1984). Scattering particle characteristics and their effect on pulsed laser measurements of fluid flow: speckle velocimetry vs particle image velocimetry. Applied Optics, 23(11), 1690-1691. Adrian, R. J. (1988). Double exposure, multiple-field particle image velocimetry for turbulent probability density. Optics and Lasers in Engineering, 9(3-4), 211-228. Adrian, R. J. (1991). Particle-imaging techniques for experimental fluid mechanics. Annual review of fluid mechanics, 23(1), 261-304. Adrian, R. J. (2005). Twenty years of particle image velocimetry. Experiments in Fluids, 39(2), 159-169. Annan, A., & Cosway, S. (1992). Ground penetrating radar survey design. 5th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems. Barker, D., & Fourney, M. (1977). Measuring fluid velocities with speckle patterns. Optics letters, 1(4), 135-137. Bikash, P., & Ajoy, K. (2016). Site Selection and Feasibility Study for Hydropower Projects. In Hydroelectric Energy. CRC Press. Blanckaert, K., & Lemmin, U. (2006). Means of noise reduction in acoustic turbulence measurements. Journal of Hydraulic Research, 44(1), 3-17. Boiten, W. (2003). Hydrometry : IHE Delft lecture note series. CRC press. Briers, D., Duncan, D. D., Hirst, E. R., Kirkpatrick, S. J., Larsson, M., Steenbergen, W., Stromberg, T., & Thompson, O. B. (2013). Laser speckle contrast imaging: theoretical and practical limitations. Journal of biomedical optics, 18(6), 066018. Carrière, S. D., Chalikakis, K., Sénéchal, G., Danquigny, C., & Emblanch, C. (2013). 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Uncertainty analysis for non-intrusive measurement of river discharge using image velocimetry. The University of Iowa. Kim, Y., Muste, M., Hauet, A., Krajewski, W. F., Kruger, A., & Bradley, A. (2008). Stream discharge using mobile large‐scale particle image velocimetry: A proof of concept. Water Resources Research, 44(9). Klema, M. R., Pirzado, A. G., Venayagamoorthy, S. K., & Gates, T. K. (2020). Analysis of acoustic Doppler current profiler mean velocity measurements in shallow flows. Flow Measurement and Instrumentation, 74, 101755. Lewis, Q. W., & Rhoads, B. L. (2018). LSPIV Measurements of Two‐Dimensional Flow Structure in Streams Using Small Unmanned Aerial Systems: 1. Accuracy Assessment Based on Comparison With Stationary Camera Platforms and In‐Stream Velocity Measurements. Water Resources Research, 54(10), 8000-8018. Lurton, X. (2002). An introduction to underwater acoustics : principles and applications (Vol. 2). Springer. Manfreda, S., McCabe, M. F., Miller, P. E., Lucas, R., Pajuelo Madrigal, V., Mallinis, G., Ben Dor, E., Helman, D., Estes, L., & Ciraolo, G. (2018). On the use of unmanned aerial systems for environmental monitoring. Remote Sensing, 10(4), 641. Marzouk, Y., & Hart, D. (1998). Asymmetric autocorrelation function to resolve directional ambiguity in PIV images. Experiments in Fluids, 25(5), 401-408. Meinhart, C. D., Wereley, S. T., & Santiago, J. G. (1999). PIV measurements of a microchannel flow. Experiments in Fluids, 27(5), 414-419. Melcher, N., Costa, J., Haeni, F., Cheng, R., Thurman, E., Buursink, M., Spicer, K., Hayes, E., Plant, W., & Keller, W. (2002). River discharge measurements by using helicopter‐mounted radar. Geophysical Research Letters, 29(22), 41-41-41-44. Meynart, R. (1980). Equal