Piezometer Time-Lag and Pore Pressure Ratio for Identification of Dam Internal Erosion
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[2] Peyras, L., Royet, P., & Boissier, D. (2006). Dam ageing diagnosis and risk analysis: Development of methods to support expert judgment. Canadian Geotechnical Journal, 43(2), 169–186. doi:10.1139/t05-096.
[3] Wang, S. W., Xu, Y. L., Gu, C. S., & Bao, T. F. (2018). Monitoring models for base flow effect and daily variation of dam seepage elements considering time lag effect. Water Science and Engineering, 11(4), 344-354.. doi:10.1016/j.wse.2018.12.004.
[4] Jiang, Z., & Chen, H. (2022). A new early warning method for dam displacement behavior based on non-normal distribution function. Water Science and Engineering, 15(2), 170–178. doi:10.1016/j.wse.2022.04.001.
[5] Zhao, M., Liu, P., Jiang, L., & Wang, K. (2021). The Influence of Internal Erosion in Earthen Dams on the Potential Difference Response to Applied Voltage. Water, 13(23), 3387. doi:10.3390/w13233387.
[6] Foster, M., Fell, R., & Spannagle, M. (2000). The statistics of embankment dam failures and accidents. Canadian Geotechnical Journal, 37(5), 1000–1024. doi:10.1139/t00-030.
[7] Zhang, L. M., Xu, Y., & Jia, J. S. (2009). Analysis of earth dam failures: A database approach. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 3(3), 184–189. doi:10.1080/17499510902831759.
[8] ICOLD. (2019). ICOLD Incident Database Bulletin 99 Update: Statistical Analysis of Dam Failures. Committee on Dam Safety, International Commission on Large Dams (ICOLD), Paris, France.
[9] Donnelly, C. R., & Acharya, A. M. (2020). A Discussion on the Evolution and Application of Quantitative Risk Informed Dam Safety Decision Making. Water Resources Development and Management, 520–548. doi:10.1007/978-981-15-1971-0_52.
[10] Fu, C., Yao, X., Li, T., Shen, H., Wang, Z., & Jiang, J. (2014). Investigation and evaluation of increasing uplift pressure in an arch dam: A case study of the Huaguangtan Dam. KSCE Journal of Civil Engineering, 18(6), 1858–1867. doi:10.1007/s12205-014-0432-3.
[11] Su, H., Chen, Z., & Wen, Z. (2015). Performance improvement method of support vector machine-based model monitoring dam safety. Structural Control and Health Monitoring, 23(2), 252–266. doi:10.1002/stc.1767.
[12] Su, H., Hu, J., & Yang, M. (2015). Dam seepage monitoring based on distributed optical fiber temperature system. IEEE Sensors Journal, 15(1), 9–13. doi:10.1109/JSEN.2014.2335197.
[13] Alonso, E. E., & Pinyol, N. M. (2016). Numerical analysis of rapid drawdown: Applications in real cases. Water Science and Engineering, 9(3), 175–182. doi:10.1016/j.wse.2016.11.003.
[14] Leyla, H., Nadia, S., & Bouchrit, R. (2022). Modeling and predictive analyses related to piezometric level in an earth dam using a back propagation neural network in comparison on non-linear regression. Modeling Earth Systems and Environment, 9(1), 1169–1180. doi:10.1007/s40808-022-01558-5.
[15] Tinoco, J., de Granrut, M., Dias, D., Miranda, T., & Simon, A.-G. (2019). Piezometric level prediction based on data mining techniques. Neural Computing and Applications, 32(8), 4009–4024. doi:10.1007/s00521-019-04392-6.
[16] Salazar, F., Morán, R., Toledo, M. í., & Oñate, E. (2015). Data-Based Models for the Prediction of Dam Behaviour: A Review and Some Methodological Considerations. Archives of Computational Methods in Engineering, 24(1), 1–21. doi:10.1007/s11831-015-9157-9.
[17] Ziggah, Y. Y., & Issaka, Y. (2023). Estimation of dam piezometric water level using new hybrid intelligent models for dam safety assessment. International Journal of Energy and Water Resources, 461–473. doi:10.1007/s42108-023-00252-1.
