Journal Articles
2023
11. Ikeagwuani, Christopher C; Nweke, Chukwuebuka C; Onah, Hyginus N: Prediction of resilient modulus of fine-grained soil for pavement design using KNN, MARS, and random forest techniques. In: Arabian Journal of Geosciences, vol. 16, no. 388, 2023. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1007/s12517-023-11469-z,
title = {Prediction of resilient modulus of fine-grained soil for pavement design using KNN, MARS, and random forest techniques},
author = {Christopher C Ikeagwuani and Chukwuebuka C Nweke and Hyginus N Onah},
url = {https://doi.org/10.1007/s12517-023-11469-z},
doi = {10.1007/s12517-023-11469-z},
year = {2023},
date = {2023-05-27},
journal = {Arabian Journal of Geosciences},
volume = {16},
number = {388},
abstract = {This study was motivated by the difficulty in determining the resilient modulus of soils using the repeated load triaxial test (RLTT) recommended by the mechanistic-empirical pavement design guide (MEPDG). An alternative means to estimate the resilient modulus of fine-grained soils has been established in the form of three models that were developed using three supervised machine-learning techniques. This includes k-nearest neighbor (KNN), multivariate adaptive regression splines (MARS), and random forest. The data utilized for the development of the models were sourced from the long-term pavement performance (LTPP) database domiciled in the Infopave database in the USA. A total of twelve routine soil properties that have significant influence on the resilient modulus of fine-grained soils were considered in this study. Results obtained from this study revealed that the three developed models (KNN, MARS, and random forest) had high prediction accuracy and high generalization ability. However, the random forest model, based on the statistical indices used to evaluate the models, gave the best prediction accuracy (R2 = 0.9312 for the testing dataset) of the three developed model. It was followed closely by the MARS model with an R2 value of 0.9057. The last model in terms of prediction accuracy was the KNN model with an R2 value of 0.8748. Furthermore, based on parameter significance assessment using the random forest model, it was revealed that the nominal maximum axial stress and confining pressure are the best predictor variables for the estimation of the resilient modulus of fine-grained soils.},
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}
10. Carey, Trevor J; Mason, Henry B; Asikmaki, Dominiki; Athanasopoulos-Zekkos, Adda; Garcia, Fernando E; Gray, Brian; Lavrentiadis, Grigorios; Nweke, Chukwuebuka C: The 2022 Chihshang, Taiwan, Earthquake: Initial GEER Team Observations. In: Journal of Geotechnical and Geoenvironmental Engineering, vol. 149, no. 5, 2023. (Type: Journal Article | Links | BibTeX) @article{doi:10.1061/JGGEFK.GTENG-11522,
title = {The 2022 Chihshang, Taiwan, Earthquake: Initial GEER Team Observations},
author = {Trevor J Carey and Henry B Mason and Dominiki Asikmaki and Adda Athanasopoulos-Zekkos and Fernando E Garcia and Brian Gray and Grigorios Lavrentiadis and Chukwuebuka C Nweke},
url = {https://doi.org/10.1061/JGGEFK.GTENG-11522},
doi = {10.1061/JGGEFK.GTENG-11522},
year = {2023},
date = {2023-03-07},
journal = {Journal of Geotechnical and Geoenvironmental Engineering},
volume = {149},
number = {5},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2022
9. Nweke, Chukwuebuka C; Stewart, Jonathan P; Wang, Pengfei; Brandenberg, Scott J: Site response of sedimentary basins and other geomorphic provinces in southern California. In: Earthquake Spectra, 2022. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1177/87552930221088609,
title = {Site response of sedimentary basins and other geomorphic provinces in southern California},
author = {Chukwuebuka C Nweke and Jonathan P Stewart and Pengfei Wang and Scott J Brandenberg},
url = {https://doi.org/10.1177/87552930221088609},
doi = {10.1177/87552930221088609},
year = {2022},
date = {2022-05-31},
journal = {Earthquake Spectra},
abstract = {Ergodic site amplification models for active tectonic regions are conditioned on the time-averaged shear wave velocity in the upper 30 m (VS30) and the depth to a shear wave velocity isosurface (zx). The depth components of such models are derived using data from sites within many geomorphic domains. We provide a site amplification model utilizing VS30 and depth, with the depth component conditioned on type of geomorphic province: basins, valleys, and mountain/hills. As with current models, the depth component of our model is centered with respect to the VS30-scaling model using differential depth δzx, taken as the difference between a site-specific depth and a VS30-conditioned average depth. Using data from southern California, we find that long-period site response for all sites combined exhibits relative de-amplification and amplification for negative and positive differential depths, respectively. Individual provinces exhibit broadly similar trends with depth, but amplification levels are on average stronger in basins such that little relative de-amplification occurs at negative differential depths. Valley and mountain/hill sites have, on average, weaker amplification levels but stronger scaling with δzx. Site-to-site standard deviations vary appreciably across geomorphic provinces, with basins having lower dispersions than mountain/hill sites and the reference ergodic model.},
keywords = {},
pubstate = {published},
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8. Nweke, Chukwuebuka C; Stewart, Jonathan P; Graves, Robert W; Goulet, Christine A; Brandenberg, Scott J: Validating Predicted Site Response in Sedimentary Basins from 3D Ground Motion Simulations. In: Earthquake Spectra, 2022. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1177/87552930211073159,
title = {Validating Predicted Site Response in Sedimentary Basins from 3D Ground Motion Simulations},
author = {Chukwuebuka C Nweke and Jonathan P Stewart and Robert W Graves and Christine A Goulet and Scott J Brandenberg},
url = {https://doi.org/10.1177/87552930211073159},
doi = {10.1177/87552930211073159},
year = {2022},
date = {2022-02-16},
journal = {Earthquake Spectra},
