- IUT Repository Home
- →
- Civil and Environmental Engineering (CEE)
- →
- Thesis
- →
- Graduate
- →
- 2023
- →
- View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
| dc.contributor.author | Islam, Samiul | |
| dc.date.accessioned | 2024-04-25T05:43:26Z | |
| dc.date.available | 2024-04-25T05:43:26Z | |
| dc.date.issued | 2023-09-30 | |
| dc.identifier.citation | Andrus, R.D. and Stokoe II, K.H., 2000. Liquefaction resistance of soils from shear-wave velocity. Journal of geotechnical and geoenvironmental engineering, 126(11), pp.1015- 1025. Andrus, R.D. and Stokoe, K.H., 1999. Liquefaction resistance based on shear wave velocity. Andrus, R.D., Chung, R.M., Juang, C.H. and Stokoe, K.H., 2003. Guidelines for evaluating liquefaction resistance using shear wave velocity measurement and simplified procedures. US Department of Commerce, National Institute of Standards and Technology. Andrus, R.D., Fairbanks, C.D., Zhang, J., Camp III, W.M., Casey, T.J., Cleary, T.J. and Wright, W.B., 2006. Shear-wave velocity and seismic response of near-surface sediments in Charleston, South Carolina. Bulletin of the Seismological Society of America, 96(5), pp.1897-1914. Andrus, R.D., Mohanan, N.P., Piratheepan, P., Ellis, B.S. and Holzer, T.L., 2007, June. Predicting shear-wave velocity from cone penetration resistance. In Proceedings of the 4th international conference on earthquake geotechnical engineering, Thessaloniki, Greece (Vol. 2528). Anbazhagan, P., Basavaraj, S. and Premalatha, K.V., 2011. Liquefaction hazard mapping of Chennai, India using SPT data. Ansari, A., Zahoor, F., Rao, K.S. and Jain, A.K., 2023. Seismic response and vulnerability evaluation of Jammu Region (Jammu and Kashmir). Indian Geotechnical Journal, 53(3), pp.509-522. Ansary, M.A. and Rashid, M.A., 2000, July. Generation of liquefaction potential map for Dhaka, Bangladesh. In 8th ASCE Specialty Conference on Probabilistic Mechanics and Structural Reliability (pp. 24-26). Ashikuzzaman, M., Hossain, A. and Salan, M.S.A., 2023. Liquefaction Assessment of Rajshahi City Corporation, Bangladesh. Indian Geotechnical Journal, 53(2), pp.455-464. 80 Arulmoli, K., Arulanandan, K. and Seed, H.B., 1985. New method for evaluating liquefaction potential. Journal of Geotechnical Engineering, 111(1), pp.95-114. Al-Hussaini, T.M., Hossain, T.R. and Al-Noman, M.N., 2012. Proposed changes to the geotechnical earthquake engineering provisions of the Bangladesh National Building Code. Geotechnical Engineering Journal of the SEAGS & AGSSEA, 43(2), pp.1-7. AASHTO., 2017. LRFD Bridge Design Specifications, Seventh Edition, American Association of State Highway and Transportation Officials, Washington, DC Asaduzzaman, A.T.M., Nasreen, N. and Olsen, H., 1999. Urban geology of Dhaka, Bangladesh. Atlas of urban geology, 11. Akhter, S.H., 2010. Earthquakes of dhaka. Environment of Capital Dhaka—Plants wildlife gardens parks air water and earthquake. Asiatic Society of Bangladesh, pp.401-426. Anderson, J.G., Lee, Y., Zeng, Y. and Day, S., 1996. Control of strong motion by the upper 30 meters. Bulletin of the Seismological Society of America, 86(6), pp.1749-1759. An, T.K. and Kim, M.H., 2010, October. A new diverse AdaBoost classifier. In 2010 International conference on artificial intelligence and computational intelligence (Vol. 1, pp. 359-363). IEEE. Boulanger, R.W. and Idriss, I.M., 2016. CPT-based liquefaction triggering procedure. Journal of Geotechnical and Geoenvironmental Engineering, 142(2), p.04015065. Brankman, C.M. and Baise, L.G., 2008. Liquefaction susceptibility mapping in Boston, Massachusetts. Environmental & Engineering Geoscience, 14(1), pp.1-16. Boulanger, R.W. and Idriss, I.M., 2014. CPT and SPT based liquefaction triggering procedures. Report No. UCD/CGM.