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1. Convolutional autoencoder-based ground motion clustering and selection

   https://doi.org/10.1016/j.soildyn.2025.109240  

   Jia, Yiming; Sasani, Mehrdad (April 2025, Soil Dynamics and Earthquake Engineering)

   Ground motion selection has become increasingly central to the assessment of earthquake resilience. The selection of ground motion records for use in nonlinear dynamic analysis significantly affects structural response. This, in turn, will impact the outcomes of earthquake resilience analysis. This paper presents a new ground motion clustering algorithm, which can be embedded in current ground motion selection methods to properly select representative ground motion records that a structure of interest will probabilistically experience. The proposed clustering-based ground motion selection method includes four main steps: 1) leveraging domain-specific knowledge to pre-select candidate ground motions; 2) using a convolutional autoencoder to learn low-dimensional underlying characteristics of candidate ground motions’ response spectra – i.e., latent features; 3) performing k-means clustering to classify the learned latent features, equivalent to cluster the response spectra of candidate ground motions; and 4) embedding the clusters in the conditional spectra-based ground motion selection. The selected ground motions can represent a given hazard level well (by matching conditional spectra) and fully describe the complete set of candidate ground motions. Three case studies for modified, pulse-type, and non-pulse-type ground motions are designed to evaluate the performance of the proposed ground motion clustering algorithm (convolutional autoencoder + k-means). Considering the limited number of pre-selected candidate ground motions in the last two case studies, the response spectra simulation and transfer learning are used to improve the stability and reproducibility of the proposed ground motion clustering algorithm. The results of the three case studies demonstrate that the convolutional autoencoder + k-means can 1) achieve 100% accuracy in classifying ground motion response spectra, 2) correctly determine the optimal number of clusters, and 3) outperform established clustering algorithms (i.e., autoencoder + k-means, time series k-means, spectral clustering, and k-means on ground motion influence factors). Using the proposed clustering-based ground motion selection method, an application is performed to select ground motions for a structure in San Francisco, California. The developed user-friendly codes are published for practical use. 

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2. Performance-based design optimization of steel structures subjected to seismic actions

   https://doi.org/10.55592/cilamce.v6i06.10425  

   Rodrigues, Isabela D; Spence, Seymour M; Beck, André T (December 2024, Ibero-Latin American Congress on Computational Methods in Engineering (CILAMCE))

   Finding an optimal design for a structural system subject to seismic actions to minimize failure probability, repair costs, and injuries to occupants, significantly contributes to the resilience of buildings in earthquake regions. This research presents a comprehensive framework for the performance-based design optimization of steel structures, incorporating the Performance-Based Earthquake Engineering (PBEE) methodology delineated in FEMA P-58 [1]. A selected set of ground motions, consistent with the seismic hazard intensity of interest, and a nonlinear finite element model, established using OpenSees, enable the assessment of the system's dynamic response. To address the computational complexity related to evaluating the probability of failure of the system during an optimization iteration when using the PBEE methodology for assessing performance, this study introduces metamodeling techniques as a substitute for the original high-fidelity nonlinear finite element model. In particular, Kriging is employed to approximate both the median and standard deviation of the Engineering Demand Parameters (EDPs) in the design domain. The parameters of the Kriging metamodels are derived from nonlinear dynamic analyses performed using the original high-fidelity model and an optimal sampling plan obtained through Latin Hypercube sampling. Under the assumption of a lognormal distribution, the metamodel is then used to generate a large number of simulated demand sets necessary for the Monte Carlo procedure adopted by FEMA P-58 to calculate the distribution of probable losses for any given value of the design variable vector. Additionally, the median and standard deviation of the fragility function modeling collapse are also approximated by a Kriging metamodel, in which the parameters are derived from an Incremental Dynamic Analysis (IDA) for any given value of the design variable vector. The scheme is illustrated in a full-scale case study consisting of the performance-based optimization of the buckling-restrained braces of a steel seismic force-resisting system in terms of expected losses and construction costs. The study demonstrates that the proposed risk-based optimization scheme effectively balances construction costs with expected financial losses from earthquakes, thus enhancing the seismic performance of the system.[1] Applied Technology Council, & National Earthquake Hazards Reduction Program (US). (2012). Seismic performance assessment of buildings. Federal Emergency Management Agency. 

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3. Open-source simulation of strongly-coupled fluid-structure interaction between non-conformal interfaces

   https://doi.org/10.3389/fbuil.2023.1120518  

   Lewis, Nicolette S.; Winter, Andrew O.; Bonus, Justin; Motley, Michael R.; Eberhard, Marc O.; Arduino, Pedro; Lehman, Dawn E. (March 2023, Frontiers in Built Environment)

   Rodriguez, Julio A. (Ed.)