abstract = {We introduce procedures to validate site response in sedimentary basins as predicted using ground motion simulations. These procedures aim to isolate contributions of site response to computed intensity measures relative to those from seismic source and path effects. In one of the validation procedures, simulated motions are analyzed in the same manner as earthquake recordings to derive non-ergodic site terms. This procedure compares the scaling with sediment isosurface depth of simulated versus empirical site terms (the latter having been derived in a separate study). A second validation procedure utilizes two sets of simulations, one that considers three-dimensional (3D) basin structure and a second that utilizes a one-dimensional (1D) representation of the crustal structure. Identical sources are used in both procedures, and after correcting for variable path effects, differences in ground motions are used to estimate site amplification in 3D basins. Such site responses are compared to those derived empirically to validate both the absolute levels and the depth scaling of site response from 3D simulations. We apply both procedures to southern California in a manner that is consistent between the simulated and empirical data (i.e. by using similar event locations and magnitudes). The results show that the 3D simulations overpredict the depth-scaling and absolute levels of site amplification in basins. However, overall patterns of site amplification with depth are similar, suggesting that future calibration may be able to remove observed biases.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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7. Omoya, Morolake; Ero, Itohan; Esteghamati, Mohsen Zaker; Burton, Henry V; Brandenberg, Scott; Sun, Han; Yi, Zhengxiang; Kang, Hua; Nweke, Chukuebuka C: A relational database to support post-earthquake building damage and recovery assessment. In: Earthquake Spectra, 2022. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1177/87552930211061167,
title = {A relational database to support post-earthquake building damage and recovery assessment},
author = {Morolake Omoya and Itohan Ero and Mohsen Zaker Esteghamati and Henry V Burton and Scott Brandenberg and Han Sun and Zhengxiang Yi and Hua Kang and Chukuebuka C Nweke},
url = {https://doi.org/10.1177/87552930211061167},
doi = {10.1177/87552930211061167},
year = {2022},
date = {2022-01-27},
journal = {Earthquake Spectra},
abstract = {Systematically collected and curated data sets from historical events provide a strong basis for simulating the physical and functional effects of natural hazards on the built environment. This article develops a relational database to support post-earthquake damage and recovery modeling of building portfolios. The current version of the database has been populated with information on the 3695 buildings affected by the 2014 South Napa, California, earthquake. The associated data categories include general building characteristics, site properties and shaking intensities, building damage and repair permitting (timing and type) information, and census-block-level sociodemographics. The Napa data set can be used to validate post-earthquake recovery simulation methodologies and explore the effectiveness of different modeling techniques in predicting damage. The database can be expanded to include other earthquakes and the overall framework can be adapted to other types of natural hazards (e.g. hurricanes, flooding).},
keywords = {},
pubstate = {published},
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2021
6. Goulet, Christine A.; Wang, Yongfei; Nweke, Chukwuebuka C.; Tang, Bo‐xiang; Wang, Pengfei; Hudson, Kenneth S.; Ahdi, Sean K.; Meng, Xiaofeng; Hudson, Martin B.; Donnellan, Andrea; Lyzenga, Gregory A.; Brandenberg, Scott J.; Stewart, Jonathan P.; Gallien, Timu; Winters, Maria A.: Comparison of Near‐Fault Displacement Interpretations from Field and Aerial Data for the M 6.5 and 7.1 Ridgecrest Earthquake Sequence Ruptures. In: Bulletin of the Seismological Society of America, 2021, ISSN: 0037-1106. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1785/0120200222,
title = {Comparison of Near‐Fault Displacement Interpretations from Field and Aerial Data for the M 6.5 and 7.1 Ridgecrest Earthquake Sequence Ruptures},
author = {Christine A. Goulet and Yongfei Wang and Chukwuebuka C. Nweke and Bo‐xiang Tang and Pengfei Wang and Kenneth S. Hudson and Sean K. Ahdi and Xiaofeng Meng and Martin B. Hudson and Andrea Donnellan and Gregory A. Lyzenga and Scott J. Brandenberg and Jonathan P. Stewart and Timu Gallien and Maria A. Winters},
url = {https://doi.org/10.1785/0120200222},
doi = {10.1785/0120200222},
issn = {0037-1106},
year = {2021},
date = {2021-08-24},
urldate = {2020-08-24},
journal = {Bulletin of the Seismological Society of America},
abstract = {Coseismic surface fault displacement presents a serious potential hazard for structures and for lifeline infrastructure. Distributed lifeline infrastructure tends to cover large distances and may cross faults in multiple locations, especially in active tectonic regions like California. However, fault displacement measurements for engineering applications are quite sparse, rendering the development of predictive models extremely difficult and fraught with large uncertainties. Detailed fault surface rupture mapping products exist for a few documented cases, but they may not capture the full width of ground deformations that are likely to impact distributed infrastructure. The 2019 Ridgecrest earthquake sequence presented an ideal opportunity to collect data and evaluate the ability of different techniques to capture coseismic deformations on and near the fault ruptures. Both the M 6.5 and 7.1 events ruptured the surface in sparsely populated desert areas where little vegetation is present to obscure surficial features. Two study areas (~400 m × 500 m each) around the surface ruptures from the two events were selected. Teams of researchers were deployed and coordinated to gather data in three ways: field measurements and photographs, imagery from small uninhabited aerial systems, and imagery from airborne light detection and ranging. Each of these techniques requires different amounts of resources in terms of cost, labor, and time associated with the data collection, processing, and interpretation efforts. This article presents the data collection methods used for the two study areas, and qualitative and quantitative comparisons of the results interpretations. While all three techniques capture the key features that are important for displacement design of distributed infrastructure, the use of remote sensing methods in combination with field measurements presents an advantage over the use of any single technique.},
keywords = {},
