Publications

(1) Graduation Thesis

  • Kim, T. (2021). Deep learning-based prediction of seismic responses and losses of nonlinear structural systems, PhD thesis, Seoul National University
    • “Best thesis award,” College of Engineering Seoul National University (only 4 students were awarded in the entire engineering department)
  • Kim, T. (2017). Enhancing Seismic Fragility Analysis of Structural System: Developing Intensity Measure and Ground Motion Selection Algorithm, MSc thesis, Seoul National University
    • “2017 English Language Master’s Thesis Award,” Institution of Civil Engineers (ICE) and Korean Society of Civil Engineers (KSCE)

(2) Archival Journals

Google Scholar

ORCID

>> Published

  1. Kim, T., and Song, J. (2018). Generalized reliability importance measure using Gaussian mixture, Reliability Engineering and System Safety, 173: 105-115.
  2. Kim, T., Kwon, O., and Song, J. (2019). Response prediction of nonlinear hysteretic systems by deep neural networks, Neural Networks, 111: 1-10.
  3. Kim, T., Song, J., and Kwon, O. (2020). Probabilistic evaluation of seismic responses using deep learning method, Structural Safety, 84: 101913. Ranked as most downloaded and most cited paper
  4. Kim, T., Song, J., and Kwon, O. (2020). Pre- and post-earthquake regional loss assessment using deep learning, Earthquake Engineering and Structural Dynamics, 49(7): 657-678. Ranked as most cited paper
  5. Kim, T., Kwon, O., and Song, J. (2021). Seismic performance of a long-span cable-stayed bridge under spatially varying bi-directional spectrum-compatible ground motions, ASCE Journal of Structural Engineering, 147(4), 04021015.
  6. Kim, T., Kwon, O., and Song, J. (2021). Clustering-based adaptive ground motion selection algorithm for efficient estimation of structural fragilities, Earthquake Engineering and Structural Dynamics, 50(6): 1755-1776.  Ranked as most downloaded paper
  7. Lim, S.1, Kim, T.1, and Song, J. (2022). System-reliability-based disaster resilience analysis: framework and applications to structural systems, Structural Safety, 96: 102202. Ranked as most downloaded paper
  8. Kim, S., and Kim, T. (2022). Machine-learning-based prediction of vortex-induced vibration in long-span bridges using limited information, Engineering Structures, 266: 114551.
  9. Oh, S.1, Kim, T.1, and Song, J. (2023). Bouc-Wen class models considering hysteresis mechanism of RC columns in nonlinear dynamic analysis, International Journal of Non-Linear Mechanics, 148: 104263. Ranked as most downloaded paper
  10. Kim, T., Kwon, O., and Song, J. (2023). Deep learning-based seismic response prediction of hysteretic systems having degradation and pinching, Earthquake Engineering and Structural Dynamics, 52(8): 2384-2406. Ranked as most downloaded paper
  11. Kang, C.1, Kim, T.1, Kwon, O., and Song, J. (2023). Deep neural network-based regional seismic loss assessment considering correlation between EDP residual of building structures, Earthquake Engineering and Structural Dynamics, 52(11): 3414-3434.
  12. Kim, T., Kwon, O., Acosta, J., Fathi-Fazl, R., Fazileh, F., and Cai Zhen. (2023). Review of nonlinear modelling parameters and acceptance criteria in ASCE 41 for seismic evaluation and upgrading of steel structures in Canada, Canadian Journal of Civil Engineering, 50(8): 688-708.
  13. Yi, S., and Kim, T. (2023). System-reliability-based disaster resilience analysis for structures considering aleatory uncertainties in external loads, Earthquake Engineering and Structural Dynamics, 52(15): 4939-4963.
  14. Kim, T., Villacres, M., Shim, J., Kwon, O., and Kim, HK. (2023). Development of a differential load cell negating inertial force, Measurement, 113789.
  15. Kim, T., Kwon, O., and Song, J. (2024). Deep learning-based response spectrum analysis method for building structures, Earthquake Engineering and Structural Dynamics, 53(4): 1638-1655.
  16. Kim, T., and Yi, S. (2024) Accelerated system-reliability-based disaster resilience analysis for structural systems, Structural Safety, 102479.

1: Equal contribution first authors

>> Under Review

  1. Kim, J., Yi, S., Park, J., and Kim, T., Efficient system-reliability-based disaster resilience analysis of structures using importance sampling

(3) Magazine articles

Song, J. and Kim, T. (2018), System reliability perspective on disaster-hazard-resilience of civil structures, the magazine of KSCE, (in Korean)