-14, 1. Bolt, B.A., 1987. Site specific study of seismic intensity and ground motion parameters for proposed Jamuna river bridge. Bangladesh: a report on Jamuna Bridge Study. Bilham, R. and England, P., 2001. Plateau ‘pop-up’in the great 1897 Assam earthquake. Nature, 410(6830), pp.806-809. Bhunia, G.S., Shit, P.K. and Maiti, R., 2018. Comparison of GIS-based interpolation methods for 81 spatial distribution of soil organic carbon (SOC). Journal of the Saudi Society of Agricultural Sciences, 17(2), pp.114-126. Borcherdt, R.D., 1994. Estimates of site-dependent response spectra for design (methodology and justification). Earthquake spectra, 10(4), pp.617-653. Brevik, E.C., Calzolari, C., Miller, B.A., Pereira, P., Kabala, C., Baumgarten, A. and Jordán, A., 2016. Soil mapping, classification, and pedologic modeling: History and future directions. Geoderma, 264, pp.256-274.Eurocode 8 (Part 5, 1998): “Design provisions for earthquake resistance of structures-foundation, retaining structures and geotechnical aspects”, European Committee for Standardization, Brussels. Cao, Z., Youd, T.L. and Yuan, X., 2013. Chinese dynamic penetration test for liquefaction evaluation in gravelly soils. Journal of Geotechnical and Geoenvironmental Engineering, 139(8), pp.1320-1333. Ceryan, S. and Ceryan, N., 2021. A new index for microzonation of earthquake prone settlement area by considering liquefaction potential and fault avoidance zone: an example case from Edremit (Balikesir, Turkey). Arabian Journal of Geosciences, 14(21), p.2216. Chung, J.W. and Rogers, J.D., 2012. Seismic site classifications for the St. Louis urban area. Bulletin of the Seismological Society of America, 102(3), pp.980-990. Cetin, K.O., Seed, R.B., Kayen, R.E., Moss, R.E., Bilge, H.T., Ilgac, M. and Chowdhury, K., 2018. The use of the SPT-based seismic soil liquefaction triggering evaluation methodology in engineering hazard assessments. MethodsX, 5, pp.1556-1575. Cetin, K.O., Seed, R.B., Kayen, R.E., Moss, R.E., Bilge, H.T., Ilgac, M. and Chowdhury, K., 2016. Summary of SPT based field case history data of cetin (2016) database (No. METU/GTENG 08/16-01). Middle East Technical University. Cetin, K.O., Youd, T.L., Seed, R.B., Bray, J.D., Stewart, J.P., Durgunoglu, H.T., Lettis, W. and Yilmaz, M.T., 2004. Liquefaction-induced lateral spreading at Izmit Bay during the Kocaeli (Izmit)-Turkey earthquake. Journal of Geotechnical and Geoenvironmental Engineering, 130(12), pp.1300-1313. Comprehensive Disaster Management Program, 2009, Seismic hazard and vulnerability 82 assessment of Dhaka, Chittagong, and Sylhet city corporation areas. Final report, Comprehensive Disaster Management Program, pp. 1-106. Council, B.S.S., 2009. NEHRP recommended seismic provisions for new buildings and other structures. Rep. FEMA P, 750. Council, B.S.S., 1998. 1997 Edition NEHRP Recommended Provisions for the Development of Seismic Regulations for New Buildings and Other Structures. FEMA, 302. Chen, B.S. and Mayne, P.W., 1996. Statistical relationships between piezocone measurements and stress history of clays. Canadian Geotechnical Journal, 33(3), pp.488-498. Chen, Q., Wang, C. and Juang, C.H., 2016. Probabilistic and spatial assessment of liquefactioninduced settlements through multiscale random field models. Engineering Geology, 211, pp.135-149. Cummins, P.R., 2007. The potential for giant tsunamigenic earthquakes in the northern Bay of Bengal. Nature, 449(7158), pp.75-78. Chowdhury, I.N., 2016. Neo-deterministic studies for seismic hazard assessment of Bangladesh. Demir, S. and