velocity fringes in a Rayleigh-Benard flow by a speckle method. Applied Optics, 19(9), 1385-1386. Meynart, R. (1983). Instantaneous velocity field measurements in unsteady gas flow by speckle velocimetry. Applied Optics, 22(4), 535-540. Morang, A., Larson, R., & Gorman, L. (1997). Monitoring the coastal environment; part III: geophysical and research methods. Journal of Coastal Research, 1064-1085. Muste, M., Fujita, I., & Hauet, A. (2008). Large‐scale particle image velocimetry for measurements in riverine environments. Water Resources Research, 44(4). Muste, M., Yu, K., & Spasojevic, M. (2004). Practical aspects of ADCP data use for quantification of mean river flow characteristics; part I: moving-vessel measurements. Flow Measurement and Instrumentation, 15(1), 1-16. Neal, A. (2004). Ground-penetrating radar and its use in sedimentology: principles, problems and progress. Earth-science reviews, 66(3-4), 261-330. Neal, A., & Roberts, C. L. (2000). Applications of ground-penetrating radar (GPR) to sedimentological, geomorphological and geoarchaeological studies in coastal environments. Geological Society, London, Special Publications, 175(1), 139-171. Peters, L, Daniels, J. J., & Young, J. D. (1994). Ground penetrating radar as a subsurface environmental sensing tool. Proceedings of the IEEE, 82(12), 1802-1822. Planchon, O., Silvera, N., Gimenez, R., Favis-Mortlock, D., Wainwright, J., Le Bissonnais, Y., & Govers, G. (2005). An automated salt-tracing gauge for flow-velocity measurement. Earth Surface Processes and Landforms, 30(7), 833-844. Raffel, M., Willert, C. E., & Kompenhans, J. (1998). Particle image velocimetry: a practical guide (Vol. 2). Springer. Ran, Q. h., Li, W., Liao, Q., Tang, H. l., & Wang, M. y. (2016). Application of an automated LSPIV system in a mountainous stream for continuous flood flow measurements. Hydrological Processes, 30(17), 3014-3029. Santiago, J. G., Wereley, S. T., Meinhart, C. D., Beebe, D., & Adrian, R. J. (1998). A particle image velocimetry system for microfluidics. Experiments in Fluids, 25(4), 316-319. Scannell, B. D., Lenn, Y.-D., & Rippeth, T. P. (2022). 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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/86712-
dc.description.abstract近年來極端降雨事件對世界各國造成不少災損,為提升洪水期間之災害應變能力,有效的河川流量監測顯得格外重要。考量觀測安全性及儀器自身限制,目前在高洪峰期間的流量量測仍多使用率定曲線進行推估。然而在高含砂水流的衝擊下,利用此種方式推算流量會增添許多不確定性。目前許多研究嘗試以非接觸式的方法量測流速與水深推估流量,本研究選擇大規模粒子影像測速法測量流速,再結合數值方法以淺水波方程式模擬水下地形,期能以安全性高、效率高及成本低的方法精進洪水期間之現地流量觀測。 本研究分為流速量測及地形數值模擬兩步驟執行。實驗於長30 m、寬1 m、高1 m之室內循環水槽進行,利用變換流速、突起物個數及突起物配置,設計五組不同的案例。實驗過程中先透過錄影記錄觀測區域內的示蹤粒子,再使用大規模粒子影像測速法辨識流速。考量數值模擬需依賴表面流速資料作為初始條件,因此將實驗所得流速與聲波都卜勒流速儀之擬合結果進行驗證,用以衡量數據可靠度;另外在數值模擬上,運用有限差分法搭配Arakawa C型網格對淺水波方程式離散,便能一次性地計算出流場內之二維水深,在假設水面高程不隨時間變化的前提下,間接推估出水下三維地形。根據實驗結果指出,與聲波都卜勒流速儀擬合結果相比,各組計算之平均表面流速誤差為3.9%;從變因分析發現,即使提升流速、增加突起物個數及縮短突起物間距會造成模擬誤差,但水下地形模擬之精度仍有95%。研究結果證實,在室內試驗條件下運用大規模粒子影像測速法與淺水波方程式推算水下地形是可行的,建議未來研究可進一步將此方法學擴展至更大尺度的水槽或現地進行驗證。zh_TW