[18] Hariri-Ardebili, M. A., Mahdavi, G., Nuss, L. K., & Lall, U. (2023). The role of artificial intelligence and digital technologies in dam engineering: Narrative review and outlook. Engineering Applications of Artificial Intelligence, 126, 106813. doi:10.1016/j.engappai.2023.106813.
[19] CAO, W., WU, X., LI, J., & KANG, F. (2024). A review of artificial intelligence in dam engineering. Journal of Infrastructure Intelligence and Resilience, 100122. doi:10.1016/j.iintel.2024.100122.
[20] Rehamnia, I., Al-Janabi, A. M. S., Sammen, S. S., Pham, B. T., & Prakash, I. (2024). Prediction of seepage flow through earth fill dams using machine learning models. HydroResearch, 7, 131–139. doi:10.1016/j.hydres.2024.01.005.
[21] Moradi Nazarpoor, S., Rezaei, M., & Mali, F. (2024). A new fuzzy method for investigating the effects of dam on aquifer: case study of Rudbal dam, south of Iran. Scientific Reports, 14(1), 14503. doi:10.1038/s41598-024-65353-1.
[22] Sarayli, S., Sert, S., & Sonmez, O. (2024). Analysis of Fill Dam Using Finite Element Method and Comparison with Monitoring Results. Water, 16(17), 2387. doi:10.3390/w16172387.
[23] Farajniya, R., Poursorkhabi, R. V., Zarean, A., & Dabiri, R. (2024). Analysis and monitoring of the behavior of a rock fill dam ten years after construction: a case study of the Iran-Madani Dam. Geoenvironmental Disasters, 11(1), 30. doi:10.1186/s40677-024-00295-4.
[24] Nhu, T. Q., Kunsuwan, N., Mairaing, W., Kunsuwan, B., & Chalermpornchai, T. (2024). Behavior of seepage in earth dams through complex foundations using three-dimensional finite element method. Geomechanics and Engineering, 39(3), 273-282. doi:10.12989/gae.2024.39.3.273.
[25] Behshad, A. (2020). Instrumentation issues and problems in earth dams (Case Study; Shah Qasim Dam in Yasouj, Iran). Nexo Revista Científica, 33(02), 737–745. doi:10.5377/nexo.v33i02.10805.
[26] Li, X., Li, Y., Lu, X., Wang, Y., Zhang, H., & Zhang, P. (2019). An online anomaly recognition and early warning model for dam safety monitoring data. Structural Health Monitoring, 19(3), 796–809. doi:10.1177/1475921719864265.
[27] Rong, Z., Pang, R., Xu, B., & Zhou, Y. (2024). Dam safety monitoring data anomaly recognition using multiple-point model with local outlier factor. Automation in Construction, 159, 105290. doi:10.1016/j.autcon.2024.105290.
[28] Chen, S., Gu, C., Lin, C., Wang, Y., & Hariri-Ardebili, M. A. (2020). Prediction, monitoring, and interpretation of dam leakage flow via adaptative kernel extreme learning machine. Measurement, 166, 108161. doi:10.1016/j.measurement.2020.108161.
[29] Olsen, R., & Stephens, I. (2016). Relearning how to look at piezometric data for seepage evaluation. USSD 2016 annual conference, 11-15 April, 2016, Denver, United States.
[30] Radzicki, K., & Stoliński, M. (2024). Seepage monitoring and leaks detection along an earth dam with a multi-sensor thermal-active system. Bulletin of Engineering Geology and the Environment, 83(9). doi:10.1007/s10064-024-03826-3.
[31] Hvorslev, M. J. (1951). Time Lag and Soil Permeability in Ground-Water Observations (No. 36). U.S. Army Waterways Experiment Station, Mississippi, United States.
[32] Bonelli, S., & Royet, P. (2001). Delayed response analysis of dam monitoring data. ICOLD European symposium on dams in a European context, 25-27 June, 2001, Geiranger, Norway.
[33] Razavi, B., Parehkar, M., & Gholami, A. (2011). Investigation on Pore Water Pressure in Core of Karkheh Dam. International Journal of Civil and Environmental Engineering, 5(11), 539-542.