Şahin, E.K., 2022. Liquefaction prediction with robust machine learning algorithms (SVM, RF, and XGBoost) supported by genetic algorithm-based feature selection and parameter optimization from the perspective of data processing. Environmental Earth Sciences, 81(18), p.459. Dobry, R., Borcherdt, R.D., Crouse, C.B., Idriss, I.M., Joyner, W.B., Martin, G.R., Power, M.S., Rinne, E.E. and Seed, R.B., 2000. New site coefficients and site classification system used in recent building seismic code provisions. Earthquake spectra, 16(1), pp.41-67. Drucker, H., Burges, C.J., Kaufman, L., Smola, A. and Vapnik, V., 1996. Support vector regression machines. Advances in neural information processing systems, 9. Engdahl, E.R., Di Giacomo, D., Sakarya, B., Gkarlaouni, C.G., Harris, J. and Storchak, D.A., 2020. ISC‐EHB 1964–2016, an improved data set for studies of Earth structure and global seismicity. Earth and Space Science, 7(1), p.e2019EA000897.F Fabbrocino, S., Lanzano, G., Forte, G., de Magistris, F.S. and Fabbrocino, G., 2015. SPT blow 83 count vs. shear wave velocity relationship in the structurally complex formations of the Molise Region (Italy). Engineering Geology, 187, pp.84-97. Freund Y, Schapire RE (1997) A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 55(1):119–139. Gurung, L. and Chatterjee, K., 2023. Evaluation of Liquefaction Potential of Kolkata City, India: A Deterministic Approach. Pure and Applied Geophysics, 180(1), pp.439-474. Gurung, D., McHugh, C.M., Mondal, D.R., Seeber, L., Steckler, M.S., Bastas-Hernandez, A., Akhter, S.H., Mustaque, S. and Goodbred Jr, S.L., 2014, December. Evidence for a tsunami generated by the 1762 Great Arakan earthquake, Southeastern Bangladesh. In AGU Fall Meeting Abstracts (Vol. 2014, pp. T43B-4732). Green, R.A., Upadhyaya, S., Wood, C.M., Maurer, B.W., Cox, B.R., Wotherspoon, L., Bradley, B.A. and Cubrinovski, M., 2017, September. Relative efficacy of CPT-versus Vs-based simplified liquefaction evaluation procedures. In Proc. 19th Intern. Conf. on Soil Mechanics and Geotechnical Engineering (pp. 1521-1524). Goh, A.T. and Goh, S.H., 2007. Support vector machines: their use in geotechnical engineering as illustrated using seismic liquefaction data. Computers and Geotechnics, 34(5), pp.410-421. Haque, D.M.E., Khan, N.W., Selim, M., Kamal, A.M. and Chowdhury, S.H., 2020. Towards improved probabilistic seismic hazard assessment for Bangladesh. Pure and Applied Geophysics, 177, pp.3089-3118. Hastie, T., Rosset, S., Zhu, J. and Zou, H., 2009. Multi-class adaboost. Statistics and its Interface, 2(3), pp.349-360. House Building Research Institute, Bangladesh National Building Code 2006, 2006. House Building Research Institute, Bangladesh National Building Code 2020, 2021. Holzer, T.L., Toprak, S. and Bennett, M.J., 2002, July. Liquefaction potential index and seismic hazard mapping in the San Francisco Bay area, California. In 7th National Conference on Earthquake Engineering, Boston, USA. Holzer, T.L., 2008. Probabilistic liquefaction hazard mapping. In Geotechnical earthquake 84 engineering and soil dynamics IV (pp. 1-32). Holzer, T.L., Bennett, M.J., Noce, T.E., Padovani, A.C. and Tinsley III, J.C., 2006. Liquefaction hazard mapping with LPI in the greater Oakland, California, area. Earthquake Spectra, 22(3), pp.693-708. Hossain, M.B., Roknuzzaman, M. and Rahman, M.M., 2022. Liquefaction Potential Evaluation by Deterministic and Probabilistic Approaches. Civil Engineering Journal, 8(7), pp.1459- 1481. Hwang, J.H., Chen, C.H. and Juang, C.H., 2005. Liquefaction hazard analysis: A fully probabilistic method. In Earthquake engineering and soil dynamics (pp. 