Selected Journal Articles
2023
Ji, C., Cabas, A., Kottke, A., Pilz, M., Macedo, J., & Liu, C. (2023). A DesignSafe earthquake ground motion database for California and surrounding regions. Earthquake Spectra, 39(1), 702-721.
2022
Macedo, J., Liu, C., & Abrahamson, N. A. (2022). On the interpretation of conditional ground‐motion models. Bulletin of the Seismological Society of America, 112(5), 2580-2586.
Macedo, J., & Liu, C. (2022). A nonergodic ground motion model for Chile. Bulletin of the Seismological Society of America, 112(5), 2542-2561.
Liu, C., & Macedo, J. (2022). Impact of Ergodic versus Nonergodic Seismic Hazard Estimation on the Risk Assessment of Liquefaction‐Induced Ground Damage. Bulletin of the Seismological Society of America, 112(5), 2562-2579.
Liu, C., & Macedo, J. (2022). Machine learning-based models for estimating seismically-induced slope displacements in subduction earthquake zones. Soil Dynamics and Earthquake Engineering, 160, 107323.
Lavrentiadis, G., Abrahamson, N. A., Nicolas, K. M., Bozorgnia, Y., Goulet, C. A., Babič, A., ... & Walling, M. (2022). Overview and introduction to development of non-ergodic earthquake ground-motion models. Bulletin of Earthquake Engineering, 1-30.
Liu, C., & Macedo, J. (2022). New conditional, scenario-based, and traditional peak ground velocity models for interface and intraslab subduction zone earthquakes. Earthquake Spectra, 38(3), 2109-2134.
Liu, C., Macedo, J., & Kuehn, N. (2022). Spatial correlation of systematic effects of non-ergodic ground motion models in the Ridgecrest area. Bulletin of Earthquake Engineering, 1-27.
Macedo, J., Ramesh, V., Liu, C., & Kottke, A. (2022). Evaluating different approaches for the hazard‐consistent assessment of the seismic performance of dams. Bulletin of the Seismological Society of America, 112(3), 1710-1726.
Liu, C., Macedo, J., & Kottke, A. R. (2022). Evaluating the performance of nonergodic ground motion models in the Ridgecrest area. Bulletin of Earthquake Engineering, 1-27.
Liu, C., & Macedo, J. (2022). New conditional, scenario-based, and non-conditional cumulative absolute velocity models for subduction tectonic settings. Earthquake Spectra, 38(1), 615-647.
2021
Liu, C., Macedo, J., & Candia, G. (2021). Performance-based probabilistic assessment of liquefaction-induced building settlements. Soil Dynamics and Earthquake Engineering, 151, 106955.
Patel, S., Ceferino, L., Liu, C., Kiremidjian, A., & Rajagopal, R. (2021). The disaster resilience value of shared rooftop solar systems in residential communities. Earthquake Spectra, 37(4), 2638-2661.
Macedo, J., Liu, C., & Soleimani, F. (2021). Machine-learning-based predictive models for estimating seismically-induced slope displacements. Soil Dynamics and Earthquake Engineering, 148, 106795.
Macedo, J., & Liu, C. (2021). Ground‐Motion Intensity Measure Correlations on Interface and Intraslab Subduction Zone Earthquakes Using the NGA‐Sub Database. Bulletin of the Seismological Society of America, 111(3), 1529-1541.
Macedo, J., Abrahamson, N., & Liu, C. (2021). New scenario‐based cumulative absolute velocity models for shallow crustal tectonic settings. Bulletin of the Seismological Society of America, 111(1), 157-172.
Liu, C., Macedo, J., & Candia, G. (2021). Performance-based probabilistic assessment of liquefaction-induced building settlements. Soil Dynamics and Earthquake Engineering, 151, 106955.
2020
Macedo, J., Candia, G., Lacour, M., & Liu, C. (2020). New developments for the performance-based assessment of seismically-induced slope displacements. Engineering Geology, 277, 105786.
Selected Conference Proceedings
2022
Soleimani, F., Macedo, J., & Liu, C. (2022). Machine Learning-Based Selection of Efficient Parameters for the Evaluation of Seismically Induced Slope Displacements. In Lifelines 2022 (pp. 185-193).
Liu, C., & Macedo, J. (2022). Cumulative absolute velocity models for use in liquefaction engineering. In Geo-Congress 2022 (pp. 638-648).
Liu, C., Macedo, J., & Soleimani, F. Using Machine Learning for the Performance-Based Seismic Assessment of Slope Systems. In Geo-Congress 2022 (pp. 649-658).
2021
Zahra, F., Málaga-Chuquitaype, C., Macedo, J., & Liu, C. (2021). Hazard-consistent residual drift demands in steel moment resisting frames. In 17th World Conference on Earthquake Engineering.
2020
Ceferino, L., Liu, C., Alisjahbana, I., Patel, S., Sun, T., Kiremidjian, A., & Rajagopal, R. (2020, September). Earthquake resilience of distributed energy resources. In 17th world conference on earthquake engineering, Tokyo, Japan.
Selected Reports
Macedo, J., Burns, S. E., Torres, J., Jung, Y. S., Liu, C., & Tsai, Y. J. (2023). Towards the Implementation of a Geotechnical Asset Management Program in the State of Georgia (No. FHWA-GA-23-2011). Georgia. Department of Transportation. Office of Performance-Based Management & Research.
Macedo, J., & Liu, C. (2022) Machine Learning Based Procedures for Estimating Seismically Induced Landslides in Subduction Tectonic Settings. U.S.Geological Survey Final Technical Report. Award Number: G21AP10264.(pdf)