pubstate = {published},
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5. Ikeagwuani, Chijioke Christopher; Nwonu, Donald Chimobi; Nweke, Chukwuebuka C: Resilient modulus descriptive analysis and estimation for fine-grained soils using multivariate and machine learning methods. In: International Journal of Pavement Engineering, vol. 0, no. 0, pp. 1-16, 2021. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1080/10298436.2021.1895993,
title = {Resilient modulus descriptive analysis and estimation for fine-grained soils using multivariate and machine learning methods},
author = {Chijioke Christopher Ikeagwuani and Donald Chimobi Nwonu and Chukwuebuka C Nweke},
url = {https://doi.org/10.1080/10298436.2021.1895993},
doi = {10.1080/10298436.2021.1895993},
year = {2021},
date = {2021-01-01},
journal = {International Journal of Pavement Engineering},
volume = {0},
number = {0},
pages = {1-16},
publisher = {Taylor \& Francis},
abstract = {ABSTRACTThe adoption of mechanistic-empirical approach to pavement design requires the use of resilient modulus of subgrade soils as a crucial input. The determination of in the laboratory is inexpedient due to the nature of the existing test protocols. This prompted the use of estimated values, which inadvertently has gained popularity lately. However, the accuracy of estimated values is questionable due to spatial variability of soil properties. This necessitated the aggressive search for robust and thorough approaches for predictive modelling of the . In the present study, a systematic approach was adopted for the descriptive analysis and estimation of . from routine soil properties using data from Long-Term Pavement Performance (LTPP) and considering the spatial variability of the soil properties. Descriptive analysis was executed using non-parametric correlation and principal component analysis (PCA), while the estimation was done using three machine learning methods which include gradient boosting regression (GBR), adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN). Based on the PCA, four factors which explained a total of 77.5% variance in the data had significant influence on the . These include the effect of moisture-induced changes on the soil consistency limits and physical condition, effect of the soil clay content, effect of the soil gradation and effect of the soil stress state. Various factors of the machine learning methods such as the learning rate, number of clusters and number of hidden layers had a significant effect on the prediction accuracy. The three machine learning methods were satisfactory for the prediction based on R2 values which were generally above 0.9. Also, when considering spatial variability of routine soil properties, the GBR and ANFIS have a comparative advantage over the ANN, since they exhibited a high stability in the prediction for both the training and testing dataset.},
keywords = {},
pubstate = {published},
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2020
4. Zimmaro, Paolo; Nweke, Chukwuebuka C.; Hernandez, Janis L.; Hudson, Kenneth S.; Hudson, Martin B.; Ahdi, Sean K.; Boggs, Matthew L.; Davis, Craig A.; Goulet, Christine A.; Brandenberg, Scott J.; Hudnut, Kenneth W.; Stewart, Jonathan P.: Liquefaction and Related Ground Failure from July 2019 Ridgecrest Earthquake Sequence. In: Bulletin of the Seismological Society of America, vol. 110, no. 4, pp. 1549-1566, 2020, ISSN: 0037-1106. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1785/0120200025,
title = {Liquefaction and Related Ground Failure from July 2019 Ridgecrest Earthquake Sequence},
author = {Paolo Zimmaro and Chukwuebuka C. Nweke and Janis L. Hernandez and Kenneth S. Hudson and Martin B. Hudson and Sean K. Ahdi and Matthew L. Boggs and Craig A. Davis and Christine A. Goulet and Scott J. Brandenberg and Kenneth W. Hudnut and Jonathan P. Stewart},
url = {https://doi.org/10.1785/0120200025},
doi = {10.1785/0120200025},
issn = {0037-1106},
year = {2020},
date = {2020-07-21},
journal = {Bulletin of the Seismological Society of America},
volume = {110},
number = {4},
pages = {1549-1566},
abstract = {The 2019 Ridgecrest earthquake sequence produced a 4 July M 6.5 foreshock and a 5 July M 7.1 mainshock, along with 23 events with magnitudes greater than 4.5 in the 24 hr period following the mainshock. The epicenters of the two principal events were located in the Indian Wells Valley, northwest of Searles Valley near the towns of Ridgecrest, Trona, and Argus. We describe observed liquefaction manifestations including sand boils, fissures, and lateral spreading features, as well as proximate non‐ground failure zones that resulted from the sequence. Expanding upon results initially presented in a report of the Geotechnical Extreme Events Reconnaissance Association, we synthesize results of field mapping, aerial imagery, and inferences of ground deformations from Synthetic Aperture Radar‐based damage proxy maps (DPMs). We document incidents of liquefaction, settlement, and lateral spreading in the Naval Air Weapons Station China Lake US military base and compare locations of these observations to pre‐ and postevent mapping of liquefaction hazards. We describe liquefaction and ground‐failure features in Trona and Argus, which produced lateral deformations and impacts on several single‐story masonry and wood frame buildings. Detailed maps showing zones with and without ground failure are provided for these towns, along with mapped ground deformations along transects. Finally, we describe incidents of massive liquefaction with related ground failures and proximate areas of similar geologic origin without ground failure in the Searles Lakebed. Observations in this region are consistent with surface change predicted by the DPM. In the same region, geospatial liquefaction hazard maps are effective at identifying broad percentages of land with liquefaction‐related damage. We anticipate that data presented in this article will be useful for future liquefaction susceptibility, triggering, and consequence studies being undertaken as part of the Next Generation Liquefaction project.},
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3. Ahdi, Sean Kamran; Mazzoni, Silvia; Kishida, Tadahiro; Wang, Pengfei; Nweke, Chukwuebuka C.; Kuehn, Nicolas M.; Contreras, Victor; Rowshandel, Badie; Stewart, Jonathan P.; Bozorgnia, Yousef: Engineering Characteristics of Ground Motions Recorded in the 2019 Ridgecrest Earthquake Sequence. In: Bulletin of the Seismological Society of America, vol. 110, no. 4, pp. 1474-1494, 2020, ISSN: 0037-1106. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1785/0120200036,