1-15). Hu, J., 2021. A new approach for constructing two Bayesian network models for predicting the liquefaction of gravelly soil. Computers and Geotechnics, 137, p.104304. Islam, M.S., Sharif, T.B. and Akter, F., Assessing Disaster Resilience Planning Approaches and Policy Framework for the Mega City Dhaka of Bangladesh. Idriss, I.M. and Boulanger, R.W., 2010. SPT-based liquefaction triggering procedures. Rep. UCD/CGM-10, 2, pp.4-13. Iai, S., Tsuchida, H. and Koizumi, K., 1989. A liquefaction criterion based on field performances around seismograph stations. Soils and Foundations, 29(2), pp.52-68. Iwasaki, T., 1978. A practical method for assessing soil liquefaction potential based on case studies at various sites in Japan. In Proc. of 2nd Int. National Conf. on Microzonation, 1978 (Vol. 2, pp. 885-896). Iwasaki, T., Tokida, K.I., Tatsuoka, F., Watanabe, S., Yasuda, S. and Sato, H., 1982, June. Microzonation for soil liquefaction potential using simplified methods. In Proceedings of the 3rd international conference on microzonation, Seattle (Vol. 3, No. 2, pp. 1310-1330). Japan Road Association, 1996. Specifications for highway bridges, Part V. Earthquake resistant design, 228. Jena, R., Pradhan, B., Almazroui, M., Assiri, M. and Park, H.J., 2023. Earthquake-induced liquefaction hazard mapping at national-scale in Australia using deep learning 85 techniques. Geoscience Frontiers, 14(1), p.101460. Juang, C.H. and Jiang, T., 2000. Assessing probabilistic methods for liquefaction potential evaluation. In Soil dynamics and liquefaction 2000 (pp. 148-162). Kayen, R., Moss, R.E.S., Thompson, E.M., Seed, R.B., Cetin, K.O., Kiureghian, A.D., Tanaka, Y. and Tokimatsu, K., 2013. Shear-wave velocity–based probabilistic and deterministic assessment of seismic soil liquefaction potential. Journal of Geotechnical and Geoenvironmental Engineering, 139(3), pp.407-419. Karim, S., Akther, K.M., Khatun, M. and Ali, R.M.E., 2019. Geomorphology and geology of the Dhaka city corporation area-an approach of remote sensing and GIS technique. Int J Astron Astrophys Space Sci, 6(2), pp.7-16. Khaleda, S., Mowla, Q.A. and Murayama, Y., 2017. Dhaka metropolitan area. Urban Development in Asia and Africa: Geospatial Analysis of Metropolises, pp.195-215. Knudsen, K.L., Sowers, J.M., Witter, R.C., Wentworth, C.M. and Helley, E.J., 2000. Description of mapping of quaternary deposits and liquefaction susceptibility, nine-county San Francisco Bay Region, California. Rep. No. United States Geologic Survey Open-File Report 00, 444. Lee, C.Y. and Chern, S.G., 2013. Application of a support vector machine for liquefaction assessment. Journal of Marine Science and Technology, 21(3), p.10. Lu, G.Y. and Wong, D.W., 2008. An adaptive inverse-distance weighting spatial interpolation technique. Computers & geosciences, 34(9), pp.1044-1055. Maurer, B.W., 2017, July. Assessing liquefaction susceptibility using the CPT soil behavior type index. In Proc. 3rd Intern. Conf. on Performance-Based Design in Earthquake Geotechnical Engineering (PBDIII). Maurer, B.W., Green, R.A., Van Ballegooy, S. and Wotherspoon, L., 2019. Development of region-specific soil behavior type index correlations for evaluating liquefaction hazard in Christchurch, New Zealand. Soil Dynamics and Earthquake Engineering, 117, pp.96-105. Martin, G.R. and Dobry, R., 1994. Earthquake site response and seismic code provisions. NCEER 86 Bulletin, 8(4), pp.1-6. Mazumder, R.K., Utsob, M.T.U. and Bhuiyan, M.R., 2018. Seismic vulnerability assessment of medical facilities: A GIS based application for Chittagong, Bangladesh. Malaysian Journal of Civil Engineering, 