[34] Thongthamchart, C., & Brohmsubha, P. (2014). The Safety Criteria for Geotechnical Instruments on the Internal Erosion in Embankment Dams. International Symposium on DAMS in a Global Environmental Challenges, 1-6 June, Bali, Indonesia.
[35] Wang, S. W., & Bao, T. F. (2013). Monitoring Model for Dam Seepage Based on Lag Effect. Applied Mechanics and Materials, 353–356, 2456–2462. doi:10.4028/www.scientific.net/amm.353-356.2456.
[36] Prasad, R., & Dixit, M. (2020). Performance Monitoring Of Dams through Piezometers-A Case Study. International Journal of Engineering and Applied Sciences, 2, 1-8.
[37] Torabi Haghighi, A., Tuomela, A., & Hekmatzadeh, A. A. (2020). Assessing the Efficiency of Seepage Control Measures in Earthfill Dams. Geotechnical and Geological Engineering, 38(5), 5667–5680. doi:10.1007/s10706-020-01371-w.
[38] Demianiuk, A., & Stefanyshyn, D. (2020). The prognostic modelling of piezometric levels based on seepage monitoring in earthen dams. MATEC Web of Conferences, 322, 01047. doi:10.1051/matecconf/202032201047.
[39] Demianiuk, A., & Stefanyshyn, D. (2023). The case of internal erosion in the earth dam of the Dnipro River Hydropower plants cascade. Proceedings of the Conference: 29th Meeting of European Working Group on Internal Erosion in Embankment Dams, Dikes and Levees and Their Foundations, 2-5 July, Lyon, France.
[40] Geotechnical Engineering Research and Development Center. (2019). Semi-Quantitative Risk Assessment on Stability of Saddle Dikes of Sirikit Dam (Final Report). Electricity Generating Authority of Thailand, Nonthaburi, Thailand. (In Thai).
[41] Research Center for Sustainable Infrastructure Engineering. (2020). Design Report Slurry Cutoff Wall Saddle Dike 4 (Final Report). Electricity Generating Authority of Thailand, Nonthaburi, Thailand. (In Thai).
[42] Chalermpornchai, T., Kunsuwan, B., & Mairaing, W. (2021). Simulation of rock crack and permeability in dam foundation during hydraulic fracturing. International Journal of GEOMATE, 21(86), 55–62. doi:10.21660/2021.86.j2276.
[43] Kunsuwan, B., Chalermpornchai, T., Mairaing, W., & Thepjanthra, W. (2023). Assessment of Hydraulic Fracturing in Earth Dams on Complex Foundations. Journal of Disaster Research, 18(3), 270–279. doi:10.20965/jdr.2023.p0270.
[44] Saejiaw, W., Kunsuwan, B., Mairaing, W., & Chalermpornchai, T. (2023). Evaluation of Hydraulic Fracturing Phenomena in Earth Dam. UBU Engineering Journal, 16(1), 44-56.
[45] Wang, J. J. (2014). Hydraulic fracturing in earth-rock fill dams. John Wiley & Sons, Hoboken, United States. doi:10.1002/9781118725542.
[46] Salari, M., Akhtarpour, A., & Ekramifard, A. (2021). Hydraulic fracturing: a main cause of initiating internal erosion in a high earth-rock fill dam. International Journal of Geotechnical Engineering, 15(2), 207–219. doi:10.1080/19386362.2018.1500122.
[47] Sherard, J. L. (1986). Hydraulic Fracturing in Embankment Dams. Journal of Geotechnical Engineering, 112(10), 905–927. doi:10.1061/(asce)0733-9410(1986)112:10(905).
[48] FEMA P-1032. (2015). Evaluation and monitoring of seepage and internal erosion. Interagency committee on dam safety (ICODS), Federal Emergency Management Agency (FEMA), Washington, United States.
[49] Singharajwarapan, S., & Berry, R. (2000). Tectonic implications of the Nan Suture zone and its relationship to the Sukhothai Fold Belt, Northern Thailand. Journal of Asian Earth Sciences, 18(6), 663–673. doi:10.1016/S1367-9120(00)00017-1.
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