title = {Engineering Characteristics of Ground Motions Recorded in the 2019 Ridgecrest Earthquake Sequence},
author = {Sean Kamran Ahdi and Silvia Mazzoni and Tadahiro Kishida and Pengfei Wang and Chukwuebuka C. Nweke and Nicolas M. Kuehn and Victor Contreras and Badie Rowshandel and Jonathan P. Stewart and Yousef Bozorgnia},
url = {https://doi.org/10.1785/0120200036},
doi = {10.1785/0120200036},
issn = {0037-1106},
year = {2020},
date = {2020-07-21},
journal = {Bulletin of the Seismological Society of America},
volume = {110},
number = {4},
pages = {1474-1494},
abstract = {We present a database and analyze ground motions recorded during three events that occurred as part of the July 2019 Ridgecrest earthquake sequence: a moment magnitude (M) 6.5 foreshock on a left‐lateral cross fault in the Salt Wells Valley fault zone, an M 5.5 foreshock in the Paxton Ranch fault zone, and the M 7.1 mainshock, also occurring in the Paxton Ranch fault zone. We collected and uniformly processed 1483 three‐component recordings from an array of 824 sensors spanning 10 seismographic networks. We developed site metadata using available data and multiple models for the time‐averaged shear‐wave velocity in the upper 30 m (VS30) and for basin depth terms. We processed ground motions using Next Generation Attenuation (NGA) procedures and computed intensity measures including spectral acceleration at a number of oscillator periods and inelastic response spectra. We compared elastic and inelastic response spectra to seismic design spectra in building codes to evaluate the damage potential of the ground motions at spatially distributed sites. Residuals of the observed spectral accelerations relative to the NGA‐West2 ground‐motion models (GMMs) show good average agreement between observations and model predictions (event terms between about −0.3 and 0.5 for peak ground acceleration to 5 s). The average attenuation with distance is also well captured by the empirical NGA‐West2 GMMs, although azimuthal variations in attenuation were observed that are not captured by the GMMs. An analysis considering directivity and fault‐slip heterogeneity for the M 7.1 event demonstrates that the dispersion in the near‐source ground‐motion residuals can be reduced.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2. Brandenberg, Scott J.; Stewart, Jonathan P.; Wang, Pengfei; Nweke, Chukwuebuka C.; Hudson, Kenneth; Goulet, Christine A.; Meng, Xiaofeng; Davis, Craig A.; Ahdi, Sean K.; Hudson, Martin B.; Donnellan, Andrea; Lyzenga, Gregory; Pierce, Marlon; Wang, Jun; Winters, Maria A.; Delisle, Marie‐Pierre; Lucey, Joseph; Kim, Yeulwoo; and Timu W. Gallien,; Lyda, Andrew; Yeung, Sean J.; Issa, Omar; Buckreis, Tristan; Yi, Zhengxiang: Ground Deformation Data from GEER Investigations of Ridgecrest Earthquake Sequence. In: Seismological Research Letters, vol. 91, no. 4, pp. 2024-2034, 2020, ISSN: 0895-0695. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1785/0220190291,
title = {Ground Deformation Data from GEER Investigations of Ridgecrest Earthquake Sequence},
author = {Scott J. Brandenberg and Jonathan P. Stewart and Pengfei Wang and Chukwuebuka C. Nweke and Kenneth Hudson and Christine A. Goulet and Xiaofeng Meng and Craig A. Davis and Sean K. Ahdi and Martin B. Hudson and Andrea Donnellan and Gregory Lyzenga and Marlon Pierce and Jun Wang and Maria A. Winters and Marie‐Pierre Delisle and Joseph Lucey and Yeulwoo Kim and and Timu W. Gallien and Andrew Lyda and Sean J. Yeung and Omar Issa and Tristan Buckreis and Zhengxiang Yi},
url = {https://doi.org/10.1785/0220190291},
doi = {10.1785/0220190291},
issn = {0895-0695},
year = {2020},
date = {2020-02-19},
journal = {Seismological Research Letters},
volume = {91},
number = {4},
pages = {2024-2034},
abstract = {Following the Ridgecrest earthquake sequence, consisting of an M 6.4 foreshock and M 7.1 mainshock along with many other events, the Geotechnical Extreme Events Reconnaissance association deployed a team to gather perishable data. The team focused their efforts on documenting ground deformations including surface fault rupture south of the Naval Air Weapons Station China Lake, and liquefaction features in Trona and Argus. The team published a report within two weeks of the M 7.1 mainshock. This article presents data products gathered by the team, which are now published and publicly accessible. The data products presented herein include ground‐based observations using Global Positioning System trackers, digital cameras, and hand‐measuring devices, as well as unmanned aerial vehicle‐based imaging products using Structure from Motion to create point clouds and digital surface models. The article describes the data products, as well as tools available for interacting with the products.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
1. Mangalathu, Sujith; Sun, Han; Nweke, Chukwuebuka C.; Yi, Zhengxiang; Burton, Henry V.: Classifying earthquake damage to buildings using machine learning. In: Earthquake Spectra, vol. 36, no. 1, pp. 183-208, 2020. (Type: Journal Article | Abstract | Links | BibTeX) @article{doi:10.1177/8755293019878137,
title = {Classifying earthquake damage to buildings using machine learning},
author = {Sujith Mangalathu and Han Sun and Chukwuebuka C. Nweke and Zhengxiang Yi and Henry V. Burton},
url = {https://doi.org/10.1177/8755293019878137},
doi = {10.1177/8755293019878137},
year = {2020},
date = {2020-01-29},
journal = {Earthquake Spectra},
volume = {36},
number = {1},
pages = {183-208},
abstract = {The ability to rapidly assess the spatial distribution and severity of building damage is essential to post-event emergency response and recovery. Visually identifying and classifying individual building damage requires significant time and personnel resources and can last for months after the event. This article evaluates the feasibility of using machine learning techniques such as discriminant analysis, k-nearest neighbors, decision trees, and random forests, to rapidly predict earthquake-induced building damage. Data from the 2014 South Napa earthquake are used for the study where building damage is classified based on the assigned Applied Technology Council (ATC)-20 tag (red, yellow, and green). Spectral acceleration at a period of 0.3 s, fault distance, and several building specific characteristics (e.g. age, floor area, presence of plan irregularity) are used as features or predictor variables for the machine learning models. A portion of the damage data from the Napa earthquake is used to obtain the forecast model, and the performance of each machine learning technique is evaluated using the remaining (test) data. It is noted that the random forest algorithm can accurately predict the assigned tags for 66% of the buildings in the test dataset.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Conferences