   Design code-based “life-safety” requirements for structural earthquake and tsunami design offer reasonable guidelines to construct buildings that will remain standing during a tsunami or seismic event. Much less consideration has been given to assessing structural resilience during sequential earthquake and tsunami multi-hazard events. Such events present a series of extreme loading scenarios, where damage sustained during the earthquake influences structural performance during the subsequent inundation. Similar difficulties exist with respect to damage sustained during tropical events, as wind and fluid loading may vary with structural response or accumulated damage. To help ensure critical structures meet a “life-safety” level of performance during such multi-hazard events, analysis software capable of simulating simultaneous structural and fluid dynamics must be developed. To address this gap in understanding of non-linear fluid-structure-interaction (FSI), an open-source tool (FOAMySees) was developed for simulation of tsunami and wave impact analysis of post-earthquake non-linear structural response of buildings. The tool is comprised of the Open-source Field Operation And Manipulation software package and OpenSeesPy, a Python 3 interpreter of OpenSees. The programs are coupledviapreCICE, a coupling library for partitioned multi-physics simulation. FOAMySees has been written to work in a Linux OS environment with HPC clusters in mind. The FOAMySees program offers a partitioned conventional-serial-staggered coupling scheme, with optional implicit iteration techniques to ensure a strongly-coupled two-way FSI solution. While FOAMySees was developed specifically for tsunami-resilience analysis, it may be utilized for other FSI applications with ease. With this coupled Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) program, tsunami and earthquake simulations may be run sequentially or simultaneously, allowing for the evaluation of non-linear structural response to multi-hazard excitation. 

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4. Numerical modeling of the post-earthquake fire performance of cold-formed steel members

   Niu, Yu; Li, Zhanjie; Enright, Sean; Dillard, Joshua; Hutchinson, Tara; Emberley, Richard; Meacham, Brian; Gernay, Thomas (April 2025, 2025 Proceedings of the Structural Stability Research Council Annual Stability Conference)

   The objective of this paper is to investigate the post-earthquake thermal-mechanical response of cold-formed steel (CFS) members. A 10-story cold-formed steel building (CFS-NHERI) will undergo seismic tests, followed by post-earthquake live fire tests. To support the fire test setup, computational models are developed to simulate the impact of varying post-earthquake damage levels on the fire response of the structure. As a panelized system, damage to different finish and nonstructural systems significantly affects the thermal behavior and load-bearing capacity of the CFS components. The computational models integrate the modeling capability in CUFSM and SAFIR for the elastic buckling, heat transfer, and transient structural analysis under fire. A parametric analysis considering different seismic damage levels is conducted to study the buckling and strength behavior of the CFS members under fire-induced nonuniform temperature fields. These pre-test models inform the duration and severity of the fire tests to maintain structural stability while achieving substantial thermal loading on the CFS load-bearing system. They also provide guidance for the sensor layout plan for the fire tests. This study advances methods for fire resilience of thin-walled CFS structures under multi-hazard scenarios. 

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5. Coupled Urban Change and Natural Hazard Consequence Model for Community Resilience Planning

   https://doi.org/10.1029/2022EF003059  

   Sanderson, Dylan R.; Cox, Daniel T.; Amini, Mehrshad; Barbosa, Andre R. (December 2022, Earth's Future)

   Abstract This paper presents a new coupled urban change and hazard consequence model that considers population growth, a changing built environment, natural hazard mitigation planning, and future acute hazards. Urban change is simulated as an agent‐based land market with six agent types and six land use types. Agents compete for parcels with successful bids leading to changes in both urban land use—affecting where agents are located—and structural properties of buildings—affecting the building's ability to resist damage to natural hazards. IN‐CORE, an open‐source community resilience model, is used to compute damages to the built environment. The coupled model operates under constraints imposed by planning policies defined at the start of a simulation. The model is applied to Seaside, Oregon, a coastal community in the North American Pacific Northwest subject to seismic‐tsunami hazards emanating from the Cascadia Subduction Zone. Ten planning scenarios are considered including caps on the number of vacation homes, relocating community assets, limiting new development, and mandatory seismic retrofits. By applying this coupled model to the testbed community, we show that: (a) placing a cap on the number of vacation homes results in more visitors in damaged buildings, (b) that mandatory seismic retrofits do not reduce the number of people in damaged buildings when considering population growth, (c) polices diverge beyond year 10 in the model, indicating that many policies take time to realize their implications, and (d) the most effective policies were those that incorporated elements of both urban planning and enforced building codes. 

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