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1. Expanded Byrne model for evaluating seismic compression

   https://doi.org/10.1177/8755293020957350  

   Jiang, Yusheng; Green, Russell A.; Taylor, Oliver-Denzil (September 2020, Earthquake Spectra)

   Seismic compression is the accrual of contractive volumetric strain in unsaturated or partially saturated sandy soils during earthquake shaking and has caused significant distress to overlying and nearby structures. The phenomenon can be well characterized by load-dependent, interaction macro-level fatigue theories. Toward this end, the Byrne cyclic shear-volumetric strain coupling model is expanded and calibrated for evaluating seismic compression for several soil types. In addition, the model was transformed to allow it to be implemented in a “simplified” manner, in addition to the original “non-simplified” formulation. Both implementation approaches are used to analyze a site in Japan impacted by the 2007, M_w6.6 Niigata-ken Chuetsu-oki earthquake. The results from the analyses are in general accord with the post-earthquake field observations and highlight the sensitivity of predicted magnitude of the seismic compression to the input variables used and modeling assumptions (e.g. relative density of the soil, magnitude of the volumetric threshold strain, orientation of the ground motions, settlement of soils below the ground water table, and accounting for multidirectional shaking). Although additional studies are needed to further validate the findings presented herein, estimation of relative density and threshold shear strain of the soil and ground motion orientation individually have moderate-to-significant influence on the computed magnitude of seismic compression, but they have a significant influence when taken in combination. Also, the seismic compression models can seemingly be used to predict the settlement in fully saturated sand when the excess pore water pressures are limited. Finally, accounting for multidirectional shaking has a significant influence on the computed magnitude of seismic compression. 

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2. Comparison of Seismic Compression Procedure Predictions: Case History from Japan

   Green, R.A. and (September 2020, Proc. 17th World Conference on Earthquake Engineering)

   null (Ed.)

   Seismic compression is the accrual of contractive volumetric strain in unsaturated or partially saturated sandy soils during earthquake shaking and has caused significant distress to overlying and nearby structures, to include the 2007, Mw6.6 Niigata-ken Chuetsu-oki, Japan earthquake. Of specific interest to this study is the seismic compression that occurred during this event at the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) site. What makes this case history of particular value is that the motions at the site were recorded by a free-field downhole array (Service Hall Array, SHA) and the magnitude of the seismic compression was accurately determined from the settlement of soil around a vertical pipe housing one of the array seismographs. The seismic compression at the site was ~10-20 cm. The profile at the site was well characterized by in-situ tests and laboratory tests performed on samples from the site, which allows seismic compression models to be calibrated. The study presented herein compares the predictions of the simplified and non-simplified forms of the expanded Byrne model. The predictions are in good accord with field observations, but the slight under-prediction by the non-simplified model may relate to estimated soil properties, assumed orientation of the ground motions and accounting for multidirectional shaking, and/or the numerical site response analyses used to compute the variation of the shear strains during shaking at depth in the soil profile. 

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3. A Discontinuous Galerkin Method for Simulating 3D Seismic Wave Propagation in Nonlinear Rock Models: Verification and Application to the M _w 7.8 2015 Gorkha, Nepal Earthquake

   https://doi.org/10.1029/2025JB031378  

   Niu, Zihua; Gabriel, Alice‐Agnes; Wolf, Sebastian; Ulrich, Thomas; Lyakhovsky, Vladimir; Igel, Heiner (July 2025, Journal of Geophysical Research: Solid Earth)