2023
8. Buckreis, Tristan E; Nweke, Chukwuebuka C; Wang, Pengfei; Brandenberg, Scott J; Mazzoni, Silvia; Stewart, Jonathan P: Relational Database for California Strong Ground Motions. Geo-Congress 2023, 2023. (Type: Conference | Abstract | Links | BibTeX) @conference{doi:10.1061/9780784484692.047,
title = {Relational Database for California Strong Ground Motions},
author = {Tristan E Buckreis and Chukwuebuka C Nweke and Pengfei Wang and Scott J Brandenberg and Silvia Mazzoni and Jonathan P Stewart},
url = {https://doi.org/10.1061/9780784484692.047},
doi = {10.1061/9780784484692.047},
year = {2023},
date = {2023-03-26},
booktitle = {Geo-Congress 2023},
pages = {461-470},
abstract = {We present a relational database of earthquake ground motion intensity measures and associated metadata for the state of California. NGA-West2 project spreadsheets have been adapted into a relational database format, and the data set has been expanded to include contributions from earthquakes, generally with magnitudes greater than M3.9, that have occurred since the conclusion of the data synthesis component of the NGA-West2 project in 2011. Aside from the newly added information, some site metadata fields have been updated for some ground motion stations. The relational-database is composed of multiple tables connected through a series of primary and foreign keys. We use various data types (beyond integers and floats) to increase the storage efficiency for several types of data. Currently the database includes 33,422 ground motions recorded at 2,739 stations for 478 events within or close to California. The database was designed to also accommodate the various fields included in other NGA databases, including NGA-East and NGA-Sub. This will eventually allow for certain database tables to be merged for all event types (e.g., a single site table could be created) in one central location.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
2022
7. Birkel, Brianna C; Vidale, John E; Nweke, Chukwuebuka C: Comparison of Observed and Simulated Ground Motions in the Los Angeles Basin. AGU Fall Meeting 2022, 2022. (Type: Conference | Abstract | Links | BibTeX) @conference{doi:,
title = {Comparison of Observed and Simulated Ground Motions in the Los Angeles Basin},
author = {Brianna C Birkel and John E Vidale and Chukwuebuka C Nweke},
url = {https://ui.adsabs.harvard.edu/abs/2022AGUFM.S45B..04B/abstract},
year = {2022},
date = {2022-12-12},
booktitle = {AGU Fall Meeting 2022},
abstract = {The deep, soft sedimentary basin surrounding Los Angeles is a region of ongoing scientific interest and study, due to its overlying dense infrastructure and tendency to amplify 3-10s period seismic waves. In this study, we evaluate the accuracy of the latest seismic velocity models \textendash CVM-S4.26.M01 and CVM-H 15.1.0 \textendash by comparing observed seismograms from several recent moderate magnitude earthquakes to their synthetic counterparts. These synthetic seismograms are computed via forward modeling simulation software using both the octree-based full-3D tomography Hercules toolchain (Taborda et al. 2016) and the finite-difference code developed by Rob Graves. In the Los Angeles basin, we see significant differences between observations and predictions, even at periods longer than 5 seconds and particularly within the 3-5 second period range. These differences are quantified using the Anderson 2004 goodness-of-fit metrics, as well as via direct waveform comparison. We additionally identify smaller, more specific regions within the Los Angeles Basin that demonstrate the largest misfit and require more detailed study. These results suggest that earthquake hazard estimation in the Los Angeles basin will benefit from specific, focused improvements of the velocity models in this region.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
6. Nweke, Chukwuebuka C; Davis, Craig A; Hudson, Kenneth S; Hudnut, Kenneth W; Brandenberg, Scott J; Stewart, Jonathan P: Performance of Water Pipelines at Fault Crossings from the 2019 Ridgecrest Earthquakes. Lifelines 2022, 2022. (Type: Conference | Abstract | Links | BibTeX) @conference{doi:10.1061/9780784484449.031,
title = {Performance of Water Pipelines at Fault Crossings from the 2019 Ridgecrest Earthquakes},
author = {Chukwuebuka C Nweke and Craig A Davis and Kenneth S Hudson and Kenneth W Hudnut and Scott J Brandenberg and Jonathan P Stewart},
url = {http://dx.doi.org/10.1061/9780784484449.031},
doi = {10.1061/9780784484449.031},
year = {2022},
date = {2022-11-16},
booktitle = {Lifelines 2022},
pages = {343-355},
abstract = {The 2019 Ridgecrest earthquake sequence produced extensive surface rupture affecting the Naval Air Weapons Station, China Lake, and multiple water pipelines that service the towns of Trona and Argus. This paper documents observations of surface rupture and their effects on buried water pipelines at four pipeline-fault crossings. At these crossing locations surface ruptures ranged from about 0\textendash60 cm (V) and 2.1\textendash330 cm (H). Some surface ruptures displayed complicated patterns. The water pipes are made of multiple materials and they are approximately 30.5 to 40.5 cm in diameter. For each crossing, the surface rupture characteristics and the observed pipe damages are described. It is anticipated that the field data presented herein will serve as a resource for subsequent research to validate and enhance existing knowledge on the behavior of faulting surface rupture and impacts on buried water pipelines.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
5. Brandenberg, Scott J; Goulet, Christine A; Zimmaro, Paolo; Wang, Yongfei; Nweke, Chukwuebuka C; Tang, Bo‐xiang; Wang, Pengfei; Hudson, Kenneth S.; Ahdi, Sean K.; Meng, Xiaofeng; Hudson, Martin B.; Donnellan, Andrea; Lyzenga, Gregory A.; Stewart, Jonathan P.; Gallien, Timu; Winters, Maria A.: Fault Rupture and Liquefaction Feature Mapping with Unmanned Aerial Systems after the Ridgecrest Earthquake Sequence. 12NCEE 2022, 2022. (Type: Conference | Abstract | BibTeX) @conference{nweke2022faultrupture,