30(1), pp.97-112. Maheswari, R.U., Boominathan, A. and Dodagoudar, G.R., 2010. Seismic site classification and site period mapping of Chennai City using geophysical and geotechnical data. Journal of Applied Geophysics, 72(3), pp.152-168. Martin, S. and Szeliga, W., 2010. A catalog of felt intensity data for 570 earthquakes in India from 1636 to 2009. Bulletin of the Seismological Society of America, 100(2), pp.562-569. Mhaske, S.Y. and Choudhury, D., 2010. GIS-based soil liquefaction susceptibility map of Mumbai city for earthquake events. Journal of Applied Geophysics, 70(3), pp.216-225. Monaco, P., Marchetti, S., Totani, G. and Calabrese, M., 2005. Sand liquefiability assessment by flat dilatometer test (DMT). In Proceedings of the 16th International Conference on Soil Mechanics and Geotechnical Engineering (pp. 2693-2698). IOS Press. Musashi, J.P., Pramoedyo, H. and Fitriani, R., 2018. Comparison of inverse distance weighted and natural neighbor interpolation method at air temperature data in Malang region. CAUCHY: Jurnal Matematika Murni dan Aplikasi, 5(2), pp.48-54. Mohammady, M., Pourghasemi, H.R. and Amiri, M., 2019. Land subsidence susceptibility assessment using random forest machine learning algorithm. Environmental Earth Sciences, 78, pp.1-12. Meisina, C., Bonì, R., Bozzoni, F., Conca, D., Perotti, C., Persichillo, P. and Lai, C.G., 2022. Mapping soil liquefaction susceptibility across Europe using the analytic hierarchy process. Bulletin of Earthquake Engineering, 20(11), pp.5601-5632. Naji, D.M., Akin, M.K. and Cabalar, A.F., 2021. Evaluation of seismic site classification for Kahramanmaras City, Turkey. Environmental Earth Sciences, 80(3), p.97. Nath, S. K., M. D. Adhikari, S. K. Maiti, N. Devaraj, N. Srivastava, and L. D. Mohapatra. "Earthquake scenario in West Bengal with emphasis on seismic hazard microzonation of 87 the city of Kolkata, India." Natural Hazards and Earth System Sciences 14, no. 9 (2014): 2549-2575. Nath, S.K., Srivastava, N., Ghatak, C., Adhikari, M.D., Ghosh, A. and Sinha Ray, S.P., 2018. Earthquake induced liquefaction hazard, probability and risk assessment in the city of Kolkata, India: its historical perspective and deterministic scenario. Journal of Seismology, 22, pp.35-68. National Earthquake Hazards Reduction Program (US) and Building Seismic Safety Council (US), 2001. NEHRP Recommended Provisions (National Earthquake Hazards Reduction Program) for Seismic Regulations for New Buildings and Other Structures. Building Seismic Safety Council. Ohta, Y. and Goto, N., 1978. Empirical shear wave velocity equations in terms of characteristic soil indexes. Earthquake engineering & structural dynamics, 6(2), pp.167-187. Oldham T (1882) The Cachar earthquake of 10 January 1869. In: Oldham RD (ed) Mem. Geological Survey of India, vol 19, pt.1, pp 1–88 Pal, M., 2006. Support vector machines‐based modelling of seismic liquefaction potential. International Journal for Numerical and Analytical Methods in Geomechanics, 30(10), pp.983-996. Papathanassiou, G., Valkaniotis, S., Chaztipetros, A. and Pavlides, S., 2010. Liquefaction susceptibility map of Greece. Bulletin of the Geological Society of Greece, 43(3), pp.1383- 1392. Pirhadi, N., Hu, J., Fang, Y., Jairi, I., Wan, X. and Lu, J., 2021. Seismic gravelly soil liquefaction assessment based on dynamic penetration test using expanded case history dataset. Bulletin of Engineering Geology and the Environment, 80, pp.8159-8170. Pokhrel, R.M., Kuwano, J. and Tachibana, S., 2012. Geostatistical analysis for spatial evaluation of liquefaction potential in Saitama City. Lowland Technology International, 14(1, June), pp.45-51. Pokhrel, R.M., Gilder, C.E., Vardanega, P.J., De