The Byrne (1991) model was developed to predict excess pore water pressure for saturated sands under cyclic loading. However, the model can also be used to predict seismic compression in dry or partially saturated clean sands, which is the focus of this research. The original Byrne (1991) model has two primary limitations. One limitation is that calibration coefficients for the model have only been developed for clean sand, while seismic compression is a concern for a variety of soil types in engineering practice. Another limitation is that the existing calibration coefficients are solely correlated with soil relative density. This is in contrast to findings from studies performed over the last two decades that show various environmental and compositional factors, in addition to relative density, influence seismic compression behavior. To overcome these shortcomings and others the model was transformed to allow it to be implemented in "simplified" and "non-simplified" manners and systematic model calibration procedures were developed by means of MATLAB code. Both "simplified" and "non-simplified" variants of the model are used to analyze a site in Japan impacted by the 2007, Mw6.6 Niigata-ken Chuetsu-oki earthquake. The results from the analyses are in general accord with the post-earthquake field observations and highlight the utility and versatility of the models. / Master of Science / Earthquake shaking can cause compression of volume in soil, which may induce damage to various infrastructures. This phenomenon is known as seismic compression. Byrne (1991) proposed one model that can be used to evaluate the magnitude of seismic compression. However, this model has two significant limitations. One limitation is its coefficient expression is suitable for merely one soil type, while seismic compression is a concern for a variety of soil types in engineering practice. Another limitation is that the existing model coefficients are only correlated with soil density. This is in contrast to findings from research conducted over the last two decades that show many other environmental and compositional factors, in addition to soil density, affect the magnitude of seismic compression. To overcome these shortcomings and others the model was modified and calibrated, where mathematical transformations were performed for the model to allow it to be implemented in “simplified” and “non-simplified” calculation manners. Also, systematic model modification procedures were established by means of codes written by one software called MATLAB. Both the “simplified” and “nonsimplified” calculation methods of the model were used to analyze a site in Japan impacted by an earthquake occurred in 2007, named Niigata-ken Chuetsu-oki Earthquake. The results from the analyses are in general accord with the records obtained after the earthquake and highlight the utility and versatility of the modified models.

Earthquake-induced liquefaction of saturated soils and seismic compression of unsaturated soils are major sources of hazard to infrastructure, as attested by the wholesale condemnation of neighborhoods surrounding Christchurch, New Zealand. The hazard continues to grow as cities expand into liquefaction- and seismic compression-susceptible areas hence accurate evaluation of both hazards is essential. The liquefaction evaluation procedure presented herein is based on dissipated energy and an SPT liquefaction/no-liquefaction case history database. It is as easy to implement as existing stress-based simplified procedures. Moreover, by using the dissipated energy of the entire loading time history to represent the demand, the proposed procedure melds the existing stress-based and strain-based liquefaction procedures in to a new, robust method that is capable of evaluating liquefaction susceptibility from both earthquake and non-earthquake sources of ground motion. New relationships for stress reduction coefficient (r_d) and number of equivalent cycles ($n_{eq}$) are also presented herein. The r_d relationship has less bias and uncertainty than other common stress reduction coefficient relationships, and both the $n_{eq}$ and $r_d$ relationships are proposed for use in active tectonic and stable continental regimes. The $n_{eq}$ relationship proposed herein is based on an alternative application of the Palmgren-Miner damage hypothesis, shifting from the existing high-cycle, low-damage fatigue framework to a low-cycle framework more applicable to liquefaction analyses. Seismic compression is the accrual of volumetric strains caused by cyclic loading, and presented herein is a "non-simplified" model to estimate seismic compression. The proposed model is based on a modified version of the Richart-Newmark non-linear cumulative damage hypothesis, and was calibrated from the results of drained cyclic simple shear tests. The proposed model can estimate seismic compression from any arbitrary strain time history. It is more accurate than other "non-simplified" seismic compression estimation models over a greater range of volumetric strains and can be used to compute number-of-equivalent shear strain cycles for use in "simplified" seismic compression models, in a manner consistent with seismic compression phenomenon. / Ph. D.

The Tamakoshi Dam in Nepal experienced 19 cm of settlement due to three earthquakes that took place from December 14, 2014 to May 12, 2015. This settlement caused massive damage and halted construction and was believed to have been caused by seismic compression. Seismic compression is the accrual of contractive volumetric strain in sandy soils during earthquake shaking for cases where the generated excess pore water pressures are low. The purpose of this case study is to investigate the settlements of the dam intake block relative to the right abutment block of the dam during the three earthquakes. Towards this end, soil profiles for the dam were developed from the boring logs and suites of ground motions were selected and scaled to be representative of the shaking at the base of the dam for the two of the three earthquakes which were well documented. Equivalent linear analysis was completed for the suites of ground motions to produce shear strain time histories which were then utilized in the Jiang et al. (2020) proposed procedure for seismic compression prediction. The results were found to not align with the settlement that was observed in the field, so post-liquefaction consolidation was also considered to be a possible cause of the settlement. The results from that analysis also showed that consideration of post-liquefaction consolidation did not yield settlements representative of those observed in the field. More detailed studies are recommended to assess the settlements that were observed at the dam site, particularly analyses that take into account below and above grade topographic effects on the ground motions and settlements at the ground surface. / Master of Science / The Tamakoshi Dam in Nepal experienced 19 cm of settlement due to three earthquakes that took place from December 14, 2014 to May 12, 2015. This settlement caused massive damage and halted construction and was believed to have been caused by seismic compression. Seismic compression is the accrual of contractive volumetric strain in sandy soils during earthquake shaking for cases where the generated excess pore water pressures are low. The purpose of this case study is to investigate the settlements of the dam intake block relative to the right abutment block of the dam during the three earthquakes. Representative soil profiles were developed based on data collected from the site for analysis of the settlement. Two approaches were used to compute predicted settlement, one which considered only seismic compression as the cause of settlement and a hybrid method that considered both seismic compression and post-liquefaction consolidation. Both approaches predicted settlement values that were less than what was observed in the field. It was found that the ground motion prediction equations used in the analysis were not representative of the tectonic setting in Nepal and thus was the main reason for the under-prediction. The relevance of this research lies in using methodology developed in academia to analyze a real world event and draw conclusions about the methodology's applicability.