title = {Fault Rupture and Liquefaction Feature Mapping with Unmanned Aerial Systems after the Ridgecrest Earthquake Sequence},
author = {Scott J Brandenberg and Christine A Goulet and Paolo Zimmaro and Yongfei Wang and Chukwuebuka C Nweke and Bo‐xiang Tang and Pengfei Wang and Kenneth S. Hudson and Sean K. Ahdi and Xiaofeng Meng and Martin B. Hudson and Andrea Donnellan and Gregory A. Lyzenga and Jonathan P. Stewart and Timu Gallien and Maria A. Winters},
year = {2022},
date = {2022-08-01},
booktitle = {12NCEE 2022},
abstract = {TheM6. 5 and M7. 1 earthquakes that occurred as part of the 2019 Ridgecrest sequence produced surface fault rupture and liquefaction features that were mapped using unmanned aerial vehicles (UAV’s) operated by different research teams [1, 2, 3]. These included engineers, scientists, and remote sensing experts organized as a GEER (Geotechnical Extreme Events Reconnaissance) team and staff of the University of Washington RAPID facility. We also made ground measurements using traditional survey techniques and digital photography and coordinated with others on aerial Light Detection and Ranging (LiDAR) surveys. The combination of these measurements provided an opportunity to assess the ability of different UAV techniques to capture coseismic deformations on and near fault ruptures, as well as permanent deformations due to liquefaction-induced ground failure. Ground failure spatial distribution maps were also used leveraging synthetic aperture radar data. The events occurred in a desert environment where little vegetation is present to obscure surficial features. This presentation will discuss the field reconnaissance efforts performed after the earthquake sequence, and provide comparisons among the different methods.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
4. Nweke, Chukwuebuka C; Stewart, Jonathan P; Wang, Pengfei; Brandenberg, Scott J: Sedimentary Basin Site Response for Different Basin Types in Southern California. 12NCEE 2022, 2022. (Type: Conference | Abstract | Links | BibTeX) @conference{nweke2022sedimentarybasins,
title = {Sedimentary Basin Site Response for Different Basin Types in Southern California},
author = {Chukwuebuka C Nweke and Jonathan P Stewart and Pengfei Wang and Scott J Brandenberg},
url = {https://escholarship.org/uc/item/6vh7q486#author},
year = {2022},
date = {2022-07-01},
booktitle = {12NCEE 2022},
abstract = {Site response effects are described by ergodic ground motion models, which are developed using global data from sites with diverse site conditions, using the time-averaged shear-wave velocity in the upper 30 m (VS30) and isosurface depths (z1.0 or z2.5). Site responses in sedimentary basins may have specific dependencies on the geometry and extent of the sedimentary structure in addition to VS30 and isosurface depths. We investigate here the effects of basin-to-basin categorization on site response. Using southern California data, we highlight differences in mean site amplification for eight large sedimentary basins with different geologic origins. The mean response in all basins shows significant relative amplification at long periods (T > 0.5 sec) and none at shorter periods (T < 0.3 sec). Comparisons of basin-specific responses reveal that coastal basins exhibit greater levels of relative long-period amplification than inland, fault-bounded sedimentary basins.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
2018
3. Nweke, Chukwuebuka C.; Wang, Pengfei; Brandenberg, Scott J.; Stewart, Jonathan P.: Reconsidering basin effects in ergodic site response models. Proc. SMIP 2018 Seminar on Utilization of Strong Motion Data California Geological Survey: Strong Motion Implementation Program 2018. (Type: Conference | Links | BibTeX) @conference{nweke2018reconsidering,
title = {Reconsidering basin effects in ergodic site response models},
author = {Chukwuebuka C. Nweke and Pengfei Wang and Scott J. Brandenberg and Jonathan P. Stewart},
url = {https://escholarship.org/content/qt6048v74k/qt6048v74k.pdf},
year = {2018},
date = {2018-10-01},
organization = {California Geological Survey: Strong Motion Implementation Program},
series = {Proc. SMIP 2018 Seminar on Utilization of Strong Motion Data},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
2. Nweke, Chukwuebuka C.; Pestana, Juan M.: Modeling Bio-Cemented Sands: A Strength Index for Cemented Sands. IFCEE 2018, 2018. (Type: Conference | Abstract | Links | BibTeX) @conference{doi:10.1061/9780784481592.006,
title = {Modeling Bio-Cemented Sands: A Strength Index for Cemented Sands},
author = {Chukwuebuka C. Nweke and Juan M. Pestana},
url = {https://ascelibrary.org/doi/abs/10.1061/9780784481592.006},
doi = {10.1061/9780784481592.006},
year = {2018},
date = {2018-06-06},
booktitle = {IFCEE 2018},
pages = {48-58},
abstract = {The establishment of the bio-inspired and bio-mediated sub-disciplines in the emerging field of biogeotechnology has led to the developments of many innovative methods and techniques. These methods and techniques potentially provide sustainable alternatives to conventional approaches that may be less desirable due to their use of high-embodied energy materials and processes. In particular, research within the bio-mediated sub-discipline over the past decade has fostered advancements in biocementation ground improvement methods that currently allow for possible field scale implementation. As a result, the ability to incorporate and sufficiently factor the associated mechanical enhancements during design is needed. The development of a constitutive model that properly assesses the level of improvement and adequately predicts the expected performance for a given level of cementation is underway. However, in order to accomplish the aforementioned goal, there is a need to develop components that are capable of capturing the behavior and transition from the cemented to uncemented state, while maintaining adherence to influential factors in the volumetric and stress states. This paper focuses on the development of strength in biocemented soils (via microbial induced calcite precipitation, MICP) and its evolution with cementation level under loading. The proposed strength correlation accounts for the observed nonlinearity of failure envelopes in sands and describes the strength of cemented sands as a function of density, confinement, mineralogy, and cementation.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
2017