Luca, F., De Risi, R., Werner, M.J. and Sextos, A., 2022. Liquefaction potential for the Kathmandu Valley, Nepal: a sensitivity 88 study. Bulletin of Earthquake Engineering, 20(1), pp.25-51. Pitilakis, K., Gazepis, C. and Anastasiadis, A., 2004, August. Design response spectra and soil classification for seismic code provisions. In Proceedings of the 13th world conference on earthquake engineering, Vancouver, BC, Canada. Rahman, M.A., Wiegand, B.A., Badruzzaman, M. and Ptak, T., 2013. Hydrogeological analysis of the upper Dupi Tila Aquifer, towards the implementation of a managed aquifer-recharge project in Dhaka City, Bangladesh. Hydrogeology Journal, 21(5), p.1071. Rahman, M.Z., Kamal, A.M. and Siddiqua, S., 2018. Near-surface shear wave velocity estimation and V s 30 mapping for Dhaka City, Bangladesh. Natural Hazards, 92, pp.1687-1715. Rahman, M.Z. and Siddiqua, S., 2017. Evaluation of liquefaction-resistance of soils using standard penetration test, cone penetration test, and shear-wave velocity data for Dhaka, Chittagong, and Sylhet cities in Bangladesh. Environmental Earth Sciences, 76, pp.1-14. Rahman, M.Z. and Karim, M.F., 2005. Geological advantages for construction of underground metro railway transit system in Dhaka city. Bangladesh J Geol, 24, pp.19-37. Rahman, M.Z., Siddiqua, S. and Kamal, A.M., 2020. Seismic source modeling and probabilistic seismic hazard analysis for Bangladesh. Natural Hazards, 103, pp.2489-2532. Rahman, M.Z., Siddiqua, S. and Kamal, A.M., 2015. Liquefaction hazard mapping by liquefaction potential index for Dhaka City, Bangladesh. Engineering geology, 188, pp.137-147. Robinson, T.P. and Metternicht, G., 2006. Testing the performance of spatial interpolation techniques for mapping soil properties. Computers and electronics in agriculture, 50(2), pp.97-108. Robertson, P.K., 2009. Performance based earthquake design using the CPT. Proc. IS-Tokyo, pp.3- 20. Robertson, P.K., 2016. Cone penetration test (CPT)-based soil behaviour type (SBT) classification system—an update. Canadian Geotechnical Journal, 53(12), pp.1910-1927. Samui, P. and Sitharam, T.G., 2011. Machine learning modelling for predicting soil liquefaction susceptibility. Natural Hazards and Earth System Sciences, 11(1), pp.1-9. 89 Samui, P. and Karthikeyan, J., 2013. Determination of liquefaction susceptibility of soil: a least square support vector machine approach. International Journal for Numerical and Analytical Methods in Geomechanics, 37(9), pp.1154-1161. Sarker, J.K., Ansary, M.A., Islam, M.R. and Safiullah, A.M.M., 2010. Potential losses for Sylhet, Bangladesh in a repeat of the 1918 Srimangal earthquake. Environmental economics, (1, Iss. 1), pp.12-31. Shawe-Taylor, J. and Cristianini, N., 2000. Support vector machines (Vol. 2). Cambridge: Cambridge university press. Sharma, B. and Chetia, M., 2016. Deterministic and probabilistic liquefaction potential evaluation of Guwahati city. Japanese Geotechnical Society Special Publication, 2(22), pp.823-828. Seismic hazard and vulnerability assessment of Dhaka, Chittagong, and Sylhet city corporation areas. Final report, Comprehensive Disaster Management Program (CDMP2009). Dhaka, Bangladesh Seed, H.B. and Idriss, I.M., 1971. Simplified procedure for evaluating soil liquefaction potential. Journal of the Soil Mechanics and Foundations division, 97(9), pp.1249-1273. Seed, H.B., 1982. Ground motions and soil liquefaction during earthquakes. Earthquake engineering research insititue. Seed, H.B., 1979. Soil liquefaction and cyclic mobility evaluation for level ground during earthquakes. Journal of the geotechnical engineering division, 