(4) Conferences (International), selected

  1. Kang, C., and Kim, T. (2023) Seismic resilience assessment of urban communities using Bayesian network, 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14), July 9-13, Dublin, Ireland.
  2. Kang, C., Kim, T., Kwon, O.S., and Song, J. (2022) Deep neural network-based regional seismic loss assessment considering correlation between EDP residuals of building structures, Engineering Mechanics Institute Conference 2022 (EMI 2022), May 31-June 3, Baltimore, USA
  3. Kim, T., and Kim, S. (2022) Data-driven identification for vortex-induced vibrations with imbalanced data, 8th World Conference on Structural Control and Monitoring (8WCSCM), 5-9 June, 2022, Orlando, Florida, USA
  4. Lim, S., Kim, T., Yi, S., Kim, H., and Song, J. (2021), Reliability-redundancy (beta-pi) analysis of cable-stayed bridges under fire hazard from system reliability perspective on disaster resilience, 2021 EMI/PMC Conference, May 25-28, Virtual
  5. Kim, T., Song, J., and Kwon, O.S. (2021), Efficient ground motion selection algorithm for seismic fragility analysis of structural systems, Engineering Mechanics Institute Conference 2021 (EMI 2021), May 25-28, Virtual
  6. Kim, T., Kwon, O.S., and Song, J. (2021), Seismic response of a cable-stayed bridge subjected to spatially varying orthogonal ground motions, 10th International Conference on Bridge Maintenance, Safety and Management, April 11-15, Virtual
  7. Kim, T., Kwon, O.S., and Song, J. (2019), New performance measures for investigating seismic responses of long-span cable-stayed bridges, 2019 International Symposium on Sea-Crossing Bridges, October 24-25, Muan, Korea
  8. Kim, T., Song, J., and Kwon, O.S. (2019), Probabilistic prediction of nonlinear hysteretic responses under stochastic excitations by deep neural network, Engineering Mechanics Institute Conference 2019 (EMI 2019), June 18-21, Pasadena, USA
  9. Kim, T., Song, J., and Kwon, O.S. (2019), Regional seismic loss assessment by deep-learning-based prediction of structural responses, 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13), May 26-30, Seoul, Korea.
  10. Kim, T., and Song, J. (2018). Development of generalized reliability importance measure (GRIM) using Gaussian mixture, 19th IFIP WG7.5 Conference, ETH Zürich, Switzerland 
  11. Kim, T., Kwon, O.S., and Song, J. (2018). Assessment of seismic responses of nonlinear structural system using deep-learning, 11th U.S. National Conference on Earthquake Engineering, Los Angeles, California, USA 
  12. Kim, T., Kwon, O.S., and Song, J. (2018). Development of a seismic response database and its applications to machine learning for inelastic seismic demand assessment, Engineering Mechanics Institute Conference (EMI 2018), May 29 – June 1, Cambridge, USA 
  13. Kim, T., Song, J., Deniz, D. (2017). Energy-based seismic collapse fragilities by clustering-based adaptive sampling of ground motions, 12th International Conference on Structural Safety and Reliability (ICOSSAR2017), August 6-10, Vienna, Austria.
  14. Kim, T., Song, J., Deniz, D. (2016). Seismic fragilities of ductile structural frames by clustering-based adaptive sampling of ground motions, International Symposium on Sustainability and Resiliency of Infrastructure 2016, November 10-12, Taipei, Taiwan
  15. Kim, T., Song, J., Deniz, D. (2016). Developing new measures of seismic intensity for collapse prediction based on cumulative and peak indices. 5th International Symposium on Reliability Engineering and Risk Management, Korea, August 17-20

(5) Conferences (In Korean), selected

  1. Han, S., Park, J., Park, C., Lee, T., and Kim, T. (2023). Analysis of vertical alignment of outdoor liquid storage tanks through review of standards and numerical investigation, COSEIK academic symposium, November 16-17, Chuncheon, Korea.
  2. Kim, T., and Yi, S. (2023).  System-reliability-based disaster resilience analysis for structures under stochastic excitations, Korean Society of Civil Engineers 2023 Convention, October 18-20, Yeosu, Korea. Won Best Paper Award
  3. Kim, T., Kwon, O.S., and Song, J. (2023).  Prediction of seismic responses of structural systems having degradation and pinching using deep learning, Transactions of the Korean Nuclear Society Spring Meeting, May 17-19, Jeju, Korea. Won Best Paper Award
  4. Oh, S., Kim, T., and Song, J. (2023). Bouc-Wen class model for predicting hysteretic behaviors of RC columns, 2023 Conference of the Earthquake Engineering Society of Korea, March 17, Seoul, Korea
  5. Kim, T., Kwon, O.S., and Song, J. (2019) Seismic behavior analysis of long-span cable-stayed bridges considering effects of wave passage and strong motion duration, 2019 KIBSE conference, November 22, Seoul, Korea
  6. Kim, T., Kwon, O.S., and Song, J. (2019) Nonlinear time history analysis of a long span cable-bridge considering spatial variations of ground motions, Korean Society of Civil Engineers 2019 Convention, October 16-18, Pyeongchang, Korea.
  7. Kim, T., Song, J., and Kwon, O.S. (2018), Deep-learning-based probabilistic prediction of seismic responses of nonlinear structural systems, Korean Society of Civil Engineers 2018 Convention, October 17-19, Kyeongju, Korea
  8. Kim, T., Kwon, O.S., and Song, J. (2017) Deep-learning-based prediction of nonlinear seismic responses of structural systems, Proceedings of Korean Society of Civil Engineers Convention, October 19-20, Busan, Korea. (in Korean)
  9. Kim, T., Song, J., and Deniz, D. (2017), Enhancing collapse risk assessment based on computational simulations by statistical learning methods, Korea Society for Computational Mechanics 2017, February 10-11, Seoul, Korea
  10. Kim, T., Song, J., and Deniz, D. (2016), Developing new intensity measure for enhancing seismic fragility analysis, 2016 KIBSE Conference, November 10-11, Mok-po, Korea
  11. Kim, T., Song, J., and Deniz, D. (2016), Developing prediction model for structural damage measure for probabilistic collapse assessment, Korean Society of Civil Engineers 2016 Convention, October 19-21, Jeju, Korea. (in Korean)
  12. Kim, T., Song, J., and Deniz, D. (2016), Ground motion selection algorithm for energy-based seismic collapse fragility of structures, 2016 Conference of the Earthquake Engineering Society of Korea, September 22-23, Seoul, Korea. (in Korean) 
  13. Deniz, D., Song, J., Hajjar, J.F., and Kim, T., (2015), New paradigm of probabilistic assessment of building collapse: energy-based collapse criteria, measures and fragility functions, 2015 Conference of the Earthquake Engineering Society of Korea, September 10-12, Jeju, Korea (in Korean, abstract+oral presentation by T. Kim)