1. Nweke, Chukwuebuka C.; Pestana, Juan M.: Modeling Bio-Cemented Sands: Shear Strength and Stiffness with Degradation. Grouting 2017, 2017. (Type: Conference | Abstract | Links | BibTeX) @conference{doi:10.1061/9780784480793.004,
title = {Modeling Bio-Cemented Sands: Shear Strength and Stiffness with Degradation},
author = {Chukwuebuka C. Nweke and Juan M. Pestana},
url = {https://ascelibrary.org/doi/abs/10.1061/9780784480793.004},
doi = {10.1061/9780784480793.004},
year = {2017},
date = {2017-06-17},
booktitle = {Grouting 2017},
pages = {34-45},
abstract = {Over the past decade, recent developments between the geotechnical and life science disciplines have establish microbial induced calcite precipitation (MICP) as a novel ground improvement method. This method improves the static and dynamic mechanical properties of the soil while maintaining its environmentally friendly characteristics. Its application process lends itself to increased compatibility with varying infrastructure where other methods pose issues due to constraints. Currently, there are no established methods to properly assess the level of improvement, or adequately predict the expected performance for a given level of cementation. It is envisioned that numerical simulations will hold the key. With this in mind, a model was developed that incorporates the key aspects of the improved biomaterial for the purpose of comparing the lightly cemented and the original uncemented soils to illustrate the potential of the MICP method. Specifically, the model incorporates the ability to capture the behavior and transition from the cemented state to the uncemented state while maintaining adherence to the controlling factors of void ratio and confining stress. This paper focuses on the changes of shear stiffness and shear strength as a result of the degradation of the calcite (CaCO3) cementation in the MICP soils.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Technical Reports
2022
3. Burton, Henry V; Dwima, Samuel; Gho, Danny; Guan, Xingquan; Gunay, Selim; Gupta, Abhineet; Zeyad, Khalil; Kusumayani, Novia; Marinkovic, Marko; Merino, Yvonne; Nweke, Chukwuebuka C.; Safiey, Amir; Mosalam, Khalid: StEER 2022 Mw 5.6 Indonesia Earthquake Preliminary Virtual Reconnaissance Report (PVRR). StEER DesignSafe-CI no. StEER 2022-12, 2022. (Type: Technical Report | Links | BibTeX) @techreport{doi:10.17603/ds2-e2vq-nq61,
title = {StEER 2022 Mw 5.6 Indonesia Earthquake Preliminary Virtual Reconnaissance Report (PVRR)},
author = {Henry V Burton and Samuel Dwima and Danny Gho and Xingquan Guan and Selim Gunay and Abhineet Gupta and Khalil Zeyad and Novia Kusumayani and Marko Marinkovic and Yvonne Merino and Chukwuebuka C. Nweke and Amir Safiey and Khalid Mosalam},
url = {https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-3781/#details-3617915731608670701-242ac118-0001-012},
doi = {10.17603/ds2-e2vq-nq61},
year = {2022},
date = {2022-12-14},
number = {StEER 2022-12},
institution = {StEER DesignSafe-CI},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
2020
2. Nweke, Chukwuebuka C.; Stewart, Jonathan P.; Brandenberg, Scott J: Site Response of Southern California Sedimentary Basins and Other Geomorphic Provinces. The B. John Garrick Institute for the Risk Sciences, Natural Hazards Risk and Resiliency Research Center, UCLA no. GIRS 2020-12, 2020. (Type: Technical Report | Links | BibTeX) @techreport{doi:10.34948/N3159F,
title = {Site Response of Southern California Sedimentary Basins and Other Geomorphic Provinces},
author = {Chukwuebuka C. Nweke and Jonathan P. Stewart and Scott J Brandenberg},
url = {https://static1.squarespace.com/static/54628adae4b0f587f5d3e03f/t/5f96d94e4185c82c6f754f65/1603721600075/Basin+Amplification+Report+-+USGS+ver03.pdf},
doi = {10.34948/N3159F},
year = {2020},
date = {2020-10-24},
urldate = {2020-10-24},
number = {GIRS 2020-12},
institution = {The B. John Garrick Institute for the Risk Sciences, Natural Hazards Risk and Resiliency Research Center, UCLA},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
2019
1. Stewart, Jonathan P.; Brandenberg, Scott J.; Wang, Pengfei; Nweke, Chukwuebuka C.; Hudson, Kenneth; Mazzoni, Silvia; Bozorgnia, Yousef; Goulet, Christine A.; Hudnut, Kenneth W.; Davis, Craig A.; Ahdi, Sean K.; Zareian, Farzin; Fayaz, Jawad; Koehler, Richard D.; Chupik, Colin; Pierce, Ian; Williams, Alana; Akciz, Sinan; Hudson, Martin B.; Kishida, Tadahiro; Brooks, Ben; Gold, Ryan; Ponti, Dan; Scharer, Katherine; McPhillips, Devin; DuRoss, Chris; Ericksen, Todd; Hernandez, Janis; Patton, Jay; Olson, Brian; Dawson, Tim; Treiman, Jerome; Blake, Kelly; Buchhuber, Jeffrey; Madugo, Chris; Sun, Joseph; Donnellan, Andrea; Lyzenga, Greg; Conway, Erik: Preliminary report on engineering and geological effects of the July 2019 Ridgecrest earthquake sequence. Geotechnical Extreme Event Reconnaissance Association no. GEER-064, 2019. (Type: Technical Report | Links | BibTeX) @techreport{doi:10.18118/G6H66K,
title = {Preliminary report on engineering and geological effects of the July 2019 Ridgecrest earthquake sequence},
author = {Jonathan P. Stewart and Scott J. Brandenberg and Pengfei Wang and Chukwuebuka C. Nweke and Kenneth Hudson and Silvia Mazzoni and Yousef Bozorgnia and Christine A. Goulet and Kenneth W. Hudnut and Craig A. Davis and Sean K. Ahdi and Farzin Zareian and Jawad Fayaz and Richard D. Koehler and Colin Chupik and Ian Pierce and Alana Williams and Sinan Akciz and Martin B. Hudson and Tadahiro Kishida and Ben Brooks and Ryan Gold and Dan Ponti and Katherine Scharer and Devin McPhillips and Chris DuRoss and Todd Ericksen and Janis Hernandez and Jay Patton and Brian Olson and Tim Dawson and Jerome Treiman and Kelly Blake and Jeffrey Buchhuber and Chris Madugo and Joseph Sun and Andrea Donnellan and Greg Lyzenga and Erik Conway},
url = {https://doi.org/10.1177/8755293019878137},
doi = {10.18118/G6H66K},
year = {2019},
date = {2019-07-19},
number = {GEER-064},
institution = {Geotechnical Extreme Event Reconnaissance Association},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
Data Collection
2022
4. Nweke, Chukwuebuka C.; Stewart, Jonathan P.; Wang, Pengfei; Brandenberg, Scott; Buckreis, Tristan: Data Files for Ground Motion Studies Pertaining to Southern California Basins and Other Geomorphic Provinces. In: Designsafe-CI, vol. PRJ-3373, 2022. (Type: Book Section | Abstract | Links | BibTeX) @incollection{DesignsafeDataSoCal,
title = {Data Files for Ground Motion Studies Pertaining to Southern California Basins and Other Geomorphic Provinces},