dc.description.abstractExtreme climate events, such as heavy rainfall, cause damage to many countries around the globe in recent years. Thus, effective river discharge monitoring is an integral part of enhancing the emergency response ability during flooding. Due to safety concerns and equipment limitations, the rating curve method is often used to estimate the discharge in high flow period; however, the high river sediment concentration generates uncertainties of the river discharge estimation. Therefore, a study of discharge estimation method without physical contact with the water is essential. The study conducted a series of model tests in a circulating water tank to investigate the bathymetry by various flow velocity and hump configuration. The test procedure can be divided into two steps, namely, velocity measurement and numerical simulation of the terrains. The surface flow velocity was identified by Large Scale Particle Image Velocimetry (LSPIV) method and verified with the fitting result of Acoustic Doppler Velocimetry (ADV). In addition, the finite difference numerical simulation analyzed 2D depths in the flow field by discretizing the shallow water equations with the Arakawa C-grid. The bathymetry was then estimated under the assumption of a time invariant system. The experimental results show that the deviation of measuring surface velocity is 3.9%. The estimation accuracy of a bathymetry is higher then 95%. Based on the results, it is feasible to determine the bathymetry in physical model tests using LSPIV method and the shallow water equations.en
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dc.description.tableofcontents摘要 III ABSTRACT IV 目錄 V 表目錄 VIII 圖目錄 IX 第一章 緒論 1 1.1 研究動機 1 1.2 研究目的 2 1.3 研究流程及架構 3 第二章 文獻回顧 4 2.1 流速量測 4 2.2 水深量測 13 2.3 淺水波方程式 18 2.4 小結 20 第三章 研究方法 21 3.1 實驗設計與流程 21 3.1.1 實驗水槽與突起物模型 21 3.1.2 ADV量測流速 23 3.1.3 影像測量 26 3.1.4 實驗操作流程 30 3.1.5 實驗案例介紹 31 3.2 大規模粒子影像測速法 32 3.2.1 影像前處理 32 3.2.2 影像校正 34 3.2.3 影像測速 35 3.3 水下地形模擬 37 3.3.1 淺水波方程式 37 3.3.2 數值方法 40 第四章 研究結果與討論 42 4.1 案例一 42 4.1.1 ADV擬合結果 42 4.1.2 質詢窗尺寸選擇 44 4.1.3 表面流速推估水深結果 47 4.1.4 地形結果分析與討論 48 4.2 案例二 51 4.2.1 影像辨識流速與ADV擬合結果驗證 51 4.2.2 表面流速推估水深結果 55 4.2.3 地形結果分析與討論 56 4.3 案例三 58 4.3.1 影像辨識流速與ADV擬合結果驗證 58 4.3.2 表面流速推估水深結果 61 4.3.3 地形結果分析與討論 62 4.4 案例四 65 4.4.1 影像辨識流速與ADV擬合結果驗證 65 4.4.2 表面流速推估水深結果 68 4.4.3 地形結果分析與討論 69 4.5 案例五 71 4.5.1 影像辨識流速與ADV擬合結果驗證 71 4.5.2 表面流速推估水深結果 74 4.5.3 地形結果分析與討論 75 4.6 小結 77 第五章 結論與建議 79 5.1 結論 79 5.2 建議 80 參考文獻 81
dc.language.isozh-TW
dc.subject淺水波方程式zh_TW
dc.subject大尺度粒子影像測速法zh_TW
dc.subject有限差分法zh_TW
dc.subject水下地形模擬zh_TW
dc.subject大尺度粒子影像測速法zh_TW
dc.subject淺水波方程式zh_TW
dc.subject有限差分法zh_TW
dc.subject水下地形模擬zh_TW
dc.subjectLarge Scale Particle Image Velocimetryen
dc.subjectLarge Scale Particle Image Velocimetryen
dc.subjectBathymetryen
dc.subjectFinite difference methoden
dc.subjectShallow water equationsen
dc.subjectBathymetryen
dc.subjectFinite difference methoden
dc.subjectShallow water equationsen
dc.title探討水下地形變化與表面流速關係之研究zh_TW
dc.titleModel tests on the relationship between surface velocity and bathymetryen
dc.typeThesis
dc.date.schoolyear110-2
dc.description.degree碩士
dc.contributor.oralexamcommittee韓仁毓(Jen-Yu Han),甯方璽(Fang-Shii Ning)
dc.subject.keyword大尺度粒子影像測速法,淺水波方程式,有限差分法,水下地形模擬,zh_TW
dc.subject.keywordLarge Scale Particle Image Velocimetry,Shallow water equations,Finite difference method,Bathymetry,en
dc.relation.page88
dc.identifier.doi10.6342/NTU202201858
dc.rights.note同意授權(全球公開)
dc.date.accepted2022-08-01
dc.contributor.author-college工學院zh_TW
dc.contributor.author-dept土木工程學研究所zh_TW
dc.date.embargo-lift2024-08-01-
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