   Abstract The nonlinear mechanical responses of rocks and soils to seismic waves play an important role in earthquake physics, influencing ground motion from source to site. Continuous geophysical monitoring, such as ambient noise interferometry, has revealed co‐seismic wave speed reductions extending tens of kilometers from earthquake sources. However, the mechanisms governing these changes remain challenging to model, especially at regional scales. Using a nonlinear damage model constrained by laboratory experiments, we develop and apply an open‐source 3D discontinuous Galerkin method to simulate regional co‐seismic wave speed changes during the 2015 M_w7.8 Gorkha earthquake. We find pronounced spatial variations of co‐seismic wave speed reduction, ranging from <0.01% to >50%, particularly close to the source and within the Kathmandu Basin, while disagreement with observations remains. The most significant reduction occurs within the sedimentary basin and varies with basin depths, whereas wave speed reductions correlate with the fault slip distribution near the source. By comparing ground motions from simulations with elastic, viscoelastic, elastoplastic, and nonlinear damage rheologies, we demonstrate that the nonlinear damage model effectively captures low‐frequency ground motion amplification due to strain‐dependent wave speed reductions in soft sediments. We verify the accuracy of our approach through comparisons with analytical solutions and assess its scalability on high‐performance computing systems. The model shows near‐linear strong and weak scaling up to 2,048 nodes, enabling efficient large‐scale simulations. Our findings provide a physics‐based framework to quantify nonlinear earthquake effects and emphasize the importance of damage‐induced wave speed variations for seismic hazard assessment and ground motion predictions. 

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4. Postliquefaction Reconsolidation Settlement of a Soil Deposit Considering Spatially Variable Properties and Ground Motion Variability

   https://doi.org/10.1061/JGGEFK.GTENG-11768  

   Basu, Devdeep; Montgomery, Jack; Stuedlein, Armin W (March 2024, Journal of Geotechnical and Geoenvironmental Engineering)

   Assessment of earthquake-induced liquefaction is an important topic in geotechnical engineering due to the significant potential for damage to infrastructure. Some of the most significant infrastructure damage occurs due to differential settlement of the ground, including due to liquefaction. Postliquefaction deformations commonly are assessed using one-dimensional empirical models, which inherently assume laterally homogeneous soil layers. Numerical models offer the potential to examine the effects of ground motion variability and spatially variable soil properties on liquefaction-induced deformations. This study explored the postliquefaction reconsolidation settlement for a site in Hollywood, South Carolina, which was characterized using a three-dimensional (3D) geostatistical model and simulated using the numerical platform FLAC and constitutive model PM4Sand. The effects of ground motion characteristics on mean and maximum differential settlements were investigated. The physical mechanisms associated with postliquefaction responses such as excess pore pressures, shear strains, and volumetric strains also were examined. The efficacy of uniform models assuming representative percentile soil properties to represent the stochastic mean settlement was investigated. The inherent inability of uniform models to capture differential settlements and therefore the need for using stochastic models is discussed. 

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5. Uncertainty quantification of ground motion time series generated at uninstrumented sites

   https://doi.org/10.1177/87552930221135286  

   Tamhidi, Aidin; Kuehn, Nicolas M; Bozorgnia, Yousef (November 2022, Earthquake Spectra)

   Following an earthquake, ground motion time series are needed to carry out site-specific nonlinear response history analysis. However, the number of currently available recording instruments is sparse; thus, the ground motion time series at uninstrumented sites must be estimated. Tamhidi et al. developed a Gaussian process regression (GPR) model to generate ground motion time series given a set of recorded ground motions surrounding the target site. This GPR model interpolates the observed ground motions’ Fourier Transform coefficients to generate the target site’s Fourier spectrum and the corresponding time series. The robustness of the optimized hyperparameter of the model depends on the surrounding observation density. In this study, we carried out sensitivity analysis and tuned the hyperparameter of the GPR model for various observation densities. The 2019 M7.1 Ridgecrest and 2020 M4.5 South El Monte earthquake data sets recorded by the Community Seismic Network and California Integrated Seismic Network in Southern California are used to demonstrate the process. To provide a tool to quantify the uncertainty of the generated motions, a methodology to develop realizations of ground motion time series is also incorporated. The results illustrate that the uncertainty of the generated motions is lower at longer periods. It is shown that the observation density in the proximity of the target site plays a vital role in both error and uncertainty reduction of the generated time series. To demonstrate the concept, the effect of additional observations from combined recording networks is investigated. 

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