author = {Chukwuebuka C. Nweke and Jonathan P. Stewart and Pengfei Wang and Scott Brandenberg and Tristan Buckreis},
url = {https://doi.org/10.17603/ds2-93rk-hz83},
doi = {10.17603/ds2-93rk-hz83},
year = {2022},
date = {2022-01-13},
booktitle = {Designsafe-CI},
volume = {PRJ-3373},
abstract = {This database is part of an on-going effort to compile and process recent earthquake ground motion data for seismic hazard assessment/analysis and model development. The provided database contains computed ground motion intensity measures (pseudo spectral accelerations, peak ground velocities) for processed earthquake time histories from events in Southern California. This includes records from the Next Generation Attenuation West-2 (NGA-West2) Project and data from earthquakes that have occurred since the completion of the NGA-West2 compilation (post-2010) such as, the 2019 Ridgecrest Earthquake Sequence and others. The data provide here was used to assess the site response of basins and other geomorphic provinces in southern California.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
3. Burton, Henry V; Dwima, Samuel; Gho, Danny; Guan, Xingquan; Gunay, Selim; Gupta, Abhineet; Zeyad, Khalil; Kusumayani, Novia; Marinkovic, Marko; Merino, Yvonne; Nweke, Chukwuebuka C.; Safiey, Amir; Mosalam, Khalid: 2022 Mw 5.6 Indonesia Earthquake Media Repository. In: Designsafe-CI, vol. PRJ-3781, 2022. (Type: Book Section | Abstract | Links | BibTeX) @incollection{DesignsafeDataM5_6Indonesia,
title = {2022 Mw 5.6 Indonesia Earthquake Media Repository},
author = {Henry V Burton and Samuel Dwima and Danny Gho and Xingquan Guan and Selim Gunay and Abhineet Gupta and Khalil Zeyad and Novia Kusumayani and Marko Marinkovic and Yvonne Merino and Chukwuebuka C. Nweke and Amir Safiey and Khalid Mosalam},
url = {https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-3781/#details-3617915731608670701-242ac118-0001-012},
doi = {10.17603/ds2-e2vq-nq61},
year = {2022},
date = {2022-12-14},
booktitle = {Designsafe-CI},
volume = {PRJ-3781},
abstract = {The first product of StEER’s Level 1 response to the M5.6 Indonesia Earthquake is this Preliminary Virtual Reconnaissance Report (PVRR), which is intended to: (1) provide details of the November 22 M 5.6 earthquake, (2) summarize the tectonic features of the event, (3) synthesize the recording ground motions and provide comparisons with design-level shaking, (4) briefly encapsulate the local building codes and construction practices and (5) provide a preliminary assessment of the damage to buildings and other infrastructure as well as the broader societal impacts. The PVRR includes both the official report as well as a supplementary media repository containing additional imagery gathered by the VAST. As the product of entirely virtual reconnaissance, the PVRR is not based upon detailed field investigations by StEER.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
2021
2. Omoya, Morolake; Ero, Itohan; Esteghamati, Mohsen Zaker; Burton, Henry V.; Brandenberg, Scott J.; Nweke, Chukwuebuka C.: Relational Database for Post-Earthquake Damage and Recovery Assessment: 2014 South Napa Earthquake. In: Designsafe-CI, vol. PRJ-3025, 2021. (Type: Book Section | Abstract | Links | BibTeX) @incollection{DesignsafeDataNapa,
title = {Relational Database for Post-Earthquake Damage and Recovery Assessment: 2014 South Napa Earthquake},
author = {Morolake Omoya and Itohan Ero and Mohsen Zaker Esteghamati and Henry V. Burton and Scott J. Brandenberg and Chukwuebuka C. Nweke},
url = {https://doi.org/10.17603/ds2-3nvj-4127},
doi = {10.17603/ds2-3nvj-4127},
year = {2021},
date = {2021-02-01},
booktitle = {Designsafe-CI},
volume = {PRJ-3025},
abstract = {The Earthquake Recovery relational database uploaded to DesignSafe contains damage and recovery information for buildings affected by the 2014 South Napa earthquake. This project contains a Jupyter notebook (RecoveryDatabaseExampleQueries.ipynb) that runs several basic queries on the Earthquake Recovery relational database. The Jupyter notebook establishes a connection to the database and illustrates how to query information about the buildings affected by the 2014 South Napa earthquake including various properties (e.g. geometry, structural and occupancy), the type and level of damage, the recovery and census-level sociodemographics. The MySQL file (EarthquakeRecovery.sql) containing the database is attached to this project. The relational database schema (Earthquakerecoveryschema.png) and a spreadsheet showing the number of entries for each attribute (EarthquakeRecoveryAttributeEntries.xslx) are also included.},
type = {Database},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
2019
1. Nweke, Chukwuebuka; Graves, Robert; Goulet, Christine; Brandenberg, Scott; Stewart, Jonathan: Southern California Earthquake Center (SCEC) Simulation Validation for Southern California Basins using Ground Motion Recordings. In: Designsafe-CI, vol. PRJ-2620, 2019. (Type: Book Section | Abstract | Links | BibTeX) @incollection{DesignsafeDataSCECBasinSim,
title = {Southern California Earthquake Center (SCEC) Simulation Validation for Southern California Basins using Ground Motion Recordings},
author = {Chukwuebuka Nweke and Robert Graves and Christine Goulet and Scott Brandenberg and Jonathan Stewart},
url = {https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2620#anchor-3723106075728613866-242ac11a-0001-012},
doi = {10.17603/ds2-762f-sg15},
year = {2019},
date = {2019-06-01},
booktitle = {Designsafe-CI},
volume = {PRJ-2620},
abstract = {This objective of this project is to validate long-period ground motion site amplification associated with basin effects as provided by three-dimensional numerical simulations. Site effects are evaluated from mixed effects residuals analyses, as described for example in Stewart et al. (2017). The simulations are performed for source conditions (location and earthquake size) for which ample recordings are available. This allows site effects in basins to be evaluated in a consistent manner from recorded data and from simulations. The project team was coordinated under the Ground Motion Simulation Validation (GMSV) group within SCEC and include: Chukwuebuka Nweke (UCLA), Jonathan Stewart (UCLA), Scott Brandenberg (UCLA), Robert Graves (USGS), Christine Goulet (USC). References: Stewart, J.P., Afshari, K., Goulet, C.A., 2017. Non-ergodic site response in seismic hazard analysis, Earthquake Spectra, 33, 1385-1414.},
type = {Dataset},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}