105(2), pp.201-255. Seed, R.B., Cetin, K.O., Moss, R.E., Kammerer, A.M., Wu, J., Pestana, J.M., Riemer, M.F., Sancio, R.B., Bray, J.D., Kayen, R.E. and Faris, A., 2003. Recent advances in soil liquefaction engineering: a unified and consistent framework. In Proceedings of the 26th Annual ASCE Los Angeles Geotechnical Spring Seminar: Long Beach, CA. Sreejaya, K.P., Raghukanth, S.T.G., Gupta, I.D., Murty, C.V.R. and Srinagesh, D., 2022. Seismic hazard map of India and neighbouring regions. Soil Dynamics and Earthquake Engineering, 163, p.107505. Shit, P.K., Bhunia, G.S. and Maiti, R., 2016. Spatial analysis of soil properties using GIS based 90 geostatistics models. Modeling Earth Systems and Environment, 2, pp.1-6. Tinsley, J.C., Youd, T.L., Perkins, D.M. and Chen, A.T.F., 1985. IMPROVING PREDICTIONS OF LIQUEFACTION POTENTIAL. FUTURE DIRECTIONS IN EVALUATING EARTHQUAKE HAZARDS OF SOUTHERN CALIFORNIA, p.293. Tunusluoglu, M.C. and Karaca, O., 2018. Liquefaction severity mapping based on SPT data: a case study in Canakkale city (NW Turkey). Environmental earth sciences, 77, pp.1-29. Toprak, S. and Holzer, T.L., 2003. Liquefaction potential index: field assessment. Journal of Geotechnical and Geoenvironmental Engineering, 129(4), pp.315-322. Tokimatsu, K. and Yoshimi, Y., 1983. Empirical correlation of soil liquefaction based on SPT Nvalue and fines content. Soils and Foundations, 23(4), pp.56-74. Upadhyaya, S., Maurer, B.W., Green, R.A. and Rodriguez-Marek, A., 2021. Selecting the optimal factor of safety or probability of liquefaction triggering for engineering projects based on misprediction costs. Journal of Geotechnical and Geoenvironmental Engineering, 147(6), p.04021026. Upadhyaya, S., Green, R.A., Rodriguez-Marek, A. and Maurer, B.W., 2023. True liquefaction triggering curve. Journal of Geotechnical and Geoenvironmental Engineering, 149(3), p.04023005. Wair, B.R., DeJong, J.T. and Shantz, T., 2012. Pacific Earthquake Engineering Research Center. Whitman, R.V., 1971. Resistance of soil to liquefaction and settlement. Soils and Foundations, 11(4), pp.59-68. Wang, M.X., Huang, D., Wang, G. and Li, D.Q., 2020. SS-XGBoost: a machine learning framework for predicting newmark sliding displacements of slopes. Journal of Geotechnical and Geoenvironmental Engineering, 146(9), p.04020074. Xia, J., Miller, R.D. and Park, C.B., 1999. Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves. Geophysics, 64(3), pp.691-700. Xie, Y., Ebad Sichani, M., Padgett, J.E. and DesRoches, R., 2020. The promise of implementing machine learning in earthquake engineering: A state-of-the-art review. Earthquake 91 Spectra, 36(4), pp.1769-1801. Yegian, M.K. and Vitelli, B.M., 1981. Analysis for liquefaction: empirical approach. Youd, T.L. and Idriss, I.M., 2001. Liquefaction resistance of soils: summary report from the 1996 NCEER and 1998 NCEER/NSF workshops on evaluation of liquefaction resistance of soils. Journal of geotechnical and geoenvironmental engineering, 127(4), pp.297-313. Youd, T.L. and Perkins, D.M., 1978. Mapping liquefaction-induced ground failure potential. Journal of the Geotechnical Engineering Division, 104(4), pp.433-446. Youd, T.L. and Perkins, D.M., 1987. Mapping of liquefaction severity index. Journal of Geotechnical Engineering, 113(11), pp.1374-1392. Zhang, W. and Goh, A.T., 2016. Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression. Geomech. Eng, 10(3), pp.269-284. Zhou, Y., Zhang, H., Li, F. and Qi, P., 2018. Local focus support vector machine algorithm. Journal of Computer Applications, 38(4), p.945. Zhang, Y., Xie, Y., Zhang, Y., Qiu, J. and Wu, S., 2021. The adoption of deep neural network (DNN) to the prediction of soil liquefaction based on shear wave velocity. Bulletin of Engineering Geology and the Environment, 80, pp.5053-5060. Zhou, J., Huang, S., Wang, M. and Qiu, Y., 2021. Performance evaluation of hybrid GA–SVM and GWO–SVM models to predict earthquake-induced liquefaction potential of soil: a multi-dataset investigation. Engineering with Computers, pp.1-19. Zhang, W. and Goh, A.T., 2016. Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression. Geomech. Eng, 10(3), pp.269-284. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/2095 | |
| dc.description | Supervised by Dr. Hossain Md. Shahin, Professor and Head, Department of Civil and Environmental Engineering (CEE), Islamic University of Technology (IUT), Gazipur, Bangladesh. | en_US |
| dc.description.abstract | Integration of regional code-based provisions considering local site effects and updated analytical techniques is a must in the field of seismic site characterization and liquefaction susceptibility assessment. This study introduces provisions from latest regional guidelines to define seismic site class and assess liquefaction susceptibility, utilizing the most comprehensive database developed for Dhaka City and produces vulnerability maps, categorizing regions into various zones based on potential risk factors. Utilizing the latest SPT based co-relationship, coupled with code-based stress reduction factors, liquefaction susceptibility assessment was conducted. Additionally, classification-based supervised machine learning algorithms were utilized to evaluate the performance of the liquefaction susceptibility calculations, which were subsequently used as an input parameter for conducting geo-statistical interpolation, resulting in risk-based zonation maps in terms of liquefaction hazard for the city. The results show that the deposition type of soil plays a significant role in triggering liquefaction in different areas of Dhaka City and the majority portion of the recent artificial fill areas are subjected to high liquefaction potential for 7.0, 7.5 and 8.0 magnitude earthquake. This study also supplements the newly published mandates and provides guidelines according to the code to conduct engineering studies as per recommended seismic site class and liquefaction susceptibility for design applications. A significant increase in the coverage area of seismic site class with low shear wave velocities have been observed, necessitating special infrastructural considerations as per the new codal guidelines compared to past researches. Areas of improvement to evaluate liquefaction susceptibility in the newly published mandate also have been identified. Furthermore, this study also outlines a generalized framework with supplementary policies integrating regional factors into consideration for development of liquefaction susceptibility-based risk maps for any location. The developed liquefaction susceptibility-based zonation map provides a clear visual representation of areas prone to liquefaction, enabling better-informed decision- making for disaster preparedness, risk reduction, and sustainable urban development. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Civil and Environmental Engineering(CEE), Islamic University of Technology(IUT), Board Bazar, Gazipur-1704, Bangladesh | en_US |
| dc.subject | Liquefaction, Earthquake, SPT, Shear Wave Velocity, Machine Learning | en_US |
| dc.title | A Framework for Liquefaction Susceptibility Mapping of Dhaka City Using Latest SPT Based Co-relationship and Regional Factors | en_US |
| dc.type | Thesis | en_US |
Files in this item
This item appears in the following Collection(s)
-
2023 [2]