A frequency‐dependent and intensity‐dependent macroelement for reduced order seismic analysis of soil‐structure interacting systems

Abstract

Summary The computational demand of the soil‐structure interaction analysis for the design and assessment of structures, as well as for the evaluation of their life‐cycle cost and risk exposure, has led the civil engineering community to the development of a variety of methods toward the model order reduction of the coupled soil‐structure dynamic system in earthquake regions. Different approaches have been proposed in the past as computationally efficient alternatives to the conventional finite element model simulation of the complete soil‐structure domain, such as the nonlinear lumped spring, the macroelement method, and the substructure partition method. Yet no approach was capable of capturing simultaneously the frequency‐dependent dynamic properties along with the nonlinear behavior of the condensed segment of the overall soil‐structure system under strong earthquake ground motion, thus generating an imbalance between the modeling refinement achieved for the soil and the structure. To this end, a dual frequency‐dependent and intensity‐dependent expansion of the lumped parameter modeling method is proposed in the current paper, materialized through a multiobjective algorithm, capable of closely approximating the behavior of the nonlinear dynamic system of the condensed segment. This is essentially the extension of an established methodology, also developed by the authors, in the inelastic domain. The efficiency of the proposed methodology is validated for the case of a bridge foundation system, wherein the seismic response is comparatively assessed for both the proposed method and the detailed finite element model. The above expansion is deemed a computationally efficient and reliable method for simultaneously considering the frequency and amplitude dependence of soil‐foundation systems in the framework of nonlinear seismic analysis of soil‐structure interaction systems.

Education, financial aid and awareness can reduce smallholder farmers’ vulnerability to drought under climate change

“…the decision model) is based on empirical data, where does the data come from? ADOPT is calibrated with data from existing longitudinal household surveys (TEGEMEO 2000(TEGEMEO 2004(TEGEMEO 2007(TEGEMEO 2010 and from a fuzzy cognitive map of key informants, and a semi-structured household questionnaire among 260 smallholder farmers (Wens 2018(Wens , 2019 https://doi.org/10.5194/nhess-2021-216 Preprint. Discussion started: 23 July 2021 c Author(s) 2021.…”

“…The setup of the model is a result of participatory concept mapping with researchers and students of SEKU University, technical advisors of Kitui County department of water, agriculture, livestock and fishing, experts from SASOL foundation and 5 pilot households that have example farms for agricultural extension. The input data for the decision model was obtained from a survey on agricultural drought risk to smallholders in the case study area (Wens, 2019). Survey data includes a short questionnaire among employees of the Kenyan national disaster coordination units (n=10), semi-structured expert interviews (n=8) with NGOs, governmental water authorities and pioneer farmers in the Kitui district in Kenya, and an in-depth questionnaire among 250 smallholder farmers in the central Kitui.…”

“…Agent-based models allow explicitly simulation of the bottom-up individual human adaptation decisions, and capture the macro-scale consequences that emerge from the interventions between individual agents and their environments. Combining risk models with an agent based approach is thus a promising way to analyse drought risk, and the evolution of it through time, in a more realistic way (Wens et al, 2019).…”

Anti-symmetric mode excitation and seismic response of base-isolated bridges under asynchronous input motion

“…Given that the dynamic stiffness and damping at the soil-foundation interface are frequency-dependent, the mean period of each input motion was used for defining the spring and dashpot properties thus accounting for the dominant frequency of each ground motion used. More refined lumpedparameter models have also been developed by the authors [72][73][74] that match the target impedance function along the entire frequency range in the framework of response history analysis, however, this was deemed out of scope of the particular study. At the abutments, the deck was assumed pinned along the transverse direction and free to slide in the longitudinal one.…”

On the assessment of seismic performance of bridge piers on caisson foundations subjected to strong ground motions

“…Recently, Gaudio and Rampello 3,4 evaluated the seismic performance of massive caisson foundations supporting bridge piers subjected to strong ground motions by performing 3D nonlinear dynamic analyses in the time domain, shedding some light on the main parameters affecting the problem. However, such time consuming analyses cannot be proposed as a design tool to account for the nonlinear and inelastic soil behaviour, even for critical facilities: therefore, advanced reduced‐order models are needed, such as modified‐Newmark 5 and macro‐element 6 formulations. Unfortunately, most of these approaches were developed either for shallow or pile foundations, whereas very little has been proposed for caisson foundations.…”